Impact of Tumor Regression Grade as a Major Prognostic Factor in Locally Advanced Rectal Cancer after Neoadjuvant Chemoradiotherapy: A Proposal for a Modified Staging System

Impact of pathological complete response on survival in gastric cancer after neoadjuvant chemotherapy: a propensity score matching analysis

PURPOSE

The survival benefits of neoadjuvant chemotherapy (NAC) for locally advanced gastric cancer (LAGC) patients are inconsistent. This study aims to investigate how different tumor regression grades (TRG) influence the survival gains associated with NAC treatment.

METHODS

This study compared the treatment outcomes of patients who underwent CSC (neoadjuvant chemotherapy - surgery - adjuvant chemotherapy) with those receiving traditional SC (surgery - adjuvant chemotherapy) treatment. Propensity score matching (PSM) was employed to minimize potential biases arising from differences in baseline characteristics and intervention factors between the treatment groups. After PSM, the CSC cohort was stratified according to TRGs, and their survival outcomes were compared to assess the impact of TRGs on survival gains associated with NAC.

RESULTS

Before PSM, a total of 506 patients were enrolled: 291 in the CSC cohort and 215 in the SC cohort. The CSC cohort had a lower 3-year survival rate (3Y-SR) than the SC cohort (64.6% vs. 76%). In the CSC cohort, patients who achieved pathological complete response (pCR, 12.1%, 26/215) demonstrated significantly improved 3Y-SR (95.5%). After PSM, 110 patients were matched in each cohort. The 3Y-SR was similar between the CSC cohort (68.3%) and the SC cohort (63.6%). In the CSC cohort, 12.7% (14/110) of patients achieved pCR. Subgroup analysis revealed that the pCR subgroup (3Y-SR 100%) was the only subgroup within the CSC cohort that maintained significantly improved survival compared to the SC cohort. Better tumor differentiation was the only pre-treatment factor significantly associated with achieving pCR (p < 0.001).

CONCLUSION

In this retrospective study, LAGC patients who achieved pCR after NAC demonstrated significantly better survival outcomes compared to other response groups. The study found tumor differentiation was a potential predictor of pCR.

Combined transrectal ultrasound and radiomics model for evaluating the therapeutic effects of neoadjuvant chemoradiotherapy in locally advanced rectal cancer

PURPOSE

This study aimed to explore a combined transrectal ultrasound (TRUS) and radiomics model for predicting tumor regression grade (TRG) after neoadjuvant chemoradiotherapy (NCRT) in patients with locally advanced rectal cancer (LARC).

METHODS

Among 190 patients with LARC, 53 belonged to GRG and 137 to PRG. Eight TRUS parameters were identified as statistically significant (P < 0.05) for distinguishing between the groups, including PSVpre, LDpost, TDpost, CEUS-IGpost, LD change rate, TD change rate, RI change rate, and CEUS-IG downgrade. The accuracies of these individual parameters in predicting TRG were 0.42, 0.62, 0.56, 0.68, 0.67, 0.70, 0.63, and 0.71, respectively. The AUC values were 0.596, 0.597, 0.630, 0.752, 0.686, 0.660, 0.650, and 0.666, respectively. The multi-parameter ultrasonic logistic regression (MPU-LR) model achieved an accuracy of 0.816 and an AUC of 0.851 (95% CI: [0.792-0.909]). The optimal pre- and post-treatment radiomics models were RF (Mean-PCA-RFE-6) and AE (Zscore-PCA-RFE-12), with accuracies of 0.563 and 0.596 and AUCs of 0.601 (95% CI: [0.561-0.641]) and 0.662 (95% CI: [0.630-0.694]), respectively. The combined model (US-RADpre-RADpost) showed the highest predictive power with accuracy and AUC of 0.863 and 0.913.

CONCLUSIONS

The combined model based on TRUS and radiomics demonstrated remarkable predictive capability for TRG after NCRT. It serves as a precision tool for assessing NCRT response in patients with LARC, impacting treatment strategies.

Tumor Immune Microenvironment Biomarkers for Recurrence Prediction in Locally Advanced Rectal Cancer Patients after Neoadjuvant Chemoradiotherapy

BACKGROUND/OBJECTIVES

The tumor microenvironment (TME) has emerged as a significant prognostic factor. This study aimed to identify prognostic factors by combining clinicopathologic parameters and the TME biomarkers in patients who underwent surgery following neoadjuvant chemoradiotherapy (nCRT) for locally advanced rectal cancer (LARC).

METHODS

CD8+ T cells, CXCR3, CXCL10, and α-smooth muscle actin (α-SMA) were analyzed via immunohistochemical staining. We also incorporated AI-powered digital pathology to assess the spatial TME. The associations between these biomarkers, clinicopathologic parameters, and survival outcomes were evaluated.

RESULTS

CD8+ T cell expression, CXCR3 expression in tumor-infiltrating lymphocytes (TILs), and immune phenotypes were correlated. LARC patients with a high expression of CD8+ T cells, CXCR3 in TILs, and an inflamed phenotype had a significantly better prognosis than their counterparts did. In the multivariate analysis, the expression of CD8+ T cells and the inflamed/immune-excluded phenotype were significant tumor immune microenvironment (TiME) biomarkers for recurrence-free survival (RFS) but not for overall survival (OS). Notably, patients with the immune-desert phenotype had a poor prognosis regardless of pathologic stage, even if postoperative chemotherapy was administered (p < 0.001).

CONCLUSIONS

CD8+ T cells and AI-powered immune phenotypes, alongside clinical factors, can guide personalized treatment in LARC patients receiving nCRT. A therapeutic strategy to modify the TiME after nCRT could help reduce recurrence after surgery.

Deep neural networks integrating genomics and histopathological images for predicting stages and survival time-to-event in colon cancer

MOTIVATION

There exists an unexplained diverse variation within the predefined colon cancer stages using only features from either genomics or histopathological whole slide images as prognostic factors. Unraveling this variation will bring about improved staging and treatment outcomes. Hence, motivated by the advancement of Deep Neural Network (DNN) libraries and complementary factors within some genomics datasets, we aggregate atypia patterns in histopathological images with diverse carcinogenic expression from mRNA, miRNA and DNA methylation as an integrative input source into a deep neural network for colon cancer stages classification, and samples stratification into low or high-risk survival groups.

RESULTS

The genomics-only and integrated input features return Area Under Curve-Receiver Operating Characteristic curve (AUC-ROC) of 0.97 compared with AUC-ROC of 0.78 obtained when only image features are used for the stage's classification. A further analysis of prediction accuracy using the confusion matrix shows that the integrated features have a weakly improved accuracy of 0.08% more than the accuracy obtained with genomics features. Also, the extracted features were used to split the patients into low or high-risk survival groups. Among the 2,700 fused features, 1,836 (68%) features showed statistically significant survival probability differences in aggregating samples into either low or high between the two risk survival groups. Availability and Implementation: https://github.com/Ogundipe-L/EDCNN.

Machine learning-based response assessment in patients with rectal cancer after neoadjuvant chemoradiotherapy: radiomics analysis for assessing tumor regression grade using T2-weighted magnetic resonance images

PURPOSE

This study aimed to assess tumor regression grade (TRG) in patients with rectal cancer after neoadjuvant chemoradiotherapy (NCRT) through a machine learning-based radiomics analysis using baseline T2-weighted magnetic resonance (MR) images.

MATERIALS AND METHODS

In total, 148 patients with locally advanced rectal cancer(T2-4 or N+) who underwent MR imaging at baseline and after chemoradiotherapy between January 2010 and May 2021 were included. A region of interest for each tumor mass was drawn by a radiologist on oblique axial T2-weighted images, and main features were selected using principal component analysis after dimension reduction among 116 radiomics and three clinical features. Among eight learning models that were used for prediction model development, the model showing best performance was selected. Treatment responses were classified as either good or poor based on the MR-assessed TRG (mrTRG) and pathologic TRG (pTRG). The model performance was assessed using the area under the receiver operating curve (AUROC) to classify the response group.

RESULTS

Approximately 49% of the patients were in the good response (GR) group based on mrTRG (73/148) and 26.9% based on pTRG (28/104). The AUCs of clinical data, radiomics models, and combined radiomics with clinical data model for predicting mrTRG were 0.80 (95% confidence interval [CI] 0.73, 0.87), 0.74 (95% CI 0.66, 0.81), and 0.75(95% CI 0.68, 0.82), and those for predicting pTRG was 0.62 (95% CI 0.52, 0.71), 0.74 (95% CI 0.65, 0.82), and 0.79 (95% CI 0.71, 0.87).

CONCLUSION

Radiomics combined with clinical data model using baseline T2-weighted MR images demonstrated feasible diagnostic performance in predicting both MR-assessed and pathologic treatment response in patients with rectal cancer after NCRT.

The prognostic model and immune landscape based on cancer-associated fibroblast features for patients with locally advanced rectal cancer

Background

This study aimed to construct a nomogram based on CAF features to predict the cancer-specific survival (CSS) rates of locally advanced rectal cancer (LARC) patients.

Methods

The EPIC algorithm was employed to calculate the proportion of CAFs. based on the differentially expressed genes between the high and low CAF proportion subgroups, prognostic genes were identified via LASSO and Cox regression analyses. They were then used to construct a prognostic risk signature. Moreover, the GSE39582 and GGSE38832 datasets were used for external validation. Lastly, the level of immune infiltration was evaluated using ssGSEA, ESTIMATE, CIBERSORTx, and TIMER.

