Tumor regression after neoadjuvant chemoradiotherapy can improve the long-term outcomes of rectal cancer. However, it is unclear how the tumor regression grade (TRG) relates to long-term outcomes. We evaluated how the TRG affects overall survival in patients with rectal cancer who underwent neoadjuvant chemoradiotherapy prior to radical surgery.

All patients who underwent low anterior resection for rectal cancer after chemoradiotherapy over a 13-year period were included in this study. Perioperative and histopathological data of patients, including the TRG (categorized as no regression, minimal regression, moderate regression, near complete regression and complete regression) were evaluated. The correlation of TRG with overall survival was assessed using the log-rank test and Cox proportional hazards regression analysis.

During the study period,193 patients underwent low anterior rectal resection after neoadjuvant chemoradiotherapy. The 90-day mortality rate was 1.5 % and the median follow up was 69.5 months. The 5-year and 10-year overall survival rates were 85.0 % and 69.8 %, respectively. Patients with complete regression had a significantly higher 10-year overall survival rate than other patients (87.3 % vs. 66.5 %, p = 0.031). Multivariate analysis revealed that older age (hazard ratio [HR] = 2.4,95 % confidence interval [95 % CI] = 1.3-4.6, p = 0.007) and complete pathological response (HR = 0.23, 95 % CI = 0.06-0.96, p = 0.044) were independent predictors of overall survival.

Complete pathological response after neoadjuvant therapy for rectal cancer improves overall survival after surgery. Further studies are needed to determine the factors that predict complete TRG to identify patients who would benefit most from neoadjuvant chemoradiotherapy.

Background/Objectives: Autophagy is a conserved self-degradation process by which cells break down and recycle their cellular constituents. This process is activated by various stressors, including nutrient deprivation and DNA damage, and has also been associated with tumor progression. In the present study, we aimed to determine the expression patterns, clinicopathological significance, and prognostic value of the autophagy marker microtubule-associated protein 1 light chain 3 alpha (LC3A)-an essential component of autophagic vacuoles-in rectal cancer. Methods: LC3A reactivity was measured by immunohistochemistry in tumor samples from 243 patients who underwent surgery for rectal cancer. Results: Three distinct patterns of LC3A expression were identified: diffuse cytoplasmic, perinuclear, and stone-like structures (SLS). In Kaplan-Meier survival analyses, patients positive for the SLS pattern of LC3A staining in the tumor periphery (TP) had worse overall survival (OS; p = 0.001) and disease-free survival (DFS; p = 0.030) than those without SLSs in this region, as determined by the log-rank test. When patients were stratified by tumor stage, this result was significant in those with stage T3-T4 (OS, p < 0.001; DFS, p = 0.001) but not T1-T2 disease. Multivariate Cox regression analysis further showed an association between TP-localized LC3A SLS positivity and reduced OS for the overall cohort (hazard ratio [HR] = 2.6313, 95% confidence interval [CI]: 1.090-6.349, p = 0.031) and specifically those in the T3-T4 subgroup (HR = 3.347, 95% CI: 1.657-6.760, p = 0.001). Conclusions: Our findings suggest that positivity for SLSs in the TP may hold clinical value as a biomarker for survival prognosis in rectal cancer patients.

Predicting the response to chemotherapy can lead to the optimization of neoadjuvant chemotherapy (NAC). The present study aimed to develop a non-invasive prediction model of therapeutic response to NAC for rectal cancer (RC).

A dataset of the prechemotherapy computed tomography (CT) images of 57 patients from multiple institutions who underwent rectal surgery after three courses of S-1 and oxaliplatin (SOX) NAC for RC was collected. The therapeutic response to NAC was pathologically confirmed. It was then predicted whether they were pathologic responders or non-responders. Cases were divided into training, validation and test datasets. A CT patch-based predictive model was developed using a residual convolutional neural network and the predictive performance was evaluated. Binary logistic regression analysis of prechemotherapy clinical factors showed that none of the independent variables were significantly associated with the non-responders.

Among the 49 patients in the training and validation datasets, there were 21 (42.9%) and 28 (57.1%) responders and non-responders, respectively. A total of 3,857 patches were extracted from the 49 patients. In the validation dataset, the average sensitivity, specificity and accuracy was 97.3, 95.7 and 96.8%, respectively. Furthermore, the area under the receiver operating characteristic curve (AUC) was 0.994 (95% CI, 0.991-0.997; P<0.001). In the test dataset, which included 750 patches from 8 patients, the predictive model demonstrated high specificity (89.9%) and the AUC was 0.846 (95% CI, 0.817-0.875; P<0.001).

The non-invasive deep learning model using prechemotherapy CT images exhibited high predictive performance in predicting the pathological therapeutic response to SOX NAC.

Background/Objectives: The aim of this study was to identify response prediction and prognostic biomarkers in muscle-invasive bladder cancer (MIBC) patients undergoing neoadjuvant chemotherapy (NAC). Methods: A retrospective multicentre study including 191 patients with MIBC who received NAC previous to radical cystectomy (RC) between 1996 and 2013. Gene expression patterns were analysed in 34 samples from transurethral resection of the bladder (TURB) using Illumina microarrays. The expression levels of 45 selected differentially expressed genes between responders and non-responders to NAC were validated by quantitative PCR in an independent cohort of 157 patients. Regression analysis was used to identify predictors of downstaging and relapse. A nomogram for predicting downstaging and relapse-including clinicopathological and gene expression variables-was developed. Results: The expression levels of 1352 transcripts differed between responders and non-responders to NAC. A nomogram based on the most predictive clinical variables (age, Tis (in situ), gender, history of NMIBC, and lymphadenopathy) and genes selected following the Akaike information criterion (AIC) (CBTB16, CHMP6, DDX54, CASP8, LOR, and PLEC) was then created. In addition, a three-gene expression prognostic model to predict tumour relapse was generated. This model was able to discriminate between two groups of patients with a significantly different probability of tumour relapse (HR: 2.11; CI: 1.16-3.83, p = 0.01). Conclusions: Our nomogram based on gene expression and clinical data is a useful tool to predict downstaging and tumour relapse after NAC in MIBC patients. Further validation is warranted.

