Phytochemical Content of Muscadine Grape Promoting Apoptosis and Inhibiting Cancer Cell Growth to Prevent Cancer Progression

Phytochemical Content of Muscadine Grape Promoting Apoptosis and Inhibiting Cancer Cell Growth to Prevent Cancer Progression | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Phytochemical Content of Muscadine Grape Promoting Apoptosis and Inhibiting Cancer Cell Growth to Prevent Cancer Progression Imrul Mosaddek Ahmed†*, Tushar Dhanani†, Mehboob Sheikh, Md Amanullah This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8711838/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Muscadine grape ( Vitis rotundifolia ) is a rich source of bioactive phytochemicals; however, links between genotype-dependent phytochemical diversity and anticancer activity remain poorly defined. Here, fifty muscadine grape genotypes were systematically evaluated for phenolic composition, antioxidant capacity, and anticancer efficacy. Total phenolic content, total flavonoid content, and DPPH radical scavenging activity varied markedly among genotypes, indicating substantial biochemical diversity. Targeted HPLC analysis revealed pronounced genotypic differences in major stilbenes (resveratrol, viniferin, and pterostilbene) and catechin derivatives, with resveratrol and epicatechin contributing most strongly to antioxidant capacity. Biological relevance was confirmed using in vitro cancer models. Muscadine grape extracts significantly reduced cell viability in A549 (lung), LNCaP (prostate), and Caco-2 (colon) cancer cell lines in a genotype-dependent manner following 48 h exposure, with IC₅₀ values ranging from 300 to 450 µg mL⁻¹. Notably, genotypes such as Southern Home exhibited elevated phytochemical accumulation and pronounced antiproliferative activity. Pearson’s correlation and multivariate analyses, including hierarchical clustering, principal component analysis, and the multi-trait genotype–ideotype distance index (MGIDI), identified elite genotypes with favorable integrated biochemical and biological profiles. Collectively, these findings demonstrate that phytochemical-rich muscadine grape genotypes exert pronounced antiproliferative effects and support their potential application in functional foods and nutraceutical strategies for cancer prevention. Food Science & Technology Horticulture Cancer Biology Muscadine grape phytochemicals stilbenes catechins antioxidant activity cancer prevention Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Highlights Fifty muscadine genotypes show strong variation in phytochemicals, antioxidants, and bioactivity HPLC profiling identifies resveratrol and epicatechin as major antioxidant contributors Muscadine extracts inhibit lung, prostate, and colon cancer cell growth in vitro Phenolic content and antioxidant capacity correlate with reduced cancer cell viability MGIDI analysis identifies elite genotypes for functional food and nutraceutical use 1. Introduction Cancer remains a major global health burden, accounting for nearly one in six deaths worldwide, with incidence projected to exceed 20 million new cases annually by 2030 [ 1 ]. Although conventional cancer therapies such as chemotherapy and radiotherapy have improved patient survival, their effectiveness is often limited by severe side effects, therapy resistance, and high recurrence rates. Consequently, there is increasing interest in complementary and preventive strategies based on dietary bioactive compounds. In this context, dietary phytochemicals plant-derived secondary metabolites with antioxidant, anti-inflammatory, and apoptosis-modulating properties have gained considerable attention as safe and effective agents for cancer prevention and management [ 2 – 4 ]. Among fruit crops, grapes ( Vitis spp.) are particularly valued for their rich polyphenolic composition, including flavonoids, phenolic acids, anthocyanins, and stilbenes, which contribute to both fruit quality and health-promoting properties [ 5 ]. While Vitis vinifera , the European grape species, has been extensively investigated for its antioxidant, cardioprotective, and anticancer effects, comparatively less attention has been paid to muscadine grape ( Vitis rotundifolia Michx.), a species native to Southeastern United States. Notably, muscadine grapes possess a genetically distinct background and a more complex phytochemical profile than V. vinifera , suggesting untapped potential for functional and nutraceutical applications [ 6 – 8 ]. Muscadine grapes are genetically and physiologically distinct from V. vinifera , characterized by thick berry skins, a high proportion of ellagitannins, and exceptional resistance to fungal and bacterial pathogens. These traits are closely associated with elevated accumulation of secondary metabolites. Previous phytochemical analyses have shown that muscadine berries are particularly rich in total phenolics, flavonoids, and stilbenes including resveratrol, viniferin, and pterostilbene, as well as catechins and proanthocyanidins [ 9 – 11 ]. Importantly, these compounds have demonstrated strong antioxidant activity and the capacity to modulate key molecular pathways involved in carcinogenesis, such as oxidative stress signaling, cell cycle regulation, apoptosis, angiogenesis, and metastasis, across diverse experimental models [ 12 – 14 ]. Among grape-derived phytochemicals, resveratrol and its dimethylated analog pterostilbene are among the most extensively studied stilbenes with documented anticancer activity. These compounds function as natural chemopreventive agents by suppressing oxidative stress, inhibiting pro-survival signaling pathways including NF-κB and PI3K/AKT, and activating p53-dependent apoptotic mechanisms [ 4 , 15 ]. Pterostilbene exhibits enhanced lipophilicity and metabolic stability relative to resveratrol, resulting in improved cellular uptake and bioavailability. In parallel, catechins such as epicatechin and epicatechin gallate contribute synergistically by inducing mitochondrial dysfunction, increasing intracellular reactive oxygen species (ROS), and activating caspase-dependent apoptosis in cancer cells [ 13 , 16 ]. Collectively, these phytochemicals preferentially target malignant cells while exerting limited toxicity toward normal tissues, highlighting their suitability for dietary-based cancer prevention strategies. Despite this growing body of evidence, the composition and concentration of bioactive compounds in muscadine grapes vary widely among genotypes due to substantial genetic and metabolic diversity. Such variation has important implications for both nutritional value and therapeutic efficacy. However, most existing studies have focused on a limited number of cultivars or pooled samples, thereby overlooking the extensive biochemical diversity present within muscadine germplasm. Comprehensive, genotype-resolved characterization is therefore essential to identify elite genotypes with superior antioxidant and anticancer potential. Advanced multivariate analytical approaches, including principal component analysis (PCA), correlation analysis, and the multi-trait genotype ideotype distance index (MGIDI), provide powerful tools to integrate biochemical and biological traits for objective genotype selection [ 17 , 18 ]. To address these gaps, the present study systematically evaluated fifty muscadine grape genotypes to elucidate genotype-dependent variation in phytochemical composition, antioxidant capacity, and anticancer activity. Total phenolic and flavonoid contents, DPPH radical scavenging activity, and key phenolic subclasses, including stilbenes and catechins, were quantified. The antiproliferative effects of berry extracts were assessed using human lung (A549), prostate (LNCaP), and colon (Caco-2) cancer cell lines by examining effects on cell viability and apoptosis. Furthermore, correlation, clustering, and multivariate analyses were employed to elucidate relationships among phytochemical traits, antioxidant activity, and cancer cell growth inhibition. This integrative approach provides new insight into the functional diversity of V. rotundifolia and establishes a robust scientific foundation for developing muscadine-based functional foods and nutraceuticals aimed at cancer prevention and health promotion. 2. Results 2.1. Variation in total phenolic and flavonoid contents and antioxidant activity Substantial genotypic variation was observed among the fifty muscadine grape genotypes for total phenolic content (TPC), total flavonoid content (TFC), and DPPH radical-scavenging activity (Fig. 1 ). TPC ranged from approximately 1.2 to 4.3 mg GAE g⁻¹ FW, while TFC varied between 14 and 23 mg CE g⁻¹ FW. Genotypes such as Southern Home, Pineapple, Black Beauty, Darlene and Fry exhibited the highest phenolic and flavonoid accumulation, corresponding to the strongest DPPH scavenging activities (70–85%). Conversely, Golden Isle, Watergate, Doreen and Magnolia displayed comparatively lower phenolic contents and weaker antioxidant responses. A highly significant positive correlation was observed among TPC, TFC, and DPPH activity (p < 0.01), indicating that phenolic concentration was a major determinant of antioxidant potential. 2.2. Genotypic variation in stilbene and catechin composition The quantification of key stilbenes resveratrol, viniferin, and pterostilbene revealed pronounced genotype-dependent differences (Fig. 2 ). Resveratrol concentrations ranged from 2.6 to 7.9 µg g⁻¹ FW, with Southern Home, Dixieland, Fry, Loomis, Hunt, Tara, Higgins, and Delight showing the highest accumulation. Viniferin displayed a wider range (1–24 µg g⁻¹ FW) and emerged as the dominant stilbene in most high-performing genotypes. Pterostilbene levels, although relatively low (2.5–3.5 µg g⁻¹ FW), were significantly elevated in Southern home and African Queen. Overall, stilbene profiles differed markedly among genotypes, suggesting that different accessions harbor distinct stilbene biosynthetic capacities. Catechin derivatives including catechin, epicatechin, and epicatechin gallate also exhibited broad quantitative variability across genotypes (Fig. 3 ). Catechin was the predominant compound, ranging between 20 and 280 µg g⁻¹ FW, followed by epicatechin (20–2000 µg g⁻¹ FW) and epicatechin gallate (1–70 µg g⁻¹ FW). High-performing genotypes (Southern Home, Pineapple Doreen, Fry, and Alachua) contained markedly greater catechin levels than low-performing ones. The representative HPLC chromatograms confirmed the presence and resolution of major phenolic compounds in muscadine grape extracts (Fig. 4 ). Stilbenes were effectively separated and detected at 319 nm, while catechins and related flavan-3-ols were monitored at 280 nm. Peaks corresponding to resveratrol, viniferin, pterostilbene, catechin, epicatechin, and epicatechin gallate were identified based on retention times and spectral characteristics relative to authentic standards, enabling reliable quantification across genotypes 2.3. Antiproliferative activity cancer cell survival assays Exposure of three human cancer cell lines (A549 lung, LNCaP prostate, and Caco-2 colon) to muscadine berry extracts for 48 h produced genotype-dependent reductions in cancer cell survival (Fig. 5 ). Mean cell survival ranged from approximately 25% to 85% depending on genotype and cell line. Extracts derived from Southern Home, Pineapple, and Pride exhibited the strongest inhibitory effects, reducing cell viability below 30% in A549 and LNCaP lines. Among the tested lines, LNCaP cells were the most sensitive, followed by Caco-2 and A549. In contrast, extracts from genotypes characterized by lower phenolic content (Ison, Janebell, Jumbo, Watergate and Florida Fry) exhibited minimal antiproliferative, maintaining cell survival levels above 75%. Overall response patterns closely mirrored antioxidant potential, suggesting that genotypes with higher polyphenol abundance were associated with stronger growth-inhibitory effects. 