Results

A higher level of CAF infiltration was associated with a worse prognosis. Additionally, the number of metastasized lymph nodes and distant metastases, as well as the level of immune infiltration were higher in the high CAF proportion subgroup. Five prognostic genes (SMOC2, TUBAL3, C2CD4A, MAP1B, BMP8A) were identified and subsequently incorporated into the prognostic risk signature to predict the 1-, 3-, and 5-year CSS rates in the training and validation sets. Differences in survival rates were also determined in the external validation cohort. Furthermore, independent prognostic factors, including TNM stage and risk score, were combined to established a nomogram. Notably, our results revealed that the proportions of macrophages and neutrophils and the levels of cytokines secreted by M2 macrophages were higher in the high-risk subgroup. Finally, the prognostic genes were significantly associated with the level of immune cell infiltration.

Conclusion

Herein, a nomogram based on CAF features was developed to predict the CSS rate of LARC patients. The risk model was capable of reflecting differences in the level of immune cell infiltration.

Development and validation of a multi-modal ultrasomics model to predict response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer

OBJECTIVES

To assess the performance of multi-modal ultrasomics model to predict efficacy to neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC) and compare with the clinical model.

MATERIALS AND METHODS

This study retrospectively included 106 patients with LARC who underwent total mesorectal excision after nCRT between April 2018 and April 2023 at our hospital, randomly divided into a training set of 74 and a validation set of 32 in a 7: 3 ratios. Ultrasomics features were extracted from the tumors' region of interest of B-mode ultrasound (BUS) and contrast-enhanced ultrasound (CEUS) images based on PyRadiomics. Mann-Whitney U test, spearman, and least absolute shrinkage and selection operator algorithms were utilized to reduce features dimension. Five models were built with ultrasomics and clinical analysis using multilayer perceptron neural network classifier based on python. Including BUS, CEUS, Combined_1, Combined_2 and Clinical models. The diagnostic performance of models was assessed with the area under the curve (AUC) of the receiver operating characteristic. The DeLong testing algorithm was utilized to compare the models' overall performance.

RESULTS

The AUC (95% confidence interval [CI]) of the five models in the validation cohort were as follows: BUS 0.675 (95%CI: 0.481-0.868), CEUS 0.821 (95%CI: 0.660-0.983), Combined_1 0.829 (95%CI: 0.673-0.985), Combined_2 0.893 (95%CI: 0.780-1.000), and Clinical 0.690 (95%CI: 0.509-0.872). The Combined_2 model was the best in the overall prediction performance, showed significantly better compared to the Clinical model after DeLong testing (P < 0.01). Both univariate and multivariate logistic regression analyses showed that age (P < 0.01) and clinical stage (P < 0.01) could be an independent predictor of efficacy after nCRT in patients with LARC.

CONCLUSION

The ultrasomics model had better diagnostic performance to predict efficacy to nCRT in patients with LARC than the Clinical model.

Predictive effect of the systemic inflammation response index (SIRI) on the efficacy and prognosis of neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer

BACKGROUND

Inflammation is a part of tumours, and inflammatory cells can affect the proliferation, invasion, and development of tumour cells. An increasing number of peripheral blood inflammatory markers have been found to play very important roles in the treatment and prognosis of cancer patients. The systemic inflammatory response index (SIRI) is a newer inflammatory marker, and its role in colorectal cancer, especially in locally advanced rectal cancer, is still unclear.

METHODS

From 2015 to 2020, 198 patients with locally advanced rectal cancer (LARC) who underwent surgery following neoadjuvant chemoradiotherapy (Neo-CRT) were analysed. Patients were categorized into good- and poor- response groups according to their pathological results, and clinical characteristics and baseline parameters were compared between the two groups. The optimal cutoff values for inflammatory indicators were determined using receiver operating characteristic (ROC) analysis. Univariate and multivariate analyses were performed using the Cox proportional hazard model. Survival analysis was performed via the Kaplan‒Meier method.

RESULTS

After patients were grouped into good and poor response groups, indicator differences were found in CEA, neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and SIRI. According to the ROC analysis, the NLR (P = 0.015), SII (P = 0.001), and SIRI (P = 0.029) were significant prognostic factors. After univariate and multivariate analyses of the Cox proportional hazards regression model, only the SIRI was found to be an independent prognostic factor for overall survival (OS) and disease-free survival (DFS). Finally, Kaplan‒Meier survival curves also confirmed the ability of the SIRI to predict survival.

CONCLUSION

The preoperative SIRI can be used to predict the response to Neo-CRT in LARC patients and is an independent predictor of OS and DFS in postoperative patients. A high SIRI was associated with poor radiotherapy response and predicted poor OS and DFS.

Construction and validation of a progression prediction model for locally advanced rectal cancer patients received neoadjuvant chemoradiotherapy followed by total mesorectal excision based on machine learning

Background

We attempted to develop a progression prediction model for local advanced rectal cancer(LARC) patients who received preoperative neoadjuvant chemoradiotherapy(NCRT) and operative treatment to identify high-risk patients in advance.

Methods

Data from 272 LARC patients who received NCRT and total mesorectal excision(TME) from 2011 to 2018 at the Fourth Hospital of Hebei Medical University were collected. Data from 161 patients with rectal cancer (each sample with one target variable (progression) and 145 characteristic variables) were included. One Hot Encoding was applied to numerically represent some characteristics. The K-Nearest Neighbor (KNN) filling method was used to determine the missing values, and SmoteTomek comprehensive sampling was used to solve the data imbalance. Eventually, data from 135 patients with 45 characteristic clinical variables were obtained. Random forest, decision tree, support vector machine (SVM), and XGBoost were used to predict whether patients with rectal cancer will exhibit progression. LASSO regression was used to further filter the variables and narrow down the list of variables using a Venn diagram. Eventually, the prediction model was constructed by multivariate logistic regression, and the performance of the model was confirmed in the validation set.

Results

Eventually, data from 135 patients including 45 clinical characteristic variables were included in the study. Data were randomly divided in an 8:2 ratio into a data set and a validation set, respectively. Area Under Curve (AUC) values of 0.72 for the decision tree, 0.97 for the random forest, 0.89 for SVM, and 0.94 for XGBoost were obtained from the data set. Similar results were obtained from the validation set. Twenty-three variables were obtained from LASSO regression, and eight variables were obtained by considering the intersection of the variables obtained using the previous four machine learning methods. Furthermore, a multivariate logistic regression model was constructed using the data set; the ROC indicated its good performance. The ROC curve also verified the good predictive performance in the validation set.

Conclusions

We constructed a logistic regression model with good predictive performance, which allowed us to accurately predict whether patients who received NCRT and TME will exhibit disease progression.

Prognostic Value of Tumor Volume, Tumor Volume Reduction Rate and Magnetic Resonance Tumor Regression Grade in Rectal Cancer

Background and Objectives: Rectal cancer poses significant treatment challenges, especially in advanced stages. Radiologic assessment, particularly with MRI, is critical for surgeons and oncologists to understand tumor dynamics and tailor treatment strategies to improve patient outcomes. The purpose of this study was to correlate MRI-based tumor volumetric and tumor regression grade analysis in patients with advanced rectal cancer, assessing the impact of preoperative chemotherapy (CT) alone or chemoradiotherapy (CRT) on surgical technique choices. Materials and Methods: Between 2015 and 2022, a prospective study was enrolled, including a cohort of 89 patients diagnosed with rectal cancer at stage II or III. The participants were divided into two distinct therapy groups, ensuring an equal distribution with a ratio of 1:1. The initial group was treated with the contemporary preoperative chemotherapy protocol FOLFOX4. In contrast, the alternative group received conventional preoperative chemoradiotherapy. Before surgery, each patient underwent a rectal MRI scan at 1.5 T, including T2-weighted and diffusion-weighted imaging (DWI) sequences. Results: The CT group showed a 36.52% tumor volume reduction rate (TVRR), and the CRT group showed 54.87%, with varying magnetic resonance and pathological tumor regression grades (mrTRG and pTRG). Analysis revealed a significant interaction between mrTRG and tumor volumetrics (volume and VRR) in both groups, especially CRT, underscoring the complexity of tumor response. Both treatment groups had similar initial tumor volumes, with CRT displaying a higher TVRR, particularly in higher pathological TRG (3/4) cases. This interaction and the strong correlation between mrTRG and pTRG suggest mrTRG's role as a non-invasive predictor for treatment response, highlighting the need for personalized treatment plans. Conclusions: Rectal tumor volume, volume reduction rate, and mrTRG are not just abstract measures; they are concrete indicators that have a direct and practical impact on surgical decision-making, planning, and prognosis, ultimately influencing the quality of care and life expectancy of patients with rectal cancer.

An MRI-based scoring system for pretreatment risk stratification in locally advanced rectal cancer

BACKGROUND

Accurately assessing the risk of recurrence in patients with locally advanced rectal cancer (LARC) before treatment is important for the development of treatment strategies. The purpose of this study is to develop an MRI-based scoring system to predict the risk of recurrence in patients with LARC.

METHODS

This was a multicenter observational study that enrolled participants who underwent neoadjuvant chemoradiotherapy. To evaluate the risk of recurrence in these patients, we developed the mrDEC scoring system and assessed inter-reader agreement. Additionally, we plotted Kaplan-Meier curves to compare the 3-year disease-free survival (DFS) and 5-year overall survival (OS) rates among patients with different mrDEC scores.

RESULTS

A total of 1287 patients with LARC were included in this study. We observed substantial inter-reader agreement for mrDEC. Based on the mrDEC scores ranging from 0 to 3, the patients were categorized into four groups. The 3-year DFS rates for the groups were 91.0%, 79.5%, 65.5%, and 44.0% (P < 0.0001), respectively, and the 5-year OS rates were 92.9%, 87.1%, 74.8%, and 44.5%, respectively (P < 0.0001).

CONCLUSIONS

The mrDEC scoring system proved to be an effective tool for predicting the prognosis of patients with LARC and can assist clinicians in clinical decision-making.

