Radiotherapy (RT) or chemoradiotherapy (CRT) are frequently used in rectal cancer, sometimes resulting in complete tumor remission (CR). The predictive capacity of all clinical factors, laboratory values and magnetic resonance imaging parameters performed in routine staging was evaluated to understand what determines an excellent response to RT/CRT. A population-based cohort of 383 patients treated with short-course RT (5 × 5 Gy in one week, scRT), CRT, or scRT with chemotherapy (scRT+CT) and having either had a delay to surgery or been entered into a watch-and-wait program were included. Complete staging according to guidelines was performed and associations between investigated variables and CR rates were analyzed in univariate and multivariate analyses. In total, 17% achieved pathological or clinical CR, more often after scRT+CT and CRT than after scRT (27%, 18% and 8%, respectively, p < 0.001). Factors independently associated with CR included clinical tumor stage, small tumor size (<3 cm), tumor level, and low CEA-value (<3.8 μg/L). Size or stage of the rectal tumor were associated with excellent response in all therapy groups, with small or early stage tumors being significantly more likely to reach CR (p = 0.01 (scRT), p = 0.01 (CRT) and p = 0.02 (scRT+CT). Elevated level of carcinoembryonic antigen (CEA) halved the chance of response. Extramural vascular invasion (EMVI) and mucinous character may indicate less response to RT alone.

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While the clinical importance of CD8+ and CD3+ cells in colorectal cancer (CRC) is well established, the impact of other immune cell subsets is less well described. We sought to provide a detailed overview of the immune landscape of CRC in the largest study to date in terms of patient numbers and in situ analyzed immune cell types. Tissue microarrays from 536 patients were stained using multiplexed immunofluorescence panels, and fifteen immune cell subclasses, representing adaptive and innate immunity, were analyzed. Overall, therapy-naïve CRC patients clustered into an ‘inflamed’ and a ‘desert’ group. Most T cell subsets and M2 macrophages were enriched in the right colon (p-values 0.046–0.004), while pDC cells were in the rectum (p = 0.008). Elderly patients had higher infiltration of M2 macrophages (p = 0.024). CD8+ cells were linked to improved survival in colon cancer stages I-III (q = 0.014), while CD4+ cells had the strongest impact on overall survival in metastatic CRC (q = 0.031). Finally, we demonstrated repopulation of the immune infiltrate in rectal tumors post radiation, following an initial radiation-induced depletion. This study provides a detailed analysis of the in situ immune landscape of CRC paving the way for better diagnostics and providing hints to better target the immune microenvironment.

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Background: Prediction models are useful tools in the clinical management of colon cancer patients, particularly when estimating the recurrence rate and, thus, the need for adjuvant treatment. However, the most used models (MSKCC, ACCENT) are based on several decades-old patient series from clinical trials, likely overestimating the current risk of recurrence, especially in low-risk groups, as outcomes have improved over time. The aim was to develop and validate an updated model for the prediction of recurrence within 5 years after surgery using routinely collected clinicopathologic variables. Material and methods: A population-based cohort from the Swedish Colorectal Cancer Registry of 16,134 stage I-III colon cancer cases was used. A multivariable model was constructed using Cox proportional hazards regression. Three-quarters of the cases were used for model development and one quarter for internal validation. External validation was performed using 12,769 stage II-III patients from the Norwegian Colorectal Cancer Registry. The model was compared to previous nomograms. Results: The nomogram consisted of eight variables: sex, sidedness, pT-substages, number of positive and found lymph nodes, emergency surgery, lymphovascular and perineural invasion. The area under the curve (AUC) was 0.78 in the model, 0.76 in internal validation, and 0.70 in external validation. The model calibrated well, especially in low-risk patients, and performed better than existing nomograms in the Swedish registry data. The new nomogram's AUC was equal to that of the MSKCC but the calibration was better. Conclusion:The nomogram based on recently operated patients from a population registry predicts recurrence risk more accurately than previous nomograms. It performs best in the low-risk groups where the risk-benefit ratio of adjuvant treatment is debatable and the need for an accurate prediction model is the largest.