Background and objective: Multiple markers have been proposed, but there are no reliable pre-treatment markers that predict tumor response to total neoadjuvant therapy in patients with locally advanced rectal cancer. The objective of this study is to evaluate the usefulness of pre-treatment SEPTIN9 gene methylation ratio as a predictor of tumor response to total neoadjuvant therapy and its correlation with tumor size and tumor stage in patients with locally advanced rectal cancer. Methods: Patients with locally advanced rectal cancer (T3/4 and/or N+ histologically confirmed rectal cancer) undergoing total neoadjuvant therapy were included. Tumor size and tumor stage were determined by magnetic resonance. SEPTIN9 gene methylation in plasmatic cfDNA was analyzed by droplet digital PCR at the time of diagnosis. After completing total neoadjuvant therapy, tumor response was assessed by magnetic resonance and proctoscopy. The correlation between pre-treatment SEPTIN9 gene methylation ratio, tumor size, tumor stage and tumor response was analyzed. Results: 39 patients with locally advanced rectal cancer were included. Pre-treatment SEPTIN9 gene methylation ratio (p = 0.033) and tumor size (p = 0.026), but not tumor stage, significantly correlated with tumor response to total neoadjuvant therapy. Pre-treatment SEPTIN9 gene methylation ratio also correlated with N stage (p = 0.040) and tumor size (p = 0.001), but not with T stage (p = 0.846). Conclusions: Pre-treatment SEPTIN9 gene methylation ratio correlates with tumor size and N stage and can predict tumor response to total neoadjuvant therapy in patients with locally advanced rectal cancer.

Rectal cancer patients display heterogeneous responses to neoadjuvant treatment-including the intensive total neoadjuvant therapy (TNT)-and reliable biomarkers are lacking to guide which tumors will benefit most from these regimens. Here, we profiled DNA methylation in tumor tissue and matched patient-derived organoids (PDOs) from 18 rectal cancer cases (50 total samples), leveraging the Illumina MethylationEPIC array and quality control filters that retained 771,964 CpG sites. Analyses used linear models (for tissue-only or PDO-only) and a joint linear mixed-effects approach (accounting for patient-level random effects) to identify significant CpGs associated with log-transformed FOLFOX IC50. We found that PDOs faithfully recapitulate patient-tumor methylation patterns (Spearman's correlation >0.95 among replicate organoids), and the joint model uncovered 745 CpGs tied to FOLFOX sensitivity, many of which were missed in tissue-only analyses. Differentially methylated regions reinforced that broader epigenetic blocks near TSS or enhancer regions may modulate chemo-resistance, while pathway enrichment pinpointed focal adhesion, ECM-receptor interaction, calcium signaling, and folate metabolism as key processes. A methylation risk score derived from these CpGs significantly predicted progression-free survival in an independent colorectal cancer cohort (p=0.019), outperforming single-sample-based signatures. These findings suggest that combining methylation profiles from both tumors and PDOs can expose robust epigenetic drivers of therapy response, aiding the development of clinically actionable biomarkers for rectal cancer TNT.

The precise prediction of response to neoadjuvant chemoradiotherapy is crucial for tailoring perioperative treatment in patients diagnosed with locally advanced rectal cancer (LARC). This retrospective study aims to develop and validate a model that integrates deep learning and sub-regional radiomics from MRI imaging to predict pathological complete response (pCR) in patients with LARC.

We retrospectively enrolled 768 eligible participants from three independent hospitals who had received neoadjuvant chemoradiotherapy followed by radical surgery. Pretreatment pelvic MRI scans (T2-weighted), were collected for annotation and feature extraction. The K-means approach was used to segment the tumor into sub-regions. Radiomics and deep learning features were extracted by the Pyradiomics and 3D ResNet50, respectively. The predictive models were developed using the radiomics, sub-regional radiomics, and deep learning features with the machine learning algorithm in training cohort, and then validated in the external tests. The models' performance was assessed using various metrics, including the area under the curve (AUC), decision curve analysis, Kaplan-Meier survival analysis.

We constructed a combined model, named SRADL, which includes deep learning with sub-regional radiomics signatures, enabling precise prediction of pCR in LARC patients. SRADL had satisfactory performance for the prediction of pCR in the training cohort (AUC 0.925 [95% CI 0.894 to 0.948]), and in test 1 (AUC 0.915 [95% CI 0.869 to 0.949]) and in test 2 (AUC 0.902 [95% CI 0.846 to 0.945]). By employing optimal threshold of 0.486, the predicted pCR group had longer survival compared to predicted non-pCR group across three cohorts. SRADL also outperformed other single-modality prediction models.

The novel SRADL, which integrates deep learning with sub-regional signatures, showed high accuracy and robustness in predicting pCR to neoadjuvant chemoradiotherapy using pretreatment MRI images, making it a promising tool for the personalized management of LARC.

There is currently a lack of standardized criteria for evaluating clinical complete response (cCR) in rectal cancer post-neoadjuvant chemoradiotherapy (nCRT), often resulting in discrepancies with true pathological complete response (pCR). Staging local lesions via MRI is challenged by tissue edema and fibrosis post-nCRT, while endoscopic biopsy accuracy is compromised by residual cancer foci in the muscular layer. Transanal local excision offers a relatively accurate assessment of lesion regression but poses challenges including impaired anal function and elevated complication rates. Building on current diagnostic frameworks, we propose enhancing cCR assessment by integrating histological criteria from transanal multipoint full-layer puncture biopsy (TMFP). This approach aims to improve accuracy while minimizing complications, offering promise for patients opting for observation-based treatments. Further research is needed for definitive conclusions.

Locally advanced rectal cancer is treated with neoadjuvant chemoradiotherapy (nCRT) followed by total mesorectal excision (TME). As this approach achieves complete pathologic remissions (pCR) in approximately 30% of patients, it raises the question of whether surgery is always necessary. Non-surgical strategies, such as "watch and wait" (W&W), have shown similarly promising outcomes. However, there is an unmet need for reliable biomarkers predicting pCR. Analysis of circulating tumor DNA (ctDNA) has shown potential for monitoring treatment response and detecting minimal residual disease. We hypothesized that monitoring ctDNA changes during nCRT might facilitate the identification of individuals who achieve pCR.

