Revisiting the Warburg-Based “Sugar Feeds Cancer” Hypothesis: A Critical Appraisal of Epidemiological, Experimental and Mechanistic Evidence

Simple Summary

The idea that “sugar feeds cancer” is widely believed and has led many people, including cancer patients, to drastically restrict sugar from their diets. This belief is often based on a misunderstanding of how cancer cells use glucose rather than on solid clinical evidence. In this review, we critically examine decades of human, experimental, and biological research to determine whether eating sugar directly causes cancer to grow or spread. We show that, while high sugar intake can worsen metabolic health and indirectly influence cancer risk, there is no convincing evidence that dietary sugar directly fuels cancer in humans. Misinterpreting this concept may cause unnecessary fear, nutritional harm, and reduced quality of life. Our findings highlight the importance of evidence-based dietary guidance that focuses on overall metabolic health rather than sugar avoidance alone.

Abstract

Background: The belief that “sugar feeds cancer” is widespread and has strongly influenced public perceptions, patient behavior, and dietary recommendations, despite uncertainty regarding its scientific validity. This belief largely stems from misinterpretation of the Warburg effect, which describes altered glucose metabolism in cancer cells rather than dietary sugar dependence. The objective of this review was to critically evaluate whether dietary sugar intake directly contributes to cancer development or progression by examining the totality of epidemiological, experimental, and mechanistic evidence. Methods: We conducted a narrative review of human epidemiological studies, experimental animal and cell-based models, and mechanistic investigations published between 1980 and July 2025. Evidence was synthesized across cancer types, sugar sources, and biological pathways, with careful consideration of study design, exposure relevance, and key confounders, including obesity, insulin resistance, and overall dietary patterns. Results: Across cancer types, epidemiological evidence showed predominantly null or inconsistent associations between sugar intake and cancer risk or outcomes, with positive findings largely confined to metabolically susceptible subgroups and often attenuated after adjustment for adiposity and energy intake. Experimental studies suggested potential tumor-promoting effects under non-physiological conditions, while mechanistic data indicated that sugar influences cancer risk indirectly through insulin signaling, inflammation, and metabolic dysfunction rather than direct tumor fueling. Conclusions: Current evidence does not support the hypothesis that dietary sugar directly “feeds” cancer in humans. Overemphasis on sugar avoidance risks nutritional and psychological harm, particularly among cancer patients. Evidence-based guidance should prioritize overall dietary quality, metabolic health, and patient well-being rather than isolated sugar restriction.

1. Introduction

The idea that “sugar feeds cancer” has become deeply embedded in public consciousness and has influenced dietary practices among patients and the general population alike [1,2,3,4]. This widespread belief stems from the core biological observation, known as the Warburg effect, where cancer cells often exhibit increased glucose uptake and preferentially rely on aerobic glycolysis for energy production [5,6]. Although this metabolic reprogramming is a hallmark of many tumors [7,8], its misinterpretation has led to the common assumption that dietary sugar directly fuels cancer growth in humans [9,10]. Consequently, many cancer patients have been adopting restrictive low-sugar diets (often without clinical indication or scientific consensus), which might be concerning given that cancer patients in specific are uniquely vulnerable to malnutrition, treatment-related anorexia, and cachexia [11,12]. Following restrictive diets that limit sugar-containing foods, especially those that are calorie-dense, can exacerbate these health challenges [13].

These restrictive dietary patterns are often influenced more by fear than by evidence [4,14]. To date, research on this topic remains inconclusive. Epidemiological studies report mixed results: while some suggest modest associations between high intake of sugar-sweetened beverages and risk of specific cancers (such as breast and endometrial), others find no association for cancers of the colon, prostate, pancreas, or liver. Additionally, experimental studies, while offering mechanistic insights, often rely on supra-physiological sugar doses or artificial cell culture conditions that limit their real-world applicability. Mechanistically, proposed links between sugar and carcinogenesis (such as via insulin signaling, inflammation, or oxidative stress) are reasonable but often confounded by broader metabolic dysfunction, including obesity [14,15] and insulin resistance [16,17,18].

The aim of this paper is to critically examine the hypothesis that dietary sugar intake directly contributes to cancer development or progression. We synthesised findings from epidemiological, experimental, and mechanistic studies to evaluate whether dietary sugar acts as an independent risk factor or serves as a proxy for broader metabolic dysregulation. Our hypothesis is that although excessive sugar intake may indirectly influence cancer risk through its effects on insulin signaling and inflammation, there is insufficient evidence to support the claim that dietary sugar directly “feeds” cancer in humans.

2. Methods

We conducted a narrative review of epidemiological, experimental, and mechanistic studies examining the relationship between dietary sugar intake and cancer risk or progression. Searches were performed in PubMed, Scopus, and Web of Science from January 1980 to July 2025. Search terms included combinations of: “sugar”, “dietary sugar”, “sucrose”, “fructose”, “sugar-sweetened beverages”, “glycemic load”, “glycemic index”, “cancer”, “tumor”, “carcinogenesis”, “Warburg effect”, and “metabolism”. Additional relevant articles were identified through citation tracking.

Inclusion criteria included human epidemiological studies, animal or cell-culture experiments evaluating sugar exposure, mechanistic studies examining glucose metabolism relevant to carcinogenesis, and systematic reviews or meta-analyses. Studies were excluded if they were non-original papers without relevant mechanistic content, case reports, or studies not isolating sugar-related exposures.

Two reviewers independently screened abstracts and full texts. Discrepancies were resolved by consensus. Risk of bias for epidemiological studies was qualitatively evaluated based on sample size, adjustment for confounders (particularly BMI, energy intake, smoking), dietary assessment quality, and outcome ascertainment.

Studies reporting null, positive, and inverse associations were all included and discussed to reflect the full spectrum of published evidence.

A narrative review design was intentionally selected due to the heterogeneity of available evidence (epidemiological, mechanistic, and experimental), which cannot be meaningfully synthesized through a systematic review or meta-analysis.

3. A General Overview of Sugar and Its Metabolic Role in Normal and Cancer Cells

3.1. Normal Cellular Energy Metabolism

Glucose is the primary substrate used by cells to generate ATP through a multistep process involving glycolysis, the tricarboxylic acid (TCA) cycle, and oxidative phosphorylation [19,20]. Glycolysis occurs in the cytosol and produces pyruvate, which is then transported into the mitochondria. There, it is converted into acetyl-CoA and enters the TCA cycle [21]. Reduced cofactors Nicotinamide Adenine Dinucleotide (NADH) and Falvin Adenine Dinucleotide (FADH₂) generated along the way [22] donate electrons to the electron transport chain (ETC) in the inner mitochondrial membrane, driving ATP synthesis [23]. This aerobic pathway produces approximately 36 to 38 ATP molecules per molecule of glucose [21,22]. Under anaerobic conditions (such as hypoxia or in certain tissues) cells rely on glycolysis alone, converting pyruvate to lactate and generating only 2 ATP per glucose molecule, due to the absence of mitochondrial oxidative phosphorylation [23].

3.2. Cancer Cell Metabolism and the Warburg Effect

The claim that sugar “fuels cancer” originates from Otto Warburg’s observation that many malignant cells preferentially utilize glucose through aerobic glycolysis, converting it into lactate despite adequate oxygen availability, a phenomenon termed the Warburg effect [4,24]. Although energetically inefficient, aerobic glycolysis supports rapid proliferation by supplying glycolytic intermediates for anabolic processes, including nucleotide, lipid, and amino acid biosynthesis [25]. In this context, glucose primarily serves as a carbon source for macromolecular synthesis rather than as a high-yield energy substrate [24,26]. An overview of these pathways is illustrated in Figure 1.

The Warburg effect does not imply a universal suppression of mitochondrial function [27]. Many cancer cells retain active mitochondria and engage in the tricarboxylic acid (TCA) cycle and oxidative phosphorylation to varying degrees, depending on tumor type, genetic mutations, and microenvironmental conditions [28,29]. This metabolic plasticity supports the heterogeneity of tumor bioenergetics, allowing cancer cells to switch between glycolysis and oxidative metabolism as needed [30].

3.3. Metabolic Rewiring and Misattributed Causality

The enhanced glucose metabolism observed in tumors arises from intrinsic oncogenic and epigenetic programs not dietary sugar availability. Mutations in MYC, RAS, and AKT, or loss of TP53, upregulate GLUT1 and glycolytic enzymes (HK2, PKM2), driving anabolic flux and metabolite diversion into biosynthesis independently of systemic nutrient intake [31,32].

High dietary sugar intake may still influence cancer risk indirectly by promoting obesity, insulin resistance, and systemic metabolic dysregulation. Chronic hyperglycemia elevates insulin and IGF-1, activating PI3K/Akt/mTOR and MAPK/ERK pathways, which stimulate proliferation, inhibit autophagy, and enhance nutrient uptake [17,33,34,35,36]. Suppression of IGF-binding proteins (e.g., Insulin-like Growth Factor Binding Protein (IGFBPs) and sex hormone-binding globulin (SHBG) increases the bioavailability of IGF-1 and sex steroids, pathways linked to hormonally driven cancers such as breast [29,37,38,39,40,41], endometrial [42,43,44], liver [45,46,47], and prostate [48,49,50,51,52,53,54].

Obesity amplifies these effects via chronic low-grade inflammation, oxidative stress, and altered adipokine signaling (↑ leptin, ↓ adiponectin), inducing a pro-tumorigenic microenvironment [55,56,57]. Parallel to this, sugar-rich diets can remodel the gut microbiome, reducing short-chain fatty acid (SCFA) production, increasing gut permeability [58,59], and promoting translocation of lipopolysaccharide (LPS) into circulation [60,61]. Elevated LPS activates NF-κB and STAT3 signaling, further sustaining systemic inflammation and insulin resistance [62]. Microbial shifts, such as enrichment of Fusobacterium and Enterobacteriaceae, are associated with colorectal [63,64,65] and hepatobiliary cancers [66], although human causality remains uncertain [67].

At the tumor level, hyperglycemia induces SREBP-1c overexpression, enhancing lipogenesis and aggressiveness [68,69], while AMPK inhibition removes a key metabolic checkpoint, enabling unchecked mTOR signaling [70,71]. Tumor cells also exhibit metabolic plasticity, utilizing glutamine, fatty acids, and pentose phosphate pathway activity to sustain growth even under low-glucose conditions [72].

Collectively, these findings indicate that any epidemiological links between sugar intake and cancer are more plausibly mediated through systemic metabolic and inflammatory pathways shaped by adiposity [73,74], insulin-IGF-1 signaling [75,76], and microbiome dysbiosis [77,78,79] rather than by direct tumor cell dependence on dietary glucose.

At the molecular level, oncogenic activation of PI3K/Akt signaling enhances GLUT1 trafficking to the cell membrane, increases glycolytic flux, and stimulates mTOR-mediated protein synthesis [34,35,36]. Loss of p53 further promotes glucose uptake through TIGAR suppression and reduces mitochondrial oxidative capacity [35]. Upregulation of SREBP-1c drives de novo lipogenesis, supporting membrane biosynthesis required for rapid proliferation [37,38,39]. These oncogene-driven pathways act independently of dietary sugar availability, highlighting that the metabolic phenotype of tumors is primarily encoded by intrinsic genetic alterations rather than substrate abundance [55]. These oncogene-driven alterations are summarized in Figure 2.

