Introduction

Therapeutic sequencing is a burning question in patients with ulcerative colitis (UC) requiring an advanced therapy. Whether starting with a less effective but safer and more convenient drug is a loss of chance for UC patients or can be rescued by later treatments is key point.

Aims & Methods

In the APPETISER study, we compared the effectiveness of two strategies based on the choice of the first biologic owing to either the drug efficacy in network meta-analyses and randomized controlled trials (vedolizumab or infliximab) or better acceptability (full subcutaneous therapy: adalimumab and golimumab) to induce and maintain steroid-free clinical remission during the first 24 months.
We collected real-world data from an IBD referral center including all consecutive UC patients ≥ 18 years-old who started a first line of biologic for active UC with follow-up > 6 months. Prior colectomy or severe acute colitis were excluded. Patients were included in either effectiveness-based sequencing (EBS) if they started with infliximab or vedolizumab, or in acceptability-based sequencing (ABS) if they received adalimumab or golimumab as first-line biologic.
The primary endpoint was remission defined according to PRO2 (PRO2-remission) as the absence of bleeding, normalization of transit (Mayo stool frequency subscore = 0) and no steroid. PRO2-remission was defined as a binary criterion each month (the statistical unit being the month and not the patient).
The secondary endpoints concerned the analysis by patient and were CFREM (partial Mayo score ≤ 2 without steroid) at week 12 and 52, endoscopic remission (CFREM + score Endoscopic Mayo ≤ 1) at week 12, time to drug discontinuation and time to colectomy.
All comparisons were adjusted using propensity scores on potential confounders. Analysis by month was performed using mixed models to account for repeated data.

Results

Overall, 130 patients were included including 60 patients in the EBS group (IFX= 50 and VDZ= 10) and 70 in the ABS group (ADA= 48 and GLM= 22).
The populations had similar characteristics at baseline apart from concomitant immunosuppressant more frequent in EBS group (55.9% vs 21.7%). 2^nd line treatment was started in 26.7% of patients in EBS group (ADA in 48.8%, VDZ 25.5% and ustekinumab 18.8%) and 87.1% of patients in ABS group (IFX in 54.1%, VDZ 31.1%).
After adjustment, the rate of CFREM was significantly higher in EBS arm than in ABS arm at week 12 (70.8% vs 33.0%, p < 0.001) and week 52 (72.8% vs 42.1%, p = 0.017). The rate of endoscopic remission at W12 was 22.1% and 10.0% in EBS and ABS arms, respectively (p =0.086).
For the primary endpoint, 3350 months were analyzed (1180 in EBS arm and 1175 in ABS arm). The percentage of months spent in PRO2-CFREM in the first 24 months (primary endpoint) was greater in EBS arm than in ABS arm (74.2% vs 46.6%; p<0.001). The percentage of months spent in CFREM was higher in the IV arm in the first 6 months (60.4% vs 18.9%), and was not rescued later: between M7 and M12 (73.1% vs 38.6%), M13 and M18 (79.9% vs 57.0%) or M19 and M24 (83.3% vs 64.6%) (p < 0.001 for all comparisons).
Regarding long-term data, EBS group had a lower risk to first-line biologic discontinuation (aHR=6.5 [2.8-15.3], p <0.001) and a clear trend for lower risk of colectomy (aHR=4.5 [0.9-22.3], p =0.068).

Conclusion

Our data highlight that the choice of first-line biological therapies is highly impacting the evolution of ulcerative colitis and cannot be rescued by later treatments. Thus, the results of the APPETISER study advocate for the use of the most effective therapeutic option as first line of biologic.

Disclosure

Anthony BUISSON: Consulting fees for Abbvie, Amgen, Arena, Biogen, Celltrion Healthcare, CTMA, Galapagos/Alfa Sigma, GutyCare/Resilience, Janssen, MSD, Nexbiome, Pfizer, Roche, Sandoz, Takeda, Tillotts. And Viatris. Lecture fees for Abbvie, Amgen, Biogen, Celltrion Healthcare, Galapagos/Alfa Sigma, Janssen, Mayoli-Spindler, MSD, Nordic Pharma, Norgine, Pfizer, Roche, Takeda, Tillotts and Vifor Pharma. Research grants from: Abbvie, Celltrion Healthcare, Galapagos/Alfa Sigma, Janssen, Lessaffre, Lilly, Pfizer, Takeda.