Does neoadjuvant rectal score predict treatment outcomes better than the all grading systems used in neoadjuvantly treated rectal cancer?

BACKGROUND

/Objective: To compare the prognostic value of the yield pathologic (yp) stage, used 4 tumor regression grading (TRG) systems, and neoadjuvant rectal score(NARS) in patients with locally advanced rectal cancer (LARC) who received long-term neoadjuvant chemoradiotherapy (nCRT).

METHODS

Between 2005 and 2017, we included 302 patients with LARC who treated with nCRT. Postoperative pathological responses were graded by using Dworak, American Joint Committee on Cancer, Mandart, Memorial Sloan Kettering Cancer Center, grading systems and NARS([5ypN-3(kT-pT)+12]2/9,61) calculations. Their results were compared in terms of treatment outcomes.

RESULTS

The median follow-up time was 51 months (range 5-136). There was a significant relation between cT stage and the response in used grading systems(p < 0,001). Median overall(OS), local recurrence free(LRFS), and distant metastasis free(MFS) survival rates were 50, 48, and 45 months, respectively. 5-year OS, LRFS, and MFS rates were 71%, 92%, and 72%, respectively. According to the NARS and treatment response grating systems, a significant difference was found between the low risk and high risk groups in terms of OS, LRFS, and MFS rates. While it was not seen any difference in terms of OS and MFS, NARS was found to predict LRFS better than other grading systems. In multivariate analysis, high NARS was found to be correlated with worse OS and worse MFS. On the other hand, pCR was the another important factor affecting treatment outcomes.

CONCLUSIONS

While used systems except NARS group patients according to ypT status in surgical tissue, NARS add the value of ypN status in addition to ypT status. It could be suggested to use NARS to predict LRFS.

Validated Pretreatment Prediction Models for Response to Neoadjuvant Therapy in Patients with Rectal Cancer: A Systematic Review and Critical Appraisal

Pretreatment response prediction is crucial to select those patients with rectal cancer who will benefit from organ preservation strategies following (intensified) neoadjuvant therapy and to avoid unnecessary toxicity in those who will not. The combination of individual predictors in multivariable prediction models might improve predictive accuracy. The aim of this systematic review was to summarize and critically appraise validated pretreatment prediction models (other than radiomics-based models or image-based deep learning models) for response to neoadjuvant therapy in patients with rectal cancer and provide evidence-based recommendations for future research. MEDLINE via Ovid, Embase.com, and Scopus were searched for eligible studies published up to November 2022. A total of 5006 studies were screened and 16 were included for data extraction and risk of bias assessment using Prediction model Risk Of Bias Assessment Tool (PROBAST). All selected models were unique and grouped into five predictor categories: clinical, combined, genetics, metabolites, and pathology. Studies generally included patients with intermediate or advanced tumor stages who were treated with neoadjuvant chemoradiotherapy. Evaluated outcomes were pathological complete response and pathological tumor response. All studies were considered to have a high risk of bias and none of the models were externally validated in an independent study. Discriminative performances, estimated with the area under the curve (AUC), ranged per predictor category from 0.60 to 0.70 (clinical), 0.78 to 0.81 (combined), 0.66 to 0.91 (genetics), 0.54 to 0.80 (metabolites), and 0.71 to 0.91 (pathology). Model calibration outcomes were reported in five studies. Two collagen feature-based models showed the best predictive performance (AUCs 0.83-0.91 and good calibration). In conclusion, some pretreatment models for response prediction in rectal cancer show encouraging predictive potential but, given the high risk of bias in these studies, their value should be evaluated in future, well-designed studies.

The Effect of Induction Chemotherapy with VEGF Inhibition on Tumor Response in Synchronously Metastasized Potentially Resectable Colorectal Cancer

(1) Background: The pathological tumor response of the primary tumor to induction chemotherapy in synchronously metastasized colorectal cancer (mCRC) patients has not been investigated. The aim of this study was to compare patients treated with induction chemotherapy combined with vascular endothelial growth factor (VEGF) or with epidermal growth factor receptor (EGFR) antibodies. (2) Methods: We present a retrospective analysis, where we included 60 consecutive patients with potentially resectable synchronous mCRC who received induction chemotherapy combined with either VEGF or EGFR antibodies. The primary endpoint of this study was the regression of the primary tumor, which was assessed by the application of the histological regression score according to Rödel. The secondary endpoints were recurrence-free survival (RFS) and overall survival (OS). (3) Results: A significantly better pathological response and a longer RFS for patients treated with the VEGF antibody therapy compared to those treated with the EGFR antibodies was demonstrated (p = 0.005 for the primary tumor and log-rank = 0.047 for RFS). The overall survival did not differ. The trial was registered with clinicaltrial.gov, number NCT05172635. (4) Conclusion: Induction chemotherapy combined with a VEGF antibody revealed a better pathological response of the primary tumor, leading to a better RFS compared to that with EGFR therapy; this has clinical relevance in patients with potentially resectable synchronously mCRC.

Forecasting Individual Patients' Best Time for Surgery in Colon-Rectal Cancer by Tumor Regression during and after Neoadjuvant Radiochemotherapy

The standard treatment of locally advanced rectal cancer is neoadjuvant chemoradiotherapy before surgery. For those patients experiencing a complete clinical response after the treatment, a watch-and-wait strategy with close monitoring may be practicable. In this respect, the identification of biomarkers of the response to therapy is extremely important. Many mathematical models have been developed or used to describe tumor growth, such as Gompertz's Law and the Logistic Law. Here we show that the parameters of those macroscopic growth laws, obtained by fitting the tumor evolution during and immediately after therapy, are a useful tool for evaluating the best time for surgery in this type of cancer. A limited number of experimental observations of the tumor volume regression, during and after the neoadjuvant doses, permits a reliable evaluation of a specific patient response (partial or complete recovery) for a later time, and one can evaluate a modification of the scheduled treatment, following a watch-and-wait approach or an early or late surgery. Neoadjuvant chemoradiotherapy effects can be quantitatively described by applying Gompertz's Law and the Logistic Law to estimate tumor growth by monitoring patients at regular intervals. We show a quantitative difference in macroscopic parameters between partial and complete response patients, reliable for estimating the treatment effects and best time for surgery.

Comparison of the predictive value of pathological response at primary tumor and lymph node status after neoadjuvant chemotherapy in locally advanced gastric cancer

BACKGROUND

Preoperative chemotherapy has been increasingly used in locally advanced gastric cancer (LAGC). However, the prognostic factors are still insufficient. This study aimed to investigate the prognostic significance of pathological response of the primary tumor to neoadjuvant chemotherapy (NACT) and the lymph node status after NACT.

METHODS

Data from 160 patients with LAGC treated with NACT followed by gastrectomy and met the inclusion criteria between March 2016 and December 2019 were retrospectively reviewed. Pathological evaluation after NACT was based on the grade of pathological response of the primary tumor and the status of lymph node. Survival curves for overall survival (OS) and disease-free survival (DFS) were estimated using the Kaplan-Meier method, and the log-rank test was used to compare survival difference. Univariate and multivariate analyses for prognostic factors were based on the Cox regression.

RESULTS

Among 160 selected cases, 90 had pathological response (PR), while 70 had no pathological response (nPR) to NACT. Smaller tumor size was presented in PR group, which also had lower level of signet ring cell features, compared to nPR group (all p < 0.05). Based on the status of lymph nodes, nodal status (-) group showed smaller tumor size, lower depth of tumor invasion, better differentiated degree, lower level of signet ring cell features, lower rate of lymphatic and venous invasion and less advanced ypTNM stage (all p < 0.05). Survival was equivalent between PR and nPR group (all p > 0.05), while patients with no lymph node metastasis had better DFS than that with lymph node metastasis (HR 0.301, 95% CI 0.194-0.468, p = 0.002). Multivariable Cox regression analysis identified that lymph node status after NACT was an independent prognostic factor associated with survival (OS: hazard ratio 1.756, 95% CI 1.114-3.278, p = 0.029; DFS: hazard ratio 1.901, 95% CI 1.331-3.093, p = 0.012).

CONCLUSION

Lymph node status is a potential independent prognostic factor for LAGC patients treated with NACT and may be more efficient than pathological response in primary tumor.

GLUT-1 may predict metastases and death in patients with locally advanced rectal cancer

Introduction

Glucose transporter-1 (GLUT-1) has been studied as a possible predictor for survival outcomes in locally advanced rectal cancer (LARC).

Methods

We aimed to investigate the prognostic role of GLUT-1 in LARC using the data of 208 patients with clinical T3-4 stage and/or node-positive rectal adenocarcinoma, all of whom underwent neoadjuvant chemoradiotherapy (CRT) and subsequent total mesorectal excision (TME). Both pre-CRT and post-CRT specimens were immunohistologically stained for GLUT-1. Patients were classified into GLUT-1-positive and GLUT-1-negative groups and distant metastasis-free survival (DMFS) and overall survival (OS) was analyzed and compared.

Results

At a median follow-up of 74 months, post-CRT GLUT-1 status showed a significant correlation with worse DMFS (p=0.027, HR 2.26) and OS (p=0.030, HR 2.30). When patients were classified into 4 groups according to yp stage II/III status and post-CRT GLUT-1 positivity [yp stage II & GLUT-1 (-), yp stage II & GLUT-1 (+), yp stage III & GLUT-1 (-), yp stage III & GLUT-1 (+)], the 5-year DMFS rates were 92.3%, 63.9%, 65.4%, and 46.5%, respectively (p=0.013). GLUT-1 (-) groups showed markedly better outcomes for both yp stage II and III patients compared to GLUT-1 (+) groups. A similar tendency was observed for OS.

Discussion

In conclusion, post-CRT GLUT-1 may serve as a prognostic marker in LARC.

