Research ArticleClinical Studies
Open Access

Anamorelin in Cancer Cachexia: Gut Microbiota Effects and CONUT Score as a Predictor of Response

SHOGEN BOKU, TOMOYO YASUDA, TATSUKI IKOMA, ERI MATSUMORI, SAWAKO YOSHIUCHI, YOSHIYUKI MATSUO, KOICHIRO HIGASA and TAKAYASU KURATA
In Vivo November 2025, 39 (6) 3626-3635; DOI: https://doi.org/10.21873/invivo.14161

Abstract

Background/Aim: Anamorelin, a ghrelin receptor agonist, increases body weight and lean body mass (LBM); however, its effects on the gut microbiota remain unclear. Furthermore, the predictive value of nutritional scores, such as the Controlling Nutritional Status (CONUT) score, for anamorelin response is not established. This study aimed to evaluate the effects of anamorelin on body weight, quality of life (QOL), and gut microbiota in patients with advanced cancer and cachexia, and to clarify the predictive role of nutritional indicators.

Patients and Methods: This single-center prospective observational study enrolled cachectic patients (non-small cell lung, pancreatic, gastric, or colorectal cancer) receiving anamorelin 100 mg/day with dietary counseling. Outcomes included change in body weight (baseline, 3, 6, 12 weeks), QOL (EORTC QLQ-C15-PAL), and gut microbiota diversity. The association between the baseline CONUT score and weight gain (>0 kg at 6 weeks) was analyzed.

Results: Sixteen patients were analyzed. Body weight significantly increased from baseline at weeks 3, 6, and 12 (mean change at 12 weeks: +2.61±0.72 kg, p=0.008). In the eight patients assessed for QOL, the overall scale showed no significant change. The score for appetite loss (Q8) was 2.125±0.835 at 0 weeks vs. 1.375±0.744 at 6 weeks (unadjusted p=0.033). Gut microbiota alpha and beta diversity showed no significant change. A high baseline CONUT score (≥5) was associated with failure to gain weight in six weeks compared to a score <5 (87.5% of non-gainers had a high score vs. 12.5%; unadjusted p=0.01).

Conclusion: In this pilot study, anamorelin significantly increased body weight and suggested an improvement in appetite in patients with cancer and cachexia. No significant changes in overall QOL or gut microbiota diversity were detected at 6 weeks. The finding that a high baseline CONUT score may predict a lack of short-term weight gain warrants further investigation.

Keywords:

Introduction

Cancer cachexia is a debilitating multifactorial syndrome frequently observed in patients with advanced cancer, characterized by involuntary weight loss, primarily from skeletal muscle depletion, often accompanied by fat loss (1). This condition significantly impairs physical function, reduces quality of life (QOL), and is associated with poor prognosis and decreased tolerance and response to cancer therapies (2-7). The pathophysiology involves complex interactions between tumor-derived factors and host inflammatory responses, leading to metabolic dysregulation and tissue wasting (8). Despite its clinical significance, establishing effective standard treatments remains a challenge, although multimodal approaches including nutritional support and exercise are recommended (9).

Anamorelin, an oral ghrelin receptor agonist, represents a pharmacological approach to counteract cachexia. By mimicking ghrelin, anamorelin stimulates appetite and growth hormone secretion, which subsequently promotes insulin-like-growth factor-1 (IGF-1) production, potentially leading to increased muscle mass and body weight (10, 11). Several clinical trials have demonstrated its efficacy in increasing lean body mass (LBM) in cancer patients with cachexia (12, 13). However, the response to anamorelin varies among patients, and a deeper understanding of its effects beyond LBM and appetite is needed.

The gut microbiota plays a crucial role in regulating host metabolism, inflammation, and immune function (14). Gut dysbiosis, an imbalance in this microbial community, often occurs in patients with cancer and may contribute to the systemic inflammation and metabolic alterations characteristic of the cachexia phenotype (15). Consequently, while modulating gut microbiota is a potential therapeutic strategy in cancer care, its interaction with specific cachexia treatments like anamorelin remains poorly understood.

Given the systemic effects of anamorelin and the influence of the gut microbiota on metabolism, investigating the impact of anamorelin on the gut microbial ecosystem warranted investigation. Furthermore, nutritional and inflammatory markers, such as the Controlling Nutritional Status (CONUT) score, are used to assess patient status in cachexia (16, 17). Therefore, the aim of this study was to investigate the effects of anamorelin on the composition and diversity of the gut microbiota in patients with cancer and to explore potential predictive factors for clinical outcomes.

