Early prediction of pathological complete response in rectal cancer: a dynamic immune remodeling hypothesis during neoadjuvant treatment
Frontiers in Oncology, cilt.16, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 16
- Basım Tarihi: 2026
- Doi Numarası: 10.3389/fonc.2026.1910961
- Dergi Adı: Frontiers in Oncology
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, EMBASE, Directory of Open Access Journals
- Anahtar Kelimeler: immune monitoring, neoadjuvant therapy, pathological complete response, rectal cancer, tumor immune microenvironment, tumor regression, watch-and-wait
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- Çukurova Üniversitesi Adresli: Evet
Özet
Achieving pathological complete response (pCR) after neoadjuvant treatment has become one of the most influential outcomes shaping organ preservation strategies, treatment intensification protocols, and long-term oncological decision-making in locally advanced rectal cancer (LARC). Current response assessment, however, remains dependent on delayed structural evaluations — magnetic resonance imaging (MRI), endoscopy, and postoperative pathology — that measure the consequences of tumor regression rather than the biological process generating it. We hypothesize that response to neoadjuvant treatment reflects the temporal dynamics of tumor immune microenvironment (TIME) remodeling: treatment-induced immune activation may precede measurable morphological change, generating immune trajectories that diverge toward complete elimination or toward resistance. We propose that serial, biology-anchored tumor sampling — rather than a single baseline biopsy — can capture these trajectories and support earlier, biologically informed prediction of pCR and sustained clinical complete response (cCR). This article presents the biological rationale for the hypothesis, defines a four-phase mechanistic model of immune remodeling, proposes a measurable and feasibility-conscious biomarker panel with a data-driven scoring approach, states five falsifiable predictions, and outlines a prospective validation framework — including its ethical prerequisites, procedural safety considerations, and analytic handling of treatment-regimen heterogeneity and tumor spatial heterogeneity.