The treatment of locally advanced rectal cancer (LARC) requires a multimodal approach combining neoadjuvant radiotherapy or chemoradiotherapy (CRT) and surgery. Predicting tumor response to CRT can guide clinical decision making and improve patient care while avoiding unnecessary toxicity and morbidity. Circulating biomarkers offer both the advantage to be easily accessed and followed over time. In recent years, biomarkers such as proteins, blood cells, or nucleic acids have been investigated for their predictive value in oncology. We conducted a comprehensive literature review with the aim to summarize the status of circulating biomarkers predicting response to CRT in LARC. Forty-nine publications, of which forty-seven full-text articles, one review and one systematic review, were retrieved. These studies evaluated circulating markers (CEA and CA 19-9), inflammatory biomarkers (CRP, albumin, and lymphocytes), hematologic markers (hemoglobin and thrombocytes), lipids and circulating nucleic acids (cell-free DNA [cfDNA], circulating tumor DNA [ctDNA], and microRNA [miRNA]). Post-CRT CEA levels had the most consistent association with tumor response, while cfDNA integrity index, MGMT promoter methylation, ERCC-1, miRNAs, and miRNA-related SNPs were identified as potential predictive markers. Although circulating biomarkers hold great promise, inconsistent results, low statistical power, and low specificity and sensibility prevent them from reliably predicting tumor response following CRT. Validation and standardization of methods and technologies are further required to confirm results.

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.

Locally advanced rectal cancer (LARC) is treated with neoadjuvant chemoradiotherapy (nCRT), but only a minority of patients achieve a pathological complete response (pCR). Predictive biomarkers of response could help guide treatment decisions, yet none have reached clinical practice. In this exploratory study, we integrated six publicly available transcriptomic datasets and applied machine learning to derive a 186-gene signature predictive of nCRT response. The signature showed good performance in cross-validation (AUC 0.80) and was associated with consensus molecular (CMS4) and immune (iCMS3) subtypes enriched in responders. Gene set enrichment analyses highlighted pathways involved in tumor growth, immune regulation, and resistance. Spatial transcriptomic profiling of pre-treatment biopsies further identified compartment-specific markers, with tumor-associated genes showing greater predictive value. These results provide biological insights into response mechanisms and generate hypotheses for future validation. Larger prospective studies are required to assess the clinical utility of this approach.