The impact of 6 years of the National Colorectal Cancer Screening Program on colorectal cancer incidence and 5-year survival

The KMeansGraphMIL Model: A Weakly Supervised Multiple Instance Learning Model for Predicting Colorectal Cancer Tumor Mutational Burden

Colorectal cancer (CRC) is one of the top three most lethal malignancies worldwide, posing a significant threat to human health. Recently proposed immunotherapy checkpoint blockade treatments have proven effective for CRC, but their use depends on measuring specific biomarkers in patients. Among these biomarkers, tumor mutational burden (TMB) has emerged as a novel indicator, traditionally requiring next-generation sequencing for measurement, which is time-consuming, labor intensive, and costly. To provide an economical and rapid way to predict patients' TMB, the KMeansGraphMIL model was proposed based on weakly supervised multiple-instance learning. Compared with previous weakly supervised multiple-instance learning models, KMeansGraphMIL leveraged both the similarity of image patch feature vectors and the spatial relationships between patches. This approach improved the model's area under the receiver operating characteristic curve to 0.8334 and significantly increased the recall to 0.7556. Thus, this study presents an economical and rapid framework for predicting CRC TMB, offering the potential for physicians to quickly develop treatment plans and saving patients substantial time and money.

Circular RNA circ_0058123 Targets the miR-939-5p/RAC1 Pathway to Promote the Development of Colorectal Cancer

Circular RNA (circRNA) can be used as a potential target for cancer treatment. However, the biological function and potential molecular mechanism of circ_0058123 in the development of colorectal cancer (CRC) are still unclear. The expression levels of circ_0058123, microRNA-939-5p (miR-939-5p) and Rac family small GTPase 1 (RAC1) were measured by quantitative real-time polymerase chain reaction or western blot assay. 5-Ethynyl-2'-deoxyuridine (EdU) incorporation assay, transwell assay, tube formation assay and flow cytometry apoptosis assay were conducted to assess CRC cell functions. In addition, protein expression was measured with western blot assay. Dual-luciferase reporter assays and RNA immunoprecipitation assay were conducted to confirm the relationships between miR-939-5p and circ_0058123, and miR-939-5p and RAC1. In vivo CRC tumor growth experiment also were carried out to determine circ_0058123-mediatede effects on tumor formation. Our data showed that circ_0058123 and RAC1 expression were increased, but miR-939-5p was decreased in both of CRC tissues and cell lines. Circ_0058123 depletion repressed CRC cell proliferation, migration, invasion and tube formation but promoted cell apoptosis. Down-regulation of circ_0058123 could significantly suppress the CRC progression, while the addition of miR-939-5p inhibitor could reverse this effect. Circ_0058123 directly targeted miR-939-5p, and RAC1 was a target of miR-939-5p. Furthermore, RAC1 overexpression could rescue the effect of miR-939-5p on CRC development. Lastly, silence of circ_0058123 inhibited CRC tumor growth in vivo. In conclusion, circ_0058123 could promote CRC progression through regulating the miR-939-5p/RAC1 axis and may be a valuable biomarker for early diagnosis and prognosis of CRC.

The Impact of a Six-Year Existing Screening Programme Using the Faecal Immunochemical Test in Flanders (Belgium) on Colorectal Cancer Incidence, Mortality and Survival: A Population-Based Study

The faecal immunochemical test (FIT) has been increasingly used for organised colorectal cancer (CRC) screening. We assessed the impact of a six-year existing FIT screening programme in Flanders (Belgium) on CRC incidence, mortality and survival. The Flemish CRC screening programme started in 2013, targeting individuals aged 50-74 years. Joinpoint regression was used to investigate trends of age-standardised CRC incidence and mortality among individuals aged 50-79 years (2004-2019). Their 5-year relative survival was calculated using the Ederer II method. We found that FIT screening significantly reduced CRC incidence, especially that of advanced-stage CRCs (69.8/100,000 in 2012 vs. 51.1/100,000 in 2019), with a greater impact in men. Mortality started to decline in men two years after organised screening implementation (annual reduction of 9.3% after 2015 vs. 2.2% before 2015). The 5-year relative survival was significantly higher in screen-detected (93.8%) and lower in FIT non-participant CRCs (61.9%) vs. FIT interval cancers and CRCs in never-invited cases (67.6% and 66.7%, respectively). Organised FIT screening in Flanders clearly reduced CRC incidence (especially advanced-stage) and mortality (in men, but not yet in women). Survival is significantly better in screen-detected cases vs. CRCs in unscreened people. Our findings support the implementation of FIT organised screening and the continued effort to increase uptake.