3.4. Metabolic Plasticity in Cancer Cells

Despite claims that carbohydrate restriction can “starve” tumors, human glucose homeostasis (70–100 mg/dL) is maintained even under fasting or ketogenic diets via gluconeogenesis and glycogenolysis [79,80,81]. Tumors further bypass glucose scarcity through metabolic flexibility utilizing glutamine for TCA cycle anaplerosis [82], nucleotide synthesis [83], and redox control [84,85], and fatty acids via CPT1A- and FATP-mediated β-oxidation for ATP production and membrane biosynthesis [86,87]. While some tumors can metabolize ketone bodies, most exhibit impaired ketolytic capacity, especially those with mitochondrial defects. This adaptability limits the therapeutic impact of dietary carbohydrate restriction [88,89,90].

Metabolic plasticity is supported by the tumor’s ability to reroute carbon sources depending on microenvironmental constraints [80]. Under glucose scarcity, glutamine becomes a dominant anaplerotic substrate via glutaminase-mediated conversion to α-ketoglutarate, supporting TCA cycle flux [81]. Fatty acid oxidation through CPT1A provides ATP and NADPH for redox defense, while activation of AMPK in low-energy states promotes catabolic pathways that sustain cell survival [87]. This adaptive capacity allows tumors to grow even when extracellular glucose is limited, further challenging the notion that restricting dietary sugar can directly ‘starve’ cancer cells [89]. Adaptive pathways supporting tumor survival under nutrient scarcity are depicted in Figure 3.

3.5. Immune Cell Glucose Uptake and Fluorodeoxyglucose Positron Emission Tomography (FDG-PET)

FDG-PET exploits high glucose uptake [91,92] but does not necessarily reflect tumor cell dependence on dietary sugars. Dual-tracer PET and flow cytometry in murine solid tumor models showed that tumor-associated macrophages and T cells had the highest FDG uptake, while malignant cells preferentially consumed glutamine [93,94,95]. This finding challenges the interpretation of FDG-PET “hot spots” as evidence of direct sugar fueling tumor growth and instead suggests they reflect immune metabolism within the tumor microenvironment [93].

4. Epidemiological Evidence

4.1. Breast Cancer

In large prospective cohorts (Supplementary Materials Tables S1 and S2), no significant associations were consistently reported between sugar intake and breast cancer risk. The Canadian cohort found no association with SSBs (HR = 1.02, 95% CI: 0.82–1.27), SCBs (HR = 1.13, 95% CI: 0.90–1.41), or fruit juice (HR = 1.17, 95% CI: 0.93–1.48) [96]. The Women’s Health Initiative likewise reported null results for glycemic load, glycemic index, sucrose, and fructose [97], while the CPS-II Nutrition Cohort [98] and the Melbourne Collaborative Cohort Study [99] also showed no associations with beverage intake. The NutriNet-Santé cohort confirmed these findings overall, with elevated risk observed only among premenopausal women [100]. In contrast, some studies have indicated adverse outcomes: the Nurses’ Health cohort reported higher breast cancer mortality with ≥1–3 SSB servings/week (HR ≈ 1.31–1.35) [101], and the WEB study showed that women consuming sugar-sweetened soda ≥5 times/week had significantly increased breast cancer-specific mortality (HR = 1.85, 95% CI: 1.16–2.94) [102]. A case-control study in African American and European American women further suggested that sugary drink intake was associated with increased risk of ER + breast cancer among women with above-median BMI [103]. Regional case-control investigations have also reported positive associations, including significantly higher odds with high SSB intake (OR = 2.8), sweets (OR = 3.7), fruits (OR = 1.6), and dairy (OR = 1.5) in Iran [104], nearly two-fold higher risk among Malaysian women in the highest quartile of sugar intake for both premenopausal (OR = 1.93) and postmenopausal women (OR = 1.87) [105], and approximately 19% increased risk with desserts and sugar-rich foods in Italy (OR = 1.19) [106]. Additional prospective evidence from the SUN cohort indicated increased risk among postmenopausal women with higher SSB consumption [107]. By contrast, in the DISC06 cohort, adolescent sucrose intake was associated with higher breast density in adulthood, whereas fructose, glycemic load, and glycemic index showed no associations [108].

While these positive associations may indicate a link between high sugar intake and breast cancer, they appear largely confined to metabolically and hormonally susceptible subgroups (such as premenopausal women [100], survivors with higher post-diagnostic SSB intake [101], women with above-median BMI [102], and postmenopausal women [105]) and often diminish after adjustment for BMI, total energy intake, and physical activity [96,97,98,99,103,104]. Mechanistically, high sugar intake can promote chronic positive energy balance, leading to central adiposity and insulin resistance [109]. This metabolic state elevates circulating insulin and activates the insulin-like growth factor-1 (IGF-1) axis, enhancing cell proliferation and inhibiting apoptosis [17,110]. In postmenopausal women, excess adipose tissue increases aromatase activity, raising estrogen levels that can drive ER + tumor growth [111,112]. Hyperinsulinemia also reduces sex hormone-binding globulin (SHBG), further increasing bioavailable estrogen [113]. The combined mitogenic and estrogenic stimulation creates a pro-tumorigenic environment in breast tissue. Given that these pathways are indirect consequences of adiposity and metabolic dysfunction, and that null associations dominate in large, well-controlled cohorts, the current evidence supports an indirect, metabolism-driven effect of sugar rather than a direct carcinogenic role.

4.2. Endometrial Cancer

In large prospective cohorts, including the Canadian cohort [96], no significant associations were observed between sugar-sweetened beverages (SSBs) or fruit juice intake and overall endometrial cancer risk. The Iowa Women’s Health Study [114] similarly reported no associations for Type II endometrial cancer with SSBs, fruit juice, or individual sugars. Consistent with these findings, the New Jersey Women’s Health Study also found no association between SSB intake and endometrial cancer [115]. Conversely, the Canadian cohort [96] found higher consumption of sugar-containing beverages was associated with increased risk of Type I endometrial cancer (HR = 1.62), while the Iowa study [114] likewise observed elevated risk of Type I tumors with SSB and glucose intake. The New Jersey study [115] further indicated that greater intake of added sugars and sweet foods (but not SSBs) was positively associated with Type I endometrial cancer.

While these positive associations may appear to support a dietary sugar-cancer link, they are biologically most plausible in the context of obesity-related metabolic and hormonal changes [116]. High sugar intake can promote chronic energy surplus, central adiposity, and insulin resistance, elevating circulating insulin and activating the insulin-like growth factor-1 (IGF-1) pathway, which enhances endometrial cell proliferation [17,36,43]. In postmenopausal women, excess adipose tissue also increases aromatase activity, raising estrogen levels that stimulate endometrial growth [117]. Concurrently, hyperinsulinemia reduces sex hormone-binding globulin (SHBG), further increasing free estrogen bioavailability [113]. Given that these pathways are indirect consequences of adiposity and metabolic dysfunction, and that null associations are reported in large, fully adjusted models, the available evidence suggests an indirect, metabolism-mediated relationship rather than a direct carcinogenic effect of sugar itself.

4.3. Ovarian Cancer

In large prospective studies, no significant associations were observed between sugar-sweetened beverages (SSBs), fruit juice, or sugary foods and ovarian cancer risk. In the Canadian Cohort, the highest versus lowest tertile yielded HRs of 0.92 (95% CI: 0.62–1.36) for SSBs and 0.98 (95% CI: 0.65–1.48) for fruit juice [96]. The Swedish Mammography Cohort similarly reported Swedish Mammography Cohort, no significant associations were found between fruit consumption and ovarian cancer risk [118]. The Melbourne study also found no significant associations [99]. Overall, current evidence does not support a causal link between sugar intake and ovarian cancer.

4.4. Colorectal Cancer

In large prospective cohorts, no significant associations have generally been observed between sugar intake and colorectal cancer risk. The Canadian cohort reported no association with SSBs (HR = 1.02, 95% CI: 0.82–1.27), SCBs (HR = 1.13, 95% CI: 0.90–1.41), or fruit juice (HR = 1.17, 95% CI: 0.93–1.48) [96], while the Melbourne Collaborative Cohort likewise found null results for both sugar-sweetened and artificially sweetened soft drinks [99]. The NIH-AARP Diet and Health Study also showed no associations for sucrose, fructose, or total sugar intake [119], the Women’s Health Initiative reported null findings for glycemic load, glycemic index, and total carbohydrate [120], and the Multiethnic Cohort observed no association for total sugars, sucrose, fructose, or food sources of sugar across diverse populations [121]. A recent JPHC analysis similarly found no significant associations for total, free, or added sugar intake and colorectal cancer risk [122]. In contrast, some studies have suggested increased risks under specific conditions. An early UK case-control analysis found elevated risk with fiber-depleted sugars (RR = 3.6, 95% CI: 1.2–10.9), though not with natural sugars or dietary fiber [123]. In the CPS-II Nutrition Cohort, higher SSB intake was associated with increased colorectal cancer mortality (HR = 1.11, 95% CI: 1.02–1.21) [124]. Subsite-specific analysis in the NIH cohorts indicated increased incidence and mortality with SSB (HR per 1-serving/day = 1.18, 95% CI: 1.03–1.34; HR for mortality = 1.39, 95% CI: 1.13–1.72) and fructose intake (HR = 1.18, 95% CI: 1.03–1.35 for incidence; HR = 1.42, 95% CI: 1.12–1.79 for mortality), specifically for proximal colon cancer [125]. Furthermore, the Nurses’ Health II found that higher adolescent intake of simple sugars and SSBs was associated with increased risk of colorectal adenomas, especially rectal lesions (OR = 1.43, 95% CI: 1.10–1.86 for fructose; OR = 1.30, 95% CI: 1.08–1.55 for SSBs), while adult sugar intake showed no association [126]. In the same cohort, SSB intake in adolescence and adulthood was also linked to increased risk of early-onset colorectal cancer [127].

Mechanistically, excessive free sugar intake may contribute to colorectal carcinogenesis through hyperinsulinemia, activation of the insulin-like growth factor-1 (IGF-1) axis, and systemic inflammation [36,51,62]. As monosaccharides are efficiently absorbed in the small intestine, the colonic epithelium has limited direct exposure to free sugars [128]. This restricted luminal exposure, together with metabolic and dietary modifiers, likely explains the largely null associations reported in well-adjusted prospective cohorts [129].

4.5. Colon Cancer

Evidence from prospective cohorts indicates no consistent associations between sugar intake and colon cancer risk [130]. In the Cancer Prevention Study II, no significant association was observed between total fruit intake and colon cancer incidence, with only women in the very lowest fruit intake category showing higher risk (RR = 1.86; 95% CI: 1.18–2.94), likely reflecting inadequate intake rather than excess sugar [124]. The Multiethnic Cohort likewise reported no associations for total sugar, fructose, glucose, sucrose, SSBs, or whole fruit intake, with an inverse association observed for fruit juice (HR = 0.79; 95% CI: 0.64–0.97) [121]. In the Japan Public Health Center cohort, sugary drink intake was not associated with colon cancer in men (HR = 0.80; 95% CI: 0.63–1.02), while a modest positive association in women (HR = 1.36; 95% CI: 1.03–1.78) did not follow a clear dose-response pattern [131]. Collectively, these findings demonstrate that across large, well-adjusted cohorts, sugar and SSB intake are not consistently linked to colon cancer incidence, and isolated positive results are more plausibly explained by residual confounding, sex-specific variation, or chance [96,99,119,121].

