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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Introduction

Very early onset inflammatory bowel disease (VEO-IBD) is often associated with a severe disease course and unique characteristics including an underlying monogenic defect. In this study, we identified new pathogenic mutations in CGNL1 associated with VEO-IBD and other inflammatory GI disease. CGNL1 (Cingulin Like 1) encodes an epithelial junctional protein whose function was previously unknown in the gastrointestinal tract.

Aims & Methods

Whole exome sequencing (WES) was performed on the affected patient with VEO-IBD and all first-degree relatives with IBD and other inflammatory disease. Intestinal epithelial organoids (IEOs) were generated from the affected patient and were characterized by transepithelial electrical resistance (TEER), FITC-dextran permeability assay on epithelial cell monolayer, immunostaining, RNA sequencing, and transmission electron microscopy (TEM). In addition, we generated a new Cgnl1^-/- mouse model, which was characterized using FITC-dextran permeability assay, TEM, dextran-sodium sulfate (DSS)-induced colitis, and infections by Citrobacter rodentium and Clostridioides difficile. Single-cell datasets were analyzed to determine CGNL1 expression in IBD, primary sclerosing cholangitis (PSC), and autoimmune hepatitis (AIH).

Results

In the affected patient with VEO-IBD who required early total colectomy and pouch formation with coexistent PSC and celiac disease, WES identified two rare, new, pathogenic variants in the CGNL1 gene. Both pathogenic variants were also present in the patient’s younger sister, who has a similar history including early-onset, fulminant ulcerative colitis requiring total colectomy with ileostomy and PSC-AIH overlap syndrome. Furthermore, multiple relatives of the patient suffer from IBD and other inflammatory conditions including celiac disease, eosinophilic esophagitis, and type-1 diabetes. The RNA and protein levels of CGNL1 were significantly diminished in the patient’s intestinal epithelial cells compared to that of healthy individuals and other IBD patients by RNA-seq, immunoblotting, and immunostaining. The patient’s IEOs from pouch body and pre-pouch ileum formed smaller 3D spheroids with altered cell composition and significantly impaired barrier function compared to those from healthy controls and other IBD patients. Immunofluorescence and TEM demonstrated that CGNL1 is required for the assembly of junctional complexes in human IEOs and an epithelial cell line. Similarly to findings from the patient, impaired junctional complexes in intestinal epithelial cells and elevated intestinal permeability were present in Cgnl1^-/- mice at steady state. Cgnl1^-/- mice showed substantial vulnerability to DSS-induced colitis and bacterial infections that directly compromise the epithelial barrier. In addition, 6-month-old Cgnl1^-/- mice exhibited spontaneous inflammation in the colon and terminal ileum due to disrupted intestinal barrier, which was microbiome-dependent. Furthermore, single-cell analysis revealed diminished expression of CGNL1 in the intestinal and hepatic epithelial cells from patients with IBD or PSC/AIH, respectively.

Conclusion

The pathogenic CGNL1 variants contribute to VEO-IBD by disrupting gut barrier integrity, as demonstrated by patient’s cells and novel murine models. This study expands our understanding of epithelial barrier impairment in the pathogenesis of VEO-IBD, and highlights intestinal epithelium as a therapeutic target in some IBD patients.

Introduction

Acute pancreatitis (AP) is an acute inflammatory autodigestive disorder triggered by dysfunction of pancreatic exocrine activity and represents the most common gastrointestinal emergency in clinical practice. Global data indicate an annual incidence rate of 33.74 per 100,000 population and a mortality rate of 1.16 per 100,000. Despite ongoing optimization of therapeutic strategies, current clinical management primarily relies on supportive care and surgery. Hypertriglyceridemia (HTG) is the second leading etiological factor for AP, accounting for 10.36% of cases. Compared to other causes, HTG-associated acute pancreatitis (HTG-AP) exhibits higher recurrence rates and more severe complications (e.g., pancreatic necrosis and renal insufficiency). With the rising prevalence of HTG, the disease burden of HTG-AP is increasing, yet its specific pathogenic mechanisms remain unclear.

Aims & Methods

This study integrated whole-genome sequencing (WGS) and next-generation sequencing (NGS) to screen for shared mutations in the exonic regions of 5 HTG-AP family members. Candidate genes were identified based on MutationTaster classification and CADD scores. A mouse model carrying the PDLIM2 gene rs145349678 mutation was constructed using CRISPR/Cas9 technology, and an HTG-AP animal model was established. Pancreatic and hepatic histopathology (HE staining) and serological markers (TG, lipase, amylase, IL-6) were analyzed to evaluate the impact of the mutation on pancreatitis severity and hepatic lipid deposition.

Results

A clinical HTG-AP family was identified, with all 5 members exhibiting hypertriglyceridemia, including 2 cases of recurrent pancreatitis. WGS revealed 278 mutation sites across 10 chromosomes (involving 23 genes) in the family, and NGS validation narrowed these to 7 candidate loci. The PDLIM2 rs145349678 mutation (NM_001368120.1:exon9:c.C1055T:p.A352V), located within the LIM domain (which mediates protein localization and signaling transduction), was selected as the target due to cross-species conservation. Experimental results demonstrated that HTG-AP mice with the PDLIM2 mutation exhibited significantly aggravated pancreatic pathological damage (edema, hemorrhage, and inflammatory cell infiltration; *P* < 0.05), elevated serological markers (TG: 2.3 ± 0.4 vs. 1.5 ± 0.3 mmol/L; lipase: 520 ± 68 vs. 320 ± 45 U/L; IL-6: 48.2 ± 6.1 vs. 28.5 ± 4.3 pg/mL; *P* < 0.01 for all), and a 2.3-fold increase in hepatic lipid deposition (*P* < 0.001) compared to controls.

Conclusion

The PDLIM2 rs145349678 mutation exacerbates inflammatory responses and hepatic lipid accumulation in HTG-AP by modulating lipid metabolism. This finding provides new insights into the pathogenesis of HTG-AP and potential therapeutic targets.