Background/Objectives: Treatment of locally advanced rectal cancer (LARC) very often requires a neoadjuvant multimodal approach. Neoadjuvant treatment (NAT) encompasses treatments like chemoradiotherapy (CRT), short-course radiotherapy (SCRT), radiotherapy (RT) or a combination of either of these two with additional induction or consolidation chemotherapy, namely total neoadjuvant treatment (TNT). In case of complete radiological and clinical response, the non-operative watch-and-wait strategy can be adopted in selected patients. This strategy is impacted by a regrowth rate of approximately 30%. Predicting biomarkers of tumor response to NAT could improve guidance of clinicians during clinical decision making, improving treatment outcomes and decreasing unnecessary treatment exposure. To this day, there is no validated biomarker to predict tumor response to any NAT strategies in clinical use. Most research focused on CRT neglects the study of other regimens. Methods: We conducted a narrative literature review which aimed at summarizing the status of biomarkers predicting tumor response to NAT other than CRT in LARC. Results: Two hundred and fourteen articles were identified. After screening, twenty-one full-text articles were included. Statistically significant markers associated with improved tumor response pre-treatment were as follows: low circulating CEA levels; BCL-2 expression; high cellular expression of Ku70, MIB-1(Ki-67) and EGFR; low cellular expression of VEGF, hPEBP4 and nuclear β-catenin; the absence of TP53, SMAD4, KRAS and LRP1B mutations; the presence of the G-allel of LCS-6; and MRI features such as the conventional biexponential fitting pseudodiffusion (Dp) mean value and standard deviation (SD), the variable projection Dp mean value and lymph node characteristics (short axis, smooth contour, homogeneity and Zhang et al. radiomic score). In the interval post-treatment and before surgery, significant markers were as follows: a reduction in the median value of circulating free DNA, higher presence of monocytic myeloid-derived suppressor cells, lower presence of CTLA4+ or PD1+ regulatory T cells and standardized index of shape changes on MRI. Conclusions: Responders to neoadjuvant SCRT and RT tended to have a tumor microenvironment with an immune–active phenotype, whereas responders to TNT tended to have a less active tumor profile. Although some biomarkers hold great promise, scarce publications, inconsistent results, low statistical power, and low reproducibility prevent them from reliably predicting tumor response following NAT.

Digital pathology (DP) has become an integral part of modern diagnostic practice, enabling efficient workflows, reproducible assessments, and the integration of computational tools. While many institutions are transitioning toward digital diagnostics, deployment, validation, and routine usage of DP tools in clinical settings remains a major challenge. Existing recommendations often remain high-level, leaving laboratories without detailed, practical guidance on how to structure and document validation processes in real-world settings. To address this gap, we present a framework derived from the experience of Geneva University Hospitals (HUG), which since 2019 has operated a fully digital primary diagnostic workflow processing more than 230,000 slides annually. Drawing on this implementation, we outline best practices and lessons learned for the development, deployment, validation, and accreditation of DP tools. Document templates are also provided, which may serve as adaptable blueprints for other laboratories. This practical guide is intended to support reproducible, transparent, and audit-ready validation processes, helping institutions bridge the gap between general recommendations and operational deployment of DP tools in accredited diagnostic environments.