# IMMUNOREACT 4: Peritumoral Microenvironment Associated with Anastomotic Leaks After Surgery for Rectal Cancer

**Authors:** Ottavia De Simoni, Melania Scarpa, Francesco Cavallin, Andromachi Kotsafti, Francesco Marchegiani, Astghik Stepanyan, Gaia Tussardi, Antonio Rosato, Gaya Spolverato, Imerio Angriman, Emanuele Damiano Luca Urso, Cesare Ruffolo, Luca Maria Saadeh, Isacco Maretto, Quoc Riccardo Bao, Silvia Negro, Chiara Vignotto, Luca Facci, Giorgio Rivella, Antonella D’Angelo, Anna Matteazzi, Francesca Galuppini, Vincenza Guzzardo, Roberta Salmaso, Valerio Pellegrini, Stefano Brignola, Carlotta Ceccon, Tommaso Stecca, Anna Pozza, Marco Massani, Pierluigi Pilati, Mario Gruppo, Boris Franzato, Ivana Cataldo, Giuseppe Portale, Chiara Cipollari, Matteo Zuin, Licia Laurino, Luca Dal Santo, Giovanni Pirozzolo, Alfonso Recordare, Lavinia Ceccarini, Michele Antoniutti, Laura Marinelli, Alberto Brolese, Mattia Barbareschi, Giovanni Bertalot, Monica Ortenzi, Mario Guerrieri, Maurizio Zizzo, Lorenzo Dell’Atti, Silvio Guerriero, Alessandra Piccioli, Giulia Pozza, Mario Godina, Isabella Mondi, Daunia Verdi, Corrado Da Lio, Giulia Noaro, Roberto Cola, Giovanni Bordignon, Roberto Merenda, Giulia Becherucci, Laura Gavagna, Salvatore Candioli, Giovanni Tagliente, Umberto Tedeschi, Dario Parini, Beatrice Salmaso, Gianluca Businello, Loretta Di Cristoforo, Francesca Bergamo, Andrea Porzionato, Federico Scognamiglio, Romeo Bardini, Salvatore Pucciarelli, Marco Agostini, Valentina Chiminazzo, Dario Gregori, Barbara Di Camillo, Ignazio Castagliuolo, Angelo Paolo Dei Tos, Matteo Fassan, Marco Scarpa

PMC · DOI: 10.3390/cancers18040571 · Cancers · 2026-02-09

## TL;DR

This study shows that immune markers in normal-looking tissue near rectal tumors can predict the risk of anastomotic leaks after surgery.

## Contribution

The first evidence that immune profiling of tumor-adjacent mucosa can predict anastomotic leaks.

## Key findings

- CD3+, CD8+, CD8β+, and Tbet+ immune markers in tumor-adjacent mucosa are predictive of anastomotic leaks.
- Combining immune markers with clinical variables like BMI and tumor location achieved ~70% accuracy in predicting leaks.
- Immune activation in normal-appearing mucosa is linked to impaired anastomotic healing.

## Abstract

In this multicenter study of 363 patients, we provide the first evidence that immune profiling of histologically normal, tumor-adjacent mucosa may identify patients at risk for anastomotic leaks (ALs) after rectal surgery. Among the markers assessed, only CD3+, CD8+, CD8β+ and Tbet+ showed predictive value, suggesting that the mucosa intended for anatomosis may already be compromised by hypoxia, extensive cell death, autoimmune inflammation or infection. We then explored combinations of clinical and immunological markers to obtain predictive models of ALs. Models including CD8+ (or CD8β+), BMI, neutrophil-to-lymphocyte ratio and tumor location achieved ~70% accuracy. Although the predictive accuracy of our models remains relatively limited, combining immune microenvironmental data from the healthy mucosa with clinical variables may represent a promising approach to identifying patients at risk of ALs and deserves further testing in clinical practice.