In the prospective single-center NEORECT trial, the plasma of forty rectal cancer patients was collected before, during, and after nCRT and before TME. Informative somatic mutations were identified in tissue biopsies by NGS and subsequently used for ctDNA quantification by dPCR.

The results identified three distinct ctDNA patterns: increase, decrease, and absence. Remarkably, undetectable DNA was observed in good responders, while a tenfold ctDNA increase was associated with the emergence of new metastases. Despite these insights, ctDNA alone demonstrated low specificity, with no significant correlation to pCR or long-term prognosis. A multimodal approach incorporating routinely available clinical parameters remains inadequate for accurately predicting pCR prior to TME.

In conclusion, the NEORECT trial establishes the feasibility of ctDNA-based personalized monitoring for rectal cancer patients undergoing nCRT. However, the utility of ctDNA in enhancing pCR prediction for a W&W strategy warrants further investigation. Larger studies integrating multi-gene analyses and expanded clinical datasets are essential in the future.

This is a protocol for a Cochrane Review (prognosis). The objectives are as follows: Primary objectives To identify and estimate the prognostic value of molecular biomarkers as predictors of pathological complete response to neoadjuvant chemoradiotherapy in people with locally advanced rectal cancer. summarises the review question in population, index prognostic factor, comparator prognostic factor(s), outcome, timing, and setting (PICOTS) format. [Table: see text] [Figure: see text] Secondary objectives To explore the following biomarker measurement, treatment, and study design factors as possible sources of heterogeneity in the association between the prognostic factor and pathological response: type of assay/measurement method, biomarker positivity criteria or cut-off point, chemotherapy regimen, and radiotherapy regimen.

To investigate the specificity of Target of Myb1-Like1 (Tom1L1) expression in colorectal adenocarcinoma tissues and analyze the predictive value of Tom1L1 in the efficacy of neoadjuvant chemotherapy for patients with rectal adenocarcinoma.

The cancerous tissues and paracancerous normal tissues of 102 patients diagnosed with colorectal adenocarcinoma without treatment were selected; quantitative polymerase chain reaction (qPCR), Western blot and immunohistochemistry (IHC) were adopted to validate the expression level of Tom1L1 in the two groups. Furthermore, 34 patients with locally progressive mid-low rectal adenocarcinoma, who were treated with neoadjuvant Xelox chemotherapy prior to the operation, IHC was adopted to detect the expression of Tom1L1 protein in patients before and after neoadjuvant chemotherapy and to analyze the relationship between the expression level of Tom1L1 and the sensitivity of neoadjuvant therapy.

The results of qPCR, Western blot and IHC showed that the expression of Tom1L1 in colorectal adenocarcinoma tissues was significantly higher than that in paracancerous normal tissues, with a statistically significant difference (P < 0.01); Neoadjuvant chemotherapy was significantly more effective in patients with low expression of Tom1L1 protein than in those with high expression of Tom1L1 protein, with a statistically significant difference (P < 0.05).

Tom1L1 is highly expressed in colorectal adenocarcinoma tissues; neoadjuvant Xelox chemotherapy can have an impact on Tom1L1 expression in progressive rectal cancer; patients with locally progressive mid-low rectal adenocarcinoma who have low Tom1L1 expression are more sensitive to neoadjuvant chemotherapy.

Predicting pathological complete response (pCR) from pre or post-treatment features could be significant in improving the process of making clinical decisions and providing a more personalized treatment approach for better treatment outcomes. However, the lack of external validation of predictive models, missing in several published articles, is a major issue that can potentially limit the reliability and applicability of predictive models in clinical settings. Therefore, this systematic review described different externally validated methods of predicting response to neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC) patients and how they could improve clinical decision-making.

An extensive search for eligible articles was performed on PubMed, Cochrane, and Scopus between 2018 and 2023, using the keywords: (Response OR outcome) prediction AND (neoadjuvant OR chemoradiotherapy) treatment in 'locally advanced Rectal Cancer'.

(i) Studies including patients diagnosed with LARC (T3/4 and N- or any T and N+) by pre-medical imaging and pathological examination or as stated by the author (ii) Standardized nCRT completed. (iii) Treatment with long or short course radiotherapy. (iv) Studies reporting on the prediction of response to nCRT with pathological complete response (pCR) as the primary outcome. (v) Studies reporting external validation results for response prediction. (vi) Regarding language restrictions, only articles in English were accepted.

(i) We excluded case report studies, conference abstracts, reviews, studies reporting patients with distant metastases at diagnosis. (ii) Studies reporting response prediction with only internally validated approaches.

Three researchers (DC-D, FB, HT) independently reviewed and screened titles and abstracts of all articles retrieved after de-duplication. Possible disagreements were resolved through discussion among the three researchers. If necessary, three other researchers (LB, GC, MG) were consulted to make the final decision. The extraction of data was performed using the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS) template and quality assessment was done using the Prediction model Risk Of Bias Assessment Tool (PROBAST).

A total of 4547 records were identified from the three databases. After excluding 392 duplicate results, 4155 records underwent title and abstract screening. Three thousand and eight hundred articles were excluded after title and abstract screening and 355 articles were retrieved. Out of the 355 retrieved articles, 51 studies were assessed for eligibility. Nineteen reports were then excluded due to lack of reports on external validation, while 4 were excluded due to lack of evaluation of pCR as the primary outcome. Only Twenty-eight articles were eligible and included in this systematic review. In terms of quality assessment, 89 % of the models had low concerns in the participants domain, while 11 % had an unclear rating. 96 % of the models were of low concern in both the predictors and outcome domains. The overall rating showed high applicability potential of the models with 82 % showing low concern, while 18 % were deemed unclear.

Most of the external validated techniques showed promising performances and the potential to be applied in clinical settings, which is a crucial step towards evidence-based medicine. However, more studies focused on the external validations of these models in larger cohorts is necessary to ensure that they can reliably predict outcomes in diverse populations.

