Milk and Egg Are Risk Factors for Adverse Effects of Capecitabine-Based Chemotherapy in Chinese Colorectal Cancer Patients

Jinrong Xu, Zeshuai Lin, Jiani Chen, Jian Zhang, Wanqing Li, Rui Zhang, Jin Xing, Zhihuan Ye, Xiaoping Liu, Qianmin Gao, Xintao Chen, Jingwen Zhai, Houshan Yao, Mingming Li, Hua Wei, Jinrong Xu, Zeshuai Lin, Jiani Chen, Jian Zhang, Wanqing Li, Rui Zhang, Jin Xing, Zhihuan Ye, Xiaoping Liu, Qianmin Gao, Xintao Chen, Jingwen Zhai, Houshan Yao, Mingming Li, Hua Wei

Abstract

Background: Chemotherapy-induced adverse effects (CIAEs) remain a challenging problem due to their high incidences and negative impacts on treatment in Chinese colorectal cancer (CRC) patients. We aimed to identify risk factors and predictive markers for CIAEs using food/nutrition data in CRC patients receiving post-operative capecitabine-based chemotherapy.

Methods: Food/nutrition data from 130 Chinese CRC patients were analyzed. Univariate and multivariate analyses were used to identify CIAE-related food/nutrition factors. Prediction models were constructed based on the combination of these factors. The area under the receiver operating characteristic curve (AUROC) was used to evaluate the discrimination ability of models.

Results: A total of 20 food/nutrition factors associated with CIAEs were identified in the univariate analysis after adjustments for total energy and potential confounding factors. Based on multivariate analysis, we found that, among these factors, dessert, eggs, poultry, and milk were associated with several CIAEs. Most importantly, poultry was an overall protective factor; milk and egg were risk factors for hand-foot syndrome (HFS) and bone marrow suppression (BMS), respectively. Developed multivariate models in predicting grade 1 to 3 CIAEs and grade 2/3 CIAEs both had good discrimination (AUROC values from 0.671 to 0.778, 0.750 to 0.946 respectively), which had potential clinical application value in the early prediction of CIAEs, especially for more severe CIAEs.

Conclusions: Our findings suggest that patients with high milk and egg intakes should be clinically instructed to control their corresponding dietary intake to reduce the likelihood of developing HFS and BMS during capecitabine-based chemotherapy, respectively.

Trial registration: ClinicalTrials.gov Identifier: NCT03030508.

Keywords: anemia; bone marrow suppression; capecitabine; chemotherapy-induced adverse effects; chemotherapy-induced nausea and vomiting; colorectal cancer; food/nutrition factor; hand-foot syndrome.

Conflict of interest statement

Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
The characteristics of CIAEs. (A) The effects of patient clinical covariates on food/nutrition data. (B) Incidence rate of CIAEs. (C) The Pearson correlations across CIAEs. The CIAEs were subject to hierarchical clustering order using the agglomeration method with “hclust” by R package corrplot. Statistical significance: ***P < .001. **P < .01. *P < .05. Abbreviations: BMS, bone marrow suppression; CINV, chemotherapy-induced nausea and vomiting; HFS, hand-foot syndrome; IALT, aspartate aminotransferase increased; IAST, aspartate aminotransferase increased; TCP, thrombocytopenia.
Figure 2.
Figure 2.
Receiver operating characteristic (ROC) curve for the developed models using relevant food and nutrition factors to predict CIAEs. (A) to (T) show the ROC curves for the models of anemia 1-3 vs 0, BMS 1-3 vs 0, BMS 2/3 vs 0, CINV 1-3 vs 0, CINV 2/3 vs 0, constipation 1-3 vs 0, diarrhea 1-3 vs 0, diarrhea 2/3 vs 0, HFS 1-3 vs 0, HFS 2/3 vs 0, IALT 1-3 vs 0, IALT 2/3 vs 0, IAST 1-3 vs 0, IAST 2/3 vs 0, leukopenia 1-3 vs 0, nausea 1-3 vs 0, neutropenia 1-3 vs 0, neutropenia 2/3 vs 0, TCP 1-3 vs 0, TCP 2/3 vs 0, respectively. “Com” indicates the multivariate models incorporating significantly relevant nutrition predictors from univariate analysis. Abbreviations: Ca, calcium; Com, combination; DGV, dark green vegetables; FWS, food with stuffing; MM, manufactured meat; SD, sweet drinks; VA, vitamin A; VB2, vitamin B2.
Figure 3.
Figure 3.
CIAE-related food/nutrition factors and plasma metabolites. Correlations between HFS-related (A) and BMS-related (B) food/nutrition factors and plasma metabolome (left), and selected average levels of related metabolites for the CRC patients in groups 1 to 3 versus 0, and groups 2/3 versus 0 (right). Abbreviations: DHT, 5α-dihydrotestosterone; FAHFA, fatty acid ester of hydroxyl fatty acid; LysoPC, lysophosphatidylcholines; PC, phosphatidylcholine; PE, phosphatidylethanolamine; PI, phosphatidylinositol; PS, phosphatidylserine; SM, sphingomyelin.

