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Colorectal cancer (CRC) represents the third most common type of cancer in developed countries and one of the leading causes of cancer deaths worldwide. Personalized management of CRC has gained increasing attention since there are large inter-individual variations in the prognosis and response to drugs used to treat CRC owing to molecular heterogeneity. Approximately 15% of CRCs are caused by deficient mismatch repair (dMMR) characterized by microsatellite instability (MSI) phenotype. The present review is aimed at highlighting the role of MMR status in informing prognosis and personalized treatment of CRC including adjuvant chemotherapy, targeted therapy, and immune checkpoint inhibitor therapy to guide the individualized therapy of CRC.

IntroductionThis longitudinal study aims to characterize distinct body mass index (BMI) trajectories during early to mid-life adulthood and to explore the association between BMI change from young adulthood to midlife and incident diabetes.Research design and methodsThis study included 7289 adults who had repeatedly measured BMI 3–9 times during 1989–2011 and information on incident diabetes. Latent class growth mixed model (LCGMM) was used to identify different BMI trajectories. Cox proportional hazard models were used to investigate the association between the trajectory group membership and incident hyperglycemia, adjusting for covariates. The hyperglycemia group included individuals with prediabetes or diabetes. The model-estimated BMI levels and slopes were calculated at each age point in 1-year intervals according to the model parameters and their first derivatives, respectively. Logistic regression analyses were used to examine the association of model-estimated levels and slopes of BMI at each age point with incident hyperglycemia. The area under the curve (AUC) was computed from longitudinal growth curve models during the follow-up for each individual. Prior to the logistic regression analyses, quartiles of total, baseline, and incremental AUC values were calculated.ResultsThree distinct trajectories were characterized by LCGMM, comprising of low-increasing group (n=5136), medium-increasing group (n=1914), and high-increasing group (n=239). Compared with the low-increasing group, adjusted HRs and 95% CIs were 1.21 (0.99 to 1.48) and 1.56 (1.06 to 2.30) for the medium-increasing and the high-increasing group, respectively. The adjusted standardized ORs of model-estimated BMI levels increased among 20–50 years, ranging from 0.98 (0.87 to 1.10) to 1.19 (1.08 to 1.32). The standardized ORs of level-adjusted linear slopes increased gradually from 1.30 (1.16 to 1.45) to 1.42 (1.21 to 1.67) during 20–29 years, then decreased from 1.41 (1.20 to 1.66) to 1.20 (1.08 to 1.33) during 30–43 years, and finally increased to 1.20 (1.04 to 1.38) until 50 years. The fourth quartile of incremental AUC (OR=1.31, 95% CI 1.03 to 1.66) was significant compared with the first quartile, after adjustment for covariates.ConclusionsThese findings indicate that the BMI trajectories during early adulthood were significantly associated with later-life diabetes. Young adulthood is a crucial period for the development of diabetes, which has implications for early prevention.

Pregnane X receptor (PXR) is a member of the nuclear receptor superfamily that differently expresses not only in human normal tissues but also in numerous types of human cancers. PXR can be activated by many endogenous substances and exogenous chemicals, and thus affects chemotherapeutic effects and intervenes drug–drug interactions by regulating its target genes involving drug metabolism and transportation, cell proliferation and apoptosis, and modulating endobiotic homeostasis. Tissue and context-specific regulation of PXR contributes to diverse effects in the treatment for numerous cancers. Genetic variants of PXR lead to intra- and inter-individual differences in the expression and inducibility of PXR, resulting in different responses to chemotherapy in PXR-positive cancers. The purpose of this review is to summarize and discuss the role of PXR in the metabolism and clearance of anticancer drugs. It is also expected that this review will provide insights into PXR-mediated enhancement for chemotherapeutic treatment, prediction of drug–drug interactions and personalized medicine.

