Personalizing Nutritional Therapy in Pediatric Oncology: The Role of Gut Microbiome Profiling and Metabolomics in Mitigating Mucositis and Enhancing Immune Response to Chemotherapy
Abstract
1. Introduction
2. Materials and Methods
2.1. Literature Search Strategy
2.1.1. Time Frame and Language Criteria
2.1.2. Keywords and Search Query Construction
- Population: Pediatric OR children OR adolescent OR oncology OR leukemia OR acute lymphoblastic leukemia (ALL) OR acute myeloid leukemia (AML) OR hematopoietic stem cell transplantation (HSCT).
- Exposure (Microbiome/Metabolome): Gut microbiome OR microbiota OR dysbiosis OR metabolomics OR short-chain fatty acids (SCFAs) OR butyrate OR propionate OR acetate.
- Outcome (Toxicity/Effect): Mucositis OR sepsis OR intestinal inflammation OR gastrointestinal toxicity OR graft-versus-host disease (GvHD) OR immune function OR T cell OR probiotic OR prebiotic OR synbiotic OR postbiotic OR nutritional intervention.
2.2. Inclusion and Exclusion Criteria
2.2.1. Inclusion Criteria
- Clinical Studies—randomized controlled trials (RCTs), prospective and retrospective cohort studies, and pilot studies.
- Preclinical/Experimental Studies—studies conducted in animal models (primarily murine models of mucositis or graft-versus-host disease) providing mechanistic evidence (for example, the role of short-chain fatty acids in immunomodulation and intestinal barrier integrity).
- Review Articles and Meta-Analyses—included as reference sources to identify additional key publications using a snowballing approach.
- Publications focusing on:
- ·
- Correlations between changes in microbiome composition (16S ribosomal ribonucleic acid sequencing or shotgun metagenomic sequencing) and clinical outcomes.
- ·
- Associations between metabolites (measurement of short-chain fatty acid concentrations in stool or serum) and the severity of complications.
- ·
- The impact of nutritional interventions on microbiome modulation in pediatric patients undergoing oncological treatment.
2.2.2. Exclusion Criteria
- Case reports and letters to the editor.
- Studies focusing exclusively on adult populations (>18 years of age).
- Publications not classified as peer-reviewed scientific articles (for example, conference abstracts without full-text availability).
- Articles that did not provide quantitative microbiome or metabolomic data.
2.3. Study Selection and Data Extraction Process
2.3.1. Study Selection
- Titles and abstracts were screened to exclude irrelevant publications or those not meeting the inclusion criteria.
- Full texts of potentially relevant articles were assessed to confirm final eligibility. Discrepancies between reviewers were resolved through discussion or consultation with a third independent researcher.
2.3.2. Data Extraction
- Study Identification—authors, year of publication, study design, population characteristics (number of patients, age, type of malignancy and treatment).
- Microbiome Analysis Methods—analytical method and taxonomic resolution.
- Metabolomic Analysis Methods—analytical technique and concentrations of key short-chain fatty acids.
- Clinical Outcomes—severity of mucositis (according to the World Health Organization scale or the Oral Mucositis Assessment Scale), incidence and type of infections (sepsis), and risk of graft-versus-host disease.
- Type of Intervention—probiotic, prebiotic, dietary intervention, or combined approaches.
- Key Findings—reported correlations between microbiome composition or short-chain fatty acid levels and treatment-related toxicity or intervention effectiveness.
2.4. Quality Assessment
2.5. Data Synthesis Methods
- Identification of consistent and reproducible dysbiosis patterns associated with clinical complications.
- Determination of short-chain fatty acid thresholds associated with increased risk.
- Integration of mechanistic (preclinical) and clinical evidence regarding the impact of interventions on the microbiome–metabolome–immune axis.
