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

1. Li J, Xu J, Zheng Y, et al. Esophageal cancer: Epidemiology, risk factors and screening. Chin J Cancer Res. 2021; 33(5): 535-547.
2. van Hagen P, Hulshof MC, van Lanschot JJ, et al. Preoperative chemoradiotherapy for esophageal or junctional cancer. N Engl J Med. 2012; 366(22): 2074-2084.
3. Schroeder W, Ghadimi M, Schloesser H, et al. Long-Term Outcome After Histopathological Complete Response with and Without Nodal Metastases Following Multimodal Treatment of Esophageal Cancer. Ann Surg Oncol. 2022.
4. Rosner S, Liu C, Forde PM, Hu C. Association of Pathologic Complete Response and Long-Term Survival Outcomes Among Patients Treated With Neoadjuvant Chemotherapy or Chemoradiotherapy for NSCLC: A Meta-Analysis. JTO Clin Res Rep. 2022; 3(9): 100384.
5. Coker OO, Nakatsu G, Dai RZ, et al. Enteric fungal microbiota dysbiosis and ecological alterations in colorectal cancer. Gut. 2019; 68(4): 654-662.
6. Dohlman AB, Klug J, Mesko M, et al. A pan-cancer mycobiome analysis reveals fungal involvement in gastrointestinal and lung tumors. Cell. 2022; 185(20): 3807-3822.
7. Wurster S, Albert ND, Kontoyiannis DP. Candida auris Bloodstream Infection Induces Upregulation of the PD-1/PD-L1 Immune Checkpoint Pathway in an Immunocompetent Mouse Model. Msphere. 2022; 7(2): e81721.

Introduction

Crohn's disease (CD) is a disabling and destructive disease. Early intervention associated with tight monitoring appear to the best way to achieve deep remission and to prevent disease progression. Whether anti-TNF (tumor necrosis factor) therapy can be interrupted in patients with early CD who have undergone a period of prolonged deep remission is unknown.

Aims & Methods

The primary objective was to evaluate the sustained deep remission rate one year after discontinuation of a 12-month course of adalimumab in adult patients with early CD who achieved deep remission at 12 months after treatment induction and who were already in clinical remission and biomarker remission at 6 months.
We carried out a multicentre prospective GETAID cohort study. All patients had early luminal CD less than 24 months since diagnosis, and were naïve to biologics. The primary study endpoint was percentage of patients with sustained deep remission one year after stopping a 12-months course of adalimumab (+/- 3 months) in adult patients with early-stage CD who achieved deep remission without therapeutic intervention (i.e. no surgery, no clinical flare-up, no introduction of CD-related treatment, no need for adalimumab optimization) AND who were already in clinical remission (CDAI < 150) and biomarker remission (CRP < 5 mg/L and fecal calprotectin < 250) at 6 months. A clinical flare-up was defined as a CDAI > 220 or an increase in CDAI between two subsequent visits > 70.

Results

A total of 171 patients received treatment with adalimumab between March 2015 and March 2019.
In this cohort, 39.2% (67/171) were active smokers. The median disease duration was 4 [2-9] months. CD location was ileal (42.7%, 73/171), colonic (12.3%, 21/171), and ileo colonic (44.4%, 76/171). Twenty-one patients (12.3%) had perianal disease. The majority of patients had an inflammatory phenotype (71.3%, 122/171). At inclusion, median CRP level was 9.0 [3.0-24.0] mg/L, and median fecal calprotectin was 440.5 [159.0-838.0] µg/g.
Overall, 38/171 (22.2%) of patients achieved deep remission after a 12-month course of adalimumab. From those who achieved deep remission, 7 patients did not discontinue adalimumab. In this study, 7/31 (22.6%) patients maintained their deep remission for one year after their treatment discontinuation (24 months from initiation of adalimumab). Among the whole cohort, only 4% (7/171) of patients were in deep remission off adalimumab at 2 years. Median time between adalimumab discontinuation and the first clinical relapse was 14 months. No predictive factor associated with loss of deep remission in the year following treatment discontinuation was identified. No serious adverse event was reported.

Conclusion

In this first prospective trial exploring withdrawal of advanced therapy in early CD, 22.6% achieved deep remission at one year with adalimumab; among them, about a quarter maintained deep remission at two years. These results demonstrate that anti-TNF therapy should not be discontinued, even in patients with early CD.