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| Name | Class |
|---|---|
| San Diego State University | OTHER |
| The Scripps Research Institute | OTHER |
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The gut microbiome is made up of the microbes (such as bacteria, viruses, and other organisms too small to see with the naked eye) that live in the digestive tract and has been shown to be important in metabolizing food, extracting vitamins and nutrients from food, and maintaining a healthy gut lining. The gut microbiome plays an important role in overall health and has been shown to dynamically change in response to early-stage triple-negative breast cancer-directed therapies, which in turn has been associated with worse outcomes. As the gut microbiome can be further modulated with dietary changes during cancer treatment, it is an ideal potential modifiable risk factor in cancer patients. However, due to multiple confounding factors such as dietary intake, mood, and activity, its utility as part of the oncologic clinical assessment remains unclear.
In this prospective randomized controlled study, the investigators propose to recruit up to 30 early-stage TNBC patients to randomize to a personalized nutritional intervention of a high-fiber diet coached by a registered dietician versus educational handout alone during neoadjuvant treatment. The investigators propose to study the gut microbiota through stool sample analysis among early-stage triple-negative breast cancer patients undergoing neoadjuvant (i.e. before surgery) chemotherapy +/- immunotherapy. The investigators will also study how the gut microbiota can be further modulated with a high-fiber diet, and the investigators hypothesize that a high-fiber diet may play a protective role in preserving gut microbial diversity. As part of the nutritional intervention, the investigators propose to administer nutritional counseling with a registered dietitian (RD) to increase fiber intake and tracking performance status, activity, and mood during neoadjuvant treatment. Finally, the investigators propose to survey participants after study completion through one-on-one interviews to determine whether participants experienced improved overall patient satisfaction in supportive care during their treatment.
This is a randomized, prospective study with a small group of 30 patients (pilot study). Once participants are enrolled, they will be randomized in a 2:1 ratio of either the nutritional intervention (personalized counseling on increasing fiber intake and maintaining adequate caloric intake during breast cancer treatment) or an educational handout on increasing fiber intake. Randomization will be concealed using a random number generator. Investigators and healthcare providers will not be blinded due to the nature of the intervention itself, but all documentation related to the personalized nutritional intervention will not be part of the participant's electronic medical record. Co-investigators completing the data analysis will be blinded to participants' group assignments.
Consent will be obtained upon enrollment. Variables to be collected as part of the baseline demographics questionnaire include: age, gender, marital status, education level, employment status, annual income, residence (ZIP code), BMI, medications and dose, TNBC stage at diagnosis, and treatment type(s).
Participants will complete: interim medication updates including antibiotic use (Interim Survey), gastrointestinal symptoms using the PROMIS GI symptom assessment, dietary intake (NCI-DSQ) with two 24-hour food logs, performance status (FACT-G Scale), anxiety (GAD-7), and depression (PHQ-9), and physical activity (RAPA). If participants report moderate-severe anxiety and/or depression through the GAD-7 and/or PHQ-9 surveys, respectively, they will be notified by telephone or email to contact their primary care provider or oncologist to seek prompt evaluation. Stool samples will be collected at baseline (pre-treatment), 6-week, 12-week, 18-week, and 24-week timepoints. The 6-week interval period was selected based on expected treatment cycles with dose-dense doxorubicin/cyclophosphamide and Taxol +/- pembrolizumab. This interval was also selected based on the minimum amount of time expected for potential changes in dietary intake and symptoms during treatment. Survey reminders will be sent via the app every 6 weeks and data will be exported to RedCap.
The nutritional intervention for the treatment group -- personalized counseling on increasing fiber intake and maintaining adequate caloric intake during treatment -- will be administered as (1) a 60-minute initial telehealth consultation within the first week of study enrollment, and (2) up to two 30-minute follow-ups throughout the study, ideally the first follow-up within 6 weeks of study enrollment. These sessions will be led by a registered dietitian using cultural awareness and symptom assessment. Session notes will be included in the participants' medical records. Control participants' intervention will be an educational handout on increasing fiber intake. San Diego State University (SDSU) masters students in Exercise and Nutritional Science will assist all participants with completing two 24-hour ASA24 food logs at each timepoint along with other surveys. Nutritional composition reported in 24-hour logs will be analyzed at SDSU using ASA24.