2.4. Cytotoxic potency (IC₅₀) of selected genotypes Based on their superior phytochemical profiles and antiproliferative performance, five elite genotypes (Pineapple, Southern Home, Pride, Sweet Jenny and Alachua) were selected for further evaluation of cytotoxic potency through IC₅₀ determination (Fig. 6 ). IC₅₀ values across the three cancer cell lines ranged from 300 to 500 µg mL⁻¹, with Southern Home and Pineapple consistently exhibiting the lowest (most potent) IC₅₀ values. Among the tested cell lines, LNCaP cells exhibited slightly lower IC₅₀ compared with A549 or Caco-2, consistent with their higher sensitivity observed in cell survival assays. These findings confirm that the antiproliferative effects of muscadine grape extracts are concentration-dependent and more pronounced in genotypes with elevated phenolic content. 2.5. Correlations among phytochemical traits, antioxidant activity and anticancer effects A comprehensive correlogram (Fig. 7 ) revealed strong interrelationships among phytochemical traits, antioxidant capacity, and anticancer activity. TPC, TFC, and DPPH activity showed strong positive correlations (r > 0.80). In contrast, these antioxidant traits were consistently and negatively correlated with cancer cell survival (r = − 0.65 to − 0.80) across all lines, confirming that genotypes with higher phenolic abundance were associated with stronger antiproliferative activity. Significant negative correlations were also found between individual compounds including resveratrol, viniferin, and epicatechin and cancer cell survival, highlighting the contribution of specific phenolic constituents to cancer cell growth inhibition. Collectively, these correlation patterns support a close linkage between phytochemical richness, antioxidant capacity, and biological activity in muscadine grape extracts, while reinforcing the concept that anticancer effects arise from the combined action of multiple phenolic constituents rather than a single dominant compound. 2.6. Cluster and heatmap analysis of genotypes Hierarchical clustering based on all measured phytochemical, antioxidant, and biological parameters grouped the fifty muscadine genotypes into three distinct clusters (Fig. 8 ). Cluster I comprised high-performing genotypes characterized by elevated TPC, TFC, DPPH, stilbenes, and catechins coupled with low cancer cell survival. Genotypes within this cluster therefore exhibited a coordinated enrichment of antioxidant capacity and growth-inhibitory potential. Cluster II included genotypes with moderate phytochemical content and intermediate biological activity, whereas Cluster III contained low-activity genotypes. The heatmap visualization further illustrated genotype-specific trait intensity, with red gradients (+ 5 to + 6) representing high antioxidant and anticancer performance and blue gradients ( − 1 to − 2) denoting weak responses. Southern Home, Sweet Jenny, and Pineapple consistently clustered within the most bioactive group, reinforcing their superior functional profiles and their repeated identification as high-value genotypes across independent biochemical, biological, and multivariate analyses. 2.7. Principal component analysis of integrated traits Principal component analysis (PCA) was employed to integrate phytochemical composition, antioxidant capacity, and anticancer activity across the fifty muscadine grape genotypes (Fig. 9 ). The first two principal components (PCs) accounted for 51.2% of the total phenotypic variation, with PC1 explaining 37.6% and PC2 explaining 13.6%, indicating that a substantial proportion of trait variability could be captured within a reduced dimensional space. The PCA biplot (Fig. 9 a) revealed clear separation of genotypes along PC1, which was primarily driven by total phenolic content (TPC), total flavonoid content (TFC), DPPH radical scavenging activity, and major stilbenes and catechins. Genotypes positioned on the positive side of PC1 clustered with high phytochemical abundance and antioxidant capacity, whereas those on the negative side were associated with higher cancer cell viability, indicating weaker antiproliferative effects. The variable contribution plot (Fig. 9 b) further clarified trait relationships. Stilbenes (resveratrol, viniferin), catechins, TPC, TFC, and DPPH loaded strongly and positively along PC1, demonstrating their dominant contribution to overall variance. In contrast, cancer cell survival metrics for A549, LNCaP, and Caco-2 loaded in the opposite direction, confirming a negative association between phytochemical richness and cancer cell viability. PC2 captured secondary variation largely associated with differences among specific stilbenes, suggesting genotype-dependent specialization in secondary metabolism rather than generalized antioxidant effects. 2.8. Variance contribution of principal components The scree plot derived from principal component analysis (PCA) illustrates the relative contribution of each principal component (PC) to the total variance among the fifty muscadine grape genotypes (Fig. 10 ). The scree plot confirmed that the first two principal components captured most of the phenotypic variation among genotypes, with subsequent components contributing progressively smaller proportions (Fig. 10 ). This result supports the robustness of the PCA model and the effectiveness of the selected traits in explaining genotype-dependent variation. 2.9. Multi-trait selection (MGIDI) and genotype strengths/weaknesses Application of the MGIDI index integrated multiple phenotypic criteria, including TPC, TFC, stilbenes, catechins, DPPH, and IC₅₀ or cancer cell survival metrics, to rank genotypes based on overall performance. The MGIDI selection (Fig. 11 a) highlighted a subset of superior genotypes that optimally balance high phytochemical content and anticancer bioactivity. Notably, genotypes identified by MGIDI largely overlapped with those ranked highly in univariate and multivariate analyses, providing internal validation of the selection strategy. The strengths weaknesses radar/stack plot (Fig. 11 b) illustrated trait domains in which selected genotypes excel (e.g., high total phenolics, strong radical scavenging, low cancer cell survival) and traits with room for improvement (e.g., some specific stilbenes or moderate activity in a particular cell line). Overall, MGIDI proved to be an effective and integrative approach for prioritizing muscadine genotypes for downstream breeding, bioactive compound isolation, or nutraceutical development. 3. Discussion This study provides a genotype-resolved evaluation of phytochemical composition, antioxidant capacity, and anticancer activity in muscadine grape ( Vitis rotundifolia ), revealing pronounced inter-genotypic variation and its functional consequences. While previous studies have reported antioxidant or cytotoxic effects of selected muscadine cultivars or isolated phenolic fractions, most investigations have been limited in scope. By systematically evaluating a large and diverse germplasm panel using an integrated phytochemical–bioactivity framework, the present study advances understanding of how genotype-dependent metabolic diversity translates into functional bioactivity (Figs. 1 – 3 ) [ 6 , 10 , 19 ]. Consistent with earlier reports, muscadine grapes exhibited higher total phenolic and flavonoid contents than those typically reported for Vitis vinifera , highlighting their nutraceutical potential. Importantly, our results demonstrate that phytochemical enrichment is highly genotype dependent. The substantial variation observed in total phenolic content (TPC), total flavonoid content (TFC), and antioxidant capacity among the fifty genotypes (Fig. 1 ) underscores the strong influence of genetic background on secondary metabolism in V. rotundifolia . Genotypes such as Southern Home and Pineapple consistently displayed elevated phenolic accumulation and enhanced antioxidant activity, in agreement with earlier compositional and metabolomic studies [ 7 – 10 ]. The strong correlations between TPC, TFC, and DPPH radical scavenging activity (Fig. 7 ) indicate that phenolic compounds are major determinants of antioxidant function in whole-berry muscadine extracts. Similar relationships have been reported across grape species and other polyphenol-rich fruits, supporting a conserved role for polyphenols in redox regulation [ 5 , 20 ]. These compounds are primarily derived from the shikimate and phenylpropanoid pathways, which generate flavonoids, stilbenes, and proanthocyanidins [ 6 ]. The elevated accumulation of resveratrol and viniferin in elite genotypes (Fig. 2 ) suggests enhanced stilbene biosynthesis, potentially reflecting adaptive responses to biotic and abiotic stress that are characteristic of muscadine grapes [ 9 , 10 , 21 ]. Beyond total phenolic measures, targeted HPLC analysis further revealed distinct, genotype-specific stilbene and catechin profiles (Figs. 2 – 4 ), indicating qualitative as well as quantitative metabolic differences. Resveratrol, viniferin, pterostilbene, catechin, and epicatechin emerged as dominant contributors to the phytochemical landscape. Oligomeric stilbenes such as viniferins have been reported to exhibit greater anticancer potency than monomeric resveratrol due to enhanced stability and bioactivity [ 22 ], while pterostilbene displays improved lipophilicity and cellular uptake [ 13 , 15 ]. Catechin derivatives, in turn, contribute to both antioxidant defense and cancer-related signaling by modulating mitochondrial function and activating apoptotic pathways [ 13 , 16 ]. The co-accumulation of these compounds in high-performing genotypes supports a model of multicomponent