3. Results
3.1. Gut Microbiome Profiling and Fecal Metabolomics as Predictors of Toxicity
3.1.1. Intestinal Dysbiosis in Pediatric Patients Undergoing Chemotherapy and HSCT
3.1.2. Depletion of Protective Taxa and Expansion of Pathobionts
3.2. Metabolomic Correlates of Treatment Toxicity: The Role of SCFAs
3.3. Potential Nutritional Therapy for Gut Microbiome Modulation
3.3.1. Probiotics
3.3.2. Prebiotics
3.3.3. Postbiotic
3.3.4. Fecal Microbiome Transplantation
3.4. Improvement in Long-Term Clinical Outcomes and QoL
3.4.1. Correlation Between Microbiome Modulation and Chemotherapy Dose Intensity
3.4.2. Reduction in Long-Term Complication Risk: Impact on Chronic Intestinal Inflammation and the Risk of Secondary Cancers
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
| HSCT | Hematopoietic stem cell transplantation |
| SCFA | Short-chain fatty acid |
| GvHD | Graft-versus-host disease |
| FMT | Fecal microbiota transplantation |
| RDI | Relative dose intensity |
| ALL | Acute lymphoblastic leukemia |
| QoL | Quality of life |
| OS | Overall survival |
| NASPGHAN | North American Society for Pediatric Gastroenterology, Hepatology and Nutrition |
| ESPEN | European Society for Clinical Nutrition and Metabolism |
| AML | Acute myeloid leukemia |
| OTU | Operational taxonomic units |
| LBP | Lactobacillus plantarum |
| IMD | Intestinal mucosal damage |
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| Identification Code | NCT04111471 | NCT04263597 |
|---|---|---|
| Type of trial | randomized | a single center prospective study |
| The studied substance | inulin | 2′-fucosyllactose |
| Drug administration | orally | orally |
| Study duration | 2019–2024 | 2020–2025 |
| Clinical trial phase | not applicable | phase I/IIa |
| Age of the patients | 2–18 years | Arm 1: 0–5 years; Arm 2: 5.1–10 years; Arm 3: >10 years |
| Number of enrolled patients | 40 | 70 |
| Time of administration | from day −7 until day +14 after transplant | from day −7 until day + 30 after HSCT |
| Organizations involved with this study | Ann & Robert H Lurie Children’s Hospital of Chicago | Children’s Hospital Medical Center, Cincinnati |
| Patient Type | Number of Patients | Age Range | Article Type | Main Results | References |
|---|---|---|---|---|---|
| refractory acute GvHD 1 | 1 | 5 years | case study | a clinical symptoms reduction and increased bacterial diversity, an enrichment of Firmicutes, and a reduction in Proteobacteria | [70] |
| patients with ALL 2 colonized by MDR 3 bacteria | 5 | 2–18 years | case series study | 80% MDR 3 bacteria decolonization within one week | [71] |
| immunocompromised included: solid organ transplantation malignancy, primary immunodeficiency, or other chronic conditions | 59 | 1.5–18 years | multi-center retrospective cohort study | 79% after 1st FMT 4, 86% after 1 or more FMT 4, no MDR 3 infections and no deaths | [72] |
| children with recurrent CDI 5 | 49 | 4 to 193 months-old | retrospective study | 26.32% short-term negative side effects (mostly mild) | [73] |
| HSCT 6 recipients with CDI 5 | 7 | 25–67 years | retrospective study | 85.7% of FMT 4 recipients had no CDI 5 recurrence and no serious side effects were identified | [74] |
| patients with hematologic malignancies (4 after and 6 before allo-HSCT 6) colonized with MDR 3 bacteria | 10 | 16–64 years | retrospective study | decolonization in 7 of 10 patients, FMT 4 was safe: 1 patient had constipation, and 2 had grade I diarrhea | [75] |
| children with GvHD 1 and antibiotic-resistant colitis developed after allo-HSCT 6 | 7 | 3–10 years | prospective single-centerstudy | 6 of 7 patients reached a clinical response, an increased number of Bacteroides fragilis, Escherichia coli and Faecalibacterium prausnitzii in fecal microbiota since day +8 after FMT 4 was achieved | [68] |
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Pawłowski, P.; Zaj, N.; Iwaniszczuk, K.; Grzelka, I.; Makuch, W.; Samardakiewicz-Kirol, E.; Kościołek, A.; Samardakiewicz, M. Personalizing Nutritional Therapy in Pediatric Oncology: The Role of Gut Microbiome Profiling and Metabolomics in Mitigating Mucositis and Enhancing Immune Response to Chemotherapy. Children 2026, 13, 293. https://doi.org/10.3390/children13020293
Pawłowski P, Zaj N, Iwaniszczuk K, Grzelka I, Makuch W, Samardakiewicz-Kirol E, Kościołek A, Samardakiewicz M. Personalizing Nutritional Therapy in Pediatric Oncology: The Role of Gut Microbiome Profiling and Metabolomics in Mitigating Mucositis and Enhancing Immune Response to Chemotherapy. Children. 2026; 13(2):293. https://doi.org/10.3390/children13020293
Chicago/Turabian StylePawłowski, Piotr, Natalia Zaj, Kamil Iwaniszczuk, Izabela Grzelka, Wojciech Makuch, Emilia Samardakiewicz-Kirol, Aneta Kościołek, and Marzena Samardakiewicz. 2026. "Personalizing Nutritional Therapy in Pediatric Oncology: The Role of Gut Microbiome Profiling and Metabolomics in Mitigating Mucositis and Enhancing Immune Response to Chemotherapy" Children 13, no. 2: 293. https://doi.org/10.3390/children13020293
APA StylePawłowski, P., Zaj, N., Iwaniszczuk, K., Grzelka, I., Makuch, W., Samardakiewicz-Kirol, E., Kościołek, A., & Samardakiewicz, M. (2026). Personalizing Nutritional Therapy in Pediatric Oncology: The Role of Gut Microbiome Profiling and Metabolomics in Mitigating Mucositis and Enhancing Immune Response to Chemotherapy. Children, 13(2), 293. https://doi.org/10.3390/children13020293