The most detrimental effect of DNA damage from radiation is DNA double-strand breaks, making it critical to identify reliable biomarkers for treatment response in cancer therapy. Gamma-H2AX (γ-H2AX), a marker of DNA double-strand breaks, was evaluated in this study as a potential biomarker for treatment response in locally advanced rectal cancer patients undergoing preoperative concurrent chemoradiation (CCRT).

Thirty patients with locally advanced rectal cancer received preoperative CCRT. Peripheral blood mononuclear cells (PBMCs) were collected at five time points: baseline, 24 hours after the first radiation fraction, mid-treatment, end of treatment, and six weeks post-CCRT. γ-H2AX levels were measured in these samples. MRI was used to assess treatment response based on magnetic resonance tumor regression grade (mrTRG). Patients were classified as responders or non-responders based on mrTRG. T-test and repeated measures analysis of variance (ANOVA) evaluated dynamic changes in γ-H2AX levels, and a multilevel linear regression model analyzed the relationship between γ-H2AX levels and treatment response.

Nineteen out of thirty patients (63.33%) were classified as responders. Significant dynamic changes in γ-H2AX levels were observed between non-responders and responders (P=0.01). The multilevel linear regression model showed a trend towards increased γ-H2AX levels in responders [1.17, 95% confidence interval (CI): -0.02 to 2.34, P=0.053]. Significant differences in γ-H2AX levels were observed from baseline to mid-treatment, end of treatment, and six weeks post-CCRT. Pathologic complete response (pCR) after CCRT was associated with significantly higher γ-H2AX ratios compared to those without pCR (P=0.04). However, no significant difference was identified in the multilevel linear regression model.

γ-H2AX may have potential as a biomarker for treatment response in locally advanced rectal cancer patients undergoing preoperative CCRT, although further validation is required.

Owing to the gradual aging of today's population, an increase in the prevalence of frailty syndrome has been noticed. This complex state of health, characterized by decreased resilience and tolerance with concurrent increased vulnerability to stressors and adverse health-related factors, has drawn researchers' attention in recent years. Rectal cancer, which constitutes ~30% of all colorectal cancers, is a disease noticeably related to the elderly. In its locally advanced form, it is conventionally treated with trimodal therapy-neoadjuvant chemoradiotherapy followed by total mesorectal excision and adjuvant chemotherapy. Despite its good clinical outcomes and improvement in rectal cancer local control, as evidenced by clinical trials, it remains unclear if all frail patients benefit from that approach since it may be associated with adverse side effects that cannot be handled by them. As old patients, and frail ones even more noticeably, are poorly represented in the clinical trials describing outcomes of the standard treatment, this article aims to review the current knowledge on the trimodal therapy of rectal cancer with an emphasis on novel approaches to rectal cancer that can be implemented for frail patients.

Neoadjuvant chemoradiotherapy is the standard treatment for patients with locally advanced rectal cancers owing to its ability to downstage primary tumours. Some patients can achieve pathological complete response after neoadjuvant therapy, and can adopt a "watch and wait" treatment strategy to avoid overtreatment. Therefore, it is essential to develop strategies for predicting responses to neoadjuvant therapy. Radiomics has shown great potential in extracting tumour features from high-throughput medical images for the construction of mathematics models for predicting the effects of anticancerous therapies. Herein, we explored MRI-based radiomics and found that it can predict responses of locally advanced rectal cancers to chemoradiation. Efficient radiomics model allow early-stage prediction of the effect of neoadjuvant chemoradiotherapy on locally advanced rectal cancers. It helps clinicians to make informed therapeutic decisions. In this review, we discuss the workflow of radiomics, and summarize the clinical application of MRI-based radiomics in predicting pathological complete response to neoadjuvant chemoradiotherapy of locally advanced rectal cancer.

Rectal cancer (RC) is a prevalent malignancy with significant morbidity and mortality rates. The accurate staging of RC is crucial for optimal treatment planning and patient outcomes. This review aims to summarize the current literature on imaging and metabolic diagnostic methods used in the stage assessment of RC. Various imaging modalities play a pivotal role in the initial evaluation and staging of RC. These include magnetic resonance imaging (MRI), computed tomography (CT), and endorectal ultrasound (ERUS). MRI has emerged as the gold standard for local staging due to its superior soft tissue resolution and ability to assess tumor invasion depth, lymph node involvement, and the presence of extramural vascular invasion. CT imaging provides valuable information about distant metastases and helps determine the feasibility of surgical resection. ERUS aids in assessing tumor depth, perirectal lymph nodes, and sphincter involvement. Understanding the strengths and limitations of each diagnostic modality is essential for accurate staging and treatment decisions in RC. Furthermore, the integration of multiple imaging and metabolic methods, such as PET/CT or PET/MRI, can enhance diagnostic accuracy and provide valuable prognostic information. Thus, a literature review was conducted to investigate and assess the effectiveness and accuracy of diagnostic methods, both imaging and metabolic, in the stage assessment of RC.

Achieving a pathologic complete response (pCR) after neoadjuvant chemoradiotherapy (NCRT) remains a challenge for most patients with rectal cancer. Exploring the potential of combining NCRT with immunotherapy or targeted therapy for those achieving a partial response (PR) offers a promising avenue to enhance treatment efficacy. This study investigated the impact of NCRT on the tumor microenvironment in locally advanced rectal cancer (LARC) patients who exhibited a PR.

This was a retrospective, observational study. Five patients demonstrating a PR after neoadjuvant treatment for LARC were enrolled in the study. Biopsy samples before treatment and resected specimens after treatment were stained with a panel of 26 antibodies targeting various immune and tumor-related markers, each labeled with distinct metal tags. The labeled samples were then analyzed using the Hyperion imaging system.