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Determination of the postmortem interval (PMI) is crucial for investigating homicide. However, there are currently only limited methods available. Especially, once the PMI exceeds the duration of pre-adult development of the flies with the adult emergence, its determination is very approximate. Herein, we report the regular changes in hydrocarbon composition during the weathering process of the puparia in the field in Chrysomya megacephala (Fabricius) (Diptera: Calliphoridae), one of the common species of necrophagous flies. Correlation analysis showed that the relative abundance of nearly all of the branched alkanes and alkenes decreased significantly with the weathering time. Especially, for 9 of the peaks, over 88% of the variance in their abundance was explained by weathering time. Further analysis indicated that the regular changes caused mainly by the different weathering rates of various hydrocarbons. Additionally, the weathering rates were found to depend on the chemical structure and molecular weight of the hydrocarbons. These results indicate strongly that hydrocarbon analysis is a powerful tool for determining the weathering time of the necrophagous fly puparia, and is expected to markedly improve the determination of the late PMI.

Epigenetics, referring to alterations in gene expression without a change in nucleotide sequence in eukaryotes, mainly includes DNA methylation, miRNA and histone modification. In recent years, accumulating evidences have shown that epigenetic aberrations not only play important roles in the initiation and development of human cancers but also affect cancer chemotherapy response by altering the expression of key genes involved in the absorption, distribution, metabolism and excretion of drugs or those correlated with progression or severity of cancers. These epigenetic alterations, along with advanced detecting techniques, have great potential to be used as predictive and prognostic biomarkers for personalized therapy, especially in the field of cancer treatment. Here we provide an overview of recent findings on epigenetic alterations involved in cancer chemotherapy response, with the aim of promoting rational use of chemotherapy drugs in the clinic.

SummaryUnderstanding the metabolic features of myocardial infarction (MI) is critical to its prevention and treatment. Here, we aimed to characterize the metabolic features of early MI using a tissue metabolomics method based on gas chromatography-mass spectrometry (GC-MS). Thirty-four pairs of infarcted myocardia and their matched non-infarcted myocardia were collected from 34 rats that underwent coronary artery ligation (CAL); their metabolic profiles were compared by GC-MS-based tissue metabolomics to characterize the metabolic features of MI. On the basis of differential metabolites, their diagnostic potential for MI was analyzed, and MI-related metabolic pathways were investigated. Serum samples before and post MI were used to validate the results obtained in myocardia. The metabolic profile of the infarcted myocardia was obviously different from that of the non-infarcted myocardia, as indicated by partial least squares discriminate analysis (PLS-DA) plots. Twenty-two metabolites were identified to be different between the infarcted myocardia and non-infarcted myocardia. These metabolic alterations reflect energy deficit, acidosis, oxidative stress, ionic imbalance, and cardiac injury post MI. Glutamine, glutamate, and lactate were confirmed to jointly confer a favorable potential for diagnosing MI, which can be well validated in serum. (Int Heart J 2017; 58: 441-446) Key words: Myocardial ischemia, Metabolic feature, Glutamate, Self-control study M yocardial ischemia is a leading cause of morbidity and mortality, accounting for approximately 12 million deaths annually worldwide, and is expected to continue to be a serious problem all over the world.1) Metabolism is among the first area affected post myocardial ischemia, which can then lead to different deleterious consequences, such as arrhythmia, myocardial infarction (MI), and heart failure, 2) and the latter is an irreversible myocardial injury secondary to persistent myocardial ischemia.3) Therefore, understanding metabolic features of MI is critical to its prevention and control.Several clinical studies concerning metabolic changes in plasma of MI have been carried out. The metabolic profiles of MI in plasma or serum of MI patients are increasingly being determined. Several potential biomarkers of MI or myocardial ischemia, such as phytosphingosine, sphinganine, acetylcarnitine, adenine, and inosine have been suggested. [4][5][6][7] However, circulating biomarkers may be easily influenced by diverse tissues which may affect their specifity.Thus, we should elucidate the global metabolic changes of myocardia per se, which serve as a source of systemic metabolic alterations post MI, as they are not yet fully understood. Such an understanding not only helps to explore the pathophysiological mechanisms of MI, but can also validate the results of clinical studies. Therefore, it needs to be retrotranslated from the clinical study stage to the animal study stage. Coronary artery ligation (CAL) rat models are widely used to study related pathophysiological ...