Participants will collect stool samples using the Zymo Research kit, which has previously been shown to be equally efficacious as a larger stool sample (scoop),10 mailed to their home. This kit includes a Fecal Collection Tube, a Feces Catcher, a Biohazard Bag, Gloves, and multi-language instructions. To encourage participation and retention, participants will be given a $40 gift certificate per stool sample with up to $200 total compensation. Participants will mail stool samples to the Scripps Biorepository and processed for storage at -80 degrees C. Once all samples are collected, they will be sent to the Scripps Genomics Core for DNA extraction and 16S sequencing. Sequencing data analysis by the CCBB will include taxonomic classification, abundance tables, diversity analysis (alpha and beta indices), and principal component analysis (PCA) plots. Subset analyses will compare participants with high/low fiber consumption, high/low caloric intake, overweight/not overweight by BMI, and cancer-directed treatment (chemotherapy alone or with immunotherapy).
Survey data will be imported into GraphPad Prism for visualization and analyses. For each survey item collected at all 5 time points, a mixed effects model will be used where the survey item result is the dependent variable, group (control or nutritional intervention) and time point are fixed effects, and participant is treated as a random effect. The mixed effects model uses restricted maximum likelihood estimation to account for missing values. Residuals will be examined to ensure approximation of normality is met. P-values will be reported for each fixed effect (group and time) and the interaction between these effects, reported as time x group.
For TME analysis, up to 3 participants with high-fiber dietary intake who experience pCR and 3 participants with residual disease (i.e. up to 6 total) will be selected based on retrospective chart review, and biopsy samples pre- and post-treatment will be identified through the Department of Pathology. Samples will be further processed and mounted onto slides, each with 1 participant with matched pre- and post-neoadjuvant treatment samples per slide for GeoMx spatial transcriptional profiling of 96 regions of interest (ROIs) through the Scripps Genomics Core. The CCBB will perform statistical analysis to identify signaling pathways and immune cell composition in TNBC.
At the end of the study, participants will be offered participation in a one-on-one session via video conferencing platform (such as Zoom) to provide an opportunity for participants to share in their own words their experiences in the study and in using the survey app. Specifically, participants will be asked to discuss the utility of educational materials provided, ease of navigating the study app and participating in the study, and other feedback that will help medical oncologists and dietitians continuously improve patients' experience during neoadjuvant treatment. Participants who uninstall the CareEvolution app or have not engaged with the app for over 60 days will be disenrolled from the study.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Educational Handout | No Intervention | Participants will receive usual standard of care for early-stage triple negative breast cancer and an educational handout on increasing dietary fiber. | |
| High Fiber Dietary Counseling | Experimental | Participants will receive usual standard of care for early-stage triple negative breast cancer and personalized nutritional counseling (initial 1 hour session with up to 2 30-minute follow-up sessions) on how to increase dietary fiber. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Nutritional Counseling | Other | The nutritional intervention for the treatment group -- personalized counseling on increasing fiber intake and maintaining adequate caloric intake during treatment -- will be administered as (1) a 60-minute initial telehealth consultation within the first week of study enrollment, and (2) up to two 30-minute follow-ups throughout the study, ideally the first follow-up within 6 weeks of study enrollment. These sessions will be led by a registered dietitian using cultural awareness and symptom assessment. |
| Measure | Description | Time Frame |
|---|---|---|
| Stool microbiome 16S bacterial species and diversity | Next generation sequencing | From date of enrollment and randomization, with collection at 0, 6, 12, 18, and 24 weeks after date of enrollment for up to 24 weeks. |
| Measure | Description | Time Frame |
|---|---|---|
| Dietary intake - food categories | As measured on NCI-DSQ which assesses consumption of general food categories | From date of enrollment and randomization, with collection at 0, 6, 12, 18, and 24 weeks after date of enrollment for up to 24 weeks. |