Introduction

Filgotinib (FIL) is an oral, JAK1 preferential inhibitor approved for the treatment of ulcerative colitis (UC). Although the clinical efficacy of FIL in UC has been demonstrated in the SELECTION trial,¹ real-world data are limited.

Aims & Methods

In total, 600 adult patients with moderately to severely active UC who initiate FIL treatment in routine clinical care will be enrolled in GALOCEAN (NCT05817942), an ongoing, European, multi-site, prospective, observational study. Here, we report baseline characteristics of the first 100 enrolled patients and effectiveness data from patients who reached week 10. Baseline demographics, disease characteristics, prior UC-related treatment and reasons for starting FIL were collected. At week 10, mean changes from baseline (CFBs) in the partial Mayo Clinic Score (pMCS) and the PRO-2 score, and the proportions of patients in pMCS remission (pMCS of ≤2) or PRO-2 remission (rectal bleeding subscore of 0 and stool frequency subscore of ≤1) were assessed. Mean CFBs at week 10 in patient-reported outcomes (Short Inflammatory Bowel Disease Questionnaire [SIBDQ], Urgency Numerical Rating Scale [NRS] and Functional Assessment of Chronic Illness Therapy-Fatigue [FACIT-Fatigue] scores) were also calculated. Safety was evaluated by documenting adverse events.

Results

As of January 2024, 100 patients (FIL 200 mg, 97% [97/100]; FIL 100 mg, 3% [3/100]) were enrolled, and had baseline data available; out of which 55 reached week 10. Baseline characteristics are shown in the Table. In total, 70% of patients (67/96) had up to moderate disease activity (pMCS of ≤6) and 30% (29/96) had severe disease activity (pMCS of ≥7) at baseline; 42% (42/100) were biologic-naive. The most common cardiovascular risk factor was active or prior smoking (37% [37/100]). FIL was used as monotherapy in 47% of patients (47/100). At week 10, the mean (standard deviation [SD]) CFB in the pMCS was –2.7 (2.5; n=43), and 58% of patients (25/43) achieved pMCS remission. The mean (SD) CFB in the PRO-2 score at week 10 was –1.8 (1.7; n=46), and 72% of patients (33/46) achieved PRO-2 remission. Mean (SD) CFBs in patient-reported outcomes at week 10 were 10.1 (12.4; n=42) for the SIBDQ score, –1.3 (2.8; n=38) for the Urgency NRS score and 4.0 (9.3; n=42) for the FACIT-Fatigue score. Overall, 10 patients discontinued FIL because of adverse events, lack of effectiveness or physician decision. No new safety signals were identified.

Conclusion

In this first interim report of GALOCEAN, week 10 data show that FIL improves symptoms in patients with UC in real-world clinical practice and has beneficial effects on health-related quality of life and fatigue. GALOCEAN is ongoing and long-term data with higher patient numbers will be evaluated to further characterize the real-world effectiveness of FIL in UC.

Table. Baseline characteristics.

Characteristic	Totala (N=100)
Age, years, median (min­–max)	37.0 (19–67)
Female, n (%)	52 (52)
UC duration, years, median (min­–max)	5.9 (0–26)
UC type, n (%) Proctitis Left-sided colitis Pancolitis Unknown	13 (13) 49 (49) 34 (34) 3 (3)
Disease activity and patient-reported outcomes, mean (SD) pMCS PRO-2 score SIBDQ score Urgency NRS score FACIT-Fatigue score	5.3 (2.0) 3.3 (1.6) 38.0 (11.5) 4.5 (2.6) 28.6 (11.7)
CRP, mg/L, median (min­–max)	3.3 (0–50)
Prior biologic therapy, n (%)	58 (58)
Number of prior biologic therapies, n (%)b 0 1 2 3 ≥4	42 (42) 23 (23) 23 (23) 7 (7) 5 (5)
aThe number of patients with missing data was n=1 for UC duration and UC type,n=4 forpMCS and PRO-2 score, n=11 for SIBDQ score, n=16 for urgency NRS score, n=11 for FACIT-Fatigue score and n=43 for CRP. bMultiple uses of the same therapy were counted once. CRP, C-reactive protein; FACIT-Fatigue, Functional Assessment of Chronic Illness Therapy-Fatigue; pMCS, partial Mayo Clinic Score; NRS, Numerical Rating Scale; PRO-2, patient-reported outcome-2; SIBDQ, Short Inflammatory Bowel Disease Questionnaire; UC, ulcerative colitis.