4.6. Liver Cancer

Evidence regarding sugar and SSB intake in relation to hepatocellular carcinoma (HCC) remains inconsistent and generally does not support a direct carcinogenic role of sugars. The NIH-AARP cohort found an inverse association with added fructose (HR = 0.43; 95% CI: 0.22–0.86; p = 0.02) and no links for other sugars [119]. The EPIC cohort (Fedirko et al., 2013) reported a positive association with total sugar intake (HR = 1.88; 95% CI: 1.16–3.03; p = 0.008), while finding no associations for glycemic index (HR = 1.08; 95% CI: 0.65–1.80) or glycemic load (HR = 0.87; 95% CI: 0.32–2.35) [132]. In the Women’s Health Initiative, there was no overall SSB association in non-diabetic individuals, but modest positive associations emerged during the early follow-up period in both non-diabetic (HR = 1.18; 95% CI: 1.03–1.35) and diabetic participants (HR = 1.12; 95% CI: 1.01–1.24) [133]. Lastly, a Japanese case-control study of patients with chronic hepatitis infection found no association between glycemic load and HCC risk (OR = 1.08; 95% CI: 0.93–1.25; p = 0.11) [134]. Taken together, the overall body of evidence points to null or inconsistent associations, with isolated positive findings more plausibly attributable to obesity, insulin resistance, and non-alcoholic fatty liver disease (NAFLD), which promote hepatic inflammation, oxidative stress, and progression to cirrhosis which is a recognized precursor of hepatocellular carcinoma [135,136,137].

4.7. Biliary Tract Cancer

The EPIC cohort found no associations between glycemic index, glycemic load, or total sugar intake and biliary tract cancer [132], with no consistent positive associations further reported or studies.

4.8. Pancreatic Cancer

Across large prospective cohorts, the predominant evidence points toward no significant associations between dietary sugars and pancreatic cancer risk. In the Women’s Health Initiative, null results were observed for sucrose, fructose, glycemic load, and glycemic index [138]. Similarly, the Nurses’ Health Study and Health Professionals Follow-up Study reported no associations for glycemic load, glycemic index, sucrose, or fructose [139]. In the Multiethnic Cohort, no significant associations were detected for total sugars, fruit juice, non-diet sodas, sucrose, or glycemic load [140]. The Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study in male smokers also showed no associations with fruits and berries [141,142].

By contrast, the NIH-AARP Diet and Health Study identified increased risk with free fructose and free glucose, but no associations with sucrose, lactose, or maltose [143]. The Nurses’ Health Study II reported elevated risk with frequent sugar-sweetened beverage intake in women, whereas no association was found in men [141]. In the Swedish Mammography Cohort, soft drink consumption was linked to increased risk, while other sugar-rich foods showed null results [144]. Finally, the Chicago Western Electric Study indicated higher risk with glycemic load in men, but not in women [145].

Taken together, the evidence points to null or inconsistent associations, with isolated positive findings more plausibly explained by metabolic confounding, measurement error, or reverse causation rather than a direct effect of sugars. Excess sugar intake promotes obesity, insulin resistance, and hyperinsulinemia, which drive pancreatic carcinogenesis via inflammation and IGF-1 signaling [36,51,146]. In addition, reliance on food frequency questionnaires introduces dietary misclassification, while preclinical diabetes may alter dietary behaviors, producing spurious associations [147,148,149]. Overall, these factors suggest that sugars act indirectly through metabolic dysfunction rather than as independent carcinogens.

4.9. Hematologic Cancers

In the CPS-II cohort, no associations were observed for leukemia (HR = 0.96, 95% CI: 0.86–1.06) or multiple myeloma (HR = 0.96, 95% CI: 0.83–1.11) [98]. Similarly, in the Nurses’ Health Study and Health Professionals Follow-Up Study, soda consumption showed no associations with leukemia or multiple myeloma in either men or women [150].

By contrast, some subgroup findings suggested potential risks. In the CPS-II cohort, SSB intake was associated with increased risk of non-Hodgkin lymphoma (HR = 1.20, 95% CI: 1.07–1.34) [130]. Consistently, the Nurses’ Health Study and Health Professionals Follow-Up Study reported elevated risk of non-Hodgkin lymphoma in men consuming soda (RR = 1.66, 95% CI: 1.10–2.51), but not in women [150]. Added fructose intake also showed a modest association with higher risk in a separate cohort (HR = 1.53, 95% CI: 0.98–2.38) [116].

Mechanistically, high sugar intake contributes to obesity, insulin resistance, and chronic hyperinsulinemia, which can promote lymphomagenesis through immune dysregulation, altered cytokine signaling, and impaired apoptosis of B and T lymphocytes [151]. Moreover, systemic inflammation and adipokine imbalance associated with obesity provide a pro-tumorigenic microenvironment that facilitates hematological malignancy development [152]. Methodological issues, including dietary misclassification from food frequency questionnaires [153] and reverse causation due to preclinical diabetes or metabolic alterations [154], further support that observed associations are likely secondary or artifactual.

4.10. Larynx, Oral Cavity, and Pharynx

In the CPS-II cohort, no significant associations were observed between SSB intake and cancers of the larynx, oral cavity, or pharynx (HR = 1.04, 95% CI: 0.88–1.24) [98]. By contrast, the NIH-AARP cohort reported a decreased risk with higher added sucrose intake (HR = 0.66, 95% CI: 0.50–0.88) [116]. Taken together, the predominant evidence supports null or inverse associations, with little indication that sugars directly contribute to cancers of the upper aerodigestive tract.

4.11. Melanoma and Skin Cancer

In the CPS-II cohort, no significant associations were observed between SSB intake and risk of melanoma or skin cancer (HR = 1.12, 95% CI: 0.96–1.31) [98]. The evidence therefore supports a null association, suggesting that sugars are unlikely to play a direct role in cutaneous carcinogenesis, where ultraviolet radiation remains the dominant risk factor.

4.12. Gastric Cancer

In the CPS-II cohort, no significant associations were observed between SSB intake and gastric cancer mortality (HR = 1.08, 95% CI: 0.93–1.26) [98]. Similarly, in the Japan Public Health Center-based Prospective Study, no association was found between sugary drink consumption and overall gastric cancer risk (HR = 0.98, 95% CI: 0.82–1.17) [155].

By contrast, case-control studies in Europe suggested elevated risks. In Italy, increased spoonfuls of added sugar were positively associated with gastric cancer risk, with the odds rising in a dose-dependent manner [156]. In France, higher intake of cakes and pastries was also linked to increased risk (OR = 2.96) [157]. Additionally, the Melbourne Collaborative Cohort Study reported a positive association between SSB intake and obesity-related cancers, including gastric cancer, although estimates were imprecise (HR = 1.24, 95% CI: 0.77–1.99) [99].

Taken together, the predominant evidence from prospective cohorts supports null associations, with positive findings largely confined to case-control designs that are more vulnerable to recall bias, selection bias, and residual confounding.

4.13. Kidney Cancer

In the Singapore Chinese Health Study, no significant association was observed between sugary drink intake and kidney cancer risk (HR = 1.02, 95% CI: 0.96–1.08) [123]. The Melbourne Collaborative Cohort Study likewise reported no significant association with SSB intake (HR = 1.32, 95% CI: 0.79–2.19) [99].

By contrast, the CPS-II Nutrition Cohort reported an increased risk of kidney cancer mortality with higher SSB consumption (HR = 1.14, 95% CI: 1.00–1.31; p = 0.003) [98]. Furthermore, in the Singapore Chinese Health Study, risk was elevated among women after exclusion of cases diagnosed within the first three years (HR = 1.11, 95% CI: 1.01–1.22) [123].

Taken together, the evidence shows null or inconsistent associations across cohorts, with isolated positive findings more likely attributable to confounding from obesity [158,159], hypertension [160], and diabetes [161], which are established risk factors for kidney cancer.

4.14. Urinary Tract (Bladder/Urothelial) Cancer

In Argentina, a case-control analysis reported that medium adherence to a high-sugar drink dietary pattern was associated with increased risk of urinary tract tumors (OR = 2.55, 95% CI: 1.28–5.07), whereas high adherence was inversely associated (OR = 0.72, 95% CI: 0.60–0.85) [162]. In the Japan Public Health Center-based Prospective Study, no overall associations were observed, although a modestly increased risk was detected among women after exclusion of cases diagnosed within the first three years (HR = 1.11, 95% CI: 1.01–1.22) [123].

In Europe, the EPIC cohort identified a weak but statistically significant positive association between soft drink intake and urothelial carcinoma risk, with each 100 mL/day increment corresponding to an HR of 1.06 (95% CI: 1.01–1.12) [163]. By contrast, the Health Professionals Follow-Up Study in the United States reported no significant association between soda consumption and bladder cancer incidence (HR = 0.99, 95% CI: 0.90–1.08) [164].

Taken together, the evidence remains inconsistent, with prospective cohorts generally reporting null or weak associations, while stronger positive signals appear primarily in case-control settings that may be subject to recall and selection biases.

4.15. Gall Bladder Cancer

In the CPS-II Nutrition Cohort, no significant association was observed between SSB intake and gallbladder cancer risk (HR = 1.10, 95% CI: 0.84–1.43) [98]. By contrast, in the NIH-AARP cohort, higher fructose intake was suggestively associated with increased gallbladder cancer risk (HR = 1.70, 95% CI: 1.00–2.90), although the result was of borderline statistical significance (p = 0.06) [116].

Taken together, the available evidence remains limited and inconsistent, with the predominant findings pointing toward no clear association between sugar consumption and gallbladder cancer risk.

4.16. Small Intestine Cancer

In the CPS-II Nutrition Cohort, no significant association was observed between SSB intake and small intestine cancer risk (HR = 1.25, 95% CI: 0.83–1.88) [98]. In the NIH-AARP cohort, fructose intake was associated with an increased risk of small intestine cancer (HR = 2.10, 95% CI: 1.06–4.16), although the estimate was based on limited cases and should be interpreted with caution [116].

Taken together, the evidence remains sparse and inconsistent, with prospective data predominantly supporting no clear association between sugar consumption and small intestine cancer risk.

4.17. Glioma and Brain Cancer

In a pooled U.S. cohort analysis, no significant association was observed between soda intake and glioma risk (HR = 0.82, 95% CI: 0.67–1.01, p = 0.06) [165]. Similarly, in the CPS-II Nutrition Cohort, sugar-sweetened beverage consumption was not associated with brain cancer mortality (HR = 0.96, 95% CI: 0.84–1.11, p = 0.714) [98].

Taken together, the current evidence supports null associations between sugar-sweetened beverages and glioma or other brain cancers.

4.18. Esophageal Cancer

In the Australian Cancer Study, no associations were found between carbonated soft drink (CSD) intake and risk of esophageal adenocarcinoma (OR = 0.94, 95% CI: 0.53–1.66) or esophagogastric junction adenocarcinoma (OR = 1.07, 95% CI: 0.67–1.73), while an inverse association was observed for cardia cancer (OR = 0.40, 95% CI: 0.20–0.78) [166]. In the CPS-II Nutrition Cohort, sugar-sweetened beverage intake showed no significant association with esophageal cancer mortality (HR = 0.87, 95% CI: 0.75–1.01) [98]. A pooled case-control study in the United States likewise reported no association between soft drink consumption and esophageal adenocarcinoma risk (OR = 1.04, 95% CI: 0.70–1.54) [167]. By contrast, in the NIH-AARP Diet and Health Study, higher added sugar intake was associated with increased esophageal cancer risk (HR = 1.81, 95% CI: 1.16–2.84) [116].

