Comprehensive analysis of gene mutations and mismatch repair in Chinese colorectal cancer patients.

BACKGROUND: RAS, BRAF, and mismatch repair (MMR)/microsatellite instability (MSI) are crucial biomarkers recommended by clinical practice guidelines for colorectal cancer (CRC). However, their characteristics and influencing factors in Chinese patients have not been thoroughly described. AIM: To analyze the clinicopathological features of KRAS, NRAS, BRAF, and PIK3CA mutations and the DNA MMR status in CRC. METHODS: We enrolled 2271 Chinese CRC patients at the China-Japan Friendship Hospital. MMR proteins were tested using immunohistochemical analysis, and the KRAS/NRAS/BRAF/PIK3CA mutations were determined using quantitative polymerase chain reaction. Microsatellite status was determined using an MSI detection kit. Statistical analyses were conducted using SPSS software and logistic regression. RESULTS: The KRAS, NRAS, BRAF, and PIK3CA mutations were detected in 44.6%, 3.4%, 3.7%, and 3.9% of CRC patients, respectively. KRAS mutations were more likely to occur in patients with moderate-to-high differentiation. BRAF mutations were more likely to occur in patients with right-sided CRC, poorly differentiated, or no perineural invasion. Deficient MMR (dMMR) was detected in 7.9% of all patients and 16.8% of those with mucinous adenocarcinomas. KRAS, NRAS, BRAF, and PIK3CA mutations were detected in 29.6%, 1.1%, 8.1%, and 22.3% of patients with dMMR, respectively. The dMMR was more likely to occur in patients with a family history of CRC, aged < 50 years, right-sided CRC, poorly differentiated histology, no perineural invasion, and with carcinoma in situ, stage I, or stage II tumors. CONCLUSION: This study analyzed the molecular profiles of KRAS, NRAS, BRAF, PIK3CA, and MMR/MSI in CRC, identifying key influencing factors, with implications for clinical management of CRC.

Rapid diagnosis of papillary thyroid carcinoma with machine learning and probe electrospray ionization mass spectrometry.

Frozen section examination could provide pathological diagnosis for surgery of thyroid nodules, which is time-consuming, skill- and experience-dependent. This study developed a rapid classification method for thyroid nodules and machine learning. Total 69 tissues were collected including 43 nodules and 26 nodule-adjacent tissues. Intraoperative frozen section was first performed to give accurate diagnosis, and the rest frozen specimen were pretreated for probe electrospray ionization mass measurement. By multivariate analysis of mass scan data, a series compounds were found downregulated in the extraction solution of papillary thyroid carcinoma (PTC), but some were found upregulated by mass spectrometry imaging. m/z 758.5713 ([PC[34:2] + H]+ ), m/z 772.5845 ([PC[32:0] + K]+ ), and m/z 786.6037 ([PC[36:2] + H]+ ) were firstly identified as potential biomarkers for nodular goiter (NG). Machine learning was employed by means of support vector machine (SVM) and random forest (RF) algorithms. For classification of PTC from NG, SVM and RF algorithms exhibited the same performance and the concordance was 94.2% and 94.4% between prediction and pathological diagnosis with positive and negative mass dataset, respectively. For the classification of PTC from PTC adjacent tissues, SVM was better than RF and the concordance was 93.8% and 83.3% with positive and negative mass dataset, respectively. With the identified compounds as training features, the sensitivity and specificity are 87.5% and 88.9% for the test set. The developed method could also correctly predict the malignancy of one medullary thyroid carcinoma and one adenomatous goiter (benign). The diagnosis time is about 10 min for one specimen, and it is very promising for the intraoperative diagnosis of papillary thyroid carcinoma.

A Toll-receptor map underlies structural brain plasticity.

Experience alters brain structure, but the underlying mechanism remained unknown. Structural plasticity reveals that brain function is encoded in generative changes to cells that compete with destructive processes driving neurodegeneration. At an adult critical period, experience increases fiber number and brain size in Drosophila. Here, we asked if Toll receptors are involved. Tolls demarcate a map of brain anatomical domains. Focusing on Toll-2, loss of function caused apoptosis, neurite atrophy and impaired behaviour. Toll-2 gain of function and neuronal activity at the critical period increased cell number. Toll-2 induced cycling of adult progenitor cells via a novel pathway, that antagonized MyD88-dependent quiescence, and engaged Weckle and Yorkie downstream. Constant knock-down of multiple Tolls synergistically reduced brain size. Conditional over-expression of Toll-2 and wek at the adult critical period increased brain size. Through their topographic distribution, Toll receptors regulate neuronal number and brain size, modulating structural plasticity in the adult brain.

Everything that you experience leaves its mark on your brain. When you learn something new, the neurons involved in the learning episode grow new projections and form new connections. Your brain may even produce new neurons. Physical exercise can induce similar changes, as can taking antidepressants. By contrast, stress, depression, ageing and disease can have the opposite effect, triggering neurons to break down and even die. The ability of the brain to change in response to experience is known as structural plasticity, and it is in a tug-of-war with processes that drive neurodegeneration. Structural plasticity occurs in other species too: for example, it was described in the fruit fly more than a quarter of a century ago. Yet, the molecular mechanisms underlying structural plasticity remain unclear. Li et al. now show that, in fruit flies, this plasticity involves Toll receptors, a family of proteins present in the brain but best known for their role in the immune system. Fruit flies have nine different Toll receptors, the most abundant being Toll-2. When activated, these proteins can trigger a series of molecular events in a cell. Li et al. show that increasing the amount of Toll-2 in the fly brain makes the brain produce new neurons. Activating neurons in a brain region has the same effect, and this increase in neuron number also depends on Toll-2. By contrast, reducing the amount of Toll-2 causes neurons to lose their projections and connections, and to die, and impairs fly behaviour. Li et al. also show that each Toll receptor has a unique distribution across the fly brain. Different types of experiences activate different brain regions, and therefore different Toll receptors. These go on to trigger a common molecular cascade, but they modulate it such as to result in distinct outcomes. By working together in different combinations, Toll receptors can promote either the death or survival of neurons, and they can also drive specific brain cells to remain dormant or to produce new neurons. By revealing how experience changes the brain, Li et al. provide clues to the way neurons work and form; these findings may also help to find new treatments for disorders that change brain structure, such as certain psychiatric conditions. Toll-like receptors in humans could thus represent a promising new target for drug discovery.