Background: Anastomotic leaks (ALs) remain a critical complication after rectal cancer surgery. Emerging evidence suggests that local immune dysregulation may play a key role in anastomotic healing. We investigated the immune microenvironment of histologically normal, tumor-adjacent rectal mucosa—a tumor-conditioned field—as a potential substrate for AL predisposition. Methods: IMMUNOREACT 4 is a sub-analysis of the IMMUNOREACT project (clinicaltrials.gov NCT04915326 and NCT04915326), a multicenter translational study evaluating immune features of histologically normal, tumor-adjacent rectal mucosa of patients undergoing colorectal anastomosis. A prospective cohort (n = 121) was analyzed using flow cytometry, in addition to a retrospective cohort (n = 262) using immunohistochemistry. Immune markers of epithelial activation and lymphocyte subsets were compared between patients with and without postoperative ALs. Exploratory predictive models combining immune and clinical variables were developed and evaluated using discrimination, calibration and decision curve analyses. Results: At flow cytometry, the CK+HLAabc+ MFI (AUC 0.66, 95% CI 0.52–0.80), CD8+CD38+ cell rate (AUC 0.65, 95% CI 0.52–0.78) and CD3+CTLA4+ cell rate (AUC 0.65, 95% CI 0.51–0.80) showed moderate predictive potential for ALs. In immunohistochemistry, CD3+ (AUC 0.57, 95% CI 0.54–0.60), CD8+ (AUC 0.57, 95% CI 0.52–0.62), CD8β+ (AUC 0.59, 95% CI 0.53–0.65) and Tbet+ (AUC 0.60, 95% CI 0.56–0.64) showed some predictive ability for ALs. The model including CD8β+, the BMI, neutrophile/lymphocyte ratio and tumor location had an AUC of 0.67 (95% CI 0.62–0.72). Conclusions: Immune activation within histologically normal, tumor-adjacent rectal mucosa—characterized by epithelial HLA upregulation and cytotoxic or Th1 T cell infiltration—is associated with postoperative ALs. Although predictive accuracy is limited, these findings support the concept that a tumor-conditioned immune microenvironment may predispose patients to impaired anastomotic healing. Integration of mucosal immune profiling with clinical variables represents a promising exploratory approach that warrants further prospective validation.

## Linked entities

- **Proteins:** cd.3 (Cd.3 conserved hypothetical protein), CD8A (CD8 subunit alpha), CD8B (CD8 subunit beta), TBX21 (T-box transcription factor 21), CTLA4 (cytotoxic T-lymphocyte associated protein 4)
- **Diseases:** rectal cancer (MONDO:0006519)