Patients and Methods

Ethical considerations. This study adhered to the principles of the Declaration of Helsinki and the Japanese “Ethical Guidelines for Medical and Biological Research Involving Human Subjects”. The protocol received approval from the Kansai Medical University Hospital Research Ethics Committee (Approval No. 2022019). All patients provided voluntarily written informed consent after being fully informed about the study’s objectives, procedures, and potential risks.

Study design and patients. This single-center, prospective observational study was conducted at the outpatient chemotherapy unit and wards of Kansai Medical University Hospital (Hirakata, Osaka, Japan) between September 2022 and December 2023. Eligible patients were aged ≥20 years with pathologically confirmed non-small cell lung, pancreatic, gastric, or colorectal cancer. They must have experienced ≥5% weight loss within six months with anorexia, and met at least two of the following criteria: fatigue, muscle weakness, C-reactive protein (CRP) >0.5 mg/dl, hemoglobin <12 g/dl, or albumin <3.2 g/dl. An Eastern Cooperative Oncology Group (ECOG) performance status (PS) of 0-2 was required. Exclusion criteria included: expected prognosis <12 weeks; prior anamorelin use; congestive heart failure; history of myocardial infarction or angina; severe conduction disorders; use of specific interacting medications (e.g., clarithromycin); moderate or severe liver dysfunction (Child-Pugh B or C); gastrointestinal obstruction; or active hematological malignancy.

Intervention and assessments. Patients received anamorelin hydrochloride (Adlumiz® 50 mg tablets) 100 mg orally once daily for up to 12 weeks and individual nutritional guidance from registered dietitians every three weeks. The primary outcome was the change in body weight from baseline at weeks 3, 6, and 12. Secondary outcomes included changes in QOL scores (EORTC QLQ-C15-PAL) and gut microbiota diversity at week 6. Clinical data, including body weight and blood tests, were collected at baseline, week 3, 6, and 12. The Controlling Nutritional Status (CONUT) score (18), CRP albumin ratio (CAR), modified Glasgow prognostic score (mGPS), neutrophil-lymphocyte ratio (NLR), and Prognostic Nutritional Index (PNI) were calculated.

Gut microbiome analysis. Fecal samples were collected at baseline and week 6. DNA was extracted using the Maxwell® RSC Fecal Microbiome DNA Kit (Promega, Madison, WI, USA). Library preparation targeting the V3-V4 regions of the 16S rRNA gene was performed using primers V3-F (5′-TCGTCGGCAGCGTCAGATGTGTATAAGAG ACAGCCTACGGGNGGCWGCAG-3′) and V4-R (5′-GTCT CGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGG TATCTAATCC-3′). Libraries were sequenced on an Illumina MiSeq platform. Sequence reads were processed using QIIME2 (v2022.2) (19) to construct a feature table of amplicon sequence variants (ASVs). Alpha diversity and beta diversity (Bray-Curtis dissimilarity) were assessed.

Statistical analysis. As an exploratory study, no prior sample size calculation was performed. Continuous variables are presented as mean±standard deviation (SD) or median (interquartile range, IQR). Categorical variables are presented as n (%). Changes from baseline were evaluated using paired t-tests or Wilcoxon signed-rank tests. Beta diversity differences were tested using PERMANOVA. Comparisons between weight gain and non-gain groups were performed using the Mann-Whitney U test or Fisher’s exact test. A two-sided p-value <0.05 was considered statistically significant. Analyses were performed using EZR (20).

Results

Patient flow and baseline characteristics. Of 18 participants, 16 were included in the final analysis (Figure 1). The median age was 74.5 years, and 9 (56.2%) were female. Pancreas was the most common primary site of cancer (10 patients, 62.5%). The median baseline body mass index (BMI) was 18.1 kg/m2. Eight patients (50.0%) had a baseline CONUT score ≥5 (Table I).

Figure 1.
Figure 1.

Patient flow diagram.

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Table I.

Baseline patient characteristics.

Body weight change. Mean body weight significantly increased from baseline at week 3 (by 1.74±0.48 kg, p=0.007), week 6 (by 2.26±0.82 kg, p=0.025), and week 12 (by 2.61±0.72 kg, p=0.008) (Figure 2).