| Activity level as measured on Rapid Assessment of Physical Activity scale |
| Measure | Description | Time Frame |
|---|---|---|
| Tumor gene expression analysis using GeoMx spatial transcriptional profiling | Up to 3 participants with high-fiber dietary intake who experience pathologic complete response (pCR) and 3 participants with residual disease (i.e. up to 6 total) will be selected based on retrospective chart review and biopsy samples pre- and post-treatment will be identified. Samples will be further processed and mounted onto slides, each with 1 participant with matched pre- and post-neoadjuvant treatment samples per slide for GeoMx spatial transcriptional profiling of 96 regions of interest (ROIs). |
Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Lee Hong, MD, PhD | Contact | 858-610-1321 | hong.lee@scrippshealth.org | |
| Thomas Buchholz, MD | Contact | 858-678-7190 | buchholz.thomas@scrippshealth.org |
| Name | Affiliation | Role |
|---|---|---|
| Lee Hong, MD, PhD | Scripps Clinic | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Scripps Clinic | Recruiting | La Jolla | California | 92037 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 26269668 | Background | Jandhyala SM, Talukdar R, Subramanyam C, Vuyyuru H, Sasikala M, Nageshwar Reddy D. Role of the normal gut microbiota. World J Gastroenterol. 2015 Aug 7;21(29):8787-803. doi: 10.3748/wjg.v21.i29.8787. | |
| 36446139 | Background | Kok CR, Rose D, Hutkins R. Predicting Personalized Responses to Dietary Fiber Interventions: Opportunities for Modulation of the Gut Microbiome to Improve Health. Annu Rev Food Sci Technol. 2023 Mar 27;14:157-182. doi: 10.1146/annurev-food-060721-015516. Epub 2022 Nov 29. |
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| ID | Term |
|---|---|
| D001943 | Breast Neoplasms |
| D064726 | Triple Negative Breast Neoplasms |
| ID | Term |
|---|---|
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D001941 | Breast Diseases |
| D012871 | Skin Diseases |
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| ID | Term |
|---|---|
| D015596 | Nutrition Assessment |
| ID | Term |
|---|---|
| D003625 | Data Collection |
| D004812 | Epidemiologic Methods |
| D008919 | Investigative Techniques |
| D017531 | Health Care Evaluation Mechanisms |
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|
To score RAPA 1, choose the question with the highest score with an affirmative response. Score as (1): I rarely or never do any physical activities. (2): I do some light or moderate physical activities, but not every week. (3): I do some light physical activity every week. (4): I do moderate physical activities every week, but less than 30 minutes a day or 5 days a week. OR I do vigorous physical activities every week, but less than 20 minutes a day or 3 days a week. (5): I do 30 minutes or more a day of moderate physical activities, 5 or more days a week. I do 20 minutes or more a day of vigorous physical activities, 3 or more days a week. To score RAPA 2, score as (1): I do activities to increase muscle strength, such as lifting weights or calisthenics, once a week or more. (2): I do activities to improve flexibility, such as stretching or yoga, once a week or more. (3) Both. (0) Neither. Add RAPA 1 and 2 for total. Min: 1; Max: 8. Higher score indicates greater activity level. |
| From date of enrollment and randomization, with collection at 0, 6, 12, 18, and 24 weeks after date of enrollment for up to 24 weeks. |
| Depression as measured on Patient Health Questionnaire-9 scale. | 9-question depression scale with each item scored 0 (not at all) to 3 (nearly every day). Min: 0; Max: 27. Higher score indicates greater severity of depression. | From date of enrollment and randomization, with collection at 0, 6, 12, 18, and 24 weeks after date of enrollment for up to 24 weeks. |
| Anxiety as measured on Generalized Anxiety Disorder-7 scale | 7-item questionnaire with each item scored 0 for not at all and 3 for nearly every day. Min: 0; Max: 21. Higher scores indicate greater severity of anxiety. | From date of enrollment and randomization, with collection at 0, 6, 12, 18, and 24 weeks after date of enrollment for up to 24 weeks. |
| Gastrointestinal symptoms | As measured on Patient Reported Outcomes Measurement Information System (PROMIS) Gastrointestinal (GI) symptom assessment. This scale assesses 8 domains: gastroesophageal reflux (13 items), disrupted swallowing (7 items), diarrhea (5 items), bowel incontinence/soilage (4 items), nausea and vomiting (4 items), constipation (9 items), belly pain (6 items), and gas/bloat/flatulence (12 items) (16). All scales are reported in percentiles, among individuals who report that symptom. All scales are calibrated using an item response theory graded response model and scored on a T-score metric with a mean of 50 and standard deviation (s.d.) of 10 in the US general population. A higher score denotes more symptoms on that scale. | From date of enrollment and randomization, with collection at 0, 6, 12, 18, and 24 weeks after date of enrollment for up to 24 weeks. |