phytochemical synergy, rather than single-compound effects. Crucially, the biological relevance of this phytochemical diversity was confirmed using in vitro cancer models. Muscadine grape extracts significantly reduced viability of lung (A549), prostate (LNCaP), and colon (Caco-2) cancer cells in a genotype-dependent manner (Fig. 5 ). Genotypes enriched in phenolics and stilbenes consistently exhibited stronger antiproliferative effects, supporting the central role of phytochemical composition in determining biological activity. The IC₅₀ values observed (300–450 µg mL⁻¹; Fig. 6 ) are comparable to those reported for crude polyphenol-rich plant extracts and are considered biologically relevant for nutraceutical screening [ 19 , 23 ]. Importantly, elite genotypes demonstrated activity across multiple cancer cell lines, suggesting broad antiproliferative potential rather than cell type–specific toxicity. Mechanistically, the strong negative correlations between antioxidant capacity and cancer cell survival (Fig. 7 ) suggest that redox modulation contributes to the observed antiproliferative effects. Polyphenols can selectively disrupt redox homeostasis in cancer cells, thereby promoting apoptosis while sparing normal cells [ 24 ]. Previous studies have shown that resveratrol activates intrinsic apoptotic pathways through Bax induction and Bcl-2 suppression, whereas catechins inhibit PI3K/AKT and MAPK signaling cascades involved in cancer cell survival [ 4 , 14 , 15 ]. Together, these mechanisms provide a plausible biological basis for the genotype-dependent anticancer effects observed in this study. Finally, multivariate analyses provided an integrative perspective on the coordination between biochemical and biological traits. Hierarchical clustering and PCA revealed clear grouping of genotypes based on combined phytochemical and anticancer attributes (Figs. 8 and 10 ), with total phenolics and antioxidant capacity emerging as primary drivers of variance. The MGIDI index enabled objective identification of elite genotypes with balanced multi-trait performance (Fig. 9 ), while the scree plot confirmed that the first two principal components captured the majority of phenotypic variation (Fig. 11 ). Such integrative approaches are increasingly recognized as effective tools for functional trait selection and nutraceutical-oriented breeding [ 17 , 18 ]. 4. Materials and methods 4.1. Plant materials and experimental design Fifty muscadine grape ( Vitis rotundifolia Michx.) genotypes representing diverse berry colors and end uses were collected from the Center for Viticulture and Small Fruit Research, Florida A&M University, Tallahassee, FL, USA, and maintained under uniform cultural conditions (Fig. S1). The experimental site is located in Florida (30°28′45.63″ N, 84°10′16.43″ W). Fully ripened berries were harvested in the morning hours between 9–10 at the same physiological maturity, cleaned, and immediately frozen at − 80°C until analysis to preserve phytochemical integrity [ 25 ]. All samples were collected within a single growing season to minimize environmental variation. Each genotype was analyzed using four biological replicates (n = 4). 4.2. Sample extraction Whole muscadine berries (10 g) were cryogenically ground to a fine powder using liquid nitrogen and extracted with methanol following established protocols for grape polyphenol extraction [ 26 ]. The mixture was vortexed for 1 min (1,814 × g), homogenized using an 850 Homogenizer (Fisher Scientific, USA), and sonicated for 30 min in a cold-water ultrasonic bath (Bransonic 3800, Emerson, USA) to enhance extraction efficiency. Samples were centrifuged at 15,000 rpm for 15 min using an Avanti J-26 XP centrifuge (Beckman Coulter, USA). The extraction was repeated on the residual pellet, and supernatants were pooled and stored at − 80°C until further analysis. 4.3. Determination of total phenolic, flavonoid content and antioxidant activity (DPPH radical scavenging assay) Total phenol content was determined according to the previously reported method by Ahmed et al. [ 27 ] Folin phenol reduction method with few modifications. Frozen samples (0.2 g) were ground with 2 mL 80% methanol and less sand in the ice bath followed by ultrasonication for 30 min. The homogenates were centrifuged at 4°C, 2000 × g 20 min and the resulting supernatant was used for total phenolic content and DPPH free radical scavenging activity assay. The reaction system was as follows: 150 µL Folin-Ciocalteu's reagent (Sigma), 200 µL supernatant, 2 mL 2% Na 2 CO 3 . The reaction mixture was incubated in dark at 25°C for 20 min. After that the absorbance was measured immediately at OD 735 and gallic acid was used to prepare standard curve for total phenol content. Flavonoid content was determined according to Zhishen et al . [ 28 ]. 0.2 g frozen sample was homogenized with 2 mL 1% HCl in methanol through ice bath grinding followed by unltrasonication for 30 min. The homogenates were centrifuged at 4°C 2000 × g for 20 min. The supernatants were used for determination of flavonoid content. Then 300 µL 5% NaNO 2 , 300 µL 10% AlCl 3 and 300 µL supernatant were added in one tube. After 6 min 2 mL 1 M NaOH was added in the previous mixture so that reaction could take place. After 1 min absorbance was measured at OD 510 . DPPH activity was measured according to the previously reported method by Ahmed et al. [ 29 ]. The reaction system was as follows: 2.5 mL 65 µM DPPH (prepared from 80% methanol) and 50 µL supernatant. The system was incubated in dark at 25°C for 30 min, the absorbance was measured immediately at OD517, denoted by A. Absorbance value of 2.5 mL 80% methanol and 50 µL supernatant at OD517 denoted by B; and absorbance value of 2.5 mL 65 µM DPPH and 50 µL 80% methanol at OD517 denoted by C. DPPH activity was calculated by the formula [1 - (AB) / C] × 100, expressed as percentage. All measurements were conducted in triplicate. 4.4. Quantification of stilbenes and catechins by HPLC Stilbenes and catechins were quantified using a Waters 1525 HPLC system equipped with a 2996 PDA detector and a 717 Plus autosampler (Waters Corp., Milford, MA, USA), following validated grape polyphenol separation protocols [ 30 , 31 ]. Separation was achieved on a Prodigy ODS3 column (5 µm, 100 Å, 250 × 4.6 mm; Phenomenex, USA). The mobile phase consisted of (A) water and (B) acetonitrile, with gradient elution programmed as follows: 0–15 min, 10–20% B; 30–50 min, sequential increases to 30, 40, 50, 70, and 10% B, followed by re-equilibration for 5 min. A 20 µL aliquot was injected, and detection was performed at 280 and 320 nm. Quantification of individual analytes was achieved using their reference standards. 4.5. Anticancer activity 4.5.1. Cell culture Three different human cancer cells, including lung (A549), prostate (LNCaP), and colon (Caco-2) cancer cell lines were obtained from the American Type Culture Collection (ATCC, Manassas, VA, USA). Cells were cultured in DMEM basal medium supplemented with 10% (v/v) heat-inactivated fetal bovine serum and 1% penicillin–streptomycin (100 U mL⁻¹ penicillin and 0.1 mg mL⁻¹ streptomycin). Cultures were maintained at 37°C in a humidified atmosphere containing 5% CO₂ (VWR, Suwanee, GA, USA). Cell growth and viability were assessed using a Bio-Rad TC-20 automated cell counter (Bio-Rad, Hercules, CA, USA) following crystal violet staining (1%) after 48 h of incubation [ 32 ]. 4.5.1. Cell viability assay Cells were seeded in 96-well plates at a density of 3 × 10⁴ cells per well and allowed to attach overnight in experimental medium. Muscadine extracts were prepared in three independent biological replicates, and each replicate was tested in triplicate on each plate. Extracts were added to the cells at final concentrations of 500 µg mL⁻¹. Cells were incubated at 37°C for 48 h. At each time point, 10 µL of Alamar Blue solution (0.5 mg mL⁻¹) was added to each well to achieve a final concentration of 10% (v/v), followed by incubation for an additional 4 h. Fluorescence was measured at excitation/emission wavelengths of 550/580 nm using an Infinite M200 microplate reader (Tecan, Männedorf, Switzerland). Control cells were treated with DMSO at the same final concentration used for the extracts (< 1%), while blank wells contained culture medium only [ 33 ]. Cell viability was expressed as a percentage relative to untreated controls, and the rate of cell growth inhibition was calculated using the following equation: Cell viability (%) = (treated cells - blank cells)/(control cells - blank cells) × 100 Cell growth inhibition (%) = 100 - (% Cell viability). IC₅₀ values were estimated from dose response curves using GraphPad Prism 10. 4.6. Statistical and multivariate analyses All experiments were conducted in quadruplicate, and results are presented as mean ± standard deviation. Analysis of variance (ANOVA) was performed using SAS v9.4 to assess significant differences among genotypes (p < 0.01). Pearson’s correlation coefficients were calculated to evaluate associations among phytochemical traits, antioxidant activity, and cancer cell viability. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were conducted using the FactoMineR package in R [ 34 ]. The multi-trait genotype–ideotype distance index (MGIDI) was applied according to Olivoto and Lúcio [ 17 ] to identify genotypes with optimal combinations of phytochemical richness and anticancer activity. Data visualization was performed using ggplot2 and corrplot packages. 5. Conclusion This study demonstrates that genotype-dependent phytochemical diversity is a primary determinant of antioxidant capacity and antiproliferative activity in muscadine grape ( Vitis rotundifolia ). By integrating comprehensive phytochemical profiling with functional bioassays and multivariate analyses, we establish a direct link between metabolic composition and biological efficacy across a diverse germplasm panel. The findings indicate that coordinated accumulation of phenolics, including stilbenes and catechins, rather than individual compounds alone, underlies variability in anticancer activity among genotypes. The multivariate framework applied here provides an objective and scalable strategy for identifying genotypes with favorable biochemical and functional attributes, supporting nutraceutical-oriented selection and breeding. Although this study is based on in vitro cancer models, it provides a robust foundation for future investigations focused on mechanistic validation, apoptosis-related pathways, bioavailability, and in vivo efficacy. Overall, this work advances understanding of the functional significance of phytochemical diversity in muscadine grape and supports its potential as a valuable bioresource for functional food development. Declarations Author Contributions: I.M.A. Conceptualization, methodology, formal analysis, data curation, original draft writing, review and editing. T.D. methodology, formal analysis, original draft, writing review and editing. M.A. statistical analysis and reviewing the draft. M.B.S contributed to the concept, resources, and reviewing the draft. Funding: Funding The research was financially supported by the USDA/NIFA Capacity Building Grant # 2021-38821-34580 and VAC/FDACS Grants Program #000005844. Data Availability Statement: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests: The authors have no relevant financial or nonfinancial interests to disclose. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. References World Health Organization (2024) Cancer. https://www.who.int/news-room/fact-sheets/detail/cancer Scalbert A et al (2023) Dietary polyphenols and disease prevention. 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Biomedicines 7:96. https://doi.org/10.3390/biomedicines7040096 Xia EQ, Deng GF, Guo YJ, Li HB (2022) Biological activities of polyphenols from grapes. Int J Mol Sci 23:6073. https://doi.org/10.3390/ijms23116073 Yi W, Fischer J, Akoh CC (2005) Anticancer activities of muscadine grape phenolics in vitro. J Agric Food Chem 53:8804–8812 Rivière C et al (2023) Oligomeric stilbenes: structural diversity and anticancer potential. Nat Prod Rep 40:123–145 Santos JS et al (2023) Bioactivity of polyphenol-rich plant extracts in cancer models. Nutrients 15:2214 Liu Z et al (2024) Redox modulation and selective apoptosis induction by dietary polyphenols. Trends Food Sci Technol 141:104–118 Chemat F et al (2012) Green extraction of natural products. Int J Mol Sci 13:8615–8627 Dai J, Mumper RJ (2010) Plant phenolics: extraction, analysis and biological activity. Molecules 15:7313–7352 Ahmed IM, Cao FB, Zhang M, Chen XH, Zhang GP, Wu F (2013) B. Differences in yield and physiological responses to combined drought and salinity stress during anthesis in Tibetan wild and cultivated barleys. PLoS ONE 8, e77869 Zhishen J, Mengcheng T, Jianming W (1999) Determination of flavonoid contents and antioxidant activity. Food Chem 64:555–559 Ahmed IM, Nadira UA, Bibi N, Cao FB, Zhang GP, Wu FB (2014) Secondary metabolism and antioxidants are involved in the tolerance to drought and salinity, separately and combined, in Tibetan wild barley. Environ Exp Bot 111:1–12 Waterhouse AL (1999) Determination of phenolics by HPLC. Methods Enzymol 299:145–155 Flamini R (2013) Mass spectrometry in grape and wine analysis. Mass Spectrom Rev 32:205–237 Freshney RI (2010) Culture of Animal Cells: A Manual of Basic Technique . Wiley-Liss Das PR, Darwish AG, Ismail A, Haikal AM, Gajjar P, Balasubramani SP, Sheikh MB, Tsolova V, Soliman KFA, Sherif SM, El-Sharkawy I (2022) Genotype- and developmental stage–dependent variation in bioactive compounds, metabolites, and cytotoxicity in blueberry. Food Chem 374:131632. https://doi.org/10.1016/j.foodchem.2021.131632 Lê S, Josse J, Husson F (2008) FactoMineR: an R package for multivariate analysis. J Stat Softw 25:1–18 Additional Declarations The authors declare no competing interests. Supplementary Files SupplementaryFig.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8711838","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":581238411,"identity":"52160b48-866c-49df-9cf5-3032093acf2f","order_by":0,"name":"Imrul Mosaddek Ahmed†*","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYBACNhDxgIEhAUgZPqiACBoQ1pIA0WJscIYYLQxIWswkiNLCJ3b2mUQCg12ebnvztooDNdsSG9ibt0ngdZh0uhlQS3Kx2ZljZTcOHLud2MBzrIyAljQ2oBbmxG03csxuf2ADapHIMSNGS33itvtvzAoO/ANqkX9DlJbDQFt4zBgOtoFs4SGohdkiweB44rYzacUSB/tuG7fxpBVb4NMiPzuN8caHiurEbccPb/xw4Ntt2X72wxtv4NMCAcgRwUZY+SgYBaNgFIwCQgAAwzJKlAT7bHgAAAAASUVORK5CYII=","orcid":"","institution":"Florida Agriculture and Mechanical University","correspondingAuthor":true,"prefix":"","firstName":"Imrul","middleName":"Mosaddek","lastName":"Ahmed†*","suffix":""},{"id":581238412,"identity":"0b6f3153-e246-46bd-9820-d1c8d78feabd","order_by":1,"name":"Tushar Dhanani†","email":"","orcid":"","institution":"Florida Agriculture and Mechanical University","correspondingAuthor":false,"prefix":"","firstName":"Tushar","middleName":"","lastName":"Dhanani†","suffix":""},{"id":581238413,"identity":"2c77e59e-48e3-424e-abc8-73dbb736d9dd","order_by":2,"name":"Mehboob Sheikh","email":"","orcid":"","institution":"Florida Agriculture and Mechanical University","correspondingAuthor":false,"prefix":"","firstName":"Mehboob","middleName":"","lastName":"Sheikh","suffix":""},{"id":581238414,"identity":"91410e0b-870d-429b-bbb3-de9930919dbf","order_by":3,"name":"Md Amanullah","email":"","orcid":"","institution":"Johns Hopkins University","correspondingAuthor":false,"prefix":"","firstName":"Md","middleName":"","lastName":"Amanullah","suffix":""}],"badges":[],"createdAt":"2026-01-27 14:50:34","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8711838/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8711838/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101304701,"identity":"3140b2b6-da0c-41bd-b388-ef66bfd34d78","added_by":"auto","created_at":"2026-01-28 10:02:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":355274,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhytochemical content and antioxidant activity of muscadine grape genotypes. \u003c/strong\u003eTotal phenolic content (TPC), total flavonoid content (TFC), and DPPH radical scavenging activity were quantified in 50 muscadine grape genotypes. TPC is expressed as mg gallic acid equivalents (GAE) g⁻¹ fresh weight (FW), TFC as mg catechin equivalents (CE) g⁻¹ FW, and DPPH activity as percentage radical inhibition. Data represents SD (n = 4).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8711838/v1/d936fecb4f368d4b9e70a783.png"},{"id":101303823,"identity":"45f6df22-6d92-4dc5-837c-b61b975606d6","added_by":"auto","created_at":"2026-01-28 10:00:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":347933,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVariation in major stilbene compounds among muscadine grape genotypes. \u003c/strong\u003eConcentrations of resveratrol, viniferin, and pterostilbene were determined in 50 muscadine grape genotypes. Stilbene contents are expressed as µg g⁻¹ FW. Error bars indicate mean ± SD (n = 4).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8711838/v1/ba97dab04fbfd5fe361a9a3e.png"},{"id":101302887,"identity":"674751d3-a635-4cb5-984f-8ba95bb43559","added_by":"auto","created_at":"2026-01-28 09:55:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":357048,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCatechin composition of muscadine grape genotypes. \u003c/strong\u003eLevels of catechin, epicatechin, and epicatechin gallate were quantified across 50 muscadine grape genotypes. Concentrations are expressed as µg g⁻¹ FW. Values represent mean ± SD (n = 4).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8711838/v1/38ff09e8a0b83d01b3ffdb90.png"},{"id":101302885,"identity":"018c06a3-f32e-4dd9-8f1f-f3bf39353164","added_by":"auto","created_at":"2026-01-28 09:55:55","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":170322,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRepresentative HPLC chromatograms of muscadine grape phenolic extracts. \u003c/strong\u003eChromatograms were monitored at (a) 319 nm for stilbenes and (b) 280 nm for catechins. Major peaks corresponding to resveratrol, viniferin, pterostilbene, catechin, epicatechin, and epicatechin gallate were used for compound identification and quantification.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8711838/v1/2fc6eb9532e2b0ec8194bae9.png"},{"id":101302967,"identity":"ecd5524e-3dee-4c92-8456-a0a112469365","added_by":"auto","created_at":"2026-01-28 09:56:33","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":464132,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffects of muscadine grape extracts on cancer cell viability. \u003c/strong\u003eCancer cell survival following 48 h treatment with muscadine grape extracts in A549 (lung), LNCaP (prostate), and Caco-2 (colon) cancer cell lines. Cell viability is expressed as percentage relative to untreated controls. Data are presented as mean ± SD (n = 4).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8711838/v1/9ed4ad45d6a196a1e36a9f20.png"},{"id":101302962,"identity":"3a288606-0a73-4e10-9c30-16c67a162108","added_by":"auto","created_at":"2026-01-28 09:56:32","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":115569,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCytotoxic potency of selected muscadine grape genotypes. \u003c/strong\u003eIC₅₀ values of elite muscadine grape genotypes against A549, LNCaP, and Caco-2 cancer cell lines after 48 h exposure. IC₅₀ values (µg mL⁻¹) indicate extract concentrations required to reduce cell viability by 50%, with lower values reflecting higher cytotoxic activity.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8711838/v1/23ffd6a0cceff3c7dcb18db9.png"},{"id":101303388,"identity":"4a2239fc-1fd8-4dab-babc-d8a3988940fc","added_by":"auto","created_at":"2026-01-28 09:58:55","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1945465,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation analysis of phytochemical, antioxidant, and anticancer traits. \u003c/strong\u003eCorrelogram showing Pearson’s correlation coefficients among measured traits across 50 muscadine grape genotypes. Green indicates positive correlations, while pink indicates negative correlations. Color intensity reflects correlation strength.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-8711838/v1/83d746f489631cdfdb1cdf2b.png"},{"id":101302833,"identity":"2f146077-286f-49d0-8414-ec84a5051126","added_by":"auto","created_at":"2026-01-28 09:55:24","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1576229,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHierarchical clustering of muscadine grape genotypes based on multi-trait profiles. \u003c/strong\u003eHeatmap illustrating hierarchical clustering of 50 muscadine genotypes based on phytochemical, antioxidant, and anticancer attributes. In Heatmap analysis, each row refers to all measure parameters, each column indicates the genotypes, the red and blue colors with values (ranged from –2 to +6) describe the higher and lower of different parameters intensities, the higher the red color intensity (from +5 to +6 values), the higher value of different parameters. In contrast, the higher blue color intensity (from –1 to –2 values) represents the lower value of different parameters.