Heterogeneity within the tumor microenvironment was observed both before and after NCRT. Notably, tumor-associated macrophages, CD4 + T cells, CD8 + T cells, CD56 + natural killer cells, tumor-associated neutrophils, cytokeratin, and E-cadherin exhibited slight increase in abundance within the tumor microenvironment following treatment (change ratios = 0.78, 0.2, 0.27, 0.32, 0.17, 0.46, 0.32, respectively). Conversely, the number of CD14 + monocytes, CD19 + B cells, CD45 + CD4 + T cells, collagen I, α-smooth muscle actin, vimentin, and β-catenin proteins displayed significant decreases post-treatment (change ratios = 1.73, 1.92, 1.52, 1.25, 1.52, 1.12, 2.66, respectively). Meanwhile, Foxp3 + regulatory cells demonstrated no significant change (change ratio = 0.001).

NCRT has diverse effects on various components of the tumor microenvironment in LARC patients who achieve a PR after treatment. Leveraging combination therapies may optimize treatment outcomes in this patient population.

The ability to predict or detect colorectal cancer (CRC) recurrence early after surgery enables physicians to apply appropriate treatment plans and different follow-up strategies to improve patient survival. Overall, 30-50% of CRC patients experience cancer recurrence after radical surgery, but current surveillance tools have limitations in the precise and early detection of cancer recurrence. Circulating tumor cells (CTCs) are cancer cells that detach from the primary tumor and enter the bloodstream. These can provide real-time information on disease status. CTCs might become novel markers for predicting CRC recurrence and, more importantly, for making decisions about additional adjuvant chemotherapy. In this review, the clinical application of CTCs as a therapeutic marker for stage II CRC is described. It then discusses the utility of CTCs for monitoring cancer recurrence in advanced rectal cancer patients who undergo neoadjuvant chemoradiotherapy. Finally, it discusses the roles of CTC subtypes and CTCs combined with clinicopathological factors in establishing a multimarker model for predicting CRC recurrence.

This study evaluated pretreatment magnetic resonance imaging (MRI)-detected extramural venous invasion (pmrEMVI) as a predictor of survival after neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC).

Medical records of 1184 patients with rectal adenocarcinoma who underwent TME between January 2011 and December 2016 were reviewed. MRI data were collected from a computerized radiologic database. Cox proportional hazards analysis was used to assess local, systemic recurrence, and disease-free survival risk based on pretreatment MRI-assessed tumor characteristics. After propensity score matching (PSM) for pretreatment MRI features, nCRT therapeutic outcomes according to pmrEMVI status were evaluated. Cox proportional hazards analysis was used to identify risk factors for early recurrence in patients receiving nCRT.

Median follow-up was 62.8 months. Among all patients, the presence of pmrEMVI was significantly associated with worse disease-free survival (DFS; HR 1.827, 95% CI 1.285-2.597, p = 0.001) and systemic recurrence (HR 2.080, 95% CI 1.400-3.090, p < 0.001) but not local recurrence. Among patients with pmrEMVI, nCRT provided no benefit for oncological outcomes before or after PSM. Furthermore, pmrEMVI( +) was the only factor associated with early recurrence on multivariate analysis in patients receiving nCRT.

pmrEMVI is a poor prognostic factor for DFS and SR in patients with non-metastatic rectal cancer and also serves as a predictive biomarker of poor DFS and SR following nCRT in LARC. Therefore, for patients who are positive for pmrEMVI, consideration of alternative treatment strategies may be warranted.

This study demonstrated the usefulness of pmrEMVI as a predictive biomarker for nCRT, which may assist in initial treatment decision-making in patients with non-metastatic rectal cancer.

• Pretreatment MRI-detected extramural venous invasion (pmrEMVI) was significantly associated with worse disease-free survival and systemic recurrence in patients with non-metastatic rectal cancer. • pmrEMVI is a predictive biomarker of poor DFS following nCRT in patients with LARC. • The presence of pmrEMVI was the only factor associated with early recurrence on multivariate analysis in patients receiving nCRT.

The non-operative management of rectal adenocarcinoma (RA) after neoadjuvant chemoradiation therapy (nCRT) has gained increasing attention. The "Watch and Wait" ("W&W") strategy allows one to avoid surgery-related reduction in the quality of life due to permanent pelvic organ dysfunction or irreversible stoma. Still, the oncological safety of this strategy is under evaluation.

To share a single-center experience of the "W&W" strategy.

The retrospective analysis of 125 patients who received nCRT in 2016-2021 was performed. Patients who met the European Society for Medical Oncology (ESMO, 2017) criteria of clinical complete response (cCR) and received non-operative management were analyzed.

Ten patients (8%) were re-staged after nCRT as cCR and followed the "W&W" strategy. Patients' characteristics: 7 female, 3 male; mean age 67.3 years. Tumor characteristics: pre-treatment N+ was present in 7 cases; G1 adenocarcinoma in a majority of cases; mean tumor distance from the anal verge - 5.85 cm; mean tumor circumference - 71%; mean tumor length - 3.87 cm. The mean follow-up time was 30 months. Local regrowth or/and distant metastases developed in 3 cases. The 2-year disease-free survival was 70%.

Most of the patients following the "W&W" strategy have benefited. However, to reduce the number of relapses, it is necessary to perform a more careful selection of patients.

Local recurrence after surgery and radiochemotherapy seriously affects the prognosis of locally advanced rectal cancer (LARC) patients. Studies on molecular markers related to the radiochemotherapy sensitivity of cancers have been widely carried out, which might provide valued information for clinicians to carry out individual treatment.

To find potential biomarkers of tumors for predicting postoperative recurrence.

In this study, LARC patients undergoing surgery and concurrent radiochemotherapy were enrolled. We focused on clinicopathological factors and PTEN, SIRT1, p-4E-BP1, and pS6 protein expression assessed by immunohistochemistry in 73 rectal cancer patients with local recurrence and 76 patients without local recurrence.

The expression of PTEN was higher, while the expression of p-4E-BP1 was lower in patients without local recurrence than in patients with local recurrence. Moreover, TNM stage, lymphatic vessel invasion (LVI), PTEN and p-4E-BP1 might be independent risk factors for local recurrence after LARC surgery combined with concurrent radiochemotherapy.

This study suggests that PTEN and p-4E-BP1 might be potential biomarkers for prognostic prediction and therapeutic targets for LARC.