A nomogram prediction model for lymph node metastasis risk after neoadjuvant chemoradiotherapy in rectal cancer patients based on SEER database

Background

Rectal cancer patients who received neoadjuvant chemoradiotherapy (CRT) may have a lower cancer stage and a better prognosis. Some patients may be able to avoid invasive surgery. It is critical to accurately assess lymph node metastases (LNM) after neoadjuvant chemoradiotherapy. The goal of this study is to identify clinical variables associated with LNM and to develop a nomogram for LNM prediction in rectal cancer patients following nCRT.

Methods

From 2010 to 2015, patients were drawn from the Surveillance, Epidemiology, and End Results (SEER) database. To identify clinical factors associated with LNM, the least absolute shrinkage and selection operator (LASSO) aggression and multivariate logistic regression analyses were used. To predict the likelihood of LNM, a nomogram based on multivariate logistic regression was created using decision curve analyses.

Reslut

The total number of patients included in this study was 6,388. The proportion of patients with pCR was 17.50% (n=1118), and the proportion of patients with primary tumor pCR was 20.84% (n = 1,331). The primary tumor was pCR in 16.00% (n=213) of the patients. Age, clinical T stage, clinical N stage, and histology were found to be significant independent clinical predictors of LNM using LASSO and multivariate logistic regression analysis. The nomogram was developed based on four clinical factors. The 5-year overall survival rate was 78.9 percent for those with ypN- and 66.3 percent for those with ypN+, respectively (P<0.001).

Conclusion

Patients over 60 years old, with clinical T1-2, clinical N0, and adenocarcinoma may be more likely to achieve ypN0. The watch-and-wait (WW) strategy may be considered. Patients who had ypN0 or pCR had a better prognosis.

Machine Learning of Histomorphological Features Predict Response to Neoadjuvant Therapy in Locally Advanced Rectal Cancer

AIM

We hypothesize that machine learning of histomorphological features can predict response to neoadjuvant therapy (NAT) in locally advanced rectal cancer (LARC).

METHOD

This retrospective study included 146 LARC patients who received NAT followed by surgery. The pathologists scanned the H&E slides of pretreatment tumor biopsy into whole slide images (WSIs). We randomly split patients into the primary and validation sets with a ratio of 80%:20%. We cut the WSIs into smaller parts (sample amount: 200-500) and used a convolutional neural network (CNN) to process these blocks directly. Then, a graph neural network (GNN) was applied to train the model in the primary set. The independent validation set was used to assess the performance of the model.

RESULT

Our model could provide indicative information to identify the patients who were most likely to benefit from NAT. When the sample amount reached 500, the tile-level classifier for distinguishing poor response from good response produced an AUC of 0.779 in the primary set and 0.733 in the validation set.

CONCLUSION

In this pilot study, we propose a novel predictive model of therapeutic response to NAT in LARC using a routine diagnostic tool employed in daily practice.

Rectal tumor fragmentation as a response pattern following chemoradiation

Background

Tumor response to neoadjuvant therapy is heterogenous and prognostically important for locally advanced rectal adenocarcinoma (LARC) patients. Commonly applied response classification approaches including tumor regression grading (TRG) and TN downstaging can be discordant. The aim of this study is to compare the prognostic value of discordant tumor response measurement categorized according to the AJCC/CAP TRG schema and ypTN stage.

Methods

This is a single-center retrospective review of 90 consecutive patients with stage II-III rectal cancer receiving neoadjuvant chemoradiation (nCRT), total mesorectal excision (TME) and adjuvant chemotherapy (ACT) between 2007 and 2018. Two pathologists re-examined each case to assign a consensus AJCC TRG. A Cox proportional hazards ratio model assessed the effect of patient, tumor, and treatment factors on disease-free survival (DFS).

Results

Median follow-up after surgery was 46 months (95% CI: 41-50 months). Median age at diagnosis was 55 years (range: 27-80). Most patients were male (58%) and Caucasian (92%) with clinical stage III disease (68%). Seventy-three patients (81%) underwent low anterior resection (LAR), 17 (19%) underwent abdominoperineal resection (APR). The median interval from completion of nCRT to surgery was 62 days (IQR: 56-70 days). The 4-year OS, DFS, and LC was 92.4%, 74.4%, and 90.2%, respectively. In the multivariate analysis, ypTN downstaging was not prognostically significant; however, AJCC TRG score 3 (minimal tumor response to treatment) was strongly predictive for inferior DFS (3-year DFS 79% vs. 25%, P<0.001). Patients with TRG 3 had a significantly higher risk of both local (75% vs. 5%) and distant failure (75% vs. 19%).

Conclusions

Minimal tumor response to neoadjuvant therapy, AJCC TRG 3, irrespective of ypTN downstaging, is a pattern of residual disease that is at highest risk for recurrence. Response categorization discrepancies may be partly explained by alternative patterns of residual disease, including tumor fragmentation, and may be best reflected by TRG. The optimal tumor response categorization method requires further study to best stratify patient risk and management.

ACY1 Downregulation Enhances the Radiosensitivity of Cetuximab-Resistant Colorectal Cancer by Inactivating the Wnt/β-Catenin Signaling Pathway

Treatment of cetuximab-resistant colorectal cancer (CRC) is a global healthcare problem. This study aimed to assess the effects of radiotherapy on cetuximab-resistant CRC and explore the underlying mechanism. We established a cetuximab-resistant HCT116 cell line (HCT116-R) by extracorporeal shock. Differentially expressed mRNAs were screened from cells treated with different radiation doses using second-generation high-throughput sequencing. Sequence data showed that ACY1 was significantly downregulated in HCT116-R cells after irradiation. Analysis of the GEO and TCGA datasets revealed that high ACY1 expression was associated with lymph node metastasis and a poor prognosis in CRC patients. In addition, immunohistochemistry results from CRC patients revealed that ACY1 protein expression was related to cetuximab resistance and lymph node metastasis. These findings suggested that ACY1 may function as an oncogene to promote CRC progression and regulate the radiosensitivity of cetuximab-resistant CRC. As expected, ACY1 silencing weakened the proliferation, migration, and invasion abilities of HCT116-R cells after radiotherapy. Mechanistically, TCGA data demonstrated that ACY1 expression was closely related to the Wnt/β-catenin pathway in CRC. We validated that radiotherapy first reduced β-catenin levels, followed by decreased expression of the metastasis-related protein E-cadherin. Silencing ACY1 dramatically enhanced these changes in β-catenin and E-cadherin after radiotherapy. In conclusion, ACY1 downregulation could enhance the radiosensitivity of cetuximab-resistant CRC by inactivating Wnt/β-catenin signaling, implying that ACY1 may serve as a radiotherapy target for cetuximab-resistant CRC.

Extramural venous invasion (EMVI) revisited: a detailed analysis of various characteristics of EMVI and their role as a predictive imaging biomarker in the neoadjuvant treatment response in rectal cancer

PURPOSE

To assess whether size, diameter, and large vein involvement of MR-detected extramural venous invasion (MR-EMVI) have an impact on neoadjuvant therapy response in rectal adenocarcinoma.

METHODS

57 patients with locally advanced rectal adenocarcinoma scanned with MRI before and after neoadjuvant therapy were included. Two abdominal radiologists evaluated the images with special emphasis on EMVI, on initial staging and after neoadjuvant treatment. The sensitivity and specificity of MRI for detection of rest EMVI were determined. The association of various MR-EMVI characteristics including number, size, and main vein involvement with treatment response was investigated. In subjects with discordance of radiology and pathology, elastin stain was performed, and images and slides were re-evaluated on site with a multidisciplinary approach.

RESULTS

At initial evaluation, 17 patients were MR-EMVI negative (29.8%) and 40 were MR-EMVI positive (70.2%). Complete/near-complete responders had less number (mean 1.45) and smaller diameter of MR-EMVI (mean 1.8 mm), when compared with partial responders (2.54 and 3.3 mm; p < 0.005). The sensitivity of MRI for rest EMVI detection was high, specificity was moderate, and in one patient elastin stain changed the final decision. In five patients with rest MR-EMVI positivity, carcinoma histopathologically had a distinctive serpiginous perivascular spread, growing along the track of vascular bundle, although it did not appear in intravascular spaces.

CONCLUSION

This study demonstrates that not only the presence, but also size and number of EMVI that may be significant clinically and thus these parameters also ought to be incorporated to the MRI evaluation and prognostication of treatment response. From pathology perspective, tumors growing alongside major vessels may also reflect EMVI even if they are not demonstrably "intravascular."

Predicting stage ypT0–1N0 for nonradical management in patients with middle or low rectal cancer who undergo neoadjuvant chemoradiotherapy: a retrospective cohort study

Purpose

It is important to discover predictive factors that can identify rectal cancer patients who will respond well to neoadjuvant concurrent chemoradiotherapy (CCRT) to develop management strategies, preserve sphincter and avoid over-treatment. This study explored clinical factors that would predict the adequacy of nonradical management after CCRT in patients with middle or low rectal cancer.

Methods

We retrospectively evaluated 447 patients with middle or low rectal cancer who were treated with curative surgery after neoadjuvant CCRT between January 2010 and December 2019. The good response group comprised patients with stages ypT0–1N0 on resection after CCRT; the remaining patients were included in the poor response group.

Results

Of 447 patients (mean age, 60.37 ± 11.85 years), 108 (24.2%) had ypT0–1N0 (71.3% with ypT0N0, 4.6% with ypTisN0, and 24.1% with ypT1N0). Overall, 19 patients with cT1–2 (50.0% vs. 21.8% with cT3–4, P < 0.001), 22 with well-differentiated tumors (51.2% vs. 21.3% with moderately/poorly differentiated tumors, P < 0.001), 16 with fungating tumors (47.1% vs. 22.3% with other types, P = 0.001), and 66 with anterior/posterior circumference direction (28.9% vs. 19.2% with lateral/encircling direction, P = 0.016) had stage ypT0–1N0. On multivariable analysis, cT1–2 (P = 0.021) and well-differentiated tumor (P = 0.001) were independent predictors of ypT0–1N0. Fungating tumors were not significantly associated with ypT0–1N0 (P = 0.054).

