Introduction

Guselkumab (GUS) is a dual-acting IL-23p19 subunit inhibitor that potently neutralizes IL-23 and binds to CD64, a receptor on cells that produce IL-23. In the QUASAR studies, GUS intravenous (IV) induction and subcutaneous (SC) maintenance demonstrated symptomatic, endoscopic, and histologic efficacy through 2 years.^1,2 Here, we describe maintenance of endoscopic and histologic efficacy in the long-term extension (LTE).

Aims & Methods

At maintenance week (W) 0, GUS IV induction responders were randomized 1:1:1 to GUS 100 mg SC every 8 weeks (q8w), GUS 200 mg SC q4w or placebo (GUS withdrawal). Participants (pts) completing the W44 visit could enter the LTE and continue the treatment regimen they were receiving at W44. Placebo pts discontinued after study unblinding. Efficacy data for randomized pts who continued to receive their GUS regimen assigned at W0 in the LTE were analyzed using 2 methods: 1) nonresponder imputation (NRI) accounting for pts with treatment failure or missing data, and 2) “as observed.”

Results

Overall, 303 randomized pts (155 for 100 mg q8w and 148 for 200 mg q4w) continued their GUS treatment assigned at W0 in the LTE. Of pts who achieved endoscopic improvement at W44, 87.2% of GUS 100 mg q8w pts and 80.2% GUS 200 mg q4w pts maintained endoscopic improvement through W92 (NRI analysis; Table). Of pts who achieved histologic improvement at W44, 77.9% and 75.2%, respectively, maintained histologic improvement at W92. Of pts who achieved histo-endoscopic mucosal improvement (HEMI) at W44, 73.5% and 75.5%, respectively, maintained HEMI through W92. Of pts who were in histologic remission at W44, 71.2% maintained histologic remission at W92 in both GUS groups. Results of the as-observed analysis were consistent with the NRI analysis; the dropout rate was low among GUS-treated pts in the LTE. Proportions of pts who maintained endoscopic and histologic outcomes from W0 to W92 are presented in the Table.

Conclusion

High rates of long-term sustained endoscopic and histologic endpoints were observed at W92 of the LTE with both GUS dose regimens.

References

1. Rubin DT, et al. Guselkumab in patients with moderately to severely active ulcerative colitis (QUASAR): phase 3 double-blind, randomised, placebo-controlled induction and maintenance studies. Lancet. 2025;405(10472):33-49.
2. Lichtenstein GR, et al. Efficacy and safety of guselkumab for ulcerative colitis through week 92 of the QUASAR long-term extension study. Presented at: Digestive Disease Week (DDW); May 4–6, 2025; San Diego, CA.