References

    1. Lam SW, Guchelaar HJ, Boven E. The role of pharmacogenetics in capecitabine efficacy and toxicity. Cancer Treat Rev. 2016;50:9-22.
    1. Benson AB, Venook AP, Al-Hawary MM, et al.. NCCN guidelines insights: colon cancer, version 2.2018. J Natl Compr Canc Netw. 2018;16:359-369.
    1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68:394-424.
    1. Newman NB, Sidhu MK, Baby R, et al.. Long-term bone marrow suppression during postoperative chemotherapy in rectal cancer patients after preoperative chemoradiation therapy. Int J Radiat Oncol Biol Phys. 2016;94:1052-1060.
    1. Yap YS, Kwok LL, Syn N, et al.. Predictors of hand-foot syndrome and pyridoxine for prevention of capecitabine-induced hand-foot syndrome: a randomized clinical trial. JAMA Oncol. 2017;3:1538-1545.
    1. Chan SL, Chan AWH, Mo F, et al.. Association between serum folate level and toxicity of capecitabine during treatment for colorectal cancer. Oncologist. 2018;23:1436-1445.
    1. Li M, Chen J, Liu S, et al.. Spermine-related DNA hypermethylation and elevated expression of genes for collagen formation are susceptible factors for chemotherapy-induced hand-foot syndrome in Chinese colorectal cancer patients. Front Pharmacol. 2021;12:2267.
    1. Li M, Chen J, Deng Y, et al.. Risk prediction models based on hematological/body parameters for chemotherapy-induced adverse effects in Chinese colorectal cancer patients. Support Care Cancer. 2021;29:7931-7947.
    1. Li M, Sun X, Yao H, et al.. Genomic methylation variations predict the susceptibility of six chemotherapy related adverse effects and cancer development for Chinese colorectal cancer patients. Toxicol Appl Pharmacol. 2021;427:115657.
    1. Yao H, Xu H, Qiu S, et al.. Choline deficiency-related multi-omics characteristics are susceptible factors for chemotherapy-induced thrombocytopenia. Pharmacol Res. 2022;178:106155.
    1. López-Pousa A, Rifà J, Casas de Tejerina A, et al.. Risk assessment model for first-cycle chemotherapy-induced neutropenia in patients with solid tumours. Eur J Cancer Care. 2010;19:648-655.
    1. Deng Y, Yao H, Chen W, et al.. Profiling of polar urine metabolite extracts from Chinese colorectal cancer patients to screen for potential diagnostic and adverse-effect biomarkers. J Cancer. 2020;11:6925-6938.
    1. Ueland PM, Ulvik A, Rios-Avila L, Midttun Ø, Gregory JF. Direct and functional biomarkers of vitamin B6 status. Annu Rev Nutr. 2015;35:33-70.
    1. Zuo H, Ueland PM, Eussen SJP, et al.. Markers of vitamin B6 status and metabolism as predictors of incident cancer: the Hordaland Health study. Int J Cancer. 2015;136:2932-2939.
    1. Chen W, Li M, Yao H, et al.. Application values of tumor markers and inflammatory markers in diagnosis of colorectal cancer and prediction of chemotherapy-related adverse effects. Tumori. 2018;38:1038-1047.
    1. Xu R, Li J, Yuan Y, Wang J, Chen B, Zhao J. Preliminary study on prediction model of adverse reactions in patients with lymphatic tumors after chemotherapy with high dose methotrexat. Chin J Mod Appl Pharm. 2018;35:878-883.
    1. Moreau M, Klastersky J, Schwarzbold A, et al.. A general chemotherapy myelotoxicity score to predict febrile neutropenia in hematological malignancies. Ann Oncol. 2009;20:513-519.
    1. Razzaghdoust A, Mofid B, Moghadam M. Development of a simplified multivariable model to predict neutropenic complications in cancer patients undergoing chemotherapy. Support Care Cancer. 2018;26:3691-3699.
    1. Seo SH, Kim SE, Kang YK, et al.. Association of nutritional status-related indices and chemotherapy-induced adverse events in gastric cancer patients. BMC Cancer. 2016;16:900.