The isolated positive findings are more plausibly explained by obesity, gastroesophageal reflux disease (GERD), and Barrett’s esophagus, well-established intermediates in esophageal adenocarcinoma [168]. Obesity increases intra-abdominal pressure and promotes reflux, while high sugar intake indirectly contributes to this through weight gain and central adiposity [169]. Furthermore, chronic mucosal injury from acid reflux and subsequent metaplasia-dysplasia sequence are the principal pathogenic drivers [170]. Sugars and SSBs lack a mutagenic mechanism in esophageal epithelial cells, and their observed associations likely reflect metabolic confounding, residual error from dietary misclassification, and reverse causation in individuals with early undiagnosed reflux or metabolic disease [171].

4.19. Lung Cancer

In the CPS-II Nutrition Cohort, an inverse association was reported between SSB intake and lung cancer mortality (HR = 0.92, 95% CI: 0.88–0.96) [98]. In the NutriNet-Santé cohort, no significant association was observed for total sugar intake (HR = 1.00, 95% CI: 0.48–2.06) [100]. The NIH-AARP Diet and Health Study suggested a borderline inverse association with fructose (HR = 0.87, 95% CI: 0.75–1.01) [116]. A case-control study in Pakistan reported inverse associations with juice, fruit, and milk intake [172], while a case-control study in Uruguay found no association between sugary beverages and lung cancer (OR = 1.09, 95% CI: 0.78–1.53) [173].

The null findings from NutriNet-Santé [100] and Uruguay [173], together with the predominance of weak or inconsistent inverse signals, indicate that sugars and SSBs are not causally linked to lung cancer risk. Lung carcinogenesis is overwhelmingly driven by tobacco smoking, occupational exposures, and air pollution [174], whereas sugars lack any mutagenic or tissue-specific mechanism in the lung.

4.20. Prostate Cancer

In the CPS-II Nutrition Cohort, no significant association was observed between SSB intake and prostate cancer mortality (HR = 1.01, 95% CI: 0.93–1.09, p = 0.474) [98]. Similarly, in the NutriNet-Santé cohort, total sugar intake was not associated with prostate cancer risk (HR = 1.04, 95% CI: 0.66–1.64, p = 0.80) [100], and sugary drink intake likewise showed null associations (HR = 1.10, 95% CI: 0.92–1.31, p = 0.30) [175].

By contrast, positive associations were reported in a Canadian case-control study, where sugary drink intake was associated with increased prostate cancer risk (OR = 1.35, 95% CI: 1.10–1.66, p = 0.002) [174], and in the UK Biobank, where SSB intake was linked to higher risk (HR = 1.21, 95% CI: 1.06–1.39, p < 0.01), although fruit juice showed no association [176]. Other large prospective studies, including the NHS and HPFS, found no significant associations between sugary foods, sugary drinks, or total sugars and prostate cancer risk [177,178]. Additionally, biomarker evidence from a Chinese cohort suggested higher PSA concentrations with increasing sugar intake (β = 0.003 ng/mL per gram, 95% CI: 0.001–0.005, p = 0.002) [179].

A recent systematic review by Khaled et al. [180] concluded that the overall body of evidence does not support a consistent association between dietary sugar intake and prostate cancer risk. From a mechanistic perspective, prostate carcinogenesis is primarily driven by androgen signaling, age, and genetic predisposition, while dietary sugars lack a plausible direct carcinogenic mechanism [180]. Apparent positive associations are more likely driven by androgen receptor signaling, age-related hormonal changes, and genetic susceptibility, whereas sugars lack direct mutagenic or androgen-modulating properties [181]. These associations can be explained by confounding from obesity, insulin resistance, and metabolic syndrome [182,183,184,185,186].

A summary of epidemiological studies assessing the link between sugar intake and different cancer types is presented in

Table 1. Summary of Epidemiological Evidence Linking Sugar Intake to Cancer Risk based on Cancer Types.