Disclosure

Study support: Johnson & Johnson.
TH: AbbVie, Bristol Myers Squibb, Daiichi-Sankyo, EA Pharma Co, Ltd., JIMRO, Eli Lilly, Gilead Sciences, Johnson & Johnson, Kissei Pharmaceutical Co, Ltd., Mitsubishi Tanabe Pharma Corporation, Mochida Pharmaceutical Co., Ltd., Nippon Kayaku Co., Ltd., Pfizer Inc, Takeda Pharmaceutical Co., Ltd.
JP: AbbVie, Alimentiv, Athos, Atomwise, Boehringer Ingelheim, Celsius, Ferring, Galapagos, Genentech/Roche, GlaxoSmithKline, Johnson & Johnson, Mirum, Nimbus, Pfizer, Progenity, Prometheus, Protagonist, Revolo, Sanofi, Sorriso, Surrozen, Takeda, Wasserman.
FM: AbbVie, Arena, Celltrion, Eli Lilly and Company, Ferring, Fresenius, Galapagos, GlaxoSmithKline, Johnson & Johnson, Merck, Pfizer, Prometheus Biosciences, Roche, Sandoz, Tillots, Takeda, Teva.
GRL: AbbVie, American College of Gastroenterology, CellCeutrix, Celgene, Clinical Advances in Gastroenterology, Ferring, Gastroenterology and Hepatology [Gastro-Hep Communications], Gilead, Johnson & Johnson, Orthobiotech, Eli Lilly, Luitpold / American Regent, Merck, McMahon Publishing, Pfizer, Prometheus, Romark, Salix/ Valeant, Shire, SLACK, Springer, Takeda, UCB, Up-To-Date, Vindico, Virgo.
JRA: Abbvie, Bristol Myer Squibb, Ferring, Finch, Iterative Scopes, Johnson & Johnson, Merck, Pfizer, Roivant, Seres Therapeutics, Roivant Adiso.
BB: AbbVie, Alimentiv, Allergan, Amgen, AMT, Bausch Health, Bristol Myers Squibb, Business Intelligence, Celgene, Celltrion, Eupraxia Fresenius Kabi, Ferring, Genentech/Roche, Gilead, Iterative Scopes, GlaxoSmithKline, Jamp, Johnson & Johnson, Merck, Microbiome Insights, Mylan, Novartis, Organon, Pendopharm, Pfizer, Protagonist, Qu Biologic, Sandoz, Takeda, Viatris.
WA: AbbVie, Amgen, BMS, Dynacare, Eli-Lilly, Johnson & Johnson, Merck, Novartis, Pfizer, Prometheus, Sandoz, Sanofi, Takeda, Theradiag.
MAS: AbbVie, Bristol-Myers Squibb, Falk, Galapagos, Janssen, Lilly, MSD, Pfizer, Samsung Bioepis, Sandoz, Sanofi, STADA, Takeda, Tillotts.
BDY: AbbVie Korea, BMS Pharmaceutical Korea Ltd., Celltrion, Chong Kun Dang Pharm, CJ Red BIO, Cornerstones Health, Curacle, Daewoong Pharm, Dong-A ST, Eisai Korea, Eli Lilly and Company Korea, Ferring Korea, Imscout, IQVIA, Johnson & Johnson, Johnson & Johnson Korea, JEIL PHARMACEUTICAL CO., Kangstem Biotech, Korea Otsuka Pharm, Korea United Pharm, Medtronic Korea, NanoEntek, ORGANOIDSCIENCES LTD, Pfizer Korea, Samsung Bioepis, Takeda, Takeda Korea, Yuhan.
SY, MG, NS, DP, YM, HZ: Johnson & Johnson.
AD: Abivax, AbbVie, Amgen, Arena Pharmaceuticals, Biogen, Boehringer Ingelheim, Bristol Myers Squibb, CED Service GmbH, Celltrion, Dr Falk Foundation, Ferring Pharmaceuticals, Fresenius Kabi, Galapagos, Gilead, High5MD, Johnson & Johnson, Lilly, Materia Prima, MedToday, MSD, Pfizer, Pharmacosmos, Roche, Sandoz, Stada, Takeda, Thieme, Tillotts, UniMed Verlag, Vifor Pharma.
DTR: Abbvie, Altrubio, Apex, Avalo Therapeutics, Bristol-Myers Squibb, Buhlmann Diagnostics Corp, Celgene, Connect BioPharma, Intouch Group, Iterative Health, Johnson & Johnson, Lilly, Pfizer, Samsung Neurologica, Takeda.
BES: AbbVie, Abivax, Adiso Therapeutics, Agomab, Alimentiv, Amgen, AnaptysBio, Arena Pharmaceuticals, AstraZeneca, Biolojic Design, Biora Therapeutics, Boehringer Ingelheim, Boston Pharmaceuticals, Bristol Myers Squibb, Celltrion, Equillium, Enthera, Enveda Biosciences, Evommune, Ferring, Galapagos, Genentech (Roche), Gilead Sciences, GlaxoSmithKline, Gossamer Bio, Imhotex, Index Pharmaceuticals, Innovation Pharmaceuticals, Inotrem, Johnson & Johnson, Kaleido, Kallyope, Lilly, Merck, Microba, Mirador Therapeutics, Mobius Care, Morphic Therapeutics, MRM Health, Nexus Therapeutics, Nimbus Discovery, Odyssey Therapeutics, Pfizer, Progenity, Prometheus Biosciences, Prometheus Laboratories, Protagonist Therapeutics, Q32 Bio, Rasayana Therapeutics, Recludix Therapeutics, Reistone Biopharma, Sanofi, Sorriso Pharmaceuticals, Spyre Therapeutics, Sun Pharma, Surrozen, Takeda, Target RWE, Teva, TLL Pharmaceutical, Tr1X, Union Therapeutics, Ventyx Biosciences, and Vividion Therapeutics.