References

1. Feagan BG et al. Lancet 2021;397:2372–84.

Disclosure

The GALOCEAN study was sponsored by Galapagos NV (Mechelen, Belgium), who funded these analyses.
Medical writing support for the development of this abstract was provided by Risha Bulusu, MBiochem, of PharmaGenesis London, London, UK, and was funded by Alfasigma S.p.A.
WS, AM, MZ are employees of Alfasigma S.p.A at the time of abstract submission.
AA reports consulting and/or advisory board fees from AbbVie, Allergan, Amgen, Arena Pharmaceuticals, Biogen, Boehringer Ingelheim, Bristol Myers Squibb, Celltrion, Eli Lilly, Ferring Pharmaceuticals, Galapagos, Gilead Sciences, Janssen Pharmaceuticals, Lionhealth, MSD, Mylan, Nestlé, Pfizer, Roche, Samsung Bioepis, Sandoz and Takeda; lecture and/or speaker bureau fees from AbbVie, Amgen, Biogen, Bristol Myers Squibb, Celltrion, Eli Lilly, Ferring Pharmaceuticals, Galapagos, Gilead Sciences, Janssen Pharmaceuticals, Mitsubishi Tanabe Pharma Corporation, MSD, Novartis, Pfizer, Roche, Samsung Bioepis, Sandoz, Takeda and Teva Pharmaceuticals; and research grants from Biogen, MSD, Pfizer and Takeda.
CGdSJ reports speaker and/or consultancy fees from AbbVie, Alfasigma, Amgen, Celltrion, Janssen, Galapagos, MSD, Pfizer and Takeda.
ER reports speaker fees from AbbVie, Faes Farma, Ferring Pharmaceuticals, Galapagos, Janssen Pharmaceuticals, Kern Pharma, MSD, Pfizer and Takeda; and consulting fees from AbbVie, Eli Lilly, Fresenius Kabi, Galapagos, Janssen Pharmaceuticals, MSD and Pfizer.
GD reports research/educational grants from Abbott, AbbVie, Celltrion, Genuity, Janssen Pharmaceuticals, MSD, Pfizer, Takeda and Tillotts Pharma; and speaker/personal fees from AbbVie, Amgen, Bristol Myers Squibb, Celltrion, Dr Falk Pharma, Galapagos, Gilead Sciences, Janssen Pharmaceuticals, MSD, Pfizer, Takeda/Shire and Tillotts Pharma.
JPS reports speaker fees from AbbVie, Fresenius Kabi, Galapagos, Janssen-Cilag, Pharmacosmos, Takeda and Tillotts Pharma; and advisory board fees from AbbVie, Bristol Myers Squibb, Dr Falk Pharma and Galapagos.
ML reports consultancy/lecture fees from AbbVie, Bristol Myers Squibb, Eli Lilly, Galapagos, Janssen-Cilag, Johnson & Johnson, Medtronic, Pfizer, Takeda, and Tillotts, grants from
Galapagos and NFU and central reading services for Alimentiv.
MLH reports research grants from Ferring, Janssen, Pfizer, Tilllotts, and Takeda, speaker fees from AbbVie, Ferring, Galapagos, Meda, MSD, Tilllotts and Takeda; and advisory board fees from AbbVie, Eli Lilly, Galapagos, Janssen, MSD, Pfizer and Takeda.
RS reports no financial disclosures or conflicts of interest.
SV reports financial support for research from AbbVie, Galapagos, Johnson & Johnson, Pfizer and Takeda; speaker and/or consultancy fees from AbbVie, Abivax, AbolerIS Pharma, AgomAb Therapeutics, Alimentiv, Arena Pharmaceuticals, AstraZeneca, Bior Therapeutics (formerly Progenity), Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Cytoki Pharma, Dr Falk Pharma, Eli Lilly, Ferring Pharmaceuticals, Galapagos, Genentech-Roche, Gilead Sciences, GSK, Hospira, IMIDomics, Janssen Pharmaceuticals, Johnson & Johnson, Materia Prima, Mestag Therapeutics, MiroBio, Morphic Therapeutic, MRM Health, MSD, Mundipharma, Pfizer, ProDigest, Prometheus Biosciences, Robarts Clinical Trials, Surrozen, Takeda, Theravance Biopharma, Tillotts Pharma AG, VectivBio, Ventyx Biosciences and Zealand Pharma.
SS reports personal fees from AbbVie, Amgen, Arena Pharmaceuticals, Biogen, Bristol Myers Squibb, Celgene, Celltrion, Dr Falk Pharma, Eli Lilly, Ferring Pharmaceuticals, Fresenius Kabi, Galapagos/Gilead Sciences, Hikma Pharmaceuticals, I-Mab, Janssen Pharmaceuticals, Morphic Therapeutic, MSD, Mylan, Pfizer, Protagonist Therapeutics, Provention Bio, Sandoz/Hexal, Takeda, Theravance Biopharma and Ventyx Biosciences.
WR reports speaker fees from AbbVie, Celltrion, Ferring Pharmaceuticals, Galapagos, Janssen Pharmaceuticals, MEDICE, MSD, Pfizer, Roche, Sobi and Takeda; consulting fees from AbbVie, Amgen, AOP Health (formerly AOP Orphan), Boehringer Ingelheim, Bristol Myers Squibb, Calyx, Celltrion, Eli Lilly, Galapagos, Gilead Sciences, InDex Pharmaceuticals, Janssen Pharmaceuticals, MedAhead, Microbiotica, Pfizer and Takeda; advisory board fees from AbbVie, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Celltrion, Galapagos, Janssen Pharmaceuticals and Pfizer; and research funding from AbbVie, Janssen Pharmaceuticals, Sandoz, Sanofi and Takeda.
AJ and WS were employees of Galapagos NV (former study sponsor), and are now employees of Alfasigma S.p.A (current study sponsor).
MZ was an employee and shareholder of Galapagos NV (former study sponsor), and is now an employee of Alfasigma S.p.A (current study sponsor).