Cancer Type	Sugar Type	Summary of Associations	Key Studies and Findings
Breast Cancer	Added sugars/SSBs	Mixed results	Arthur et al. (2021) [96] No association with SSB (HR = 1.02, 95% CI: [0.82–1.27], p = 0.465) and SCB (HR = 1.13, 95% CI: [0.90–1.41], p = 0.265)
			Farvid et al. (2021) [101] Increased risk with SSB intake of >1 to 3 servings/week (HR = 1.31 [1.09–1.58], p = 0.001) and >3 servings/week (HR = 1.35, 95% CI: [1.12–1.62], p = 0.001)
			Koyratty et al. (2021) [102] Increased risk of breast cancer mortality with high SSB intake (HR = 1.85, 95% CI: [1.16–2.94], p < 0.01).
			Romanos-Nanclares et al. (2019) [107] No association in premenopausal women (HR = 1.16, 95% CI: [0.66–2.07], p = 0.602) Increased risk with post-menopausal women (HR = 2.12, 95% CI: [1.02–4.41], p < 0.05)
			Chandran et al. (2014) [103] No association for SSB (OR = 1.4, 95% CI: [ 0.8–2.4], p = 0.96)
			Hodge et al. (2018) [99] No association with SSB intake (HR = 1.26, 95% CI: [1.00–1.58], p = 0.05/0.09)
			McCullough et al. (2022) [98] No significant association with SSB intake (HR: 1.02; 95% CI: [0.91–1.16]; p = 0.944).
	Individual sugars	Predominantly null associations	Shikany et al. (2011) [97] No association with glycemic load (HR = 1.08, 95% CI: [0.99–1.17], p = 0.23); glycemic index (HR = 1.02, 95% CI: [0.94–1.11], p = 0.65); total carbohydrate (HR = 1.00, 95% CI: [0.91–1.09], p = 0.98); sucrose (HR = 0.99, 95% CI: [0.91–1.08], p = 0.84); and fructose (HR = 0.97, 95% CI: [0.89–1.06], p = 0.50).
			Jung et al. (2018) [108] Increased %DBV with sucrose (23.5, 95% CI: [20.4–27.2], p < 0.001), and fructose intake (18.9, 95% CI: [16.3–21.8], p = 0.19) No association %DBV with GL (18.9, 95% CI: [15.3–23.2], p = 0.56), and GI (1 8.3, 95% CI: [14.1–23.6], p = 0.80)
	Naturally occurring sugars	Mostly null or inconsistent	Arthur et al. (2021) [96] No association with fruit juice (HR = 1.17, 95% CI: [0.93–1.48], p = 0.357)
			Chandran et al. (2014) [103] Increased risk with fruit drinks (OR = 1.4, 95% CI: [0.8–2.4], p = 0.03)
	Others (total sugar intake)	No consistent association	Sulaiman et al. (2014) [105] Increased risk with pre-menopausal (OR = 1.93, 95% CI: [1.53–2.61], p = 0.001), and post-menopausal women (OR = 1.87, 95% CI: [1.03–2.61], p = 0.001)
			Debras et al. (2020) [100] No association with total sugar intake (HR = 1.05, 95% CI: [0.90–1.23], p = 0.4)
			Tavani et al. (2006) [106] Increased risk with sugar intake (log2 = 4.70, p = 0.030)
			Marzbani et al. (2019) [104] Increased risk with SSB (OR = 2.8, 95% CI: [1.9–4.3]), fruits (OR = 1.6, 95% CI: [0.9–2.8]), dairy consumption (OR = 1.5, 95% CI: [1.0–2.3]), and sweets (OR = 3.7, 95% CI: [2.6–5.3]).
Endometrial Cancer	Added sugars/SSBs	Mixed findings	Arthur et al. (2021) [96] No association for SSB (HR = 1.46, 95% CI: [0.97–2.22], p = 0.071), and fruit juice (HR = 1.41, 95% CI: [0.94–2.12], p = 0.095) Increased risk with SCB (HR = 1.62, 95% CI: [1.09–2.60], p = 0.019).
			Inoue-Choi et al. (2013) [114] Type I endometrial cancer: Increased risk with SSB intake (OR = 1.78, 95% CI: [1.32–2.40], p = 0.001) Type II endometrial cancer: no associations with SSB (OR = 1.47, 95% CI: [0.69–3.12], p = 0.63)
			King et al. (2013) [115] No association for SSB (OR = 1.46, 95% CI: 0.97–2.22, p = 0.071). Increased risk with SCB (OR = 1.62, 95% CI: 1.09–2.60, p = 0.019).
			McCullough et al. (2022) [98] No significant association with SSB intake (HR: 1.10; 95% CI: [0.87–1.34]; p = 0.514).
	Individual and naturally occurring sugars	No consistent association	Inoue-Choi et al. (2013) [114] Type I endometrial cancer: Increased risk with glucose (OR = 1.50, 95% CI: [1.08–2.08], p = 0.04); no significant association for sucrose (OR = 1.23, 95% CI: [0.90–1.69], p = 0.06), fructose (OR = 1.32, 95% CI: [0.96–1.82], p = 0.11), or fruit juice (OR = 1.16, 95% CI: [0.87–1.56], p = 0.14). Type II endometrial cancer: no associations with fruit juice (OR = 1.06, 95% CI: [0.54–2.07], p = 0.73), sucrose (OR = 1.00, 95% CI: [0.49–2.05], p = 0.41), glucose (OR = 0.99, 95% CI: [0.53–1.88], p = 0.92), or fructose (OR = 0.90, 95% CI: [0.47–1.73], p = 0.53).
			King et al. (2013) [115] No association for fruit juice (OR = 1.41, 95% CI: 0.94–2.12, p = 0.095).
Ovarian Cancer	Added sugars/SSBs	No association	Arthur et al. (2021) [96] No associations with SCB (OR = 1.50, 95% CI: [0.96–2.60], p = 0.078), fruit juice (OR = 1.42, 95% CI: [0.80–2.52], p = 0.228), and SSB (OR = 1.30, 95% CI: [0.79–2.16], p = 0.327).
			McCullough et al. (2022) [98] No significant association with SSB intake (HR: 0.98; 95% CI: [0.83–1.16]; p = 0.678).
			Hodge et al. (2018) [99] No association with SSB intake (OR = 1.32, 95% CI: [0.73–2.41], p = 0.36/0.96).
			King et al. (2013) [115] No significant association with sugary drinks (OR = 1.09, 95% CI: [0.65–1.84], p = 0.47), and total sugary foods/drinks (OR = 1.25, 95% CI: [0.73–2.17], p = 0.46).
			Tasevska et al. (2012) [119] Decreased risk with added fructose intake (HR = 0.72; 95% CI: [0.52–1.01]; p = 0.03).
Colorectal Cancer	Added sugars/SSBs	Mixed findings	Arthur et al. (2021) [96] No significant associations with SSB (HR = 1.08, 95% CI: [0.73–1.59], p = 0.453), SCB (HR = 1.21, 95% CI: [0.82–1.77], p = 0.361), or fruit juice (HR = 1.08, 95% CI: [0.73–1.59], p = 0.864).
			McCullough et al. (2022) [98] Increased risk with SSB intake (HR: 1.07; 95% CI: [1.00–1.15]; p = 0.043).
			Hodge et al. (2018) [99] (OR = 1.17, 95% CI: [0.79–2.19], p = 0.12/0.06).
			Leung et al. (2021) [131] No association with sugary drink intake in men (HR = 0.84; 95% CI: [0.70–1.02]; p = 0.22), but an increased risk among women (HR = 1.20; 95% CI: [0.96–1.50], p = 0.04).
			Hur et al. (2021) [127] Increased early onset risk of SSB ≥ 2 servings/day in women (RR = 2.18; 95% CI: [1.10–4.35], p = 0.02).
			Yuan et al. (2022) [125] Increased incidence and mortality with SSB (HR per 1-serving/d increment = 1.18; 95% CI: [1.03, 1.34]; p = 0.02; HR: 1.39; 95% CI: [1.13, 1.72]; p = 0.002 respectively) and fructose consumption (HRs per 25-g/d increment =1.18; 95% CI: [1.03–1.35]; and 1.42; 95% CI: [1.12–1.79], respectively).
	Total sugars and others	No association	Debras et al. (2020) [100] Decreased risk with total sugar intake (HR = 0.46, 95% CI: [0.24–0.88], p = 0.03).
			Tasevska et al. (2012) [119] No association with any sugar type.
			Bristol et al. (1985) [123] Increased risk with higher intake of sugars depleted in fiber (RR = 3.6, 95% CI: [1.2–10.9], p < 0.05). No association with natural sugars, alcohol, or dietary fiber intake.
			Kanehara et al. (2024) [121] No association with total sugar (HR = 0.91; 95% CI: [0.73–1.13]; p = 0.47). or fructose intake (HR = 0.92; 95% CI: [0.74–1.13], p = 0.32) in men. No association with total sugar (HR= 1.17; 95% CI: [0.90–1.52], p = 0.47), or fructose intake (HR= 1.14; 95% CI: [0.89–1.46], p = 0.48) in women.
			Joh et al. (2021) [126] Increased risk of adenoma in adolescence with total fructose, but not serrated lesions (OR = 1.12; 95% CI: [0.96–1.30], p > 0.05 for proximal, OR = 1.24; 95% CI: [1.05–1.47], p > 0.05 for distal, and OR = 1.43; 95% CI: [1.10–1.86], p > 0.05 for rectal adenoma) and SSB intake (OR = 1.11; 95% CI: [1.02–1.20], p > 0.05 for total adenoma and OR = 1.30; 95% CI: [1.08–1.55], p > 0.05 for rectal adenoma). No associated risk in adults with sugar and SSB intake.
			Kabat et al. (2008) [120] No association for total carbohydrate (HR = 0.99, 95% CI: 0.82–1.19, p = 0.92), glycemic index (HR = 0.97, 95% CI: 0.80–1.18, p = 0.76), and glycemic load (HR = 1.04, 95% CI: 0.86–1.27, p = 0.68).
			Kanehara et al. (2023) [122] No associations for total sugar (HR = 1.04, 95% CI: 0.80–1.36 in men; HR = 1.05, 95% CI: 0.74–1.50 in women), free sugar (HR = 0.99, 95% CI: 0.75–1.30 in men; HR = 1.06, 95% CI: 0.74–1.53 in women), and fructose (HR = 1.08, 95% CI: 0.82–1.41 in men; HR = 1.04, 95% CI: 0.72–1.49 in women).
Colon cancer	Total sugars/Naturally occurring sugars	Mixed findings	Laguna et al. (2021) [134] Increased risk with total liquid sugar intake (HR = 1.08; 95% CI: [1.03–1.13]; p = 0.004), liquid glucose (HR = 1.19; 95% CI: [1.07–1.31]; p = 0.001), liquid fructose (HR = 1.14; 95% CI: [1.05–1.23]; p = 0.013), and fruit juice fructose (HR = 1.39; 95% CI: [1.10–1.74]; p = 0.035). No association with total solid sugar, solid glucose, solid fructose, or fructose from fruits. Increased all-cause mortality with table sugar intake (HR = 1.07; 95% CI: [1.00–1.14]; p not stated).
			McCullough et al. (2003) [124] No significant association between total fruit and colon cancer risk (N/A) Women with very low fruit intake showed increased colon cancer risk (RR = 1.86; 95% CI: [1.18–2.94], p = 0.06) No association with fruit intake and colon cancer risk (RR = 1.18; 95% CI: [0.86–1.63], p > 0.05)
			Kanehara et al. 2024 [121] Increased risk with fruit juice (HR = 0.79; 95% CI: [0.64–0.97], p = 0.02) No significant association for with total sugar (HR = 1.11; 95% CI: [0.88–1.39], p = 0.67), total fructose (HR = 1.00; 95% CI: [0.80–1.25], p = 0.92), glucose (HR = 1.02; 95% CI: [0.82–1.27], p = 0.73), Fructose (HR = 1.04; 95% CI: [0.83–1.30], p = 0.78). SSB (HR = 0.99; 95% CI: [0.80–1.23], p = 0.93), Sucrose (HR = 1.03; 95%CI: [0.83–1.28], p = 0.99), and whole fruits (HR = 1.13; 95% CI: [0.85–1.49], p = 0.45) intake.
	Added sugars/SSBs	Increased risk	Fuchs et al. (2014) [135] High SSB intake associated with increased risk of recurrence or death stage III patients, (HR = 1.67, 95% CI: [1.04–2.68], p = 0.02)
			Leung et al. (2021) [131] No association with sugary drink intake among men (HR = 0.80; 95% CI: [0.63–1.02]; p = 0.11), but an increased risk among women with higher sugary drink intake (HR = 1.36; 95% CI: [1.03–1.78], p = 0.04).
Liver Cancer	Added sugars/SSBs	Mixed findings	Tasevska et al. (2012) [119] Decreased risk with added fructose intake (HR = 0.43; 95% CI: [0.22–0.86]; p = 0.02).
			Jones et al. (2022) [138] No associations for SSB in non-diabetic. Increased risk in the initial follow-up period for SSB intake in non-diabetic (HR = 1.18, 95% CI: [1.03–1.35], p < 0.05), and diabetic (HR = 1.12, 95% CI: [1.01–1.24], p < 0.05) patients.
			Zhao et al. (2023) [139] Sugar-sweetened beverage daily intake associated with significantly higher liver cancer incidence (HR = 1.85; 95% CI: 1.16–2.96; p = 0.01) in postmenopausal women
	Glycemic load and total sugar	No association	Fedirko et al. (2013) [132] No significant associations for glycemic index (HR = 1.08, 95% CI: [0.65–1.80], p < 0,05) or glycemic load (HR = 0.87, 95% CI: [0.32–2.35], p < 0.05). Increase risk with total sugar intake (HR = 1.88, 95% CI: [1.16–3.03], p = 0.008).
			Lagiou et al. (2009) [140] No associations for glycaemic load (OR = 1.08, 95% CI: [0.93–1.25], p = 0.11)
Biliary Tract Cancer	Glycemic load and total sugar	No association	Fedirko et al. (2013) [132] No associations for glycemic index (HR = 1.05, 95% CI: [0.73–1.52]), p < 0.05), glycemic load (HR = 0.89, 95% CI: [0.50–1.56], p < 0.05), or total sugar (HR = 0.78, 95% CI: [0.52–1.18], p = 0.472).
Pancreatic Cancer	Added sugars/SSBs	Mixed findings	McCullough et al. (2022) [98] Increased risk with SSB intake (HR: 1.17; 95% CI: [1.02–1.35]; p = 0.025).
			Schernhammer et al. (2005) [150] Increased risk with SSB intake in women consuming ≥3 servings/week (RR = 1.57; 95% CI: 1.00–2.46; p for trend = 0.05). No association in men (RR = 0.93; 95% CI: 0.65–1.34; p for trend = 0.70).
			Tasevska et al. (2012) [119] Decreased risk with added sucrose intake (HR = 0.63; 95% CI: [0.42–0.94]; p = 0.03).
			Larsson et al. (2006) [147] Increased risk with soft drink intake (HR = 2.30, 95% CI: [1.35–3.92], p = 0.006) No significant associations for sweetened fruit soups/stewed fruits (HR = 1.46, 95% CI: [0.89–2.40], p = 0.11), jam/marmalade (HR = 0.98, 95% CI: [0.57–1.70], p = 0.79), and sweets intake (HR = 0.96, 95% CI: [0.58–1.59], p = 0.89).
	Individual, and naturally occurring sugars	Mixed findings	Simon et al. (2010) [146] No association sucrose (OR = 1.30, 95% CI: [0.89–1.89], p = 0.25), fructose (OR = 0.79, 95% CI: [0.54–1.17], p = 0.20), glycemic load (OR = 1.08, 95% CI: [0.93–1.25], p = 0.11 and OR = 0.80, 95% CI: [0.55–1.15], p = 0.31), and glycemic index (OR = 1.13, 95% CI: [0.78–1.63], p = 0.94)
			Michaud et al. (2002) [148] No associations for glycemic load (RR = 1.53, 95% CI: [0.96–2.45], p = 0.14), glycemic index (RR = 1.16, 95% CI: [0.69–1.97], p = 0.53), sucrose (RR = 1.34, 95% CI: [0.82–2.17], p = 0.17), and fructose intake (RR = 1.57, 95% CI: [0.95–2.57], p = 0.07).
			Nöthlings et al. (2007) [149] Increased cancer risk with fructose (RR = 1.35, 95% CI: [1.02–1.80], p = 0.046), and fruit intake (RR = 1.42, 95% CI: [1.05–1.93], p = 0.03). No significant associations for total sugars (RR = 1.28, 95% CI: [0.95–1.73], p = 0.09), fruit juices (RR = 1.08, 95% CI: [0.83–1.41], p = 0.56), non-diet sodas (RR = 1.07, 95% CI: [0.82–1.40], p = 0.54), glycemic load (RR = 1.10, 95% CI: [0.80–1.52], p = 0.65), and sucrose (RR = 1.23, 95% CI: [0.91–1.65], p = 0.21).
			Jiao et al. (2009) [151] Increased risk with free fructose (RR = 1.29, 95% CI: [1.04–1.59], p = 0.004), free glucose (RR = 1.35, 95% CI: [1.10–1.67], p-trend = 0.005). no associations with sucrose (RR = 0.95, 95% CI: [0.78–1.16], p = 0.68), lactose (RR = 0.89, 95% CI: [0.73–1.09], p = 0.22), or maltose (RR = 1.07, 95% CI: [0.88–1.29], p = 0.45).
			Stolzenberg-Solomon et al. (2002) [143] No associations with fruits and berries (HR = 0.85, 95% CI: [0.53–1.35], p = 0.52).
			Gapstur et al. (2000) [145] Increased risk with glycemic load in (RR = 2.39, 95% CI: [1.20–4.79], p = 0.02), but not in women (RR = 1.68, 95% CI: [0.57–4.89], p = 0.43).
Hematologic Cancers	Added sugars/SSBs	Mixed findings	McCullough et al. (2022) [98] No significant association with SSB intake for leukemia (HR: 0.96; 95% CI: [0.86–1.06]; p = 0.969) or multiple myeloma (HR: 0.96; 95% CI: [0.83–1.11]; p = 0.837). Increased risk for non-Hodgkin lymphoma (HR: 1.20; 95% CI: [1.07–1.34]; p = 0.004).
			Tasevska et al. (2012) [119] Increased risk with added fructose intake (HR = 1.53; 95% CI: [0.98–2.38]; p = 0.03).
			Schernhammer et al. (2012) [157] Increased risk of non-Hodgkin lymphoma with soda consumption (RR = 1.66, 95% CI: [1.10–2.51], p = 0.03) in men, but not in women (RR = 1.01, 95% CI: [0.63–1.62], p = 0.59). No associations for leukaemia with soda consumption in men (RR = 0.92, 95% CI: [0.42–2.02], p = 0.61), and women (RR = 1.39, 95% CI: [0.47–4.07], p = 0.21), No associations for multiple myeloma with soda consumption in men (RR = 1.76, 95% CI: [0.77–4.03], p = 0.37), and women (RR = 1.07, 95% CI: [0.36–3.16], p = 0.58).
Larynx/oral cavity/pharynx	Added sugars/SSBs	No or decreased association	McCullough et al. (2022) [98] No significant association with SSB intake (HR: 1.04; 95% CI: [0.88–1.24]; p = 0.592).
			Tasevska et al. (2012) [119] Decreased risk with added sucrose intake (HR = 0.66; 95% CI: [0.50–0.88]; p = 0.003).
Melanoma/Skin Cancer	Added sugars/SSBs	No association	McCullough et al. (2022) [98] No significant association with SSB intake (HR: 1.12; 95% CI: [0.96–1.31]; p = 0.247).
Gastric Cancer	Added sugars/SSBs	Mixed findings	McCullough et al. (2022) [98] No significant association with SSB intake (HR: 1.08; 95% CI: [0.93–1.26]; p = 0.108).
			Hodge et al. (2018) [99] Increased risk with SSB intake (HR = 1.24, 95% CI: [0.77–1.99], p = 0.02/0.37).
			La Vecchia et al. (1998) [159] Increased risk with increasing numbers of spoonful sugar: 1–2 spoons (OR = 1.19, 95% CI: [0.92–1.54], p = 0.001), 3–4 spoons (OR = 1.42, 95% CI: [1.05–1.91], p = 0.001), and 5 spoons (OR = 2.07, 95% CI: [1.47–2.92], p = 0.001).
			Cornée et al. (1995) [160] Increased risk with increased intake of cakes and pastries (OR = 2.96)
			Khairan et al. (2023) [158] No association with overall gastric cancer risk (HR: 0.98; 95% CI: [0.82–1.17], p = 0.48)
Kidney Cancer	Added sugars/SSBs	Mixed findings (mostly no association)	Leung et al. (2021) [131] No association with sugary drinks intake (HR = 1.02, 95% CI: [0.96–1.08], p = 0.51).
			Hodge et al. (2018) [99] No association with SSB intake (HR = 1.32, 95% CI: [0.79–2.19], p = 0.06/0.12).
			McCullough et al. (2022) [98] Increased risk with SSB intake (HR: 1.14; 95% CI: [1.00–1.31]; p = 0.003).
Urinary Tract (Bladder/Urothelial) Cancer	Added sugars/SSBs	Mixed findings	Pou et al. (2014) [168] Increased risk with medium adherence to high-sugar drinks pattern (OR = 2.55, 95% CI: [1.28–5.07], p = 0.008), but not with high adherence (OR = 0.72, 95% CI: [0.60–0.85], p < 0.001).
			Leung et al. (2021) [131] Increased risk with sugary drinks in women after excluding cases diagnosed within the first three years (HR= 1.11 [1.01–1.22]).
			Ros et al. (2011) [171] Weak positive association with urothelial carcinoma per 100 mL/day increase in soft drink intake (HR = 1.06, 95% CI: [1.01–1.12]).
			Michaud et al. (2000) [172] No significant association between soda consumption and bladder cancer risk (HR = 0.99, 95% CI: [0.90–1.08]).
Gall Bladder Cancer	Added sugars/SSBs	No association	McCullough et al. (2022) [98] No significant association with SSB intake (HR: 1.10; 95% CI: [0.84–1.43]; p = 0.099).
	Individual sugar	Increased risk	Tasevska et al. (2012) [119] Increased risk with fructose intake (HR = 1.70; 95% CI: [1.00–2.90]; p = 0.06).
Small intestine Cancer	Added sugars/SSBs	No association	McCullough et al. (2022) [98] No significant association with SSB intake (HR: 1.25; 95% CI: [0.83–1.88]; p = 0.645).
	Individual sugar	Increased risk	Tasevska et al. (2012) [119] Increased risk with fructose intake (HR = 2.10; 95% CI: [1.06–4.16]; p = 0.05).
Glioma/Brain Cancer	Added sugars/SSBs	No association	Dubrow et al. (2012) [173] No association with soda intake and glioma risk (HR = 0.82, 95% CI: [0.67–1.01], p = 0.06).
			McCullough et al. (2022) [98] No significant association with SSB intake (HR: 0.96; 95% CI: [0.84–1.11]; p = 0.714).
Esophageal Cancer	Added sugars/SSBs	Mixed findings (mostly no association)	McCullough et al. (2022) [98] No significant association with SSB intake (HR: 0.87; 95% CI: [0.75–1.01]; p = 0.082).
			Tasevska et al. (2012) [119] Increased risk with added sugar intake (HR = 1.81; 95% CI: [1.16–2.84]; p = 0.008).
			Mayne et al. (2006) [170] No association between soft drink consumption and oesophageal adenocarcinoma (OR = 1.04, 95% CI: [0.70–1.54], p = 0.84).
			Ibiebele et al. (2012) [169] No association between CSD intake and risk of EAC (OR = 0.94, 95% CI: [0.53–1.66], p = 0.85), EJAC (OR = 1.07, 95% CI: [0.67–1.73], p = 0.89). Inverse association with CC (OR = 0.40, 95% CI: [0.20–0.78], p = 0.04).
Gall Bladder Cancer	Added sugars/SSBs	Mixed findings	Leung et al. (2021) [131] Increased risk with sugary drink intake (HR = 1.11, 95% CI: [1.01–1.22], p = 0.03).
			McCullough et al. (2022) [98] No significant association with SSB intake (HR: 1.11; 95% CI: [0.97–1.27]; p = 0.161).
Lung Cancer	Added sugars/SSBs	Mixed findings	McCullough et al. (2022) [98] Decreased risk with SSB intake (HR: 0.92; 95% CI: [0.88–0.96]; p < 0.001).
			De Stefani et al. (1998) [182] No association between sugary beverage intake and lung cancer risk (OR = 1.09, 95% CI: [0.78–1.53], p = 0.61).
	Total sugar intake	No association	Debras et al. (2020) [100] No association with total sugar intake (HR = 1.00, 95% CI: [0.48–2.06], p = 0.9).
	Individual sugar	Decreased risk	Tasevska et al. (2012) [119] Decreased risk with fructose intake (HR = 0.87; 95% CI: [0.75–1.01]; p = 0.03).
	Naturally occurring sugars	Decreased risk	Luqman et al. (2014) [178] Decreased risk with juice intake (OR = 0.3, 95% CI: [0.3–0.4], p < 0.0001), fruit intake (OR = 0.7, 95% CI: [0.5–0.9], p = 0.0135), and milk intake (OR = 0.6, 95% CI: [0.5–0.8], p < 0.0001
Prostate Cancer	Added sugars/SSBs	Mixed findings (mostly no association)	McCullough et al. (2022) [98] No significant association with SSB intake (HR: 1.01; 95% CI: [0.93–1.09]; p = 0.474).
			Drake et al. (2012) [185] No associations for sugar-sweetened beverages (HR = 1.13, 95% CI: [0.92–1.38], p = 0.22), cakes and biscuits (HR = 1.21, 95% CI: [0.94–1.56], p = 0.23), sweets and sugar (HR = 0.93, 95% CI: [0.73–1.19], p = 0.63), or fruit juices (HR = 0.99, 95% CI: [0.81–1.22], p = 0.62).
			Trudeau et al. (2020) [183] Increased risk with sugary drink intake (OR = 1.35, 95% CI: [1.10–1.66], p = 0.002).
			Chazelas et al. (2019) [184] No association with sugary drink intake (HR = 1.10, 95% CI: [0.92–1.31], p = 0.30).
			Makarem et al. (2018) [181] No significant association with sugary foods (HR = 1.00, 95% CI: [0.62–1.62], p > 0.05) or sugary drinks (HR = 1.36, 95% CI: [0.88–2.09], p > 0.05).
			Miles et al. (2018) [179] Increased risk with SSB intake (HR = 1.21, 95% CI: [1.06–1.39], p < 0.01); no significant association with fruit juice intake (HR = 1.07, 95% CI: [0.94–1.22], p > 0.05).
	Individual sugar	No association	Drake et al. (2012) [185] No association for monosaccharides (HR = 1.18, 95% CI: [0.92–1.52], p = 0.59) and sucrose (HR = 0.90, 95% CI: [0.71–1.15], p = 0.83).
	Total sugar	Mixed findings	Liu et al. (2021) [186] Increased PSA concentration (biomarker) with increased sugar intake by 1 g (β = 0.003 ng/mL, 95% CI: [0.001–0.005], p = 0.002).
			Debras et al. (2020) [100] No association with total sugar intake (HR = 1.04, 95% CI: [0.66–1.64], p = 0.8).