Colorectal cancer is the fourth leading cause of cancer-related death in both men and women in our population. In this regard, rectal cancer accounts for more than half of colorectal cancer deaths, and its incidence is expected to increase in the coming years. There have been significant changes in neoadjuvant therapy regimens, with promising results, as demonstrated by the recent RAPIDO and PRODIGE23 studies. Around 40% of patients diagnosed with locally advanced rectal cancer show some degree of response to neoadjuvant treatment, with complete tumor regression observed in up to one in five patients.

Retrospective observational study. A total of 181 patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy followed by surgery were analyzed. Clinical and pathological data were collected from the patients, including assessment of tumor regression through histopathological studies after surgery. The Mandard tumor regression grading system was used to categorize tumor response into different grades.

The results showed a significant association between the degree of tumor regression and several important clinical outcomes. Specifically, patients with higher tumor regression had significantly better disease-free survival than those with less regression (p = 0.004). In addition, tumor regression was also correlated with the incidence of local recurrence (p = 0.018) and distant metastasis (p = 0.032). These associations suggest that tumor responsiveness to neoadjuvant therapy may influence the long-term progression of the disease. Regarding tumor deposits and the presence of lymphadenopathy, these factors were also found to be significantly associated with clinical outcomes. Patients with tumor deposits had a higher incidence of local recurrence (p = 0.025) and distant metastases (p = 0.041), while the presence of lymphadenopathy increased the risk of local recurrence (p = 0.013). These findings highlight the importance of evaluating not only tumor regression but also other pathological markers to predict prognosis and guide clinical management.

The degree of tumor regression was not an independent predictor of survival compared to other variables such as nodal stage and presence of tumor deposits. This indicates that while tumor regression is an important factor, other elements also play a crucial role in determining the prognosis of patients with locally advanced rectal cancer. This study provides additional evidence for the importance of tumor regression, tumor deposits, and lymphadenopathy as predictors of clinical outcomes in patients with rectal cancer treated with neoadjuvant chemoradiotherapy.

Watch-and-wait has emerged as a new strategy for the management of rectal cancer when a complete clinical response is achieved after neoadjuvant therapy. In an attempt to standardize this new clinical approach, initiated by the Spanish Cooperative Group for the Treatment of Digestive Tumors (TTD), and with the participation of the Spanish Association of Coloproctology (AECP), the Spanish Society of Pathology (SEAP), the Spanish Society of Gastrointestinal Endoscopy (SEED), the Spanish Society of Radiation Oncology (SEOR), and the Spanish Society of Medical Radiology (SERAM), we present herein a consensus on a watch-and-wait approach for the management of rectal cancer. We have focused on patient selection, the treatment schemes evaluated, the optimal timing for evaluating the clinical complete response, the oncologic outcomes after the implementation of this strategy, and a protocol for surveillance of these patients.

The accurate prediction of treatment response in locally advanced rectal cancer (LARC) patients undergoing MRI-guided radiotherapy (MRIgRT) is essential for optimising treatment strategies. This multi-institutional study aimed to investigate the potential of radiomics in enhancing the predictive power of a known radiobiological parameter (Early Regression Index, ERITCP) to evaluate treatment response in LARC patients treated with MRIgRT.

Patients from three international sites were included and divided into training and validation sets. 0.35 T T2*/T1-weighted MR images were acquired during simulation and at each treatment fraction. The biologically effective dose (BED) conversion was used to account for different radiotherapy schemes: gross tumour volume was delineated on the MR images corresponding to specific BED levels and radiomic features were then extracted. Multiple logistic regression models were calculated, combining ERITCP with other radiomic features. The predictive performance of the different models was evaluated on both training and validation sets by calculating the receiver operating characteristic (ROC) curves.

A total of 91 patients was enrolled: 58 were used as training, 33 as validation. Overall, pCR was observed in 25 cases. The model showing the highest performance was obtained combining ERITCP at BED = 26 Gy with a radiomic feature (10th percentile of grey level histogram, 10GLH) calculated at BED = 40 Gy. The area under ROC curve (AUC) of this combined model was 0.98 for training set and 0.92 for validation set, significantly higher (p = 0.04) than the AUC value obtained using ERITCP alone (0.94 in training and 0.89 in validation set).

The integration of the radiomic analysis with ERITCP improves the pCR prediction in LARC patients, offering more precise predictive models to further personalise 0.35 T MRIgRT treatments of LARC patients.

Colorectal cancer (CRC) is one of the most aggressive, heterogenous, and fatal types of human cancer for which screening, and more effective therapeutic drugs are urgently needed. Early-stage detection and treatment greatly improve the 5-year survival rate. In the era of targeted therapies for all types of cancer, a complete metabolomic profile is mandatory before neoadjuvant therapy to assign the correct drugs and check the response to the treatment given. The aim of this study is to discover specific metabolic biomarkers or a sequence of metabolomic indicators that possess precise diagnostic capabilities in predicting the efficacy of neoadjuvant therapy. After searching the keywords, a total of 108 articles were identified during a timeframe of 10 years (2013-2023). Within this set, one article was excluded due to the use of non-English language. Six scientific papers were qualified for this investigation after eliminating all duplicates, publications not referring to the subject matter, open access restriction papers, and those not applicable to humans. Biomolecular analysis found a correlation between metabolomic analysis of colorectal cancer samples and poor progression-free survival rates. Biomarkers are instrumental in predicting a patient's response to specific treatments, guiding the selection of targeted therapies, and indicating resistance to certain drugs.

To develop and validate a multiparametric model to predict neoadjuvant treatment response in rectal cancer at baseline using a heterogeneous multicenter MRI dataset.

