Shrinkage versus fragmentation response in neoadjuvantly treated oesophageal adenocarcinoma: significant prognostic relevance

Relevance of shrinkage versus fragmented response patterns in rectal cancer

AIMS

Partial response to neoadjuvant chemoradiotherapy (CRT) presents with one of two main response patterns: shrinkage or fragmentation. This study investigated the relevance of these response patterns in rectal cancer, correlation with other response indicators, and outcome.

METHODS AND RESULTS

The study included a test (n = 197) and a validation cohort (n = 218) of post-CRT patients with rectal adenocarcinoma not otherwise specified and a partial response. Response patterns were scored by two independent observers using a previously developed three-step flowchart. Tumour regression grading (TRG) was established according to both the College of American Pathologists (CAP) and Dworak classifications. In both cohorts, the predominant response pattern was fragmentation (70% and 74%), and the scoring interobserver agreement was excellent (k = 0.85). Patients with a fragmented pattern presented with significantly higher pathological stage (ypTNM II-IV, 78% versus 35%; P < 0.001), less tumour regression with Dworak (P = 0.004), and CAP TRG (P = 0.005) compared to patients with a shrinkage pattern. As a predictor of prognosis, the shrinkage pattern outperformed the TRG classification and stratified patients better in overall (fragmented pattern, hazard ratio [HR] 2.04, 95% confidence interval [CI] 1.19-3.50, P = 0.008) and disease-free survival (DFS; fragmented pattern, HR 2.50, 95% CI 1.23-5.10, P = 0.011) in the combined cohorts. The multivariable regression analyses revealed pathological stage as the only independent predictor of DFS.

CONCLUSIONS

The heterogeneous nature of tumour response following CRT is reflected in fragmentation and shrinkage. In rectal cancer there is a predominance of the fragmented pattern, which is associated with advanced stage and less tumour regression. While not independently associated with survival, these reproducible patterns give insights into the biology of tumour response.

Size and depth of residual tumor after neoadjuvant chemoradiotherapy in rectal cancer - implications for the development of new imaging modalities for response assessment

With the shift towards organ preserving treatment strategies in rectal cancer it has become increasingly important to accurately discriminate between a complete and good clinical response after neoadjuvant chemoradiotherapy (CRT). Standard of care imaging techniques such as CT and MRI are well equipped for initial staging of rectal tumors, but discrimination between a good clinical and complete response remains difficult due to their limited ability to detect small residual vital tumor fragments. To identify new promising imaging techniques that could fill this gap, it is crucial to know the size and invasion depth of residual vital tumor tissue since this determines the requirements with regard to the resolution and imaging depth of potential new optical imaging techniques. We analyzed 198 pathology slides from 30 rectal cancer patients with a Mandard tumor regression grade 2 or 3 after CRT that underwent surgery. For each patient we determined response pattern, size of the largest vital tumor fragment or bulk and the shortest distance from the vital tumor to the luminal surface. The response pattern was shrinkage in 14 patients and fragmentation in 16 patients. For both groups combined, the largest vital tumor fragment per patient was smaller than 1mm for 38% of patients, below 0.2mm for 12% of patients and for one patient as small as 0.06mm. For 29% of patients the vital tumor remnant was present within the first 0.01mm from the luminal surface and for 87% within 0.5mm. Our results explain why it is difficult to differentiate between a good clinical and complete response in rectal cancer patients using endoscopy and MRI, since in many patients submillimeter tumor fragments remain below the luminal surface. To detect residual vital tumor tissue in all patients included in this study a technique with a spatial resolution of 0.06mm and an imaging depth of 8.9mm would have been required. Optical imaging techniques offer the possibility of detecting majority of these cases due to the potential of both high-resolution imaging and enhanced contrast between tissue types. These techniques could thus serve as a complimentary tool to conventional methods for rectal cancer response assessment.

Deep learning for multi-class semantic segmentation enables colorectal cancer detection and classification in digital pathology images

In colorectal cancer (CRC), artificial intelligence (AI) can alleviate the laborious task of characterization and reporting on resected biopsies, including polyps, the numbers of which are increasing as a result of CRC population screening programs ongoing in many countries all around the globe. Here, we present an approach to address two major challenges in the automated assessment of CRC histopathology whole-slide images. We present an AI-based method to segment multiple ([Formula: see text]) tissue compartments in the H &E-stained whole-slide image, which provides a different, more perceptible picture of tissue morphology and composition. We test and compare a panel of state-of-the-art loss functions available for segmentation models, and provide indications about their use in histopathology image segmentation, based on the analysis of (a) a multi-centric cohort of CRC cases from five medical centers in the Netherlands and Germany, and (b) two publicly available datasets on segmentation in CRC. We used the best performing AI model as the basis for a computer-aided diagnosis system that classifies colon biopsies into four main categories that are relevant pathologically. We report the performance of this system on an independent cohort of more than 1000 patients. The results show that with a good segmentation network as a base, a tool can be developed which can support pathologists in the risk stratification of colorectal cancer patients, among other possible uses. We have made the segmentation model available for research use on https://grand-challenge.org/algorithms/colon-tissue-segmentation/ .

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.

The immune microenvironment landscape shows treatment-specific differences in rectal cancer patients

Neoadjuvant therapy is the cornerstone of modern rectal cancer treatment. Insights into the biology of tumor responses are essential for the successful implementation of organ-preserving strategies, as different treatments may lead to specific tumor responses. In this study, we aim to explore treatment-specific responses of the tumor microenvironment. Patients with locally advanced adenocarcinoma of the rectum who had received neo-adjuvant chemotherapy (CT), neo-adjuvant radiochemotherapy (RCT), neo-adjuvant radiotherapy with a long-interval (LRT) or short-interval (SRT) or no neoadjuvant therapy (NT) as control were included. Multiplex-immunofluorescence was performed to determine the presence of cytotoxic T-cells (T-cyt; CD3+CD8+), regulatory T-cells (T-reg; CD3+FOXP3+), T-helper cells (T-helper; CD3+CD8-FOXP3-), B cells (CD20+), dendritic cells (CD11c+) and tumor cells (panCK+). A total of 80 rectal cancer patients were included. Treatment groups were matched for gender, tumor location, response to therapy, and TNM stage. The pattern of response (shrinkage vs. fragmentation) was, however, different between treatment groups. Our analyses reveal that RCT-treated patients exhibited lower stromal T-helper, T-reg, and T-cyt cells compared to other treatment regimens. In conclusion, we demonstrated treatment-specific differences in the immune microenvironment landscape of rectal cancer patients. Understanding the underlying mechanisms of this landscape after a specific therapy will benefit future treatment decisions.