Introduction

A dysfunctional intestinal mucosal barrier is a key pathophysiological hallmark and driver of a broad range of gastrointestinal diseases including celiac disease and inflammatory bowel disease. To date, there are no adequate treatment strategies to ameliorate impaired barrier function.
IMU-856 is an orally available and systemically acting small molecule modulator of sirtuin 6 (SIRT6), a histone/non-histone protein deacetylase which serves as a transcriptional regulator of intestinal barrier function and regeneration of bowel epithelium. IMU-856 may represent a new approach to treat gastrointestinal diseases with compromised barrier function.

Aims & Methods

This was a first-in-human, double-blind, randomized, placebo-controlled clinical trial of IMU-856 in healthy volunteers and patients with celiac disease. In the multiple ascending dose part, healthy human subjects were dosed once-daily for 14 consecutive days with IMU-856 at three different dose levels or placebo. Additionally, the Phase 1/1b study was designed to assess safety and tolerability of IMU-856 at two different dose levels in patients with celiac disease during periods of gluten-free diet and a 15-day gluten challenge. Further objectives included pharmacokinetics and the assessment of histological changes. Biomarkers reflecting intestinal enterocyte mass and function, nutrient absorption, and enteroendocrine hormones like GLP-1 were analyzed to assess potential effects on gut health.

Results

IMU-856 was safe and well-tolerated with a benign adverse event profile and pharmacokinetics that allow once-daily dosing. Treatment with IMU-856 protected against gluten-induced histologic deterioration, improved the health and metabolic function of intestinal enterocytes as measured by nutrient uptake and citrulline [1], and had positive effects on enteroendocrine cells increasing endogenous GLP-1 levels in a dose-dependent manner.

Conclusion

IMU-856 is a safe, highly selective and potent epigenetic modulator, improving the intestinal barrier function in patients with celiac disease undergoing a gluten challenge.
Positive effects of IMU-856 on gut hormones and various biomarkers for overall gut health including intestinal function and integrity were observed. Therefore, IMU-856 may offer extensive potential for treatment of gastrointestinal diseases with compromised intestinal barrier function and metabolic diseases.

References

1. Daveson AJM, Stubbs R, Polasek TM, Isola J, Anderson R, Tye-Din JA, et al. Safety, clinical activity, pharmacodynamics, and pharmacokinetics of IMU-856, a SIRT6 modulator, in coeliac disease: a first-in-human, randomised, double-blind, placebo-controlled, phase 1 trial.

Disclosure

AS, MW, EP: employees of Immunic AG, option and shareholders of Immunic, Inc.
IPO, JF, IK, SE: employees of Immunic AG, option and/or shareholders of Immunic, Inc.
HK: employee of Immunic AG, shareholder of Immunic, Inc., co-inventor of patents for the drug in investigation
DP: option holder of Immunic, Inc.
DV, AM: employees of Immunic AG and Immunic, Inc., shareholders of Immunic, Inc., co-inventors of patents for the drug in investigation

Introduction

Esophageal squamous cell carcinoma (ESCC) is associated with poor prognosis despite advances in neoadjuvant immunochemotherapy (NICT). With highly variable treatment responses, identifying reliable predictive biomarkers remains crucial. While gut microbiome influences on immunotherapy efficacy are increasingly recognized, the specific role of the fungal microbiome (mycobiome) in NICT outcomes for ESCC remains unexplored, representing a significant gap in developing personalized treatment strategies.

Aims & Methods

This study aimed to characterize gut mycobiome signatures in ESCC patients and develop fungal biomarker-based predictive models for NICT response. We conducted ITS2 sequencing on 136 fecal samples collected from 68 ESCC patients (pre- and post-NICT) and 19 healthy controls (HC). Patients were stratified as responders (R, n=26) or non-responders (NR, n=42) based on tumor regression grade (TRG) scores. We performed comprehensive analyses of mycobiome diversity, composition, co-occurrence networks, and functional pathways across groups. The Boruta algorithm was employed for feature selection to identify fungal biomarkers, followed by multilayer perceptron (MLP) machine learning with five-fold cross-validation to develop predictive models. Additionally, ESCC xenograft models were established to investigate gut mycobiome-immune interactions through fecal microbiota transplantation (FMT) and targeted fungal manipulation experiments.

Results

ESCC patients demonstrated significant mycobiome dysbiosis compared to healthy controls, characterized by reduced fungal alpha diversity and distinct beta diversity patterns. At baseline, ESCC patients showed enrichment of Rhodotorula minuta, Actinomucor elegans, and several Candida species. Responders exhibited significantly higher baseline fungal diversity than non-responders, with enrichment of Meyerozyma, Candida boidinii, Trichosporon dermatis, and Cryptococcus species, whereas non-responders showed predominance of Saccharomyces, Nakaseomyces, and pathogenic Candida species (C. glabrata, C. parapsilosis, C. albicans). Responders also displayed more complex, stable fungal co-occurrence networks with higher density and clustering coefficients. Post-NICT, both groups showed partial recovery of mycobiome diversity, with significant increases in beneficial fungal taxa. Functional pathway analysis revealed distinct metabolic profiles between responders and non-responders. Using the Boruta algorithm, we identified 23 genus-level and 22 species-level fungal biomarkers that demonstrated high predictive value. The MLP model based on genus-level markers achieved AUCs of 90.2% (training) and 91.9% (test), while the species-level model showed comparable performance. In animal experiments, mice receiving R-FMT exhibited reduced tumor growth and enhanced CD8+ T cell infiltration compared to NR-FMT recipients. Notably, Candida boidinii supplementation synergized with anti-PD-1 therapy, while Saccharomyces depletion enhanced treatment sensitivity.

Conclusion

Our findings establish the gut mycobiome as a powerful predictor of NICT response in ESCC, with machine learning models achieving >90% accuracy using fungal biomarkers. Experimental validation not only confirms mechanistic links between specific fungi and antitumor immunity but also demonstrates that targeted mycobiome modulation can enhance immunotherapy efficacy. This dual approach of prediction and intervention offers a novel framework for precision oncology in ESCC, potentially transforming clinical decision-making and treatment outcomes in this challenging malignancy.

References

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