Baseline staging MRIs (T2W (T2-weighted)-MRI, diffusion-weighted imaging (DWI) / apparent diffusion coefficient (ADC)) of 509 patients (9 centres) treated with neoadjuvant chemoradiotherapy (CRT) were collected. Response was defined as (1) complete versus incomplete response, or (2) good (Mandard tumor regression grade (TRG) 1-2) versus poor response (TRG3-5). Prediction models were developed using combinations of the following variable groups: (1) Non-imaging: age/sex/tumor-location/tumor-morphology/CRT-surgery interval (2) Basic staging: cT-stage/cN-stage/mesorectal fascia involvement, derived from (2a) original staging reports, or (2b) expert re-evaluation (3) Advanced staging: variables from 2b combined with cTN-substaging/invasion depth/extramural vascular invasion/tumor length (4) Quantitative imaging: tumour volume + first-order histogram features (from T2W-MRI and DWI/ADC) Models were developed with data from 6 centers (n = 412) using logistic regression with the Least Absolute Shrinkage and Selector Operator (LASSO) feature selection, internally validated using repeated (n = 100) random hold-out validation, and externally validated using data from 3 centers (n = 97).

After external validation, the best model (including non-imaging and advanced staging variables) achieved an area under the curve of 0.60 (95%CI=0.48-0.72) to predict complete response and 0.65 (95%CI=0.53-0.76) to predict a good response. Quantitative variables did not improve model performance. Basic staging variables consistently achieved lower performance compared to advanced staging variables.

Overall model performance was moderate. Best results were obtained using advanced staging variables, highlighting the importance of good-quality staging according to current guidelines. Quantitative imaging features had no added value (in this heterogeneous dataset).

Predicting tumour response at baseline could aid in tailoring neoadjuvant therapies for rectal cancer. This study shows that image-based prediction models are promising, though are negatively affected by variations in staging quality and MRI acquisition, urging the need for harmonization.

This multicenter study combining clinical information and features derived from MRI rendered disappointing performance to predict response to neoadjuvant treatment in rectal cancer. Best results were obtained with the combination of clinical baseline information and state-of-the-art image-based staging variables, highlighting the importance of good quality staging according to current guidelines and staging templates. No added value was found for quantitative imaging features in this multicenter retrospective study. This is likely related to acquisition variations, which is a major problem for feature reproducibility and thus model generalizability.

Local tumor response evaluation following neoadjuvant treatment(s) in rectal adenocarcinoma requires a multi-modality approach including physical and endoscopic evaluations, rectal protocoled MRI, and cross-sectional imaging. Clinical tumor response exists on a spectrum from complete clinical response (cCR), defined as the absence of clinical evidence of residual tumor, to near-complete response (nCR), which assumes a significant reduction in tumor burden but with increased uncertainty of residual microscopic disease, to incomplete clinical response (iCR), which incorporates all responses less than nCR that is not progressive disease. This article aims to review the clinical tools currently routinely available to evaluate treatment response and offers a potential management approach based on the extent of local tumor response.

The overall prognosis of locally advanced rectal cancer (LARC) remains unsatisfactory due to a high incidence of disease relapse. The present understanding of the factors that determine the likelihood of recurrence is limited or ineffective. We aimed to identify the main risk factors influencing tumor relapse in LARC patients after neoadjuvant chemoradiotherapy (nCRT) and surgical treatment in a single center in Republika Srpska. Patients with stage II or stage III who received nCRT before surgery for primary rectal cancer at the Oncology Clinic, University Clinical Center of Republika Srpska from January 2017 and December 2022 were included in the study. We collected patient demographics, clinical stage and characteristics, neoadjuvant therapy, and surgical methods, along with the pathological response after treatment completion, and analyzed them to identify the risk factors for tumor relapse. Out of 109 patients diagnosed with LARC, 34 (31,2%) had tumor relapse. The median time to relapse was 54 months. Participants with clinical T4 stage had a significantly shorter relapse time compared to the patients with clinical T2/3 stage. Subjects with positive lymph nodes removed, perivascular and perineural invasion, intraoperative perforation and patients without ypN stage improvement had significantly shorter time to relapse. Subjects with T4 stage had more than 4 times higher risk of relapse than patients with clinical T2/3 stage. Higher clinical T stage was an essential risk factor for tumor relapse in LARC patients after nCRT and surgical treatment. Comprehensive understanding and identification of the risk factors for tumor relapse in LARC patients are crucial for improving their long-term outcomes.

Mismatch repair deficiency, immunological fertility, and PD-L1 expression status are key histopathological and molecular features defining tumor responsiveness to immunotherapy and, eventually, prognosis. These were investigated in a series of locally advanced rectal cancer patients treated with postoperative chemotherapy and radiotherapy.

Tumor-infiltrating lymphocyte (TIL) density was assessed in hematoxylin-eosin tissue sections. PD-L1 expression and the expression of MMR proteins (MLH1, PSM2, MSH2, and MSH6) were assessed with immunohistochemistry. Their association with histopathological variables (node involvement and tumor budding) and prognosis was assessed.

The TIL-density was significantly higher in the invading tumor front and was inversely related to tumor budding and directly with better overall survival (OS) and distant metastasis-free survival (DMFS) (p = 0.02 and 0.02, respectively). Cancer cell PD-L1 expression was related to high TIL-density (p < 0.01) but not to prognosis, although its overexpression defined a trend for poorer OS in patients with high TIL-density. High PD-L1 expression by stroma infiltrating immune cells was linked with better OS and DMFS (p = 0.007 and 0.001, respectively. MMR deficiency was recorded in 26.2 % of cases, and this was linked with higher TIL-density, but not with prognosis.

Dense intratumoral lymphocytic infiltration relates to a better prognosis in rectal cancer, although it is also linked with PD-L1 expression that may adversely modulate the anti-tumor effects of TILs. This latter subgroup of patients (high TIL-density/high cancer cell PD-L1 expression) could be an additional target for anti-PD-1/PD-L1 immunotherapy, along with the established subgroup of MMR deficient patients.

Extramural vascular invasion (EMVI) and tumor deposits (TD) are poor prognostic factors in rectal cancer (RC), especially when resistant to neoadjuvant chemotherapy (NAC). We aimed to define differential expression in NAC responders and non-responders with concomitant EMVI and TD.

From 52 RC surgical patients, post-NAC resected specimens were extracted, comprising two groups: cases with residual EMVI and TD (NAC-resistant) and cases without (NAC-effective). Proteomic analysis was conducted to define differential protein expression in the two groups. To validate the findings, immunohistochemistry was performed in another cohort that included 58 RC surgical patients. Based on the findings, chemosensitivity and prognosis were compared.