Introduction

Therapeutic drug monitoring (TDM) of intravenous (IV) infliximab is increasingly practiced to improve therapeutic outcomes of patients with inflammatory bowel diseases (IBD). Recently, a subcutaneous (SC) formulation of infliximab was approved for maintenance treatment of IBD [1].
In the present work, we introduce a software tool to guide infliximab dosing by predicting infliximab concentrations after switching to the SC formulation.

Aims & Methods

The infliximab population pharmacokinetics (popPK) model was previously developed using data from pivotal trials [2]. The popPK model code was reconstructed using R (v4.3.0). A software tool was developed using the Shiny package (v1.7.4). Bayesian forecasting was implemented using mapbayr (v0.10.0), which was used to estimate individual PK parameters through maximum a posteriori estimation.

External validation data were obtained from the prospective, multicenter REMSWITCH trial [3]. For each patient, a pre-switch infliximab trough concentration (TC) was used to predict a post-switch TC. Predicted and observed post-switch TCs were compared, and absolute and relative prediction errors (PE) were calculated. Prediction errors were compared between patients with and without relapse. Relapse was defined as an increase in fecal calprotectin ≥150 mg/g from baseline.

A simulation study was performed to demonstrate how the software tool can guide the IV-to-SC switch. Simulation conditions were:
- Dosing: 10 mg/kg IV every four weeks (q4w) to 240 mg SC every two weeks (q2w)
- Patient: 70 kg, no antibodies towards infliximab (ATI), no co-administration of methotrexate
- Pre-switch TC: 17.6 mg/L

Results

A total of 77 patients contributed one pre/post-switch TC pair each. Three patients had detectable ATI in the pre-switch sample. Three other patients were cotreated with methotrexate.
Predicted infliximab TCs were unbiased in the absence of relapse (Table 1). However, the model tended to overpredict infliximab TC in patients who experienced a relapse.

