Clinical-grade whole-genome sequencing and 3' transcriptome analysis of colorectal cancer patients

Multiparametric magnetic resonance imaging (MRI)-based radiomics model explained by the Shapley Additive exPlanations (SHAP) method for predicting complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a multicenter retrospective study

Background

Predicting the response to neoadjuvant chemoradiotherapy (nCRT) before initiating treatment is essential for tailoring therapeutic strategies and monitoring prognosis in locally advanced rectal cancer (LARC). In this study, we aimed to develop and validate radiomic-based models to predict clinical and pathological complete responses (cCR and pCR, respectively) by incorporating the Shapley Additive exPlanations (SHAP) method for model interpretation.

Methods

A total of 285 patients with complete pretreatment clinical characteristics and T1-weighted (T1W) and T2-weighted (T2W) magnetic resonance imaging (MRI) at 3 centers were retrospectively recruited. The features of tumor lesions were extracted by PyRadiomics and selected using least absolute shrinkage and selection operator (LASSO) algorithm. The selected features were used to build multilayer perceptron (MLP) models alone or combined with clinical features. Area under the receiver operating characteristic curve (AUC), decision curve, and calibration curve were applied to evaluate performance of models. The SHAP method was adopted to explain the prediction models.

Results

The radiomic-based models all showed better performances than clinical models. The clinical-radiomic models showed the best differentiation on cCR and pCR with mean AUCs of 0.718 and 0.810 in the validation set, respectively. The decision curves of the clinical-radiomic models showed its values in clinical application. The SHAP method powerfully interpreted the prediction models both at a holistic and individual levels.

Conclusions

Our study highlights that the radiomic-based prediction models have more excellent abilities than clinical models and can effectively predict treatment response and optimize therapeutic strategies for patients with LARCs.

Proteogenomic characterization of primary colorectal cancer and metastatic progression identifies proteome-based subtypes and signatures

Metastatic progression of colorectal adenocarcinoma (CRC) remains poorly understood and poses significant challenges for treatment. To overcome these challenges, we performed multiomics analyses of primary CRC and liver metastases. Genomic alterations, such as structural variants or copy number alterations, were enriched in oncogenes and tumor suppressor genes and increased in metastases. Unsupervised mass spectrometry-based proteomics of 135 primary and 123 metastatic CRCs uncovered distinct proteomic subtypes, three each for primary and metastatic CRCs, respectively. Integrated analyses revealed that hypoxia, stemness, and immune signatures characterize these 6 subtypes. Hypoxic CRC harbors high epithelial-to-mesenchymal transition features and metabolic adaptation. CRC with a stemness signature shows high oncogenic pathway activation and alternative telomere lengthening (ALT) phenotype, especially in metastatic lesions. Tumor microenvironment analysis shows immune evasion via modulation of major histocompatibility complex (MHC) class I/II and antigen processing pathways. This study characterizes both primary and metastatic CRCs and provides a large proteogenomics dataset of metastatic progression.

Bile acids as carcinogens in the colon and at other sites in the gastrointestinal system

Colon cancer incidence is associated with a high-fat diet. Such a diet is linked to elevated levels of bile acids in the gastrointestinal system and the circulation. Secondary bile acids are produced by microorganisms present at high concentrations in the colon. Recent prospective studies and a retrospective study in humans associate high circulating blood levels of secondary bile acids with increased risk of colon cancer. Feeding mice a diet containing a secondary bile acid, so their feces have the bile acid at a level comparable to that in the feces of humans on a high-fat diet, also causes colon cancer in the mice. Studies using human cells grown in culture illuminate some mechanisms by which bile acids cause cancer. In human cells, bile acids cause oxidative stress leading to oxidative DNA damage. Increased DNA damage increases the occurrence of mutations and epimutations, some of which provide a cellular growth advantage such as apoptosis resistance. Cells with such mutations/epimutations increase by natural selection. Apoptosis, or programmed cell death, is a beneficial process that eliminates cells with unrepaired DNA damage, whereas apoptosis-resistant cells are able to survive DNA damage using inaccurate repair processes. This results in apoptosis-resistant cells having more frequent mutations/epimutations, some of which are carcinogenic. The experiments on cultured human cells have provided a basis for understanding at the molecular level the human studies that recently reported an association of bile acids with colon cancer, and the mouse studies showing directly that bile acids cause colon cancer. Similar, but more limited, findings of an association of dietary bile acids with other cancers of the gastrointestinal system suggest that understanding the role of bile acids in colon carcinogenesis may contribute to understanding carcinogenesis in other organs.