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-8711838/v1/55cbf35b082a32a73b8f39d5.png"},{"id":101302974,"identity":"4c096e97-56e9-4461-b0a4-0731bc03e179","added_by":"auto","created_at":"2026-01-28 09:56:35","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":1219312,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrincipal component analysis of muscadine grape traits. (a) PCA biplot showing the distribution of muscadine grape genotypes and trait loadings along the first two principal components. (b) Variable PCA plot illustrating the contribution and direction of individual traits to overall phenotypic variation.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-8711838/v1/605d694f04b88da77f2904bc.png"},{"id":101302958,"identity":"7658d2a8-c5d1-4b90-97c1-3d2b2aea8fde","added_by":"auto","created_at":"2026-01-28 09:56:30","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":471238,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eScree plot of principal component analysis. \u003c/strong\u003eEigenvalues and percentage variance explained by each principal component. The first two principal components account for the majority of the total phenotypic variation.\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-8711838/v1/2f15202cc0eb7b4d4cc9d8b0.png"},{"id":101303606,"identity":"42ce53d4-2d4b-402c-ac4a-e4fe674fe0b0","added_by":"auto","created_at":"2026-01-28 10:00:02","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":1640195,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMulti-trait genotype evaluation using MGIDI analysis. \u003c/strong\u003e(a) Ranking of muscadine grape genotypes based on the Multi-trait Genotype–Ideotype Distance Index (MGIDI), integrating phytochemical, antioxidant, and anticancer traits. Lower MGIDI values indicate superior overall performance. (b) Strengths–weaknesses radar plot illustrating relative trait contributions of selected genotypes.\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-8711838/v1/011366dc3cc41e1802bfe7c9.png"},{"id":101305160,"identity":"b541fbcd-05aa-48dd-93bd-c557df31be2e","added_by":"auto","created_at":"2026-01-28 10:04:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":11776574,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8711838/v1/7109eb1c-0f03-448e-93ff-6074401b4516.pdf"},{"id":101303386,"identity":"91c459d8-bfdd-4bcf-a985-508a86cf5f40","added_by":"auto","created_at":"2026-01-28 09:58:54","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16878,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFig.docx","url":"https://assets-eu.researchsquare.com/files/rs-8711838/v1/ef358f300ad1075122ee4dd6.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003ePhytochemical Content of Muscadine Grape Promoting Apoptosis and Inhibiting Cancer Cell Growth to Prevent Cancer Progression\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Highlights","content":"\u003cul start=\"5\"\u003e\n \u003cli\u003eFifty muscadine genotypes show strong variation in phytochemicals, antioxidants, and bioactivity\u003c/li\u003e\n \u003cli\u003eHPLC profiling identifies resveratrol and epicatechin as major antioxidant contributors\u003c/li\u003e\n \u003cli\u003eMuscadine extracts inhibit lung, prostate, and colon cancer cell growth \u003cem\u003ein vitro\u003c/em\u003e\u003c/li\u003e\n \u003cli\u003ePhenolic content and antioxidant capacity correlate with reduced cancer cell viability\u003c/li\u003e\n \u003cli\u003eMGIDI analysis identifies elite genotypes for functional food and nutraceutical use\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eCancer remains a major global health burden, accounting for nearly one in six deaths worldwide, with incidence projected to exceed 20\u0026nbsp;million new cases annually by 2030 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Although conventional cancer therapies such as chemotherapy and radiotherapy have improved patient survival, their effectiveness is often limited by severe side effects, therapy resistance, and high recurrence rates. Consequently, there is increasing interest in complementary and preventive strategies based on dietary bioactive compounds. In this context, dietary phytochemicals plant-derived secondary metabolites with antioxidant, anti-inflammatory, and apoptosis-modulating properties have gained considerable attention as safe and effective agents for cancer prevention and management [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Among fruit crops, grapes (\u003cem\u003eVitis\u003c/em\u003e spp.) are particularly valued for their rich polyphenolic composition, including flavonoids, phenolic acids, anthocyanins, and stilbenes, which contribute to both fruit quality and health-promoting properties [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. While \u003cem\u003eVitis vinifera\u003c/em\u003e, the European grape species, has been extensively investigated for its antioxidant, cardioprotective, and anticancer effects, comparatively less attention has been paid to muscadine grape (\u003cem\u003eVitis rotundifolia\u003c/em\u003e Michx.), a species native to Southeastern United States. Notably, muscadine grapes possess a genetically distinct background and a more complex phytochemical profile than \u003cem\u003eV. vinifera\u003c/em\u003e, suggesting untapped potential for functional and nutraceutical applications [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMuscadine grapes are genetically and physiologically distinct from \u003cem\u003eV. vinifera\u003c/em\u003e, characterized by thick berry skins, a high proportion of ellagitannins, and exceptional resistance to fungal and bacterial pathogens. These traits are closely associated with elevated accumulation of secondary metabolites. Previous phytochemical analyses have shown that muscadine berries are particularly rich in total phenolics, flavonoids, and stilbenes including resveratrol, viniferin, and pterostilbene, as well as catechins and proanthocyanidins [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Importantly, these compounds have demonstrated strong antioxidant activity and the capacity to modulate key molecular pathways involved in carcinogenesis, such as oxidative stress signaling, cell cycle regulation, apoptosis, angiogenesis, and metastasis, across diverse experimental models [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmong grape-derived phytochemicals, resveratrol and its dimethylated analog pterostilbene are among the most extensively studied stilbenes with documented anticancer activity. These compounds function as natural chemopreventive agents by suppressing oxidative stress, inhibiting pro-survival signaling pathways including NF-κB and PI3K/AKT, and activating p53-dependent apoptotic mechanisms [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Pterostilbene exhibits enhanced lipophilicity and metabolic stability relative to resveratrol, resulting in improved cellular uptake and bioavailability. In parallel, catechins such as epicatechin and epicatechin gallate contribute synergistically by inducing mitochondrial dysfunction, increasing intracellular reactive oxygen species (ROS), and activating caspase-dependent apoptosis in cancer cells [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Collectively, these phytochemicals preferentially target malignant cells while exerting limited toxicity toward normal tissues, highlighting their suitability for dietary-based cancer prevention strategies.\u003c/p\u003e \u003cp\u003eDespite this growing body of evidence, the composition and concentration of bioactive compounds in muscadine grapes vary widely among genotypes due to substantial genetic and metabolic diversity. Such variation has important implications for both nutritional value and therapeutic efficacy. However, most existing studies have focused on a limited number of cultivars or pooled samples, thereby overlooking the extensive biochemical diversity present within muscadine germplasm. Comprehensive, genotype-resolved characterization is therefore essential to identify elite genotypes with superior antioxidant and anticancer potential. Advanced multivariate analytical approaches, including principal component analysis (PCA), correlation analysis, and the multi-trait genotype ideotype distance index (MGIDI), provide powerful tools to integrate biochemical and biological traits for objective genotype selection [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo address these gaps, the present study systematically evaluated fifty muscadine grape genotypes to elucidate genotype-dependent variation in phytochemical composition, antioxidant capacity, and anticancer activity. Total phenolic and flavonoid contents, DPPH radical scavenging activity, and key phenolic subclasses, including stilbenes and catechins, were quantified. The antiproliferative effects of berry extracts were assessed using human lung (A549), prostate (LNCaP), and colon (Caco-2) cancer cell lines by examining effects on cell viability and apoptosis. Furthermore, correlation, clustering, and multivariate analyses were employed to elucidate relationships among phytochemical traits, antioxidant activity, and cancer cell growth inhibition. This integrative approach provides new insight into the functional diversity of \u003cem\u003eV. rotundifolia\u003c/em\u003e and establishes a robust scientific foundation for developing muscadine-based functional foods and nutraceuticals aimed at cancer prevention and health promotion.\u003c/p\u003e"},{"header":"2. Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Variation in total phenolic and flavonoid contents and antioxidant activity\u003c/h2\u003e \u003cp\u003eSubstantial genotypic variation was observed among the fifty muscadine grape genotypes for total phenolic content (TPC), total flavonoid content (TFC), and DPPH radical-scavenging activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). TPC ranged from approximately 1.2 to 4.3 mg GAE g⁻\u0026sup1; FW, while TFC varied between 14 and 23 mg CE g⁻\u0026sup1; FW. Genotypes such as Southern Home, Pineapple, Black Beauty, Darlene and Fry exhibited the highest phenolic and flavonoid accumulation, corresponding to the strongest DPPH scavenging activities (70\u0026ndash;85%). Conversely, Golden Isle, Watergate, Doreen and Magnolia displayed comparatively lower phenolic contents and weaker antioxidant responses. A highly significant positive correlation was observed among TPC, TFC, and DPPH activity (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), indicating that phenolic concentration was a major determinant of antioxidant potential.