Conclusion

Stage cT1–2 and well differentiation are predictors of ypT0–1N0, while fungating tumors could be considered clinically meaningful, possibly identifying candidates for nonradical treatment post-CCRT.

Factors Predicting Pathological Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer: The Experience of a Single Institution with 269 Patients (STONE-01)

Simple Summary

Neoadjuvant chemoradiotherapy (CRT) followed by total mesorectal excision is currently the standard of care for locally advanced rectal cancer (LARC). This retrospective cohort study evaluated the pathological response after CRT in relation to treatment factors and patient and disease factors in order to find useful indicators to further improve the efficacy of CRT and create tailored therapeutic approaches. To date, the optimal timing for surgery after CRT has not been established. In literature, there are controversial results regarding the risk of higher surgical morbidity and perioperative complications due to delayed surgery. In our study carried out on 269 consecutive LARC patients, among the items analyzed, an interval time from CRT to surgery of >8 weeks was the only independent significant factor for pCR and downstaging.

Abstract

Aims: The aim of this study was to define a potential benefit of pathological complete response rate (pCR) and downstaging rate after neoadjuvant chemoradiotherapy (CRT) in relation to treatment and patient factors in locally advanced rectal cancer. Methods: We performed a retrospective cohort study. Patients were divided according to chemotherapy regimens concurrent to radiotherapy (1-drug vs. 2-drug) and according to the time interval between the end of CRT and surgery (≤8 weeks vs. >8 weeks), as well as in relation to specific relevant clinical factors. Logistic regression was used to estimate the independent factors for pCR and downstaging. Results: 269 patients were eligible for this study. Overall, pCR and downstaging rates were 26% and 75.4%, respectively. Univariate analysis showed that female gender (p = 0.01) and time to surgery >8 weeks (p = 0.04) were associated with pCR; age > 70 years (p = 0.05) and time to surgery >8 weeks (p = 0.002) were correlated to downstaging. At multivariate analysis, interval time to surgery of >8 weeks was the only independent factor for both pCR and downstaging (p = 0.02; OR: 0.5, CI: 0.27–0.93 and p = 0.003; OR: 0.42, CI: 0.24–0.75, respectively). Conclusions: This study indicates that, in our population, an interval time to surgery of >8 weeks is an independent significant factor for pCR and downstaging. Further prospective studies are needed to define the best interval time.

Survival landscape of different tumor regression grades and pathologic complete response in rectal cancer after neoadjuvant therapy based on reconstructed individual patient data

BACKGROUND

Neoadjuvant therapy can lead to different tumor regression grades (TRG) in rectal cancer after neoadjuvant therapy. The purposes of this study are to investigate the relationships among TRG, pathologic complete response (pCR) and long-term survival, on the basis of reconstructed individual patient data (IPD).

METHODS

The PubMed, Embase, Ovid and Cochrane CENTRAL databases were searched. The primary endpoint was to evaluate the survival landscape of different TRGs after neoadjuvant therapy and the secondary endpoint was to evaluate the associations between pCR and survival. IPD were reconstructed with Kaplan-Meier curves.

RESULTS

The 10-year overall survival (OS) and 5-year disease-free survival (DFS) were clearly higher in the pCR group than in the non-pCR (npCR) group (80.5% vs. 48.3, 90.1% vs. 69.8%). Furthermore, the OS and DFS increased with improvement in tumor regression after neoadjuvant therapy. According to the IPD, the pCR group had longer OS (HR = 0.240, 95% CI = 0.177-0.325, p < 0.001) and DFS (HR = 0.274, 95% CI = 0.205-0.367, p < 0.001) than the npCR group. Better tumor regression was associated with better survival outcomes (p < 0.005). Direct calculation of published HR values yielded similar results.

CONCLUSIONS

Our results indicate a positive relationship between better tumor regressions and improved survival benefits among the npCR group and patients with rectal cancer achieving pCR had much longer OS and DFS than patients achieving npCR, presenting a survival landscape of different TRGs and pCR in rectal cancer after neoadjuvant therapy.

Current evidence regarding the role of adjuvant chemotherapy in rectal cancer patients with pathologic complete response after neoadjuvant chemoradiotherapy: a systematic review and meta-analysis

PURPOSE

The aim of this meta-analysis was to investigate the role of adjuvant chemotherapy (AC) in rectal cancer patients with pathologic complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) and curative resection.

METHODS

This study was completed in accordance to the PRISMA guidelines and the Cochrane Handbook for Systematic Reviews of Interventions. The electronic scholar databases (Medline, Web of Science, Scopus) were screened for eligible articles. The level of evidence (LoE) was assessed using the GRADE methodology.

RESULTS

Overall, 23 non-randomized studies and 17,406 patients were included in the present meta-analysis. Pooled comparisons confirmed that AC improved overall survival (HR: 0.68, p=0.0003), but not disease-free (p=0.22) and recurrence-free survival (p=0.39). However, the LoE for all outcomes was characterized as "very low," due to the absence of RCTs.

CONCLUSIONS

Considering the study limitations and the lack of randomized studies, further high-quality RCTs are required to confirm the findings of our study.

Prognostic Impact of the Neoadjuvant Rectal Score as Compared With the Tumor Regression Grade and Yield Pathologic TNM Stage in Patients With Locally Advanced Rectal Cancer After Neoadjuvant Chemoradiotherapy

BACKGROUND/AIM

The present study compared the prognostic value of the yield pathologic (yp) stage, tumor regression grade (TRG), and neoadjuvant rectal (NAR) score in patients with locally advanced rectal cancer (LARC) who received neoadjuvant chemoradiotherapy (nCRT).

PATIENTS AND METHODS

For the assessment of tumor regression, the Dworak grading system was used. The NAR score was calculated using the following equation: (5ypN-3[cT-ypT]+12)²÷9.61.

RESULTS

In univariate analysis, the NAR score and ypTNM stage were significantly associated with DFS [hazard ratio (HR)=2.514, p<0.001 and HR=3.200, p<0.001] and OS (HR=2.292, p=0.001 and HR=2.859, p<0.001), whereas the TRG was significantly associated with only DFS (HR=2.008, p=0.017). In multivariate analysis, the ypTNM stage was the only independent prognostic factor for DFS (HR=3.796, p<0.001) and OS (HR=3.591, p=0.0034).

CONCLUSION

Only the ypTNM stage was significantly associated with survival outcomes in multivariate analysis, suggesting that it is the most powerful prognostic factor of nCRT in patients with LARC.

Image-based deep learning model for predicting pathological response in rectal cancer using post-chemoradiotherapy magnetic resonance imaging

INTRODUCTION

To develop an image-based deep learning model for predicting pathological response in rectal cancer using post-chemoradiotherapy magnetic resonance (MR) imaging.

MATERIALS AND METHODS

A total of 466 patients with locally advanced rectal cancer who received preoperative chemoradiotherapy followed by surgical resection were collected from single center, among whom 113 (24.3%) were allocated to the holdout testing set. Complete response (pCR) was defined as Dworak tumor regression grade (TRG) 4, while good response (GR) was defined as TRG 3 or 4. Based on post-chemoradiotherapy T2-weighted axial MR images, two deep learning models were developed to predict pCR and GR, respectively. The prediction performance of the deep learning models was evaluated in the testing set and was compared to that of a senior radiologist and a radiation oncologist.

RESULTS

The deep learning model showed an area under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 0.76, 0.30, 0.96, 0.67, 0.87, and 85.0% for predicting pCR and 0.72, 0.54, 0.81, 0.60, 0.77, and 71.7% for predicting GR, respectively. The deep learning model had a superior predictive performance than the observers. Fair agreement between the ground truth and the model was shown for pCR prediction (kappa = 0.34) and GR prediction (kappa = 0.36).

CONCLUSIONS

The post-chemoradiotherapy T2-weighted axial MR image-based deep learning model showed acceptable performance in predicting pCR or GR in patients with rectal cancer, compared with human observers.

Pathological response post neoadjuvant therapy for locally advanced rectal cancer is an independent predictor of survival

AIM

Neoadjuvant treatment (NaT) for locally advanced rectal cancer prior to surgery has led to improved outcomes. However, the relationship between pathological response to NaT and survival is not entirely clear. The aim of this study was to assess the degree of pathological response to NaT on survival outcomes.

METHODS

Clinical and pathological data were collected from a prospectively maintained pathology database between 2005 and 2017. The primary outcome was the overall survival based on pathological response categorized as complete, good partial, partial and minimal. Univariate and multivariate analyses were conducted to identify variables predictive of survival. Cox proportional hazard ratios were used for survival.

RESULTS

A total of 596 patients had surgery following NaT for locally advanced rectal cancer. The median follow-up was 4.57 years (interquartile range 2.21-8.15 years). The overall survival for complete pathological response was 75.6% vs. 37.3% for minimal response (P < 0.001). The overall survival at the end of the study in the good partial vs. partial response groups was 58.9% vs. 39% (P < 0.001). On multivariate analysis, the degree of pathological response remains an independent variable for overall and disease-specific survival across all categories.

DISCUSSION

In addition to other pathological variables, the degree of pathological response to NaT is an independent predictor for survival outcomes. Future verification of these findings elsewhere could support NaT response being used for adjuvant therapy decision making.

