RESUMO
Diagnostic performance of molecular markers in surrogate tissues like stool may be affected by colorectal cancer (CRC) morphological heterogeneity. The mucinous histotype represents a subgroup of CRC with a peculiar molecular program and unfavorable disease progression. However, the percentage of mucinous morphology necessary to define this subtype is still a matter of debate. In this study, we investigated whether stool miRNA profiles of CRC patients differ in patients with mucinous histopathological subtypes compared to non-mucinous cancers. In this respect, we also explored how the stool miRNA signature reported in our previous multicentric study (Pardini et al., Gastroenterology 2023) behave in this histotype. Small-RNA sequencing was performed in fecal and tissue samples of an Italian cohort (n=172), including 27 CRC with mucinous morphology (mucinous cancers with >50% mucinous morphology and those with mucinous component >5% but <50%), 58 non-mucinous CRC, and 87 colonoscopy-negative controls. Results were compared with fecal miRNA profiles of a cohort from the Czech Republic (n=98). Most of the differentially expressed (DE) stool miRNAs (n=324) were in common between CRC with mucinous morphology and non-mucinous histopathological subtypes in comparison with healthy controls. Interestingly, the altered levels of 25 fecal miRNAs previously identified distinguishing CRC cases from controls in both cohorts were also confirmed after stratification for mucinous morphology. Forty-nine miRNAs were DE exclusively in CRC with mucinous morphology and 61 in non-mucinous CRC. Mucinous cancers and those with mucinous component showed fairly similar profiles that were comparable in the Czech cohort. Among the stool DE miRNAs observed in CRC with mucinous morphology, 20 were also altered in the comparison between tumor and adjacent mucosa tissue. This study highlights miRNAs specifically altered in CRC with mucinous morphology. Nevertheless, the performance of our stool miRNA signature in accurately distinguishing CRC cases from controls was not significantly affected by this histological subtype. This aspect further supports the use of stool miRNAs for noninvasive diagnosis and screening strategies.
RESUMO
Predicting the difference in thermodynamic stability between protein variants is crucial for protein design and understanding the genotype-phenotype relationships. So far, several computational tools have been created to address this task. Nevertheless, most of them have been trained or optimized on the same and 'all' available data, making a fair comparison unfeasible. Here, we introduce a novel dataset, collected and manually cleaned from the latest version of the ThermoMutDB database, consisting of 669 variants not included in the most widely used training datasets. The prediction performance and the ability to satisfy the antisymmetry property by considering both direct and reverse variants were evaluated across 21 different tools. The Pearson correlations of the tested tools were in the ranges of 0.21-0.5 and 0-0.45 for the direct and reverse variants, respectively. When both direct and reverse variants are considered, the antisymmetric methods perform better achieving a Pearson correlation in the range of 0.51-0.62. The tested methods seem relatively insensitive to the physiological conditions, performing well also on the variants measured with more extreme pH and temperature values. A common issue with all the tested methods is the compression of the $\Delta \Delta G$ predictions toward zero. Furthermore, the thermodynamic stability of the most significantly stabilizing variants was found to be more challenging to predict. This study is the most extensive comparisons of prediction methods using an entirely novel set of variants never tested before.