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Genotypic variation in stilbene and catechin composition\u003c/h2\u003e \u003cp\u003eThe quantification of key stilbenes resveratrol, viniferin, and pterostilbene revealed pronounced genotype-dependent differences (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Resveratrol concentrations ranged from 2.6 to 7.9 \u0026micro;g g⁻\u0026sup1; FW, with Southern Home, Dixieland, Fry, Loomis, Hunt, Tara, Higgins, and Delight showing the highest accumulation. Viniferin displayed a wider range (1\u0026ndash;24 \u0026micro;g g⁻\u0026sup1; FW) and emerged as the dominant stilbene in most high-performing genotypes. Pterostilbene levels, although relatively low (2.5\u0026ndash;3.5 \u0026micro;g g⁻\u0026sup1; FW), were significantly elevated in Southern home and African Queen. Overall, stilbene profiles differed markedly among genotypes, suggesting that different accessions harbor distinct stilbene biosynthetic capacities.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCatechin derivatives including catechin, epicatechin, and epicatechin gallate also exhibited broad quantitative variability across genotypes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Catechin was the predominant compound, ranging between 20 and 280 \u0026micro;g g⁻\u0026sup1; FW, followed by epicatechin (20\u0026ndash;2000 \u0026micro;g g⁻\u0026sup1; FW) and epicatechin gallate (1\u0026ndash;70 \u0026micro;g g⁻\u0026sup1; FW). High-performing genotypes (Southern Home, Pineapple Doreen, Fry, and Alachua) contained markedly greater catechin levels than low-performing ones. The representative HPLC chromatograms confirmed the presence and resolution of major phenolic compounds in muscadine grape extracts (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Stilbenes were effectively separated and detected at 319 nm, while catechins and related flavan-3-ols were monitored at 280 nm. Peaks corresponding to resveratrol, viniferin, pterostilbene, catechin, epicatechin, and epicatechin gallate were identified based on retention times and spectral characteristics relative to authentic standards, enabling reliable quantification across genotypes\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Antiproliferative activity cancer cell survival assays\u003c/h2\u003e \u003cp\u003eExposure of three human cancer cell lines (A549 lung, LNCaP prostate, and Caco-2 colon) to muscadine berry extracts for 48 h produced genotype-dependent reductions in cancer cell survival (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Mean cell survival ranged from approximately 25% to 85% depending on genotype and cell line. Extracts derived from Southern Home, Pineapple, and Pride exhibited the strongest inhibitory effects, reducing cell viability below 30% in A549 and LNCaP lines. Among the tested lines, LNCaP cells were the most sensitive, followed by Caco-2 and A549. In contrast, extracts from genotypes characterized by lower phenolic content (Ison, Janebell, Jumbo, Watergate and Florida Fry) exhibited minimal antiproliferative, maintaining cell survival levels above 75%. Overall response patterns closely mirrored antioxidant potential, suggesting that genotypes with higher polyphenol abundance were associated with stronger growth-inhibitory effects.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Cytotoxic potency (IC₅₀) of selected genotypes\u003c/h2\u003e \u003cp\u003eBased on their superior phytochemical profiles and antiproliferative performance, five elite genotypes (Pineapple, Southern Home, Pride, Sweet Jenny and Alachua) were selected for further evaluation of cytotoxic potency through IC₅₀ determination (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). IC₅₀ values across the three cancer cell lines ranged from 300 to 500 \u0026micro;g mL⁻\u0026sup1;, with Southern Home and Pineapple consistently exhibiting the lowest (most potent) IC₅₀ values. Among the tested cell lines, LNCaP cells exhibited slightly lower IC₅₀ compared with A549 or Caco-2, consistent with their higher sensitivity observed in cell survival assays. These findings confirm that the antiproliferative effects of muscadine grape extracts are concentration-dependent and more pronounced in genotypes with elevated phenolic content.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Correlations among phytochemical traits, antioxidant activity and anticancer effects\u003c/h2\u003e \u003cp\u003eA comprehensive correlogram (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) revealed strong interrelationships among phytochemical traits, antioxidant capacity, and anticancer activity. TPC, TFC, and DPPH activity showed strong positive correlations (r\u0026thinsp;\u0026gt;\u0026thinsp;0.80). In contrast, these antioxidant traits were consistently \u003cem\u003eand\u003c/em\u003e negatively correlated with cancer cell survival (r = \u0026minus;\u0026thinsp;0.65 to \u0026minus;\u0026thinsp;0.80) across all lines, confirming that genotypes with higher phenolic abundance were associated with stronger antiproliferative activity. Significant negative correlations were also found between individual compounds including resveratrol, viniferin, and epicatechin and cancer cell survival, highlighting the contribution of specific phenolic constituents to cancer cell growth inhibition. Collectively, these correlation patterns support a close linkage between phytochemical richness, antioxidant capacity, and biological activity in muscadine grape extracts, while reinforcing the concept that anticancer effects arise from the combined action of multiple phenolic constituents rather than a single dominant compound.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Cluster and heatmap analysis of genotypes\u003c/h2\u003e \u003cp\u003eHierarchical clustering based on all measured phytochemical, antioxidant, and biological parameters grouped the fifty muscadine genotypes into three distinct clusters (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Cluster I comprised high-performing genotypes characterized by elevated TPC, TFC, DPPH, stilbenes, and catechins coupled with low cancer cell survival. Genotypes within this cluster therefore exhibited a coordinated enrichment of antioxidant capacity and growth-inhibitory potential. Cluster II included genotypes with moderate phytochemical content and intermediate biological activity, whereas Cluster III contained low-activity genotypes. The heatmap visualization further illustrated genotype-specific trait intensity, with red gradients (+\u0026thinsp;5 to +\u0026thinsp;6) representing high antioxidant and anticancer performance and blue gradients ( \u0026minus;\u0026thinsp;1 to \u0026minus;\u0026thinsp;2) denoting weak responses. Southern Home, Sweet Jenny, and Pineapple consistently clustered within the most bioactive group, reinforcing their superior functional profiles and their repeated identification as high-value genotypes across independent biochemical, biological, and multivariate analyses.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Principal component analysis of integrated traits\u003c/h2\u003e \u003cp\u003ePrincipal component analysis (PCA) was employed to integrate phytochemical composition, antioxidant capacity, and anticancer activity across the fifty muscadine grape genotypes (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). The first two principal components (PCs) accounted for 51.2% of the total phenotypic variation, with PC1 explaining 37.6% and PC2 explaining 13.6%, indicating that a substantial proportion of trait variability could be captured within a reduced dimensional space. The PCA biplot (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ea) revealed clear separation of genotypes along PC1, which was primarily driven by total phenolic content (TPC), total flavonoid content (TFC), DPPH radical scavenging activity, and major stilbenes and catechins. Genotypes positioned on the positive side of PC1 clustered with high phytochemical abundance and antioxidant capacity, whereas those on the negative side were associated with higher cancer cell viability, indicating weaker antiproliferative effects. The variable contribution plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eb) further clarified trait relationships. Stilbenes (resveratrol, viniferin), catechins, TPC, TFC, and DPPH loaded strongly and positively along PC1, demonstrating their dominant contribution to overall variance. In contrast, cancer cell survival metrics for A549, LNCaP, and Caco-2 loaded in the opposite direction, confirming a negative association between phytochemical richness and cancer cell viability. PC2 captured secondary variation largely associated with differences among specific stilbenes, suggesting genotype-dependent specialization in secondary metabolism rather than generalized antioxidant effects.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8. Variance contribution of principal components\u003c/h2\u003e \u003cp\u003eThe scree plot derived from principal component analysis (PCA) illustrates the relative contribution of each principal component (PC) to the total variance among the fifty muscadine grape genotypes (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). The scree plot confirmed that the first two principal components captured most of the phenotypic variation among genotypes, with subsequent components contributing progressively smaller proportions (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). This result supports the robustness of the PCA model and the effectiveness of the selected traits in explaining genotype-dependent variation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9. Multi-trait selection (MGIDI) and genotype strengths/weaknesses\u003c/h2\u003e \u003cp\u003eApplication of the MGIDI index integrated multiple phenotypic criteria, including TPC, TFC, stilbenes, catechins, DPPH, and IC₅₀ or cancer cell survival metrics, to rank genotypes based on overall performance. The MGIDI selection (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003ea) highlighted a subset of superior genotypes that optimally balance high phytochemical content and anticancer bioactivity. Notably, genotypes identified by MGIDI largely overlapped with those ranked highly in univariate and multivariate analyses, providing internal validation of the selection strategy. The strengths weaknesses radar/stack plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eb) illustrated trait domains in which selected genotypes excel (e.g., high total phenolics, strong radical scavenging, low cancer cell survival) and traits with room for improvement (e.g., some specific stilbenes or moderate activity in a particular cell line). Overall, MGIDI proved to be an effective and integrative approach for prioritizing muscadine genotypes for downstream breeding, bioactive compound isolation, or nutraceutical development.