_{Table 1. Predictive performance of the model.}

	No relapse (N=60)		Relapse (N=17)
	Median	[IQR]	Median	[IQR]
aPE (mg/L)	-0.06	[-2.4–3.3]	+3.8	[-1.0–5.7]
rPE (%)	-0.6	[-20.1–30.2]	+34.3	[-10.0–67.1]

^{Abbreviations: aPE, absolute prediction error (calculated as; predicted - observed); IQR, interquartile range; N, number of patients; rPE, relative prediction error (calculated as; [predicted - observed] / observed * 100%).}

In the IV-to-SC simulation case, individual PK parameters (clearance 0.44 L/day, central volume of distribution 2.9 L, peripheral volume of distribution 27.0 L, and intercompartmental clearance 13.0 L/day) resulted in a post-switch TC of 18.6 mg/L right before the third SC injection. The simulation thus predicted no drop in TC after switching, thus presenting a likely safe switch strategy (considering the general belief that TCs drive efficacy).

Conclusion

The clinically validated, in-house developed software tool (https://lpmx.shinyapps.io/infliximab/) allows interactive simulations and personalized predictions to guide infliximab dosing while switching formulations. Predictions for patients without relapse were unbiased yet precision is likely compromised by variable SC bioavailability or possibly by time-varying PK. Overprediction of TC is likely driven by increased disease activity, characterized by an increased infliximab clearance and thus lower-than-expected infliximab observations, serving as a clinical alarm signal and warranting closer monitoring [4,5].

References

[1] S. Schreiber et al., “Randomized Controlled Trial: Subcutaneous vs Intravenous Infliximab CT-P13 Maintenance in Inflammatory Bowel Disease,” Gastroenterology, vol. 160, no. 7, pp. 2340–2353, Jun. 2021, doi: 10.1053/j.gastro.2021.02.068.
[2] “Remsima European Public Assessment Report.pdf.”
[3] A. Buisson et al., “Effectiveness of switching from intravenous to subcutaneous infliximab in patients with inflammatory bowel diseases: the REMSWITCH study,” Clin Gastroenterol Hepatol, vol. 21, no. 9, pp. 2338-2346.e3, 2023, doi: 10.1016/j.cgh.2022.08.011.
[4] W. Kantasiripitak, Z. Wang, I. Spriet, M. Ferrante, and E. Dreesen, “Recent advances in clearance monitoring of monoclonal antibodies in patients with inflammatory bowel diseases,” Expert Review of Clinical Pharmacology, vol. 14, no. 12, pp. 1455–1466, Dec. 2021, doi: 10.1080/17512433.2021.2028619.
[5] J. F. Brandse et al., “Loss of Infliximab Into Feces Is Associated With Lack of Response to Therapy in Patients With Severe Ulcerative Colitis,” Gastroenterology, vol. 149, no. 2, pp. 350-355.e2, Aug. 2015, doi: 10.1053/j.gastro.2015.04.016.

Disclosure

YH and ZW are supported by a research grant by Research Foundation Flanders–FWO (1SHAA24N, 1SF2922N). MF has received consulting/lecture fees from AbbVie, Amgen, Arena, Biogen, Celltrion Healthcare, CTMA, Galapagos, Janssen, MSD, Pfizer, Takeda, Tillotts. MSD, Gilead, Celgene, Sandoz, and Ferring. MN has received board membership, consultancy, or lecture fees from AbbVie, Adacyte, Amgen, Arena, Biogen, CTMA, Celltrion Healthcare, Ferring, Fresenius-Kabi, Janssen, Mayoli-Spindler, MSD, Pfizer, and Takeda. AB has received consulting fees from AbbVie, Amgen, Arena, Biogen, Celltrion Healthcare, CTMA, Galapagos, Janssen, MSD, Nexbiome, Pfizer, Roche, Takeda, and Tillotts; and lecture fees from AbbVie, Amgen, Biogen, Galapagos, Janssen, Mayoli-Spindler, MSD, Norgine, Pfizer, Roche, Takeda, Tillotts, and Vifor Pharma. ED has received consultancy fees from Alimentiv and argenx, lecture fees from Galapagos and Celltrion, and financial support from Janssen, Prometheus, and Sandoz. The remaining authors disclose no conflicts.

Introduction

Colorectal cancer (CRC) is the third-most common malignancy worldwide. Lysyl oxidase-like protein 2 (LOXL2), which promotes crosslinking of collagen and elastin, contributes to tumor progression in different tumour entities, but its role in CRC has not been evaluated. Here, we unraveled the role of LOXL2 in regulating tumour immune microenvironment of CRC and identified LOXL2 as a potential target for immunotherapy.