The NAC-resistant group was associated with a lower 3-year disease-free survival rate than the NAC-effective group (p = 0.041). Discriminative proteins in the NAC-resistant group were highly associated with the sulfur metabolism pathway. Among these pathway constituents, selenium-binding protein 1 (SELENBP1) expression in the NAC-resistant group decreased to less than one-third of that of the NAC-effective group. Immunohistochemistry in another RC cohort consistently validated the relationship between decreased SELENBP1 and poorer NAC sensitivity, in both pre-NAC biopsy and post-NAC surgery specimens. Furthermore, decrease in SELENBP1 was associated with a lower 3-year disease-free survival rate (p = 0.047).

We defined one of the differentially expressed proteins in NAC responders and non-responders, concomitant with EMVI and TD. SELENBP1 was suspected to contribute to NAC resistance and poor prognosis in RC.

Aside from surgical resection, locally advanced rectal cancer is regularly treated with neoadjuvant chemoradiotherapy. Since the concept of cancer treatment has shifted from only focusing on tumor cells as drivers of disease progression towards a broader understanding including the dynamic tumor microenvironment (TME), the impact of radiotherapy on the TME and specifically the tumor immune microenvironment (TIME) is increasingly recognized. Both promoting as well as suppressing effects on anti-tumor immunity have been reported in response to rectal cancer (chemo-)radiotherapy and various targets for combination therapies are under investigation. A literature review was conducted searching the PubMed database for evidence regarding the pleiotropic effects of (chemo-)radiotherapy on the rectal cancer TIME, including alterations in cytokine levels, immune cell populations and activity as well as changes in immune checkpoint proteins. Radiotherapy can induce immune-stimulating and -suppressive alterations, potentially mediating radioresistance. The response is influenced by treatment modalities, including the dosage administered and the highly individual intrinsic pre-treatment immune status. Directly addressing the main immune cells of the TME, this review aims to highlight therapeutical implications since efficient rectal cancer treatment relies on personalized strategies combining conventional therapies with immune-modulating approaches, such as immune checkpoint inhibitors.

Previous observations have demonstrated that the response to neoadjuvant chemoradiotherapy (nCRT) is highly variable in patients with locally advanced rectal cancer (LARC). Recent studies focusing on the intratumoral microbiota of colorectal cancer have revealed its role in oncogenesis and tumor progression. However, limited research has focused on the influence of intratumoral microbiota on the nCRT of LARC.

We explored the microbial profiles in the tumor microenvironment of LARC using RNA-seq data from a published European cohort. Microbial signatures were characterized in pathological complete response (pCR) and non-pCR groups. Multi-omics analysis was performed between intratumor microbiomes and transcriptomes.

Microbial α and β diversity were significantly different in pCR and non-pCR groups. Twelve differential microbes were discovered between the pCR and non-pCR groups, six of which were related to subclusters of cancer-associated fibroblasts (CAFs) associated with extracellular matrix formation. A microbial risk score based on the relative abundance of seven differential microbes had predictive value for the nCRT response (AUC = 0.820, p < 0.001).

Our study presents intratumoral microbes as potential independent predictive markers for the response of nCRT to LARC and demonstrates the underlying mechanism by which the interaction between intratumoral microbes and CAFs mediates the response to nCRT.

For locally advanced rectal cancer (LARC), accurate response evaluation is necessary to select complete responders after neoadjuvant therapy (NAT) for a watch-and-wait (W&W) strategy. Algorithms based on deep learning have shown great value in medical image analyses. Here we used deep learning algorithms of endoscopic images for the assessment of NAT response in LARC.

214 LARC patients were retrospectively included in the study. After NAT, these patients underwent total mesorectal excision (TME) surgery. Among them, 51 (23.8%) of the patients achieved a pathological complete response (pCR). 160 patients from Shanghai Changzheng Hospital were regarded as primary dataset, and the other 54 patients from Zhejiang Cancer Hospital were regarded as validation dataset. ResNet-18 and DenseNet-121 were applied to train the models based on endoscopic images after NAT. Deep learning models were valid in the validation dataset and compared to manual method.

The performances were comparable in AUC between deep learning models and manual method. For mean metrics, sensitivity (0.750 vs. 0.417) and AUC (0.716 vs. 0.601) in ResNet-18 deep learning model were higher than those in the manual method. The deep learning models were able to identify the endoscopic features associated with NAT response by the heatmaps. A diagnostic flow diagram which integrated the deep learning model to assist the clinicians in making decisions for W&W strategy was constructed.

We created deep learning models using endoscopic features for assessment of NAT in LARC. The deep learning models achieved modest accuracies and performed comparably to manual method.

To establish a prediction model for the efficacy of neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC), using pretreatment magnetic resonance imaging (MRI) multisequence image features and clinical parameters.

Patients with clinicopathologically confirmed LARC were included (training and validation datasets, n = 100 and 27, respectively). Clinical data of patients were collected retrospectively. We analyzed MRI multisequence imaging features. The tumor regression grading (TRG) system proposed by Mandard et al was adopted. Grade 1-2 of TRG was a good response group, and grade 3-5 of TRG was a poor response group. In this study, a clinical model, a single sequence imaging model, and a comprehensive model combined with clinical imaging were constructed, respectively. The area under the subject operating characteristic curve (AUC) was used to evaluate the predictive efficacy of clinical, imaging, and comprehensive models. The decision curve analysis method evaluated the clinical benefit of several models, and the nomogram of efficacy prediction was constructed.

The AUC value of the comprehensive prediction model is 0.99 in the training data set and 0.94 in the test data set, which is significantly higher than other models. Radiomic Nomo charts were developed using Rad scores obtained from the integrated image omics model, circumferential resection margin(CRM), DoTD, and carcinoembryonic antigen(CEA). Nomo charts showed good resolution. The calibrating and discriminating ability of the synthetic prediction model is better than that of the single clinical model and the single sequence clinical image omics fusion model.

Nomograph, based on pretreatment MRI characteristics and clinical risk factors, has the potential to be used as a noninvasive tool to predict outcomes in patients with LARC after nCRT.