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Discussion","content":"\u003cp\u003eThis study provides a genotype-resolved evaluation of phytochemical composition, antioxidant capacity, and anticancer activity in muscadine grape (\u003cem\u003eVitis rotundifolia\u003c/em\u003e), revealing pronounced inter-genotypic variation and its functional consequences. While previous studies have reported antioxidant or cytotoxic effects of selected muscadine cultivars or isolated phenolic fractions, most investigations have been limited in scope. By systematically evaluating a large and diverse germplasm panel using an integrated phytochemical\u0026ndash;bioactivity framework, the present study advances understanding of how genotype-dependent metabolic diversity translates into functional bioactivity (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConsistent with earlier reports, muscadine grapes exhibited higher total phenolic and flavonoid contents than those typically reported for \u003cem\u003eVitis vinifera\u003c/em\u003e, highlighting their nutraceutical potential. Importantly, our results demonstrate that phytochemical enrichment is highly genotype dependent. The substantial variation observed in total phenolic content (TPC), total flavonoid content (TFC), and antioxidant capacity among the fifty genotypes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) underscores the strong influence of genetic background on secondary metabolism in \u003cem\u003eV. rotundifolia\u003c/em\u003e. Genotypes such as Southern Home and Pineapple consistently displayed elevated phenolic accumulation and enhanced antioxidant activity, in agreement with earlier compositional and metabolomic studies [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe strong correlations between TPC, TFC, and DPPH radical scavenging activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) indicate that phenolic compounds are major determinants of antioxidant function in whole-berry muscadine extracts. Similar relationships have been reported across grape species and other polyphenol-rich fruits, supporting a conserved role for polyphenols in redox regulation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. These compounds are primarily derived from the shikimate and phenylpropanoid pathways, which generate flavonoids, stilbenes, and proanthocyanidins [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The elevated accumulation of resveratrol and viniferin in elite genotypes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) suggests enhanced stilbene biosynthesis, potentially reflecting adaptive responses to biotic and abiotic stress that are characteristic of muscadine grapes [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBeyond total phenolic measures, targeted HPLC analysis further revealed distinct, genotype-specific stilbene and catechin profiles (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), indicating qualitative as well as quantitative metabolic differences. Resveratrol, viniferin, pterostilbene, catechin, and epicatechin emerged as dominant contributors to the phytochemical landscape. Oligomeric stilbenes such as viniferins have been reported to exhibit greater anticancer potency than monomeric resveratrol due to enhanced stability and bioactivity [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], while pterostilbene displays improved lipophilicity and cellular uptake [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Catechin derivatives, in turn, contribute to both antioxidant defense and cancer-related signaling by modulating mitochondrial function and activating apoptotic pathways [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The co-accumulation of these compounds in high-performing genotypes supports a model of multicomponent phytochemical synergy, rather than single-compound effects.\u003c/p\u003e \u003cp\u003eCrucially, the biological relevance of this phytochemical diversity was confirmed using \u003cem\u003ein vitro\u003c/em\u003e cancer models. Muscadine grape extracts significantly reduced viability of lung (A549), prostate (LNCaP), and colon (Caco-2) cancer cells in a genotype-dependent manner (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Genotypes enriched in phenolics and stilbenes consistently exhibited stronger antiproliferative effects, supporting the central role of phytochemical composition in determining biological activity. The IC₅₀ values observed (300\u0026ndash;450 \u0026micro;g mL⁻\u0026sup1;; Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) are comparable to those reported for crude polyphenol-rich plant extracts and are considered biologically relevant for nutraceutical screening [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Importantly, elite genotypes demonstrated activity across multiple cancer cell lines, suggesting broad antiproliferative potential rather than cell type\u0026ndash;specific toxicity.\u003c/p\u003e \u003cp\u003eMechanistically, the strong negative correlations between antioxidant capacity and cancer cell survival (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) suggest that redox modulation contributes to the observed antiproliferative effects. Polyphenols can selectively disrupt redox homeostasis in cancer cells, thereby promoting apoptosis while sparing normal cells [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Previous studies have shown that resveratrol activates intrinsic apoptotic pathways through Bax induction and Bcl-2 suppression, whereas catechins inhibit PI3K/AKT and MAPK signaling cascades involved in cancer cell survival [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Together, these mechanisms provide a plausible biological basis for the genotype-dependent anticancer effects observed in this study.\u003c/p\u003e \u003cp\u003eFinally, multivariate analyses provided an integrative perspective on the coordination between biochemical and biological traits. Hierarchical clustering and PCA revealed clear grouping of genotypes based on combined phytochemical and anticancer attributes (Figs.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e and \u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e), with total phenolics and antioxidant capacity emerging as primary drivers of variance. The MGIDI index enabled objective identification of elite genotypes with balanced multi-trait performance (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e), while the scree plot confirmed that the first two principal components captured the majority of phenotypic variation (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e). Such integrative approaches are increasingly recognized as effective tools for functional trait selection and nutraceutical-oriented breeding [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e"},{"header":"4. Materials and methods","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Plant materials and experimental design\u003c/h2\u003e \u003cp\u003eFifty muscadine grape (\u003cem\u003eVitis rotundifolia\u003c/em\u003e Michx.) genotypes representing diverse berry colors and end uses were collected from the Center for Viticulture and Small Fruit Research, Florida A\u0026amp;M University, Tallahassee, FL, USA, and maintained under uniform cultural conditions (Fig. S1). The experimental site is located in Florida (30\u0026deg;28\u0026prime;45.63\u0026Prime; N, 84\u0026deg;10\u0026prime;16.43\u0026Prime; W). Fully ripened berries were harvested in the morning hours between 9\u0026ndash;10 at the same physiological maturity, cleaned, and immediately frozen at \u0026minus;\u0026thinsp;80\u0026deg;C until analysis to preserve phytochemical integrity [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. All samples were collected within a single growing season to minimize environmental variation. Each genotype was analyzed using four biological replicates (n\u0026thinsp;=\u0026thinsp;4).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Sample extraction\u003c/h2\u003e \u003cp\u003eWhole muscadine berries (10 g) were cryogenically ground to a fine powder using liquid nitrogen and extracted with methanol following established protocols for grape polyphenol extraction [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The mixture was vortexed for 1 min (1,814 \u0026times; g), homogenized using an 850 Homogenizer (Fisher Scientific, USA), and sonicated for 30 min in a cold-water ultrasonic bath (Bransonic 3800, Emerson, USA) to enhance extraction efficiency. Samples were centrifuged at 15,000 rpm for 15 min using an Avanti J-26 XP centrifuge (Beckman Coulter, USA). The extraction was repeated on the residual pellet, and supernatants were pooled and stored at \u0026minus;\u0026thinsp;80\u0026deg;C until further analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Determination of total phenolic, flavonoid content and antioxidant activity (DPPH radical scavenging assay)\u003c/h2\u003e \u003cp\u003eTotal phenol content was determined according to the previously reported method by Ahmed \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] Folin phenol reduction method with few modifications. Frozen samples (0.2 g) were ground with 2 mL 80% methanol and less sand in the ice bath followed by ultrasonication for 30 min. The homogenates were centrifuged at 4\u0026deg;C, 2000 \u0026times; \u003cem\u003eg\u003c/em\u003e 20 min and the resulting supernatant was used for total phenolic content and DPPH free radical scavenging activity assay. The reaction system was as follows: 150 \u0026micro;L Folin-Ciocalteu's reagent (Sigma), 200 \u0026micro;L supernatant, 2 mL 2% Na\u003csub\u003e2\u003c/sub\u003eCO\u003csub\u003e3\u003c/sub\u003e. The reaction mixture was incubated in dark at 25\u0026deg;C for 20 min. After that the absorbance was measured immediately at OD\u003csub\u003e735\u003c/sub\u003e and gallic acid was used to prepare standard curve for total phenol content.\u003c/p\u003e \u003cp\u003eFlavonoid content was determined according to \u003cem\u003eZhishen et al\u003c/em\u003e. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. 