    1. He Y, Jian Z, Ou Yang M, Peng W, Zhang M. Using mini-nutritional assessment to investigate the nutritional status of the aged hospitalized patients. Chin J Clin Nutr. 2004;2004:20-23.
    1. Lei B, Zheng G. Chemotherapy-induced myelosuppression of non-small cell lung cancer: clinical analysis of risk factors and development of a predictive model. J Clin Med Lit. 2015;2:7378-7379.
    1. Kim SH, Lee SM, Jeung HC, et al.. The effect of nutrition intervention with oral nutritional supplements on pancreatic and bile duct cancer patients undergoing chemotherapy. Nutrients. 2019;11:E1145.
    1. Gao J, Fei J, Jiang L, Yao W, Lin B, Guo H. Assessment of the reproducibility and validity of a simple food-frequency questionnnaire used in dietary patterns studies. Acta Nutr Sin. 2011;33:452-456.
    1. Zang J, Luo B, Chang S, et al.. Validity and reliability of a food frequency questionnaire for assessing dietary intake among Shanghai residents. Nutr J. 2019;18:30.
    1. Yang Y, Wang G, Pan X. China Food Composition Table. Peking University Medical Press; 2002.
    1. Yang Y. China Food Composition Table. 1st ed. Peking University Medical Press; 2004.
    1. Bushel P. PVCA: Principal Variance Component Analysis (PVCA). R Package Version 1.30.0. 2020. doi:10.18129/B9.bioc.pvca
    1. Willett WC, Howe GR, Kushi LH. Adjustment for total energy intake in epidemiologic studies. Am J Clin Nutr. 1997;65:1220S-1228S; discussion 1229S.
    1. Miller KK, Gorcey L, McLellan BN. Chemotherapy-induced hand-foot syndrome and nail changes: a review of clinical presentation, etiology, pathogenesis, and management. J Am Acad Dermatol. 2014;71:787-794.
    1. Isoardi KZ, Harris K, Carmichael KE, Dimeski G, Chan BSH, Page CB. Acute bone marrow suppression and gastrointestinal toxicity following acute oral methotrexate overdose. Clin Toxicol. 2018;56:1204-1206.
    1. Hu W, Sung T, Jessen BA, et al.. Mechanistic investigation of bone marrow suppression associated with palbociclib and its differentiation from cytotoxic chemotherapies. Clin Cancer Res. 2016;22:2000-2008.
    1. Szewczuk M, Gasiorowska E, Matysiak K, Nowak-Markwitz E. The role of artificial nutrition in gynecological cancer therapy. Ginekol Pol. 2019;90:167-172.
    1. Marangoni F, Corsello G, Cricelli C, et al.. Role of poultry meat in a balanced diet aimed at maintaining health and wellbeing: an Italian consensus document. Food Nutr Res. 2015;59:27606. doi:10.3402/fnr.v59.27606
    1. Kim SR, Kim K, Lee SA, et al.. Effect of red, processed, and white meat consumption on the risk of gastric cancer: an overall and dose−response meta-analysis. Nutrients. 2019;11:826. doi:10.3390/nu11040826
    1. Zhang RX, Wu XJ, Wan DS, et al.. Celecoxib can prevent capecitabine-related hand-foot syndrome in stage II and III colorectal cancer patients: result of a single-center, prospective randomized phase III trial. Ann Oncol. 2012;23:1348-1353.
    1. Vors C, Joumard-Cubizolles L, Lecomte M, et al.. Milk polar lipids reduce lipid cardiovascular risk factors in overweight postmenopausal women: towards a gut sphingomyelin-cholesterol interplay. Gut. 2020;69:487-501.
    1. Ulven SM, Holven KB, Gil A, Rangel-Huerta OD. Milk and dairy product consumption and inflammatory biomarkers: an updated systematic review of randomized clinical trials. Adv Nutr. 2019;10:S239-S250.
    1. Benmoussa A, Diallo I, Salem M, et al.. Concentrates of two subsets of extracellular vesicles from cow’s milk modulate symptoms and inflammation in experimental colitis. Sci Rep. 2019;9:14661.