Impact of a ketogenic diet intervention during radiotherapy on body composition: IV. Final results of the KETOCOMP study for rectal cancer patients

BACKGROUND & AIMS

Obesity and low muscle mass are associated with worse outcomes of colorectal cancer patients. We conducted a controlled trial to study the impact of a ketogenic diet (KD) based on natural foods versus an unspecified standard diet (SD) on body composition in rectal cancer patients undergoing radiotherapy.

METHODS

Patients with non-metastasized rectal cancer were allocated to either the KD (N = 24) or the SD (N = 25) group during radiotherapy. Body composition was measured weekly by bioimpedance analysis and analyzed using linear mixed effects models. Pathologic response in patients undergoing neoadjuvant treatment was evaluated at the time of surgery.

RESULTS

A total of 18 KD and 23 SD patients completed the study and were eligible for analysis. The SD group experienced no noteworthy changes in any body composition parameter. In contrast, patients in the KD group lost significant amounts of body weight and fat mass, averaging 0.5 and 0.65 kg/week (p < 0.0001). There was a rapid loss of intracellular water consistent with initial intramuscular glycogen and water depletion, but skeletal muscle tissue was conserved. Pathological tumor responses were somewhat greater in the KD group, with a larger mean Dworak regression grade (p = 0.072) and larger percentage of near-complete (yT0N0 or yT1N1) responses (43 versus 15%, p = 0.116) that almost reached statistical significance in intention-to-treat analysis (50% versus 14%, p = 0.018).

CONCLUSIONS

In rectal cancer patients undergoing curative radiotherapy, a KD significantly reduced body weight and fat mass while preserving skeletal muscle mass. We could demonstrate a trend for KDs contributing synergistically to pathological tumor response, a finding in line with preclinical data that warrants future confirmation in larger studies.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT02516501, registered on August 06, 2015.

Systemic Inflammatory Markers Combined with Tumor-Infiltrating Lymphocyte Density for the Improved Prediction of Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer

BACKGROUND

Previous studies have reported the utility of systemic inflammatory markers and CD8+ tumor-infiltrating lymphocyte (TIL) separately in predicting response to chemoradiotherapy (CRT) in rectal cancer; however, the efficacy of combining these markers remains unclear.

OBJECTIVE

This study aimed to elucidate the predictive efficacy of systemic inflammatory markers combined with CD8+ TIL density on response to neoadjuvant CRT in locally advanced rectal cancer.

METHODS

Ten systemic inflammatory markers and CD8+ TIL density were assessed in 267 patients with rectal cancer using pretreatment clinical data and biopsy samples. Response to CRT was determined using the Dworak tumor regression grade (TRG), with good responders classified as TRG3-4.

RESULTS

Receiver operating characteristic curve analysis showed high areas under the curve for the lymphocyte-to-C-reactive protein ratio (LCR) and neutrophil × monocyte (N × M) value (0.58 and 0.62, respectively). In the multivariate analysis, LCR, N × M value, and CD8+ TIL density were independently associated with good responders (p = 0.016, 0.005, and 0.002, respectively). Stratified analysis with these three markers showed a positive correlation between TRG3-4 ratio and the number of positive predictive factors (8.2%, 20.0%, 34.2%, and 59.1% in patients with 0, 1, 2, and 3 predictors, respectively). Overall and disease-free survival were significantly worse in patients with zero factors present compared with those with one to three factors present.

CONCLUSIONS

LCR, N × M value, and CD8+ TIL density are independently associated with response to CRT. Assessing local TIL density along with systemic inflammatory markers may be useful for selecting a multimodal neoadjuvant approach in rectal cancer therapy.

Contemporary snapshot of tumor regression grade (TRG) distribution in locally advanced rectal cancer: a cross sectional multicentric experience

Pre-operative chemoradiotherapy (CRT) followed by surgical resection is still the standard treatment for locally advanced low rectal cancer. Nowadays new strategies are emerging to treat patients with a complete response to pre-operative treatment, rendering the optimal management still controversial and under debate. The primary aim of this study was to obtain a snapshot of tumor regression grade (TRG) distribution after standard CRT. Second, we aimed to identify a correlation between clinical tumor stage (cT) and TRG, and to define the accuracy of magnetic resonance imaging (MRI) in the restaging setting. Between January 2017 and June 2019, a cross sectional multicentric study was performed in 22 referral centers of colon-rectal surgery including all patients with cT3-4Nx/cTxN1-2 rectal cancer who underwent pre-operative CRT. Shapiro-Wilk test was used for continuous data. Categorical variables were compared with Chi-squared test or Fisher's exact test, where appropriate. Accuracy of restaging MRI in the identification of pathologic complete response (pCR) was determined evaluating the correspondence with the histopathological examination of surgical specimens.In the present study, 689 patients were enrolled. Complete tumor regression rate was 16.9%. The "watch and wait" strategy was applied in 4.3% of TRG4 patients. A clinical correlation between more advanced tumors and moderate to absent tumor regression was found (p = 0.03). Post-neoadjuvant MRI had low sensibility (55%) and high specificity (83%) with accuracy of 82.8% in identifying TRG4 and pCR.Our data provided a contemporary description of the effects of pre-operative CRT on a large pool of locally advanced low rectal cancer patients treated in different colon-rectal surgical centers.

Immunogenic Cell Death by the Novel Topoisomerase I Inhibitor TLC388 Enhances the Therapeutic Efficacy of Radiotherapy

Simple Summary

This study aims to evaluate the induction of immunogenic cell death (ICD) for anticancer immunity by the novel topoisomerase I inhibitor lipotecan. These results show that lipotecan can remarkably elicit ICD and increase tumor immunogenicity, which promotes the therapeutic efficacy of radiotherapy compared to conventional chemoradiotherapy in vivo. These results provide potential therapeutic strategies to improve the efficacy of chemoradiotherapy in colorectal cancer (CRC), which may increase the local control rate and decrease tumor relapse in locally advanced rectal cancer (LARC) patients who receive preoperative chemoradiotherapy.

Abstract

Rectal cancer accounts for 30–40% of colorectal cancer (CRC) and is the most common cancer-related death worldwide. The preoperative neoadjuvant chemoradiotherapy (neoCRT) regimen is the main therapeutic strategy for patients with locally advanced rectal cancer (LARC) to control tumor growth and reduce distant metastasis. However, 30–40% of patients achieve a partial response to neoCRT and suffer from unnecessary drug toxicity side effects and a risk of distant metastasis. In our study, we found that the novel topoisomerase I inhibitor lipotecan (TLC388) can elicit immunogenic cell death (ICD) to release damage-associated molecular patterns (DAMPs), including HMGB1, ANXA1, and CRT exposure. Lipotecan thereby increases cancer immunogenicity and triggers an antitumor immune response to attract immune cell infiltration within the tumor microenvironment (TME) in vitro and in vivo. Taken together, these results show that lipotecan can remodel the tumor microenvironment to provoke anticancer immune responses, which can provide potential clinical benefits to the therapeutic efficacy of neoCRT in LARC patients.

Downregulation of miR-423-5p Contributes to the Radioresistance in Colorectal Cancer Cells

Resistance to radiotherapy is the main reason causing treatment failure in locally advanced rectal cancer. MicroRNAs (miRNAs) have been well demonstrated to regulate cancer development and progression. However, how miRNAs regulate radiotherapy resistance in colorectal cancer remains unknown. Herein, we established two human colorectal cancer cell lines resistant to radiotherapy, named HCT116-R and RKO-R, using the strategy of fractionated irradiation. The radioresistant phenotypical changes of the two cell lines were validated by cell viability assay, colony formation assay and apoptosis assay. The miRNA expression profilings of HCT116-R and RKO-R were determined using RNA-seq analyses, and further confirmed by quantitative real-time PCR. Multiple miRNAs, including miR-423-5p, miR-7-5p, miR-522-3p, miR-3184-3p, and miR-3529-3p, were identified with altered expression in both of the radiotherapy-resistant cells, compared to the parental cells. The downregulation of miR-423-5p was further validated in the rectal cancer tissues from radiotherapy-resistant patients. Silencing of miR-423-5p in parental HCT116 and RKO cells decreased the sensitivity to radiation treatment, and inhibited the radiation-induced apoptosis. In consistence, overexpression of miR-423-5p in HCT116-R and RKO-R cells partially rescued their sensitivity to radiotherapy, and promoted the radiation-induced apoptosis. Bcl-xL (Bcl-2-like protein 1) was predicted to be a potential target gene for miR-423-5p, and miR-423-5p/Bcl-xL axis could be a critical mediator of radiosensitivity in colorectal cancer cells. The current finding not only revealed a novel role of miR-423-5p in regulating the radiosensitivity in colorectal cancer, but also suggested miR-423-5p as a molecular candidate for combination therapy with radiation to treat colorectal cancer.

Clinical predictors of response to chemoradiotherapy for rectal cancer as an aid to organ preservation

AIM

Clinical predictors of pathological response to chemoradiotherapy for rectal cancer can influence patient management including selection for organ preservation. This study aimed to identify clinical predictors at a tertiary referral hospital.

METHODS

A retrospective review of clinical records was undertaken after identifying all patients with stage 1-3 rectal cancer treated with long course chemoradiotherapy and total mesorectal excision from 2013 to 2018. Clinicopathological factors were recorded and multivariate analysis performed to identify predictors of pathological complete response (pCR) and good response (AJCC TRG 0-1).

RESULTS

A total of 470 patients with rectal cancer were identified of which 164 met the inclusion criteria for the study. The pCR rate was 14.6% and good response (TRG 0-1) rate 43.7%. On univariate analysis, lower T stage, older age, node negative status, anterior tumour position and shorter tumour length on magnetic resonance imaging (MRI) were associated with good response (TRG 0-1). On univariate analysis cN stage, carcinoembryonic antigen <5 and shorter tumour length on MRI were associated with pCR. On binary logistic regression shorter length on MRI and lower clinical nodal stage were predictive of pCR and lower body mass index, anterior tumour position and higher haemoglobin were predictive of good response (TRG 0-1).