## Full-text entities

- **Genes:** GZMB (granzyme B) [NCBI Gene 3002] {aka C11, CCPI, CGL-1, CGL1, CSP-B, CSPB}, HLA-A (major histocompatibility complex, class I, A) [NCBI Gene 3105] {aka HLAA}, CD4 (CD4 molecule) [NCBI Gene 920] {aka CD4mut, IMD79, Leu-3, OKT4D, T4}, CMPK1 (cytidine/uridine monophosphate kinase 1) [NCBI Gene 51727] {aka CK, CMK, CMPK, UMK, UMP-CMPK, UMPK}, CD274 (CD274 molecule) [NCBI Gene 29126] {aka ADMIO5, B7-H, B7H1, PD-L1, PDCD1L1, PDCD1LG1}, HMGB1 (high mobility group box 1) [NCBI Gene 3146] {aka HMG-1, HMG1, HMG3, SBP-1}, FGF2 (fibroblast growth factor 2) [NCBI Gene 2247] {aka BFGF, FGF-2, FGFB, HBGF-2}, CD8A (CD8 subunit alpha) [NCBI Gene 925] {aka CD8, CD8alpha, IMD116, Leu2, p32}, CD28 (CD28 molecule) [NCBI Gene 940] {aka IMD123, Tp44}, TBX21 (T-box transcription factor 21) [NCBI Gene 30009] {aka IMD88, T-PET, T-bet, TBET, TBLYM}, CD86 (CD86 molecule) [NCBI Gene 942] {aka B7-2, B7.2, B70, BU63, CD28LG2, CD86 v6}, IL6 (interleukin 6) [NCBI Gene 3569] {aka BSF-2, BSF2, CDF, HGF, HSF, IFN-beta-2}, FN1 (fibronectin 1) [NCBI Gene 2335] {aka CIG, ED-B, FINC, FN, FNZ, GFND}, NLRP3 (NLR family pyrin domain containing 3) [NCBI Gene 114548] {aka AGTAVPRL, AII, AVP, C1orf7, CIAS1, CLR1.1}, CTLA4 (cytotoxic T-lymphocyte associated protein 4) [NCBI Gene 1493] {aka ALPS5, CD, CD152, CELIAC3, CTLA-4, GRD4}, CCL3 (C-C motif chemokine ligand 3) [NCBI Gene 6348] {aka G0S19-1, LD78, LD78ALPHA, MIP-1-alpha, MIP1A, SCI}, IL2RA (interleukin 2 receptor subunit alpha) [NCBI Gene 3559] {aka CD25, IDDM10, IL2R, IMD41, TCGFR, p55}, IL12B (interleukin 12B) [NCBI Gene 3593] {aka CLMF, CLMF2, IL-12B, IMD28, IMD29, NKSF}, FOXP3 (forkhead box P3) [NCBI Gene 50943] {aka AIID, DIETER, IPEX, JM2, PIDX, XPID}, NFKB1 (nuclear factor kappa B subunit 1) [NCBI Gene 4790] {aka CVID12, EBP-1, KBF1, NF-kB, NF-kB1, NF-kappa-B1}, CXCL8 (C-X-C motif chemokine ligand 8) [NCBI Gene 3576] {aka GCP-1, GCP1, IL8, LECT, LUCT, LYNAP}, CD80 (CD80 molecule) [NCBI Gene 941] {aka B7, B7-1, B7.1, BB1, CD28LG, CD28LG1}, CD8B (CD8 subunit beta) [NCBI Gene 926] {aka CD8B1, CD8beta, LEU2, LY3, LYT3, Ly-3}, CD38 (CD38 molecule) [NCBI Gene 952] {aka ADPRC 1, ADPRC1, cADPR1}, CCL2 (C-C motif chemokine ligand 2) [NCBI Gene 6347] {aka GDCF-2, HC11, HSMCR30, MCAF, MCP-1, MCP1}, TLR4 (toll like receptor 4) [NCBI Gene 7099] {aka ARMD10, CD284, TLR-4, TOLL}, IL1A (interleukin 1 alpha) [NCBI Gene 3552] {aka IL-1 alpha, IL-1A, IL1, IL1-ALPHA, IL1F1}, TNF (tumor necrosis factor) [NCBI Gene 7124] {aka DIF, IMD127, TNF-alpha, TNFA, TNFSF2, TNLG1F}, CSF3 (colony stimulating factor 3) [NCBI Gene 1440] {aka C17orf33, CSF3OS, GCSF}, HSPA4 (heat shock protein family A (Hsp70) member 4) [NCBI Gene 3308] {aka APG-2, HEL-S-5a, HS24/P52, HSPH2, RY, hsp70}
- **Diseases:** immune dysregulation (OMIM:614878), infection (MESH:D007239), Anastomotic Leaks (MESH:D057868), blood (MESH:D006402), hypoxia (MESH:D000860), hypoxic (MESH:D002534), obesity (MESH:D009765), rectal adenocarcinoma (MESH:D000230), Tumor (MESH:D009369), diabetes (MESH:D003920), ischemic (MESH:D002545), AL (MESH:D009101), blood loss (MESH:D016063), Rectal Cancer (MESH:D012004), autoimmune inflammation (MESH:D007249), injury to (MESH:D014947), dysplasia (MESH:D015792)
- **Chemicals:** formalin (MESH:D005557), steroid (MESH:D013256), ATP (MESH:D000255), ICG (MESH:D007208), H&amp;E (MESH:D006371)
- **Species:** Homo sapiens (human, species) [taxon 9606], Mus musculus (house mouse, species) [taxon 10090]

## Full text

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## Figures

6 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12938832/full.md

## References

38 references — full list in the complete paper: https://tomesphere.com/paper/PMC12938832/full.md

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Source: https://tomesphere.com/paper/PMC12938832