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

As a small but important component of the intestinal microbiota, the fungal community (mycobiota) has received increasing attention for its involvement in the pathogenesis of Crohn's disease (CD)¹. In our previous study, we identified a significantly increased relative abundance of Exophiala dermatitidis (E. dermatitidis) in the gut of patients with CD, particularly those with active disease². Caspase recruitment domain family member 9 (CARD9), a key adaptor molecule in antifungal immune responses³, has also been strongly associated with CD susceptibility⁴. In this study, we aimed to explore the potential role and underlying mechanisms of E. dermatitidis in intestinal inflammation.

Aims & Methods

To evaluate the impact of E. dermatitidis on intestinal inflammation, we generated Card9-knockout (KO) (Card9^-/-) mice and constructed a dextran sulfate sodium (DSS)-induced colitis model colonized by E. dermatitidis. The underlying molecular mechanisms were investigated by a range of biochemical approaches. Flow cytometry was performed to analyze the proportions of myeloid cells, including CX3CR1⁺ macrophages, in the colonic lamina propria (LP).

Results

Compared to mice with DSS-induced colitis alone (WT-DSS group), the DSS-treated mice colonized by E. dermatitidis (WT-DSS + Ed group) showed a significant weight loss, a worsening of disease activity, a shorter length of the large intestine, and more severe intestinal inflammation characterized by increased inflammatory cell infiltration and crypt destruction in the histological examination of colon hematoxylin and eosin (H&E) staining. Card9^-/- mice were used to further investigate whether E. dermatitis-mediated inflammation was dependent on the CARD9 signaling pathway. We observed that CARD9 deficiency protected against E. dermatitidis-exacerbated colitis, as measured by a higher trend of body weight, longer colon lengths, and amelioration of disease activity in the KO-DSS + Ed group. In addition, flow cytometric analysis of the colonic lamina propria revealed a higher percentage proportion of CX3CR1+ macrophages in the WT-DSS + Ed group and a markedly reduced proportion in the KO-DSS + Ed group. Furthermore, we identified the Mincle-Syk-CARD9-nuclear factor kappa-B (NF-κB) signaling pathway as playing an important role in mediating the inflammatory immune responses to E. dermatitidis.

Conclusion

E. dermatitidis exacerbates the DSS-induced colitis in mice through the Mincle-Syk-CARD9-NF-κB pathway with the participation of CX3CR1+ macrophages, providing a novel therapeutic strategy for CD targeting specific intestinal fungi.

References

1. Sokol H, Leducq V, Aschard H, et al. Fungal microbiota dysbiosis in IBD. Gut 2017;66:1039-1048.
2. Zeng L, Feng Z, Zhuo M, et al. Fecal fungal microbiota alterations associated with clinical phenotypes in Crohn's disease in southwest China. PeerJ 2022;10:e14260.
3. Hu A, Hu Z, Zou H, et al. CARD9 in host immunity to fungal, bacterial, viral, and parasitic infections: An update. Frontiers In Microbiology 2022;13:1021837.
4. Franke A, McGovern DPB, Barrett JC, et al. Genome-wide meta-analysis increases to 71 the number of confirmed Crohn's disease susceptibility loci. Nature Genetics 2010;42:1118-1125.