Identification of methyltransferase-like protein 11B as a new prognostic biomarker for colorectal cancer through an analysis of The Cancer Genome Atlas

Post-diagnosis adiposity and colorectal cancer prognosis: A Global Cancer Update Programme (CUP Global) systematic literature review and meta-analysis

The adiposity influence on colorectal cancer prognosis remains poorly characterised. We performed a systematic review and meta-analysis on post-diagnosis adiposity measures (body mass index [BMI], waist circumference, waist-to-hip ratio, weight) or their changes and colorectal cancer outcomes. PubMed and Embase were searched through 28 February 2022. Random-effects meta-analyses were conducted when at least three studies had sufficient information. The quality of evidence was interpreted and graded by the Global Cancer Update Programme (CUP Global) independent Expert Committee on Cancer Survivorship and Expert Panel. We reviewed 124 observational studies (85 publications). Meta-analyses were possible for BMI and all-cause mortality, colorectal cancer-specific mortality, and cancer recurrence/disease-free survival. Non-linear meta-analysis indicated a reverse J-shaped association between BMI and colorectal cancer outcomes (nadir at BMI 28 kg/m2). The highest risk, relative to the nadir, was observed at both ends of the BMI distribution (18 and 38 kg/m2), namely 60% and 23% higher risk for all-cause mortality; 95% and 26% for colorectal cancer-specific mortality; and 37% and 24% for cancer recurrence/disease-free survival, respectively. The higher risk with low BMI was attenuated in secondary analyses of RCTs (compared to cohort studies), among studies with longer follow-up, and in women suggesting potential methodological limitations and/or altered physiological state. Descriptively synthesised studies on other adiposity-outcome associations of interest were limited in number and methodological quality. All the associations were graded as limited (likelihood of causality: no conclusion) due to potential methodological limitations (reverse causation, confounding, selection bias). Additional well-designed observational studies and interventional trials are needed to provide further clarification.

Three's a crowd - why did three N-terminal methyltransferases evolve for one job?

N-terminal methylation of the α-amine group (Nα-methylation) is a post-translational modification (PTM) that was discovered over 40 years ago. Although it is not the most abundant of the Nα-PTMs, there are more than 300 predicted substrates of the three known mammalian Nα-methyltransferases, METTL11A and METTL11B (also known as NTMT1 and NTMT2, respectively) and METTL13. Of these ∼300 targets, the bulk are acted upon by METTL11A. Only one substrate is known to be Nα-methylated by METTL13, and METTL11B has no proven in vivo targets or predicted targets that are not also methylated by METTL11A. Given that METTL11A could clearly handle the entire substrate burden of Nα-methylation, it is unclear why three distinct Nα-methyltransferases have evolved. However, recent evidence suggests that many methyltransferases perform important biological functions outside of their catalytic activity, and the Nα-methyltransferases might be part of this emerging group. Here, we describe the distinct expression, localization and physiological roles of each Nα-methyltransferase, and compare these characteristics to other methyltransferases with non-catalytic functions, as well as to methyltransferases with both catalytic and non-catalytic functions, to give a better understanding of the global roles of these proteins. Based on these comparisons, we hypothesize that these three enzymes do not just have one common function but are actually performing three unique jobs in the cell.

Comprehensive analysis of the differences between left- and right-side colorectal cancer and respective prognostic prediction

Background

Previous studies have reported that the tumor heterogeneity and complex oncogenic mechanisms of proximal and distal colon cancer (CRC) are divergent. Therefore, we aim to analyze the differences between left-sided CRC (L_cancer) and right-sided CRC (R_cancer), as well as constructing respective nomograms.

Methods

We enrolled 335 colon cancer patients (146 L_cancer patients and 189 R_cancer patients) from The Cancer Genome Atlas (TCGA) data sets, and 102 pairs of color cancer tissue and adjacent normal tissue (51 L_cancer patients and 51 R_cancer patients) from our hospital. Firstly, we analyzed the differences between the L_cancer patients and R_cancer patients, and then established the L_cancer and R_cancer prognostic models using LASSO Cox.

Results

R_cancer patients had lower survival than L_cancer patients. R_cancer patients had higher ESTIMATE and immune scores and lower tumor purity. These patterns of expression of immune checkpoint-related genes and TMB level were higher in R_cancer than in L_cancer patients. Finally, we using Lasso Cox regression analyses established a prognostic model for L_cancer patients and a prognostic model for R_cancer patients. The AUC values of the risk score for OS in L_cancer were 0.862 in the training set and 0.914 in the testing set, while those in R_cancer were 0.835 in the training set and 0.857 in the testing set. The AUC values in fivefold cross-validation were between 0.727 and 0.978, proving that the two prognostic models have great stability. The nomogram of L_cancer included prognostic genes, age, pathological M, pathological stage, and gender, the AUC values of which were 0.800 in the training set and 0.905 in the testing set. Meanwhile, the nomogram of R_cancer comprised prognostic genes, pathological N, pathological T, and age, the AUC values of which were 0.836 in the training set and 0.850 in the testing set. In the R_cancer patients, high-risk patients had a lower proportion of ‘B cells memory’, ‘Dendritic cells resting’, immune score, ESTIMATE score, immune checkpoint-related genes, and HLA-family genes, and a higher proportion of ‘T cells follicular helper’, ‘Dendritic cells activated’, and ‘Mast cells activated’.

Conclusions

We found significant differences between L_cancer and R_cancer patients and established a clinical predictive nomogram for L_cancer patients and a nomogram for R_cancer patients. Additionally, R_cancer patients in low-risk groups may be more beneficial from immunotherapy.