Figure 2.
Figure 2.

Change in body weight.

Quality of life. One of the nine cases missed the QOL survey at 6 weeks. Change in QOL was assessed in eight patients at week 6 (Table II, Table III). While no significant changes were observed in the overall global health status or any of the functioning and symptom scales after adjusting for multiple comparisons (all p >0.05), an item-level analysis addressed appetite loss (Q8). The score for this item showed a numerical improvement from 2.13±0.84 at baseline to 1.38±0.74 at 6 weeks (uncorrected p=0.033). However, this finding did not remain statistically significant after applying a Bonferroni correction for multiple comparisons (adjusted significance level: p<0.0033).

View this table:
Table II.

Change in EORTC QLQ-C15-PAL scores from baseline to week 6.

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Table III.

Change in EORTC QLQ-C15-PAL scale from baseline to week 6.

Gut microbiota diversity. To assess the alpha diversity of the gut microbiota, we analyzed samples from baseline (week 0) and post-intervention (week 6). All evaluated alpha diversity indices–Pielou’s evenness, Faith’s Phylogenetic Diversity (PD), Observed features, Shannon entropy, and Chao1–were compared between the two time points using a paired t-test. No statistically significant differences were found in any of the metrics (Figure 3). Specifically, the Pielou’s evenness index, a measure of community evenness, remained unchanged between week 0 (mean±SD: 0.65±0.15) and week 6 (0.65±0.16; p=0.525). Similarly, Faith’s PD, which reflects phylogenetic diversity, showed no significant change from week 0 (12.55±4.66) to week 6 (12.09±3.62; p=0.870). Furthermore, measures of species richness, including Observed features (week 0: 140.50±74.68; week 6: 150.50±63.88; p=0.125) and the Chao1 index (week 0: 142.27±75.69; week 6: 152.56±62.77; p=0.127), did not differ significantly between the time points. The Shannon entropy index, which accounts for both richness and evenness, also remained stable from week 0 (4.58±1.41) to week 6 (4.69±1.49; p=0.724). Next, PERMANOVA was performed to evaluate differences in overall gut microbiota composition (β-diversity) between baseline and week 6. No statistically significant difference in β-diversity was observed between the two time points (pseudo-F=0.645, p=0.976).

Figure 3.
Figure 3.
Figure 3.

Gut microbiota alpha diversity.

Exploratory analysis of weight gain predictors. Patients were divided into a “gain group” (weight gain >0 kg at week 6, n=8) and a “non-gain group” (n=8). The proportion of patients with a baseline CONUT score ≥5 was higher in the non-gain group than in the gain group (87.5% vs. 12.5%, p=0.01). No other significant predictive factors were identified (Table IV).

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Table IV.

Comparison of baseline nutritional markers between gain and non-gain groups.

Discussion

Anamorelin is a key therapeutic option for cancer cachexia (21). In this prospective study, anamorelin administration in 16 patients cancer and cachexia resulted in a statistically significant increase in body weight at 12 weeks. This finding is consistent with previous Phase III trials (12, 13) and supports its effectiveness in a real-world clinical setting alongside nutritional guidance.

Regarding QOL, the lack of significant improvement in any of the formal EORTC QLQ-C15-PAL scales, including the appetite loss scale (p=0.12), should be noted. This may be attributable to the small sample size. However, it is intriguing that item-level analysis isolated a numerical improvement in the specific question for appetite loss (Q8, p=0.033). While this finding must be interpreted with caution due to the issue of multiple comparisons, it may suggest a specific, albeit modest, initial effect of anamorelin on patient-perceived appetite that was insufficient to alter the overall scale scores in this pilot study.

We did not detect significant changes in overall gut microbiota alpha or beta diversity. This suggests that anamorelin may not induce rapid, community-wide shifts in the gut microbiome. However, we observed considerable inter-individual variability in the trajectory of diversity metrics (Table V). Whether this variability is related to treatment response is an interesting question for future, larger studies, which should also incorporate functional analyses such as metabolomics to investigate changes beyond community structure.

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Table V.

Changes in the diversity of the gut microbiota in each case.