SSB (sugar-sweetened beverages), SCB (sugar-containing beverages), GI (glycemic index), DBV (dense breast volume).

.

5. Experimental Evidence

Experimental studies investigating dietary sugars and tumorigenesis have generated mechanistic hypotheses, but most are constrained by artificial models, exaggerated exposures, and surrogate endpoints, limiting their translational value.

Cui et al. [187] reported that fructose enhanced endothelial proliferation and angiogenesis in vitro, with modest in vivo effects. Yet their reliance on inadequate controls (sugar-free serum or water) [188] and mRNA-level endpoints without protein validation [189] undermines experimental validity. While Akt and Src activation were observed [190], absence of pathway crosstalk analysis [191] weakens mechanistic inference. Consistently, Wang et al. [192] found no sucrose-related differences in apoptosis markers in APC^Min mice, underscoring the variability of results across models.

Healy et al. [193] implicated dietary sugar in exacerbating DEN-induced hepatocarcinogenesis, but their conclusions rested on indirect indices of insulin resistance (HOMA-IR, fasting insulin) [194], speculative apoptosis readouts, and confounded ketogenic-diet effects. Similarly, Stamp et al. [195] reported refined sugar-induced colonic proliferation but failed to differentiate malignant from physiological trophic effects on the epithelium.

Frequently cited murine studies repeat these methodological weaknesses. Goncalves et al. [196] demonstrated that daily HFCS gavage accelerated intestinal tumor growth in APC^Min mice, but this required a genetically predisposed background and employed non-physiological dosing. Jiang et al. [197] reported that sucrose-enriched diets (>50% calories) increased mammary tumor burden and metastasis, attributing effects to 12-lipoxygenase activity and 12-HETE accumulation. However, the MMTV-PyMT model invariably develops tumors irrespective of diet, and the extreme sucrose exposure lacks human relevance. Earlier findings by Hei and Sudilovsky [198] in DEN-treated rats follow the same trajectory: sucrose increased hepatic foci but only after chemical initiation, and the surrogate endpoint (enzyme-altered foci) is now recognized as imprecise [199].