    1. Redondo N, García-González N, Diaz-Prieto LE, et al.. Effects of ewe’s milk yogurt (whole and semi-skimmed) and cow’s milk yogurt on inflammation markers and gut microbiota of subjects with borderline-high plasma cholesterol levels: a crossover study. Eur J Nutr. 2019;58:1113-1124.
    1. Bordoni A, Danesi F, Dardevet D, et al.. Dairy products and inflammation: a review of the clinical evidence. Crit Rev Food Sci Nutr. 2017;57:2497-2525.
    1. Tall AR, Yvan-Charvet L. Cholesterol, inflammation and innate immunity. Nat Rev Immunol. 2015;15:104-116.
    1. Shi H, Lo TH, Ma D, et al.. Dihydrotestosterone (DHT) enhances wound healing of major burn injury by accelerating resolution of inflammation in mice. Int J Mol Sci. 2020;21:6231.
    1. Forbes CA, Worthy G, Harker J, et al.. Dose efficiency of erythropoiesis-stimulating agents for the treatment of patients with chemotherapy-induced anemia: a systematic review. Clin Ther. 2014;36:594-610.
    1. Grimes CN, Fry MM. Nonregenerative anemia: mechanisms of decreased or ineffective erythropoiesis. Vet Pathol. 2015;52:298-311.
    1. Seita J, Weissman IL. Hematopoietic stem cell: self-renewal versus differentiation. Wiley Interdiscip Rev Syst Biol Med. 2010;2:640-653.
    1. Mendelson A, Frenette PS. Hematopoietic stem cell niche maintenance during homeostasis and regeneration. Nat Med. 2014;20:833-846.
    1. Baumgartner S, Kelly ER, van der Made S, et al.. The influence of consuming an egg or an egg-yolk buttermilk drink for 12 wk on serum lipids, inflammation, and liver function markers in human volunteers. Nutrition. 2013;29:1237-1244.
    1. Lemos BS, Medina-Vera I, Blesso CN, Fernandez ML. Intake of 3 eggs per day when compared to a choline bitartrate supplement, downregulates cholesterol synthesis without changing the LDL/HDL ratio. Nutrients. 2018;10:E258.
    1. Billah MM, Anthes JC. The regulation and cellular functions of phosphatidylcholine hydrolysis. Biochem J. 1990;269:281-291.
    1. Kabarowski JH, Xu Y, Witte ON. Lysophosphatidylcholine as a ligand for immunoregulation. Biochem Pharmacol. 2002;64:161-167.
    1. Liu C, Han T, Stachura DL, et al.. Lipoprotein lipase regulates hematopoietic stem progenitor cell maintenance through DHA supply. Nat Commun. 2018;9:1310.
    1. Obeid R, Awwad HM, Knell AI, Hübner U, Geisel J. Glucose and fat tolerance tests induce differential responses in plasma choline metabolites in healthy subjects. Nutrients. 2018;10:E1209.
    1. Chen M, Zheng H, Wei T, et al.. High glucose-induced PC12 cell death by increasing glutamate production and decreasing methyl group metabolism. Biomed Res Int. 2016;2016:4125731.
    1. Hannun YA, Obeid LM. Principles of bioactive lipid signalling: lessons from sphingolipids. Nat Rev Mol Cell Biol. 2008;9:139-150.
    1. Niazi H, Zoghdani N, Couty L, et al.. Murine platelet production is suppressed by S1P release in the hematopoietic niche, not facilitated by blood S1P sensing. Blood Adv. 2019;3:1702-1713.
    1. Marks PW. Hematologic manifestations of liver disease. Semin Hematol. 2013;50:216-221.
    1. Millar CL, Norris GH, Vitols A, et al.. Dietary egg sphingomyelin prevents aortic root plaque accumulation in apolipoprotein-E knockout mice. Nutrients. 2019;11:E1124. doi:10.3390/nu11051124
    1. Dorninger F, Wiesinger C, Braverman NE, Forss-Petter S, Berger J. Ether lipid deficiency does not cause neutropenia or leukopenia in mice and men. Cell Metab. 2015;21:650-651.
    1. Estrela GR, Arruda AC, Torquato HFV, et al.. Gemfibrozil induces anemia, leukopenia and reduces hematopoietic stem cells via PPAR-α in mice. Int J Mol Sci. 2020;21:E5050. doi:10.3390/ijms21145050

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