Interestingly, our exploratory analysis revealed a significant association between a high baseline CONUT score (≥5) and a failure to gain weight. This observation, while preliminary, aligns with the findings of Fujii et al. (22), who also identified the CONUT score as a predictor for anamorelin efficacy. This suggests the potential of the CONUT score, an easily accessible marker of immunonutritional status, to help stratify patients who are more likely to respond to anamorelin. While the need for early intervention in cachexia is emphasized, it should be noted that these results are derived from exploratory analyses of a small subgroup evaluated using multiple nutritional markers. Therefore, this result should be interpreted with caution until it is validated in larger studies designed to confirm this hypothesis.

Study limitations. First, it is a single-center, non-randomized observational study with a small sample size. Second, the absence of a control group makes it difficult to attribute eff\ects solely to anamorelin (23). Third, we acknowledge that the 6-week duration for microbiota analysis is a limitation. Nevertheless, gut microbiota is known to be highly dynamic and responsive to diet in the short term. Significant changes have been reported in as few as five days on an animal-based diet (24) and within two weeks on a high-fiber, low-fat diet (25). Given this evidence of rapid plasticity, the 6-week timeframe in our study is considered adequate to detect significant intervention-related shifts in the microbial community. However, future longitudinal studies are required to confirm the persistence of these effects and their impact over an extended period.

Despite these limitations, this study provides real-world data on anamorelin and is novel in its inclusion of gut microbiota analysis. The exploratory finding linking the CONUT score to weight gain response provides a valuable hypothesis for future personalized treatment strategies. Larger, multicenter, controlled trials incorporating LBM measurements and longer-term follow-up are needed (26).

Conclusion

In a real-world setting, anamorelin administration leads to significant weight gain, and improves appetite in patients with advanced cancer cachexia. While no significant short-term changes were observed in overall QOL or gut microbiota diversity, the exploratory finding that a high baseline CONUT score is associated with a lack of weight gain warrants validation. The CONUT score may be a useful, accessible marker for predicting anamorelin response.

Acknowledgements

The Authors would like to thank the staff of the Central Research Center at Kansai Medical University for their contributions to the work presented in this manuscript.

Footnotes

  • Authors’ Contributions

    All Authors contributed to the study conception and design. Material preparation, data collection, and patient recruitment were performed by S.B., T.Y., T.I., E.M., S.Y. Microbiome data analysis was performed by K.H. This project was supervised by S.B. and Y.M. The first draft of the manuscript was written by S.B. All Authors commented on previous versions of the manuscript and read and approved the final manuscript.

  • Conflicts of Interest

    Shogen Boku reports research funding from Amgen, Ono Pharmaceutical, Taiho Pharmaceutical Co., Ltd., and Kyo Diagnostics and honoraria from Chugai Pharmaceutical, Ono Pharmaceutical and MSD outside the submitted work. Takayasu Kurata reports research funding from AstraZeneca, MSD, Chugai Pharmaceutical, Bristol-Myers Squibb, Johnson & Johnson, Daiichi Sankyo and Amgen, and honoraria from AstraZeneca, Eli Lilly and Company, Ono Pharmaceutical, Bristol-Myers Squibb, Chugai Pharmaceutical, MSD and Takeda Pharmaceutical. All other Authors have no conflicts of interest to disclose in relation to this study.

  • Funding

    This research was supported by a JSPS KAKENHI grant (grant number 20K23179, to SB).

  • Artificial Intelligence (AI) Disclosure

    During the preparation of this manuscript, a large language model (Google’s Gemini) was used solely for language editing and stylistic improvements in select paragraphs. No sections involving the generation, analysis, or interpretation of research data were produced by generative AI. All scientific content was created and verified by the authors. Furthermore, no figures or visual data were generated or modified using generative AI or machine learning-based image enhancement tools.

  • Received July 29, 2025.
  • Revision received September 10, 2025.
  • Accepted September 15, 2025.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).

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Anamorelin in Cancer Cachexia: Gut Microbiota Effects and CONUT Score as a Predictor of Response
SHOGEN BOKU, TOMOYO YASUDA, TATSUKI IKOMA, ERI MATSUMORI, SAWAKO YOSHIUCHI, YOSHIYUKI MATSUO, KOICHIRO HIGASA, TAKAYASU KURATA
In Vivo Nov 2025, 39 (6) 3626-3635; DOI: 10.21873/invivo.14161
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