Extended the 12-LOX hypothesis to xenograft models, a study reported enhanced mammary tumor growth under sucrose/fructose feeding, yet again employing supraphysiological diets and offering speculative claims of immune modulation without direct mechanistic evidence [197]. More recently, Chang et al. [200] showed that a high-sugar diet upregulated PEPCK1 and promoted Ras/Src-driven tumors in Drosophila, but invertebrate models under exaggerated exposure remain too distant to inform human biology. Nevertheless, the reproducible activation of the 12-LOX/12-HETE axis across multiple dietary sugar models suggests a coherent lipid-mediated signaling pathway that may be relevant to tumor progression under conditions of metabolic excess [198,199,200,201], warranting further investigation in human-relevant experimental systems.

These experimental studies highlight a recurring pattern: dietary sugars may accelerate tumor progression only under conditions of genetic predisposition, chemical initiation, or extreme dietary exposure, but they provide no evidence that sugar initiates carcinogenesis in humans. The consistency lies not in demonstrating causality, but in illustrating the metabolic adaptability of tumor cells which is a property not unique to sugars but shared with amino acids and lipids. Misinterpretation of these preclinical findings has fueled the popular misconception that “sugar feeds cancer,” when the actual evidence is context-dependent, mechanistically limited, and non-translatable to human populations. Importantly, these limitations do not invalidate the mechanistic hypotheses generated by experimental models. Several studies consistently identify biological pathways, such as fructose-mediated de novo lipogenesis, altered lipid signaling through 12-lipoxygenase (12-LOX) and its downstream metabolite 12-HETE, and tumor metabolic flexibility in response to carbohydrate availability, that may contribute to tumor progression under specific metabolic conditions [202,203]. While these mechanisms have largely been demonstrated under supra-physiological sugar exposure or in genetically predisposed systems [203], they remain valuable as hypothesis-generating frameworks. Their relevance should therefore be tested in more human-relevant contexts using physiologic dietary exposures, intact hormonal environments, and translational approaches such as stable isotope tracing, patient-derived organoids, and spatial or single-cell metabolomics.

A summary of experimental evidence is summarized in

Table 2. Critical Summary of Key Experimental Findings.

Study	Model/System	Sugar Exposure	Key Findings	Limitations/Critique
Cui et al. (2023) [187]	CT26, MC38, SW620, SVEC4-10, HUVEC	Fructose, glucose	1—Fructose promoted angiogenesis by activating the Akt/Src pathway, enhancing VEGF expression via ROS-HIF1α, and increasing ATP through Glut5 in endothelial cells 2—Fructose also elevated tumor growth and microvascular density in CT26, MC38, and Panc02 models	Lack of hormonal context (insulin, IGF-1, cytokines)
				Non-physiological in vitro conditions
				Glucose deprivation not reflective of in vivo circulation
				Absence of a fully supplemented control medium
				Potential misinterpretation of fructose effects due to energy rescue; use of dialysed FBS
				Unclear GLUT5 specificity due to compensatory uptake pathways
Healy et al. (2015) [193]	C57BL/6N mice treated with DEN	- Sucrose and fructose - Specific diets (NC, WD-L, WD-C, KD)	1—Sugar increases liver tumor burden independently of obesity/insulin resistance 2—Tumor burden correlated with postprandial insulin, liver IL-6, and liver fat 3—High sugar intake suppressed apoptosis 4—Low sugar diets showed minimal tumor burden.	Tumor promotion may reflect interaction with DEN toxicity rather than dietary sugar alone
				The fructose diet (FD) contained far exceeding typical human dietary patterns
				Absence of true control for sugar media
				Matbolic pathway interactions
				Low statistical Power for some subgroups
Stamp et al. (1993) [195]	Female CF1 (outbred) and C57BL/6J (inbred) mice, treated with Azoxymethane (AOM)	Sucrose, fructose, glucose	Increased proliferation and aberrant crypt foci	No comparison to normal cells and unclear specificity
				Non-physiological dosing-sugar boluses were extremely high, not reflective of normal human intake
				Short-term exposure-acute gavage model does not mimic chronic dietary patterns
				No sucrose-only group without AOM-cannot isolate whether sugar itself induces pre-neoplastic changes
				Endpoints were ACF, not actual tumors
				ACF are early markers, not definitive evidence of cancer
				Lack of dietary complexity (sugars were given without fiber or fat, unlike real diets)
				Increased mitosis alone is not sufficient to infer cancer promotion
Jiang et al. (2016) [197]	MTV-PyMT transgenic mice	Sucrose-enriched diet vs. starch-based diet controls	1—Mice fed high-sucrose diets developed larger and more numerous mammary tumors compared with controls. 2—Sucrose (specifically the fructose component) stimulated 12-lipoxygenase (12-LOX) activity, elevating 12-HETE, a lipid mediator linked to tumor growth and lung metastasis.	Genetically Predisposed Background Non-Physiological Diet Mechanistic Overstatement Failure to Control for Caloric Excess Translational Limitations
Wang et al. (2009) [192]	APC^Min mice	High sucrose diet vs. corn starch	1—Increased tumorigenesis; insulin/IGF-1 pathway implicated 2—More tumors in the proximal small intestine and higher colon adenoma incidence 3—Sucrose-fed mice showed increased colonic epithelial cell proliferation (Increased Ki67 index, Increased PCNA expression) and reduced apoptosis (Decreased TUNEL-positive cells) 4—Sucrose intake was associated with higher serum glucose, insulin, and hepatic IGF-I mRNA expression, supporting a growth-promoting endocrine environment	Results are confounded by fat/energy, sulindac use, and no protein validation
				Exaggerated sucrose exposure
				Apoptosis markers not comprehensive—no use of molecular apoptosis
				No isocaloric macronutrient diversity
Goncalves et al. (2019) [196]	APC^Min mice	High-fructose corn syrup (HFCS)	1—HFCS promoted growth of pre-existing tumors without causing obesity or metabolic syndrome. 2—Tumors showed increased glycolysis and fructose metabolism 3—Fructose “directly feeds” tumor metabolism and accelerates progression.	Mouse Model Bias Cancer-cell specific metabolic dependency Non-Physiological Sugar Exposure Dose Translation Problem No Causation for Tumor Initiation Oversimplification of Metabolism In Dietary fructose intake are incomparable to direct in vivo exposure levels
Hei & Sudilovsky (1985) [198]	Rat model of treated with (DEN)	High-sucrose diet vs. control diets with starch/glucose	High-sucrose diet increased the number of enzyme-altered foci (precancerous lesions) in the liver of DEN-treated rats	Chemical Initiation Required Outdated Methodology Unrealistic Dietary Composition Species-Specific Effects No Mechanistic Clarity Historical Context
Jiang et al. (2016) [197]	MMTV-neu, 4T1, MDA-MB-231 xenografts)	Diets enriched in sucrose/fructose at levels comparable to Western diets	Increased mammary tumor growth and lung metastasis; elevated 12-LOX expression and 12-HETE production, specifically linked to fructose intake	Genetically Predisposed Background Non-Physiological Diet Lack of immune-modulation data Translational Limitations
Chang et al. (2024) [200]	Drosophila Ras/Src tumor model	High-sugar diet (HDS)	DS induced PEPCK1 upregulation; knockdown reduced tumor growth, metastasis signals (Wnt/TOR), and improved survival	Invertebrate model Extreme sugar intake Reflects tumor adaptation, not dietary causation Translational Limitations

CT26 (Colon Tumor 26), MC38 (Murine Colon Adenocarcinoma), SW620 (Human Colorectal Carcinoma), SVEC4-10 (Simian Virus 40-transformed Endothelial Cells), HUVEC (Human Umbilical Vein Endothelial Cells), GLUT5 (Glucose Transporter 5), ATP (Adenosine Triphosphate), VEGF (Vascular Endothelial Growth Factor), ROS (Reactive Oxygen Species), HIF1α (Hypoxia-Inducible Factor 1-alpha), FBS (Fetal Bovine Serum), APC^Min (Adenomatous Polyposis Coli Multiple Intestinal Neoplasia), PCNA (Proliferating Cell Nuclear Antigen), Ki67 (Proliferation Marker Antigen Ki-67), TUNEL (Terminal deoxynucleotidyl transferase dUTP nick end labeling), IGF-I (Insulin-like Growth Factor I), C57BL/6N (Inbred Laboratory Mouse Strain-N substrain), DEN (Diethylnitrosamine), NC (Normal Chow), WD-L (Western Diet-Lard-based), WD-C (Western Diet-Coconut Oil-based), KD (Ketogenic Diet), IL-6 (Interleukin-6), CF1 (Outbred Mouse Strain), C57BL/6J (Inbred Laboratory Mouse Strain-J substrain), AOM (Azoxymethane) and ACF (Aberrant Crypt Foci).

.

6. Psychological Significance

The belief that dietary sugar promotes cancer progression remains prevalent despite lacking clinical and mechanistic support [199]. In contrast, moderate sugar intake integrated into a balanced diet may offer neuropsychological benefits during cancer care [200]. Sucrose and glucose activate dopaminergic, opioidergic, and serotonergic pathways that modulate stress, mood, and emotional resilience, specifically under the psychological strain of diagnosis and treatment [201]. These neurochemical effects are clinically relevant in patients experiencing chemotherapy-induced anorexia, taste alterations, and involuntary weight loss, where sweet foods often remain palatable and support caloric intake [201,202,203]. However, several of the misconceptions shown in

Table 3. Scientific and Epidemiological Refutations of Common Sugar-Cancer Misconceptions.

Myth	Scientific Refutations
Conceptual & Mechanistic Considerations
Dietary sugar is the same as glucose in the body.	Dietary sugars include a range of molecules (such as sucrose (glucose + fructose), lactose, and fructose) that must first be digested and metabolized. The glucose circulating in the bloodstream comes from multiple sources: dietary carbohydrates, glycogen breakdown, and gluconeogenesis from non-carbohydrate sources. Glucose is present in the blood and its levels are maintained independently of dietary sugar intake.
Glucose fuels cancer cell growth, so more glucose means more cancer.	Cancer cells do take up more glucose than normal cells, but this does not mean that higher glucose availability accelerates their growth. Through the Warburg effect, glucose is metabolized inefficiently producing little ATP and instead supplying carbon for biosynthesis. This uptake reflects internal demands of already-malignant cells, not an external stimulus. Critically, increasing glucose levels within physiological limits does not enhance tumor growth, because cancer cell proliferation is driven by oncogenic signaling, not glucose abundance.
Reducing sugar intake limits glucose availability to cancer cells in glycolysis.	Blood glucose levels are tightly regulated by homeostatic mechanisms, including gluconeogenesis and glycogenolysis. Even when dietary sugar is eliminated, the body maintains normal glucose levels by synthesizing glucose from non-carbohydrate sources such as amino acids, lactate, and glycerol. As a result, cancer cells continue to access glucose for glycolysis regardless of dietary sugar intake. Restricting sugar in the diet does not deprive tumors of glucose.
Cancer cells depend entirely on glucose to grow, so limiting glucose will starve cancer cells.	Cancer cells exhibit metabolic plasticity and are not exclusively dependent on glucose. In addition to glycolytic substrates, tumors can utilize glutamine, fatty acids, lactate, and ketone bodies to support ATP production, redox balance, and biosynthesis. This flexibility allows cancer cells to adapt to variable nutrient environments and maintain proliferation even under glucose-limited conditions.
High blood glucose directly activates cancer growth pathways.	Hyperglycemia alone does not initiate oncogenesis. While elevated glucose can modulate signaling cascades (e.g., PI3K/Akt/mTOR), these are primarily activated by oncogenic mutations and hormonal dysregulation. Cancer progression requires persistent genetic and epigenetic alterations, not transient glucose elevations.
High sugar intake is directly linked to cancer development.	High sugar intake is linked with obesity, insulin resistance, and inflammation, and is thus indirectly linked to cancer pathways.
Epidemiological Considerations
Sugar leads to cancer.	Epidemiological studies detect associations, not causations. Causation requires experimental and mechanistic evidence, which is lacking in this context. Thus, sugar intake alone has not been shown to directly initiate cancer.
Most epidemiological evidence shows a significant positive association between sugar intake and cancer progression and risk.	Most large-scale studies report no clear link between sugar intake and cancer. Although some evidence shows weak positive associations (e.g., with colorectal or endometrial cancer), others show no or inverse association (e.g., with lung cancer).
There are some epidemiological studies showing a significant association between sugar intake and cancer risk and progression.	Some studies do report significant positive associations, but still suffer from methodological limitations that affect the reliability and accuracy of the findings (e.g., self-reporting, lack of long-term follow-up).

have led patients to adopt restrictive dietary practices that exclude carbohydrate-rich and nutritionally valuable foods. Such behaviors are associated with increased emotional distress, food-related guilt, and compromised nutritional status [204,205,206], and thus addressing misinformation around diet and cancer has ethical importance, especially that fear-driven dietary restriction can negatively affect patient well-being and treatment tolerance.