CONCLUSION

Anterior tumour position is newly identified as an independent predictor of good response (TRG 0-1) to nCRT for rectal cancer and this should be explored in future studies. Higher haemoglobin and lower body mass index were also independent predictors of good response (TRG 0-1) and optimisation of these factors should be considered when using neoadjuvant chemoradiotherapy for rectal cancer.

3.0 T MRI IVIM-DWI for predicting the efficacy of neoadjuvant chemoradiation for locally advanced rectal cancer

Purpose

The purpose of this study was to determine the diagnostic performance of intravoxel incoherent motion (IVIM) on assessing response to neoadjuvant chemoradiation (nCRT) in patients with Locally Advanced Rectal Cancer (LARC).

Methods

50 patients with rectal cancer who underwent magnetic resonance (MR) imaging before and after nCRT, the values of pre-nCRT and post-nCRT IVIM-DWI parameters apparent diffusion coefficient (ADC), diffusion coefficient (D), false diffusion coefficient (D*), and perfusion fraction (f), together with the percentage changes (∆% parametric value) induced by nCRT were calculated. According to the patient's response to nCRT, the patients were divided into pathological complete response (pCR) and non-pCR groups, Good Response (GR) group and Poor Response (PR) group, and the above values were compared between different groups. Univariate and multiple logistic regression analysis were done to investigate the relation between different parameters and patient nCRT. Draw ROC curve according to sensitivity and specificity, and compare its diagnostic efficacy.

Results

There were no significant differences in the baseline data of 50 patients. After nCRT, the ADC and D values for LARC increased significantly (all p < 0.05). The pCR group (n = 9) had higher preD*, pref, postD*, ∆%ADC and ∆%D values than the non-pCR group (n = 41) (all p < 0.05). The GR group (n = 17) exhibited higher post D, ∆%ADC and ∆%D values than the PR group (n = 33) (all p < 0.05). From the results of Logistic regression analysis found that ∆%ADC and ∆%D were significantly correlated with patients' response to nCRT. Based on ROC analysis, ∆%D had a higher area under the curve value than ∆%ADC (p = 0.009) in discriminating the pCR from non-pCR groups.

Conclusions

IVIM-DWI technology may be helpful in identifying the pCR and GR patients to nCRT for LARC.

Nomograms and risk score models for predicting survival in rectal cancer patients with neoadjuvant therapy

BACKGROUND

Colorectal cancer is a common digestive cancer worldwide. As a comprehensive treatment for locally advanced rectal cancer (LARC), neoadjuvant therapy (NT) has been increasingly used as the standard treatment for clinical stage II/III rectal cancer. However, few patients achieve a complete pathological response, and most patients require surgical resection and adjuvant therapy. Therefore, identifying risk factors and developing accurate models to predict the prognosis of LARC patients are of great clinical significance.

AIM

To establish effective prognostic nomograms and risk score prediction models to predict overall survival (OS) and disease-free survival (DFS) for LARC treated with NT.

METHODS

Nomograms and risk factor score prediction models were based on patients who received NT at the Cancer Hospital from 2015 to 2017. The least absolute shrinkage and selection operator regression model were utilized to screen for prognostic risk factors, which were validated by the Cox regression method. Assessment of the performance of the two prediction models was conducted using receiver operating characteristic curves, and that of the two nomograms was conducted by calculating the concordance index (C-index) and calibration curves. The results were validated in a cohort of 65 patients from 2015 to 2017.

RESULTS

Seven features were significantly associated with OS and were included in the OS prediction nomogram and prediction model: Vascular_tumors_bolt, cancer nodules, yN, body mass index, matchmouth distance from the edge, nerve aggression and postoperative carcinoembryonic antigen. The nomogram showed good predictive value for OS, with a C-index of 0.91 (95%CI: 0.85, 0.97) and good calibration. In the validation cohort, the C-index was 0.69 (95%CI: 0.53, 0.84). The risk factor prediction model showed good predictive value. The areas under the curve for 3- and 5-year survival were 0.811 and 0.782. The nomogram for predicting DFS included ypTNM and nerve aggression and showed good calibration and a C-index of 0.77 (95%CI: 0.69, 0.85). In the validation cohort, the C-index was 0.71 (95%CI: 0.61, 0.81). The prediction model for DFS also had good predictive value, with an AUC for 3-year survival of 0.784 and an AUC for 5-year survival of 0.754.

CONCLUSION

We established accurate nomograms and prediction models for predicting OS and DFS in patients with LARC after undergoing NT.

Magnetic resonance imaging tumor response score (mrTRS) predicts therapeutic effect and prognosis of locally advanced rectal cancer after neoadjuvant chemoradiotherapy: A prospective, multi-center study

BACKGROUND AND PURPOSE

The MRI-assessed tumor regression grade (mrTRG) is limited due to its subjectivity and poor consistency on pathological tumor regression grade (pTRG). A new MRI criterion was established to predict the prognosis of locally advanced rectal cancer (LARC).

MATERIALS AND METHODS

The new MRI criterion magnetic resonance imaging tumor response score (mrTRS) was based on the retrospective sample of 214 LARC patients (unpublished data). Subsequently, 878 LARC patients were enrolled for a prospective, multicenter study. Baseline and postoperative MRI were obtained, and imaging features were measured by collecting the pathological, clinical and follow-up data. Kaplan-Meier method with log-rank estimate and multivariate cox regression model was used to determine the prognosis of mrTRS in LARC patients with neoadjuvant chemoradiotherapy (NACRT). The predictive capability of 3-year prognosis between mrTRS and mrTRG was determined by time-dependent ROC curves.

RESULTS

The results demonstrated that mrTRS acted as an independent predictor of survival outcomes. mrTRS stratified by good and moderate responders showed significantly lower risk of death (HR = 0.04, 95%CI 0.01-0.31; HR = 0.35, 95%CI 0.23-0.52), distant metastasis (HR = 0.25, 95%CI 0.13-0.52; HR = 0.42, 95%CI 0.30-0.58), and local recurrence when compared with poor responders(HR = 0.01 95%CI 0.23-0.52;HR = 0.38, 95%CI 0.16-0.90). In contrast, no significant difference was observed among mrTRG stratified groups. Excellent and substantial interobserver agreement for mrTRS and mrTRG evaluation was observed (κ = 0.92 and 0.62), respectively.

CONCLUSION

mrTRS can serve as an effective predictor for assessing tumor regression grade in LARC patients with NACRT.

Evaluation and Comparison of Predictive Value of Tumor Regression Grades according to Mandard and Becker in Locally Advanced Gastric Adenocarcinoma

Purpose

Tumor regression grade (TRG) has been widely used in gastrointestinal carcinoma to assess pathological responses to neoadjuvant chemotherapy (NCT). There are various standards without a consensus, and it is still unclear which kind of system has better predictive value. This study aims to investigate and compare the predictive ability of the Mandard and Becker TRGs in patients with locally advanced gastric cancer.

Materials and Methods

A total of 290 patients with locally advanced gastric adenocarcinoma who underwent NCT and curative surgery were studied. Survival analysis for overall survival (OS) and disease-free survival (DFS) were based on the Kaplan-Meier method and Cox proportional hazards method. Predictive values of TRGs and models were assessed by time-dependent receiver operating characteristic (ROC) curve, the area under the ROC curve (AUC), nomogram, and calibration curve.

Results

In multivariable analysis, the Mandard TRG was associated with OS (hazard ratio [HR], 1.806; p=0.026) and DFS (HR, 1.792; p=0.017). The Becker TRG was also related to OS (HR, 1.880; p=0.014) and DFS (HR, 1.919; p=0.006). The Mandard and Becker TRG AUCs for 5-year survival were 0.72 and 0.71, respectively. The whole models showed an increased predictive value, with AUCs of 0.85 and 0.86, respectively. There was no significant difference between the two TRGs and two models.

Conclusion

TRG was an independent predictor for survival, and there was no significant difference between these two systems.

Multiparametric MRI and Whole Slide Image-Based Pretreatment Prediction of Pathological Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer: A Multicenter Radiopathomic Study

Background

The aim of this work is to combine radiological and pathological information of tumor to develop a signature for pretreatment prediction of discrepancies of pathological response at several centers and restage patients with locally advanced rectal cancer (LARC) for individualized treatment planning.

Patients and Methods

A total of 981 consecutive patients with evaluation of response according to tumor regression grade (TRG) who received nCRT were retrospectively recruited from four hospitals (primary cohort and external validation cohort 1–3); both pretreatment multiparametric MRI (mp-MRI) and whole slide image (WSI) of biopsy specimens were available for each patient. Quantitative image features were extracted from mp-MRI and WSI and used to construct a radiopathomics signature (RPS) powered by an artificial-intelligence model. Models based on mp-MRI or WSI alone were also constructed for comparison.

Results

The RPS showed overall accuracy of 79.66–87.66% in validation cohorts. The areas under the curve of RPS at specific response grades were 0.98 (TRG0), 0.93 (≤ TRG1), and 0.84 (≤ TRG2). RPS at each grade of pathological response revealed significant improvement compared with both signatures constructed without combining multiscale tumor information (P < 0.01). Moreover, RPS showed relevance to distinct probabilities of overall survival and disease-free survival in patients with LARC who underwent nCRT (P < 0.05).

Conclusions

The results of this study suggest that radiopathomics, combining both radiological information of the whole tumor and pathological information of local lesions from biopsy, could potentially predict discrepancies of pathological response prior to nCRT for better treatment planning.

Electronic supplementary material

The online version of this article (10.1245/s10434-020-08659-4) contains supplementary material, which is available to authorized users.