| Dietary intake - 24hour food log | As measured on Automated Self-Administered Dietary Assessment Tool (ASA24) food logs which documents every food item consumed over 24 hour period. | From date of enrollment and randomization, with collection at 0, 6, 12, 18, and 24 weeks after date of enrollment for up to 24 weeks. |
| Functional assessment as measured on FACT-G scale | The Functional Assessment of Cancer Therapy-General (FACT-G) scale is comprised of 7 items with a 5-point rating scale (0 = Not at all; 1 = A little bit; 2 = Somewhat; 3 = Quite a bit; and 4 = Very much). Negatively worded items are reverse scored prior to summing so that higher total scores indicate better quality of life. Min: 0; Max: 35. | From date of enrollment and randomization, with collection at 0, 6, 12, 18, and 24 weeks after date of enrollment for up to 24 weeks. |
| 1 year |
| 36428677 | Background | Frak M, Grenda A, Krawczyk P, Milanowski J, Kalinka E. Interactions between Dietary Micronutrients, Composition of the Microbiome and Efficacy of Immunotherapy in Cancer Patients. Cancers (Basel). 2022 Nov 14;14(22):5577. doi: 10.3390/cancers14225577. |
| 37539732 | Background | Jotshi A, Sukla KK, Haque MM, Bose C, Varma B, Koppiker CB, Joshi S, Mishra R. Exploring the human microbiome - A step forward for precision medicine in breast cancer. Cancer Rep (Hoboken). 2023 Nov;6(11):e1877. doi: 10.1002/cnr2.1877. Epub 2023 Aug 4. |
| 34941392 | Background | Spencer CN, McQuade JL, Gopalakrishnan V, McCulloch JA, Vetizou M, Cogdill AP, Khan MAW, Zhang X, White MG, Peterson CB, Wong MC, Morad G, Rodgers T, Badger JH, Helmink BA, Andrews MC, Rodrigues RR, Morgun A, Kim YS, Roszik J, Hoffman KL, Zheng J, Zhou Y, Medik YB, Kahn LM, Johnson S, Hudgens CW, Wani K, Gaudreau PO, Harris AL, Jamal MA, Baruch EN, Perez-Guijarro E, Day CP, Merlino G, Pazdrak B, Lochmann BS, Szczepaniak-Sloane RA, Arora R, Anderson J, Zobniw CM, Posada E, Sirmans E, Simon J, Haydu LE, Burton EM, Wang L, Dang M, Clise-Dwyer K, Schneider S, Chapman T, Anang NAS, Duncan S, Toker J, Malke JC, Glitza IC, Amaria RN, Tawbi HA, Diab A, Wong MK, Patel SP, Woodman SE, Davies MA, Ross MI, Gershenwald JE, Lee JE, Hwu P, Jensen V, Samuels Y, Straussman R, Ajami NJ, Nelson KC, Nezi L, Petrosino JF, Futreal PA, Lazar AJ, Hu J, Jenq RR, Tetzlaff MT, Yan Y, Garrett WS, Huttenhower C, Sharma P, Watowich SS, Allison JP, Cohen L, Trinchieri G, Daniel CR, Wargo JA. Dietary fiber and probiotics influence the gut microbiome and melanoma immunotherapy response. Science. 2021 Dec 24;374(6575):1632-1640. doi: 10.1126/science.aaz7015. Epub 2021 Dec 23. |
| 32101663 | Background | Schmid P, Cortes J, Pusztai L, McArthur H, Kummel S, Bergh J, Denkert C, Park YH, Hui R, Harbeck N, Takahashi M, Foukakis T, Fasching PA, Cardoso F, Untch M, Jia L, Karantza V, Zhao J, Aktan G, Dent R, O'Shaughnessy J; KEYNOTE-522 Investigators. Pembrolizumab for Early Triple-Negative Breast Cancer. N Engl J Med. 2020 Feb 27;382(9):810-821. doi: 10.1056/NEJMoa1910549. |
| 28490673 | Background | Thompson FE, Midthune D, Kahle L, Dodd KW. Development and Evaluation of the National Cancer Institute's Dietary Screener Questionnaire Scoring Algorithms. J Nutr. 2017 Jun;147(6):1226-1233. doi: 10.3945/jn.116.246058. Epub 2017 May 10. |
| 8445433 | Background | Cella DF, Tulsky DS, Gray G, Sarafian B, Linn E, Bonomi A, Silberman M, Yellen SB, Winicour P, Brannon J, et al. The Functional Assessment of Cancer Therapy scale: development and validation of the general measure. J Clin Oncol. 1993 Mar;11(3):570-9. doi: 10.1200/JCO.1993.11.3.570. |
| 34957939 | Background | Hajj-Boutros G, Landry-Duval MA, Comtois AS, Gouspillou G, Karelis AD. Wrist-worn devices for the measurement of heart rate and energy expenditure: A validation study for the Apple Watch 6, Polar Vantage V and Fitbit Sense. Eur J Sport Sci. 2023 Feb;23(2):165-177. doi: 10.1080/17461391.2021.2023656. Epub 2022 Jan 31. |
| 32833508 | Background | Kurian SM, Gordon S, Barrick B, Dadlani MN, Fanelli B, Cornell JB, Head SR, Marsh CL, Case J. Feasibility and Comparison Study of Fecal Sample Collection Methods in Healthy Volunteers and Solid Organ Transplant Recipients Using 16S rRNA and Metagenomics Approaches. Biopreserv Biobank. 2020 Oct;18(5):425-440. doi: 10.1089/bio.2020.0032. Epub 2020 Aug 21. |
| D017437 |
| Skin and Connective Tissue Diseases |
| D011787 | Quality of Health Care |
| D017530 | Health Care Quality, Access, and Evaluation |
| D015991 | Epidemiologic Measurements |
| D011634 | Public Health |
| D004778 | Environment and Public Health |