Physiological data further support a regulatory role for sugar in stress responses. Intermittent sucrose intake attenuates HPA-axis activation, reducing stress-induced corticosterone release and altering basolateral amygdala circuitry associated with stress resilience [207,208,209,210]. Also, habitual added sugar intake correlates with a blunted cortisol response during acute stress (such as the Cold Pressor Test) even after adjusting for BMI and sex [211,212]. These findings underscore the psychological significance of moderate sugar consumption during cancer treatment, challenging the oversimplified notion that all sugar intake is detrimental in oncology. Addressing these misconceptions by acknowledging sugar’s role in stress modulation may help reduce dietary anxiety and support more effective, evidence-based nutritional care.

7. Public Health, Clinical, and Research Priorities

From a clinical standpoint, dispelling the entrenched belief that dietary sugar promotes cancer progression is essential for optimising care and preserving scientific clarity. Although unsupported by causal evidence, this misconception has driven restrictive dietary practices that may compromise immune function, wound healing, and treatment tolerance specifically in patients undergoing chemotherapy or radiotherapy [213,214,215]. Often rooted in a misapplication of the Warburg effect, this narrative mistakes tumor-intrinsic metabolic reprogramming for dietary dependency.

The singular focus on sugar elimination has also overshadowed more robust, evidence-based nutritional strategies. Dietary patterns that emphasise on nutrient density, fiber, and metabolic homeostasis, such as the Mediterranean and DASH diets, offer greater benefit in survivorship and quality of life [216,217]. Moreover, several of the misconceptions shown in (Table 3) have shaped not only public behavior but also research trajectories, leading to studies confounded by obesity, insulin resistance, and inflammation, and drawing misleading associations.

More critically, the reductive “sugar feeds cancer” paradigm detracts from meaningful scientific inquiry into tumor-host metabolic interactions, hormone-sensitive pathways, and systemic drivers of malignancy. It has also fueled a commercial landscape of “anti-cancer” diets and supplements [218,219] often unsupported by evidence yet capable of delaying treatment and increasing patient burden. Reorienting oncology nutrition toward systems biology and precision medicine is therefore not only scientifically necessary but a public health imperative.

Public health guidance regarding sugar consumption should prioritize overall dietary quality rather than isolated nutrient restriction. The World Health Organization recommends limiting free and added sugars to less than 10% of total energy intake, with a conditional recommendation of less than 5% for additional metabolic benefit [220]. The American Cancer Society similarly emphasizes minimizing sugar-sweetened beverages while promoting dietary patterns rich in whole grains, fruits, vegetables, and legumes [221]. Importantly, oncology-specific nutrition guidelines from the European Society for Clinical Nutrition and Metabolism (ESPEN) caution against unnecessary dietary restriction in cancer patients, highlighting the risks of malnutrition, sarcopenia, and treatment intolerance [222].

For individuals with cancer, there is currently no evidence to support strict sugar avoidance as a strategy to “starve” tumors. Clinicians should counsel patients that circulating glucose levels are tightly regulated through homeostatic mechanisms, even during carbohydrate restriction, and that tumors exhibit metabolic flexibility that limits the efficacy of sugar elimination. Fear-driven restrictive diets may therefore offer no oncologic benefit while increasing nutritional risk and psychological distress. Clinical counseling should focus on: (1) preventing malnutrition and unintended weight loss during treatment, (2) addressing metabolic risk factors such as obesity, insulin resistance, and physical inactivity, (3) reframing sugar as a marker of dietary pattern quality rather than a direct tumor fuel, and (4) encouraging evidence-based dietary patterns rather than elimination of single nutrients.

8. Emerging Technologies and Critical Perspectives on Sugar Metabolism in Tumor Ecosystems

While the current body of epidemiological and mechanistic evidence does not support the notion that dietary sugar directly “feeds” cancer in humans, emerging technologies now offer opportunities to refine how host metabolism, specific sugar substrates, and tumor ecosystems interact in vivo [223]. These approaches may help resolve long-standing ambiguities that have been difficult to address using conventional dietary assessment tools, bulk tissue analyses, and static biomarkers [223].

8.1. Single-Cell and Spatial Approaches

A central limitation of prior metabolic studies is their reliance on bulk tumor or plasma measurements, which obscure profound intra-tumoral heterogeneity [224]. Recent advances in single-cell metabolomics and spatially resolved transcriptomics now enable direct interrogation of metabolic states across distinct cellular compartments within tumors, including malignant cells, immune infiltrates, fibroblasts, and endothelial cells [224]. Spatial transcriptomic studies have demonstrated that expression of glycolytic and pentose phosphate pathway genes varies substantially across tumor regions and correlates with hypoxia, immune exclusion, and stromal composition rather than uniform glucose availability [225,226]. More recently, spatial metabolomic platforms combining mass spectrometry imaging with histopathology have revealed that glucose-derived metabolites and lactate gradients are shaped by vascular proximity and immune cell density rather than dietary intake [227,228]. These technologies are particularly well suited to disentangling whether sugars such as glucose or fructose are preferentially utilized by specific cell populations within the tumor microenvironment [228]. For example, immune cells, especially activated T cells and macrophages, exhibit high glycolytic flux and glucose uptake, often exceeding that of malignant cells, a phenomenon that complicates interpretation of FDG-PET imaging as a proxy for tumor sugar dependence [229,230]. Applying single-cell metabolomics in patient-derived tissues may therefore clarify whether observed glucose avidity reflects anti-tumor immune activity rather than tumor cell fueling [229].

8.2. Stable Isotope Tracing

Stable isotope-resolved metabolomics (SIRM) offers a dynamic approach to track how labeled sugars are metabolized in vivo, providing direct evidence of substrate utilization rather than inferred associations [231]. Human studies using ^13C-glucose and ^13C-fructose tracers have already demonstrated that fructose is predominantly metabolized by the liver and contributes minimally to systemic glucose pools under physiological conditions [232,233,234]. These findings challenge the assumption that dietary fructose directly reaches peripheral tumors in biologically meaningful quantities. In oncology, isotope tracing studies in patients undergoing surgical resection have shown that tumor carbon utilization is highly context-dependent, with many cancers relying heavily on glutamine, lactate, or fatty acids rather than circulating glucose [235,236]. Importantly, isotope tracing in patients also allows separation of host-level metabolic effects (e.g., insulin secretion, hepatic lipogenesis) from tumor-intrinsic metabolism, reinforcing the distinction between indirect systemic effects of sugar intake and direct tumor fueling [237].

8.3. Fructose Versus Glucose Debate

The relative roles of fructose and glucose in cancer biology remain an area of active debate. Experimental studies have shown that some cancer cells can upregulate fructose transporters (GLUT5) and fructolytic enzymes (KHK, ALDOB), enabling fructose to support glycolysis and lipogenesis under specific conditions [238,239] which has fueled concerns that fructose may uniquely promote tumor growth. However, such effects are highly context-specific and often observed under supra-physiological fructose concentrations or in genetically engineered models that may not reflect human exposure [239]. Human feeding studies indicate that fructose is largely cleared by the liver, where excessive intake contributes to de novo lipogenesis, insulin resistance, and non-alcoholic fatty liver disease (NAFLD), rather than direct delivery to peripheral tissues [240,241]. Thus, any cancer-promoting effects of fructose are more plausibly mediated through systemic metabolic dysfunction rather than direct tumor utilization [240]. New research integrating isotope tracing with spatial and single-cell analyses could clarify whether fructose contributes meaningfully to tumor metabolism in vivo or whether its effects are confined to host-level metabolic derangements that secondarily influence cancer risk.

8.4. Timing and Source of Sugar

Another unresolved issue is whether the timing and source of sugar intake modify cancer-relevant metabolic pathways. Emerging evidence suggests that postprandial glycemic excursions, circadian misalignment, and consumption of sugars within ultra-processed foods may exert different metabolic effects compared with sugars consumed within whole-food matrices such as fruits [242]. Whole fruits, despite containing fructose, are consistently associated with neutral or inverse cancer risk, likely due to their fiber content, polyphenols, and effects on satiety and gut microbiota [243]. In contrast, liquid sugars and sugar-sweetened beverages produce rapid glucose and insulin spikes and contribute disproportionately to positive energy balance [242]. These distinctions underscore the importance of dietary context rather than sugar content alone. Combining continuous glucose monitoring, time-restricted feeding paradigms, and metabolic flux analysis may help determine whether sugar timing influences tumor biology indirectly through insulin-IGF-1 signaling, inflammation, or immune modulation.

9. Conclusions

In conclusion, although excessive sugar intake indirectly contributes to cancer through pathways involving obesity, insulin resistance, and chronic inflammation, the current body of epidemiological, experimental, and mechanistic evidence does not support the claim that dietary sugar directly “feeds” cancer in humans. Misrepresenting this relationship perpetuates psychological harm, disordered eating, and nutritional inadequacy specifically among vulnerable patients.

To advance the field, healthcare providers, researchers, and institutions must work collaboratively to dismantle persistent myths (such as the sugar-cancer link) through evidence-based communication, empathetic counseling, and systems-informed research. Nutrition education should emphasise whole-diet patterns, metabolic health, and individualised care, steering away from fear-based dietary narratives. Public engagement efforts must also counter misinformation and empower patients to make confident, informed decisions.

Furthermore, research priorities should shift toward understanding the complex interplay between metabolism, tumor biology, and patient outcomes through integrative, systems-level frameworks not single-nutrient reductionism. It is time to reframe the narrative from fear to resilience, from restriction to science-informed compassion. By replacing reductionist myths with thoughtful, evidence-driven guidance, we can achieve a more accurate, humane, and empowering approach to cancer nutrition, one that truly supports healing in all its dimensions.