Monitoring of Early Changes of Circulating Tumor DNA in the Plasma of Rectal Cancer Patients Receiving Neoadjuvant Concomitant Chemoradiotherapy: Evaluation for Prognosis and Prediction of Therapeutic Response

Introduction: Patients with locally advanced rectal cancer (LARC) are undergoing neoadjuvant chemoradiotherapy (NCRT) prior to surgery. Although in some patients the NCRT is known to prevent local recurrence, it is also accompanied by side effects. Accordingly, there is an unmet need to identify predictive markers allowing to identify non-responders to avoid its adverse effects. We monitored circulating tumor DNA (ctDNA) as a potential liquid biopsy-based biomarker. We have investigated ctDNA changes plasma during the early days of NCRT and its relationship to the overall therapy outcome.

Methods and Patients: The studied cohort included 36 LARC patients (stage II or III) undergoing NCRT with subsequent surgical treatment. We have detected somatic mutations in tissue biopsies taken during endoscopic examination prior to the therapy. CtDNA was extracted from patient plasma samples prior to therapy and at the end of the first week. In order to optimize the analytical costs of liquid-biopsy testing, we have utilized a two-level approach in which first a low-cost detection method of denaturing capillary electrophoresis was used followed by examination of initially negative samples by a high-sensitivity BEAMING assay. The ctDNA was related to clinical parameters including tumor regression grade (TRG) and TNM tumor staging.

Results: We have detected a somatic mutation in 33 out of 36 patients (91.7%). Seven patients (7/33, 21.2%) had ctDNA present prior to therapy. The ctDNA positivity before treatment reduced post-operative disease-free survival and overall survival by an average of 1.47 and 1.41 years, respectively (p = 0.015, and p = 0.010). In all patients, ctDNA was strongly reduced or completely eliminated from plasma by the end of the first week of NCRT, with no correlation to any of the parameters analyzed.

Conclusions: The baseline ctDNA presence represented a statistically significant negative prognostic biomarker for the overall patient survival. As ctDNA was reduced indiscriminately from circulation of all patients, dynamics during the first week of NCRT is not suited for predicting the outcome of LARC. However, the general effect of rapid ctDNA disappearance apparently occurring during the initial days of NCRT is noteworthy and should further be studied.

Tumor Regression Grade Predicts Survival in Locally Advanced Gastric Adenocarcinoma Patients with Lymph Node Metastasis

Background

Tumor regression grade (TRG) is widely used in gastrointestinal carcinoma to evaluate pathological responses to neoadjuvant chemotherapy (NCT), but whether it is an independent prognostic factor is still controversial. The aim of this study is to investigate the value of TRG in locally advanced gastric adenocarcinoma patients who underwent NCT and curative resection.

Methods

Pathological regression was reevaluated according to the Mandard TRG. Survival curves were obtained by the Kaplan–Meier method, and differences in overall survival (OS) and disease-free survival (DFS) were compared using the log-rank test. Univariate and multivariate analyses for survival were based on the Cox proportional hazards method.

Results

In total, 290 patients were identified in our electronic database. In univariable analysis, TRG was associated with OS (HR = 3.822, P ≤ 0.001) and DFS (HR = 3.374, P ≤ 0.001). However, in multivariable analysis, TRG was not an independent factor for OS (P = 0.231) or DFS (P = 0.191). In the stratified analysis, TRG retrieved prognostic significance in patients with the metastasis of lymph node (HR = 2.034, P = 0.035 for OS; HR = 2.220, P = 0.016 for DFS), while not in patients with negative lymph node (P = 0.296 for OS; P = 0.172 for DFS).

Conclusions

TRG was not an independent predictor for survival, but the system regained its predicting significance in patients with lymph node metastasis.

Gut Microbiome Composition Is Associated with a Pathologic Response After Preoperative Chemoradiation in Patients with Rectal Cancer

PURPOSE

There are ongoing investigations to find promising biomarkers for predicting a complete response (CR) after concurrent chemoradiation (CCRT) in rectal cancer. We aimed to find the predictive value in the gut microbiome in terms of response after preoperative CCRT.

METHODS AND MATERIALS

We collected a total of 45 fecal samples from patients with rectal cancer before CCRT. Tumor response after CCRT was assessed according to the American Joint Committee on Cancer tumor regression grading system. Analysis of linear discriminant analysis effect size and MetaCyc pathway abundance predictions were performed to compare composition and metabolic function of microbiome between patients with and without CR. We also established a Bayesian network model to identify microbial networks and species to be related with CCRT response.

RESULTS

Seven patients (15.6%) demonstrated pathologically CR, and 38 patients (84.4%) showed non-CR after preoperative CCRT. Between CR and non-CR patients, there was a significant difference in terms of β-diversity (P = .028), but no difference in α-diversity was found. Bacteroidales (Bacteroidaceae, Rikenellaceae, Bacteroides) were relatively more abundant in patients with non-CR than those with CR. Pathways related to anabolic function predominated in CR patients. According to Bayesian network analysis, Duodenibacillus massiliensis was linked with the improved CR rate.

CONCLUSIONS

From the fecal microbiome using samples obtained before preoperative CCRT, differences in microbial community composition and functions were observed between patients with and without CR in rectal cancer. However, the finding that a specific taxon may be linked with the improved therapeutic response should be verified in a prospective setting.

Adjuvant chemotherapy in rectal cancer patients who achieved a pathological complete response after preoperative chemoradiotherapy: a systematic review and meta-analysis

This study evaluated the prognostic impact of ACT in patients who achieved a pathological complete response (pCR). Articles published from January 1990 to September 2018 were searched in EMBASE, PubMed, Ovid, Web of Science, and Cochrane Library. Hazard ratios (HRs) and 95% confidence intervals (CIs) of overall survival (OS) were extracted. Thirteen observational studies were included. There were four National Cancer Database studies with overlapping study periods, thus individual pooled analyses of four different datasets were conducted (n = 3,182, 3,330, 3,575, and 4,739 for pooled analysis sets including Dossa et al., Polanco et al., Xu et al., and Shahab et al., respectively). Although a trend toward improved OS with ACT was observed, statistical significance was not proven (P = 0.09, P = 0.03, P = 0.12, and P = 0.10, respectively). When we performed a stratified analysis comparing the results from single institution and multicenter studies, there was no significant prognostic benefit of ACT. Publication bias was not observed. Routine use of ACT in patients with a pCR could not be warranted from the present meta-analysis. Further study of individual patient data from randomized trials is needed to clarify the role of ACT.

Nomogram for predicting disease-free survival among a multicenter cohort of Chinese patients with locally advanced rectal cancer

Purpose: This study aimed to develop and validate a nomogram for predicting 3-year disease-free survival (DFS) among a multicenter cohort of Chinese patients with locally advanced rectal cancer (LARC) who underwent preoperative therapy followed by surgery. This nomogram might help identify patients who would benefit from postoperative adjuvant chemotherapy and close follow-up.

Materials and methods: All data from 228 patients in two independent Chinese cohorts (118 patients and 110 patients) were pooled and subjected to survival analysis. One cohort’s data were used to develop multivariate nomograms based on Cox regression, and the second cohort was used for external validation. The variables were sex, age, clinical tumor stage, tumor location, preoperative therapy protocol, adjuvant chemotherapy, surgical procedure, surgical approach, pTNM stage, tumor deposit, tumor regression grade, lymphovascular invasion, perineural invasion, pretreatment serum carcinoembryonic antigen (CEA) level, preoperative CEA level, and postoperative CEA level. The model’s performance was evaluated based on its discrimination, calibration, and clinical usefulness.

Results: The nomogram was based on ypT stage and ypN stage, and the C-index values for 3-year DFS were 0.70 in the training cohort (95% confidence interval: 0.62–0.78) and 0.78 in the validation cohort (95% confidence interval: 0.68–0.89). The Hosmer-Lemeshow calibration test revealed good calibration for predicting 3-year DFS in the training and validation cohorts, and decision curve analysis demonstrated that the nomogram was clinically useful.

Conclusion: This nomogram including the ypT stage and ypN stage could predict DFS at 3 years after surgery, which may help better identify Chinese patients who would benefit from additional postoperative adjuvant systemic treatment.

Delta-radiomics signature predicts treatment outcomes after preoperative chemoradiotherapy and surgery in rectal cancer

Background

To develop and compare delta-radiomics signatures from 2- (2D) and 3-dimensional (3D) features that predict treatment outcomes following preoperative chemoradiotherapy (CCRT) and surgery for locally advanced rectal cancer.

Methods

In total, 101 patients (training cohort, n = 67; validation cohort, n = 34) with locally advanced rectal adenocarcinoma between 2008 and 2015 were included. We extracted 55 features from T2-weighted magnetic resonance imaging (MRI) scans. Delta-radiomics feature was defined as the difference in radiomics feature before and after CCRT. Signatures were developed to predict local recurrence (LR), distant metastasis (DM), and disease-free survival (DFS) from 2D and 3D features. The least absolute shrinkage and selection operator regression was used to select features and build signatures. The delta-radiomics signatures and clinical factors were integrated into Cox regression analysis to determine if the signatures were independent prognostic factors.

Results

The radiomics signatures for LR, DM, and DFS were developed and validated using both 2D and 3D features. Outcomes were significantly different in the low- and high-risk patients dichotomized by optimal cutoff in both the training and validation cohorts. In multivariate analysis, the signatures were independent prognostic factors even when considering the clinical parameters. There were no significant differences in C-index from 2D vs. 3D signatures.

Conclusions

This is the first study to develop delta-radiomics signatures for rectal cancer. The signatures successfully predicted the outcomes and were independent prognostic factors. External validation is warranted to ensure their performance.

Electronic supplementary material

The online version of this article (10.1186/s13014-019-1246-8) contains supplementary material, which is available to authorized users.