0.2 g frozen sample was homogenized with 2 mL 1% HCl in methanol through ice bath grinding followed by unltrasonication for 30 min. The homogenates were centrifuged at 4\u0026deg;C 2000 \u0026times; g for 20 min. The supernatants were used for determination of flavonoid content. Then 300 \u0026micro;L 5% NaNO\u003csub\u003e2\u003c/sub\u003e, 300 \u0026micro;L 10% AlCl\u003csub\u003e3\u003c/sub\u003e and 300 \u0026micro;L supernatant were added in one tube. After 6 min 2 mL 1 M NaOH was added in the previous mixture so that reaction could take place. After 1 min absorbance was measured at OD\u003csub\u003e510\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003eDPPH activity was measured according to the previously reported method by Ahmed \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The reaction system was as follows: 2.5 mL 65 \u0026micro;M DPPH (prepared from 80% methanol) and 50 \u0026micro;L supernatant. The system was incubated in dark at 25\u0026deg;C for 30 min, the absorbance was measured immediately at OD517, denoted by A. Absorbance value of 2.5 mL 80% methanol and 50 \u0026micro;L supernatant at OD517 denoted by B; and absorbance value of 2.5 mL 65 \u0026micro;M DPPH and 50 \u0026micro;L 80% methanol at OD517 denoted by C. DPPH activity was calculated by the formula [1 - (AB) / C] \u0026times; 100, expressed as percentage. All measurements were conducted in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Quantification of stilbenes and catechins by HPLC\u003c/h2\u003e \u003cp\u003eStilbenes and catechins were quantified using a Waters 1525 HPLC system equipped with a 2996 PDA detector and a 717 Plus autosampler (Waters Corp., Milford, MA, USA), following validated grape polyphenol separation protocols [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Separation was achieved on a Prodigy ODS3 column (5 \u0026micro;m, 100 \u0026Aring;, 250 \u0026times; 4.6 mm; Phenomenex, USA). The mobile phase consisted of (A) water and (B) acetonitrile, with gradient elution programmed as follows: 0\u0026ndash;15 min, 10\u0026ndash;20% B; 30\u0026ndash;50 min, sequential increases to 30, 40, 50, 70, and 10% B, followed by re-equilibration for 5 min. A 20 \u0026micro;L aliquot was injected, and detection was performed at 280 and 320 nm. Quantification of individual analytes was achieved using their reference standards.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.5. Anticancer activity\u003c/h2\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e4.5.1. Cell culture\u003c/h2\u003e \u003cp\u003eThree different human cancer cells, including lung (A549), prostate (LNCaP), and colon (Caco-2) cancer cell lines were obtained from the American Type Culture Collection (ATCC, Manassas, VA, USA). Cells were cultured in DMEM basal medium supplemented with 10% (v/v) heat-inactivated fetal bovine serum and 1% penicillin\u0026ndash;streptomycin (100 U mL⁻\u0026sup1; penicillin and 0.1 mg mL⁻\u0026sup1; streptomycin). Cultures were maintained at 37\u0026deg;C in a humidified atmosphere containing 5% CO₂ (VWR, Suwanee, GA, USA). Cell growth and viability were assessed using a Bio-Rad TC-20 automated cell counter (Bio-Rad, Hercules, CA, USA) following crystal violet staining (1%) after 48 h of incubation [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e4.5.1. Cell viability assay\u003c/h2\u003e \u003cp\u003eCells were seeded in 96-well plates at a density of 3 \u0026times; 10⁴ cells per well and allowed to attach overnight in experimental medium. Muscadine extracts were prepared in three independent biological replicates, and each replicate was tested in triplicate on each plate. Extracts were added to the cells at final concentrations of 500 \u0026micro;g mL⁻\u0026sup1;. Cells were incubated at 37\u0026deg;C for 48 h. At each time point, 10 \u0026micro;L of Alamar Blue solution (0.5 mg mL⁻\u0026sup1;) was added to each well to achieve a final concentration of 10% (v/v), followed by incubation for an additional 4 h. Fluorescence was measured at excitation/emission wavelengths of 550/580 nm using an Infinite M200 microplate reader (Tecan, M\u0026auml;nnedorf, Switzerland). Control cells were treated with DMSO at the same final concentration used for the extracts (\u0026lt;\u0026thinsp;1%), while blank wells contained culture medium only [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCell viability was expressed as a percentage relative to untreated controls, and the rate of cell growth inhibition was calculated using the following equation:\u003c/p\u003e \u003cp\u003eCell viability (%) = (treated cells - blank cells)/(control cells - blank cells) \u0026times; 100\u003c/p\u003e \u003cp\u003eCell growth inhibition (%)\u0026thinsp;=\u0026thinsp;100 - (% Cell viability).\u003c/p\u003e \u003cp\u003eIC₅₀ values were estimated from dose response curves using GraphPad Prism 10.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.6. Statistical and multivariate analyses\u003c/h2\u003e \u003cp\u003eAll experiments were conducted in quadruplicate, and results are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Analysis of variance (ANOVA) was performed using SAS v9.4 to assess significant differences among genotypes (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Pearson\u0026rsquo;s correlation coefficients were calculated to evaluate associations among phytochemical traits, antioxidant activity, and cancer cell viability. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were conducted using the FactoMineR package in R [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The multi-trait genotype\u0026ndash;ideotype distance index (MGIDI) was applied according to Olivoto and L\u0026uacute;cio [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] to identify genotypes with optimal combinations of phytochemical richness and anticancer activity. Data visualization was performed using ggplot2 and corrplot packages.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study demonstrates that genotype-dependent phytochemical diversity is a primary determinant of antioxidant capacity and antiproliferative activity in muscadine grape (\u003cem\u003eVitis rotundifolia\u003c/em\u003e). By integrating comprehensive phytochemical profiling with functional bioassays and multivariate analyses, we establish a direct link between metabolic composition and biological efficacy across a diverse germplasm panel. The findings indicate that coordinated accumulation of phenolics, including stilbenes and catechins, rather than individual compounds alone, underlies variability in anticancer activity among genotypes. The multivariate framework applied here provides an objective and scalable strategy for identifying genotypes with favorable biochemical and functional attributes, supporting nutraceutical-oriented selection and breeding. Although this study is based on \u003cem\u003ein vitro\u003c/em\u003e cancer models, it provides a robust foundation for future investigations focused on mechanistic validation, apoptosis-related pathways, bioavailability, and \u003cem\u003ein vivo\u003c/em\u003e efficacy. Overall, this work advances understanding of the functional significance of phytochemical diversity in muscadine grape and supports its potential as a valuable bioresource for functional food development.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e I.M.A. Conceptualization, methodology, formal analysis, data curation, original draft writing, review and editing. T.D. methodology, formal analysis, original draft, writing review and editing. M.A. statistical analysis and reviewing the draft. M.B.S contributed to the concept, resources, and reviewing the draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e Funding The research was financially supported by the USDA/NIFA Capacity Building Grant # 2021-38821-34580 and VAC/FDACS Grants Program #000005844.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors have no relevant financial or nonfinancial interests to disclose.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e Not applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization (2024) Cancer. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/news-room/fact-sheets/detail/cancer\u003c/span\u003e\u003cspan address=\"https://www.who.int/news-room/fact-sheets/detail/cancer\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScalbert A et al (2023) Dietary polyphenols and disease prevention. 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Food Chem 374:131632. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.foodchem.2021.131632\u003c/span\u003e\u003cspan address=\"10.1016/j.foodchem.2021.131632\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eL\u0026ecirc; S, Josse J, Husson F (2008) FactoMineR: an R package for multivariate analysis. J Stat Softw 25:1\u0026ndash;18\u003c/span\u003e\u003c/li\u003e \u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Florida Agricultural and Mechanical University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Muscadine grape, phytochemicals, stilbenes, catechins, antioxidant activity, cancer prevention","lastPublishedDoi":"10.21203/rs.3.rs-8711838/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8711838/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMuscadine grape (\u003cem\u003eVitis rotundifolia\u003c/em\u003e) is a rich source of bioactive phytochemicals; however, links between genotype-dependent phytochemical diversity and anticancer activity remain poorly defined. Here, fifty muscadine grape genotypes were systematically evaluated for phenolic composition, antioxidant capacity, and anticancer efficacy. Total phenolic content, total flavonoid content, and DPPH radical scavenging activity varied markedly among genotypes, indicating substantial biochemical diversity. Targeted HPLC analysis revealed pronounced genotypic differences in major stilbenes (resveratrol, viniferin, and pterostilbene) and catechin derivatives, with resveratrol and epicatechin contributing most strongly to antioxidant capacity. Biological relevance was confirmed using \u003cem\u003ein vitro\u003c/em\u003e cancer models. Muscadine grape extracts significantly reduced cell viability in A549 (lung), LNCaP (prostate), and Caco-2 (colon) cancer cell lines in a genotype-dependent manner following 48 h exposure, with IC₅₀ values ranging from 300 to 450 µg mL⁻¹. Notably, genotypes such as Southern Home exhibited elevated phytochemical accumulation and pronounced antiproliferative activity. Pearson’s correlation and multivariate analyses, including hierarchical clustering, principal component analysis, and the multi-trait genotype–ideotype distance index (MGIDI), identified elite genotypes with favorable integrated biochemical and biological profiles. Collectively, these findings demonstrate that phytochemical-rich muscadine grape genotypes exert pronounced antiproliferative effects and support their potential application in functional foods and nutraceutical strategies for cancer prevention.\u003c/p\u003e","manuscriptTitle":"Phytochemical Content of Muscadine Grape Promoting Apoptosis and Inhibiting Cancer Cell Growth to Prevent Cancer Progression","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-28 09:41:28","doi":"10.21203/rs.3.rs-8711838/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c644f279-ab47-4d27-a761-26bf751def01","owner":[],"postedDate":"January 28th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":61834993,"name":"Food Science \u0026 Technology"},{"id":61834994,"name":"Horticulture"},{"id":61834995,"name":"Cancer Biology"}],"tags":[],"updatedAt":"2026-01-28T09:41:29+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-28 09:41:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8711838","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8711838","identity":"rs-8711838","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}