Aims & Methods

We analyzed the expression of LOXL2 in the Cancer Genome Atlas (TCGA) data. The effect of LOXL2 on CRC cell growth was determined by cell viability and colony formation assays. In vivo models were established by subcutaneous injection of colorectal cancer cell lines into immunodeficient NOD-SCID-γ (NSG) mice and immunocompetent wild-type BALB/c mice. Flow cytometry and immunohistochemistry were used to analyze immune cell composition. The collagen fibers in the extracellular matrix (ECM) were observed by masson staining, second harmonic generation imaging (SHG), and two-photon fluorescence imaging.

Results

Survival prognosis analysis revealed that high LOXL2 expression was correlated with poor survival of patients with CRC in TCGA cohort. However, we found that LOXL2 overexpression in human (HCT116 and DLD1) and mouse (CT26 and MC38) CRC cell lines had little effect on tumor growth in vitro and in immunodeficient mice. But its overexpression in mouse CRC cell lines could significantly promote tumor growth in immunocompetent mice (p<0.05). Overexpression of LOXL2 led to CXCL1 upregulation in the supernatant of CRC cells and CRC tumor tissues; subsequently, upregulation of CXCL1 induced more migration of myeloid-derived suppressor cells (MDSCs) in vitro and recruited more MDSCs in the tumor microenvironment. On the other hand, LOXL2 increased the crosslinking of collagen fibers in vitro and in the tumor microenvironment, which subsequently activated the function of MDSCs (up-expression of Arg1, IDO1, and INOS) and increased the oncostatin M (OSM) secreted by MDSCs. In turn, OSM secreted by MDSCs induced the expression of LOXL2 in CRC cells. The accumulation and activation of MDSCs in the tumor microenvironment inhibited the infiltration and function of CD8+ T cells, which suppressed the anti-tumour immunity of the host. Targeting of LOXL2 with a neutralizing antibody or inhibitor (PAT-1251) significantly impaired tumor growth (p<0.05) and MDSC infiltration and activation (p<0.05) in immunodeficient mice. Finally, PAT-1251 boosted anti-PD1 efficacy in colorectal cancer, suggesting that it could be repurposed to improve immunotherapy efficacy.

Conclusion

Our findings revealed that LOXL2 exerted a pro-tumorigenic role in CRC. LOXL2 recruited and activated MDSCs through CXCL1 and crosslinking of collagen fibers, respectively, subsequently reducing infiltration and activation of anti-tumor CD8⁺ T cells in the tumor microenvironment. Targeting this axis with PAT-1251 improved the efficacy of immunotherapy in colorectal cancer.

Introduction

In patients with colorectal cancer (CRC), intestinal dysbiosis has been observed, with abnormal colonization of the colonic mucosa by pathogenic Escherichia coli strains producing a cyclomodulin named cytotoxic necrotizing factor (CNF). Cyclomodulins are bacterial toxins capable of altering the cell cycle of the infected cell. One of the mechanisms involved in host defence against pathogens and in carcinogenesis is autophagy. However, the role of autophagy in the host response to the infection by CNF-producing E. coli, designated as CyPEC, has not yet been described.

Aims & Methods

Thus, the aim of this study was to investigate the role of autophagy in colorectal carcinogenesis in the context of CyPEC infection.
Mice predisposed to CRC development with autophagy deficiency specifically intestinal epithelial cells (Apc^Min/+/Atg16l1^ΔIEC mice) and their control littermates with functional autophagy (Apc^Min/+ mice) were infected with the clinical CyPEC strain 21F8. Tumor size and number were determined using a dissecting microscope. The mouse colons were collected and used for histological score assessment, and to analyse the levels of markers of autophagy, cell proliferation, apoptosis and inflammation by immunoblot, immunohistochemical staining and ELISA.

Results

We showed that in Apc^Min/+/Atg16l1^ΔIEC mice, infection with the CyPEC 21F8 strain led to increases in the number and the size of colonic tumours, compared with the uninfected condition. However, this was not observed in Apc^Min/+ mice. The increase in tumorigenesis in Apc^Min/+/Atg16l1^ΔIEC mice upon 21F8 infection versus uninfected condition was associated with increased pro-inflammatory cytokine production, enhanced cellular proliferation and decreased apoptosis in colonic epithelial cells.