Overall and stage-specific survival of patients with screen-detected colorectal cancer in European countries: A population-based study in 9 countries

Background

An increasing proportion of colorectal cancers (CRCs) are detected through screening due to the availability of organised population-based programmes. We aimed to analyse survival probabilities of patients with screen-detected CRC in European countries.

Methods

Data from CRC patients were obtained from 16 population-based cancer registries in nine European countries. We included patients with cancer diagnosed from the year organised CRC screening programmes were introduced until the most recent year with available data at the time of analysis, whose ages at diagnosis fell into the age groups targeted by screening. Patients were followed up with regards to vital status until 2016-2020 across the various countries. Overall and CRC-specific survival were analysed by mode of detection and stage at diagnosis for all countries combined and for each country separately using the Kaplan-Meier method.

Findings

We included data from 228 134 patients, of whom 134 597 (aged 60-69 years at diagnosis targeted by screening in all countries) were considered in analyses for all countries combined. 22·3% (38 080/134 597) of patients had cancer detected through screening. Most screen-detected cancers were found at stages I-II (65·6% [12 772/19 469 included in stage-specific analyses]), while the majority of non-screen-detected cancers were found at stages III-IV (56·4% [31 882/56 543 included in stage-specific analyses]). Five-year overall and CRC-specific survival rates for patients with screen-detected cancer were 83·4% (95% CI 82·9-83·9) and 89·2% (88·8-89·7), respectively; for patients with non-screen-detected cancer, they were much lower (57·5% [57·2-57·8] and 65·7% [65·4-66·1], respectively). The favourable survival of patients with screen-detected cancer was also seen within each stage – five-year overall survival rates for patients with screen-detected stage I, II, III, and IV cancers were 92.4% (95% CI 91·6-93·1), 87·9% (86·6-89·1), 80·7% (79·3-82·0), and 32·3 (29·4-35·2), respectively. These patterns were also consistently seen for each individual country.

Interpretation

Patients with cancer diagnosed at screening have a very favourable prognosis. In the rare case of detection of advanced stage cancer, survival probabilities are still much higher than those commonly reported for all patients regardless of mode of detection. Although these results cannot be taken to quantify screening effects, they provide useful and encouraging information for patients with screen-detected CRC and their physicians.

Funding

This study was supported in part by grants from the German Federal Ministry of Education and Research and the German Cancer Aid.

Prediction of Tumor Mutation Load in Colorectal Cancer Histopathological Images Based on Deep Learning

Colorectal cancer (CRC) is one of the most prevalent malignancies, and immunotherapy can be applied to CRC patients of all ages, while its efficacy is uncertain. Tumor mutational burden (TMB) is important for predicting the effect of immunotherapy. Currently, whole-exome sequencing (WES) is a standard method to measure TMB, but it is costly and inefficient. Therefore, it is urgent to explore a method to assess TMB without WES to improve immunotherapy outcomes. In this study, we propose a deep learning method, DeepHE, based on the Residual Network (ResNet) model. On images of tissue, DeepHE can efficiently identify and analyze characteristics of tumor cells in CRC to predict the TMB. In our study, we used ×40 magnification images and grouped them by patients followed by thresholding at the 10th and 20th quantiles, which significantly improves the performance. Also, our model is superior compared with multiple models. In summary, deep learning methods can explore the association between histopathological images and genetic mutations, which will contribute to the precise treatment of CRC patients.