Conclusion

Our results suggest that autophagy is necessary to limit the pro-carcinogenesis effects of the CyPEC 21F8 strain, thereby decreasing colorectal tumorigenesis. In another word, autophagy deficiency could be a susceptibility factor for the development of CRC in a host with colonization by CyPEC strains.

Introduction

Colonoscopic surveillance reduces colorectal cancer (CRC) incidence and mortality in Lynch syndrome (LS) carriers. Still, its invasiveness and high costs highlight the need for a non-invasive approach to predict the presence of neoplastic lesions.

Aims & Methods

This study aimed to identify faecal bacterial biomarkers to discern between carriers with colorectal lesions and those with normal colon.
Two independent Spanish cohorts (a training and a validation cohort) were recruited through two multicenter studies (Table 1). Participants provided a faecal sample before surveillance colonoscopy to quantify the abundance of F. prausnitzii (FPRA) and its phylogroups I and II (PHGI and PHGII), P. stomatis (PTST), B. fragilis (BCTF), B. thetaiotaomicron (BCTT), B46 (best BLAST match S. variabile), G. morbillorum (GMLL), B48 (best BLAST match R. faecis), and E. coli (ECO) through qPCR. Eubacteria (EUB) was quantified as the total bacterial load. Participants were classified based on colonoscopy findings as normal colonoscopy (NC), non-advanced adenoma (NAA), and advanced neoplasia (AN, including advanced adenoma and CRC). A bacterial signature for neoplasia prediction was defined and validated in the training and validation cohorts, respectively.

Table 1. Main characteristics of the study participants. NC, normal colonoscopy; NAA, non-advanced adenoma; AA, advanced adenoma; CRC, colorectal cancer.

			Training cohort	Validation cohort
Age	mean (range)		51 (25-83)	47 (20-75)
Sex (female)	n (%)		32 (64.0)	75 (65.8)
Diagnosis	NC (%)		40 (80.0)	71 (64.5)
	NAA (%)		6 (12.0)	35 (31.8)
	AA (%)		3 (6.0)	3 (2.8)
	CRC (%)		1 (2.0)	1 (0.9)
Mutated gene	High penetrance	MLH1 (%) - MSH2 (%) - EPCAM (%)	18 (36.0) - 9 (18.0) - 0 (0.0)	37 (33.6) - 25 (22.9) - 1 (0.9)
	Low penetrance	MSH6 (%) - PMS2 (%)	16 (32.0) - 7 (14.0)	37 (33.6) - 10 (9.0)
Total	n		50	110

Results

The bacterial abundances were analysed in the training cohort according to age, sex, body mass index (BMI), germline mutation, and colonoscopy findings. Significant moderate positive correlations were identified between the abundances of BCTF and age (r=0.325, p=0.040), and PHGII and BMI (r=0.399, p=0.010). A significant negative correlation was identified between GMLL abundance and BMI (r=-0.331, p=0.036). Patients harbouring MLH1 mutations exhibited a significantly higher abundance of FPRA compared to PMS2 carriers (p=0.048). Patients with neoplasia (NAA+AN) presented significantly lower abundances of BCTF (p=0.027) and B48 (p=0.038) than patients with NC. Patients with AN presented a significantly lower abundance of PTST compared to patients with NC or NAA (p=0.032).
Although all the bacterial markers achieved a sensitivity of 100% to predict the presence of neoplasia, none of them presented a specificity higher than 25% by itself. To maintain sensitivity and increase specificity a bacterial signature was defined including ECO, BCTF, GMLL, FPRA, PHGI, PHGII, and B46 combined with the inherited mutation. The signature showed 100% sensitivity (SS), 52.50% specificity (SP), 34.48% positive predictive value (PPV), and 100% negative predictive value (NPV). This signature was subsequently validated demonstrating 100% SS, 56.45% SP, 53.44% PPV, and 100% NPV.

Conclusion

A new faecal bacterial signature to predict the presence of colorectal neoplasia in LS carriers has been identified, showcasing its potential usefulness to improve and personalise LS surveillance, optimising endoscopic resources, and providing a less invasive and cost-effective approach.

Disclosure

S. Taboada-López, M. Malagón, S. Ramió-Pujol and M. Serra-Pagès are employees of GoodGut.