Identification of biomarkers for radiation-induced acute intestinal symptoms (RIAISs) in cervical cancer patients by serum protein profiling

Decision Tree Analysis: A Retrospective Analysis of Postoperative Recurrence of Adhesions in Patients with Moderate-to-Severe Intrauterine

OBJECTIVE

To establish and validate a decision tree model to predict the recurrence of intrauterine adhesions (IUAs) in patients after separation of moderate-to-severe IUAs.

DESIGN

A retrospective study.

SETTING

A tertiary hysteroscopic center at a teaching hospital.

POPULATION

Patients were retrospectively selected who had undergone hysteroscopic adhesion separation surgery for treatment of moderate-to-severe IUAs.

INTERVENTIONS

Hysteroscopic adhesion separation surgery and second-look hysteroscopy 3 months later.

MEASUREMENTS AND MAIN RESULTS

Patients' demographics, clinical indicators, and hysteroscopy data were collected from the electronic database of the hospital. The patients were randomly apportioned to either a training or testing set (332 and 142 patients, respectively). A decision tree model of adhesion recurrence was established with a classification and regression tree algorithm and validated with reference to a multivariate logistic regression model. The decision tree model was constructed based on the training set. The classification node variables were the risk factors for recurrence of IUAs: American Fertility Society score (root node variable), isolation barrier, endometrial thickness, tubal opening, uterine volume, and menstrual volume. The accuracies of the decision tree model and multivariate logistic regression analysis model were 75.35% and 76.06%, respectively, and areas under the receiver operating characteristic curve were 0.763 (95% CI 0.681-0.846) and 0.785 (95% CI 0.702-0.868).

CONCLUSIONS

The decision tree model can readily predict the recurrence of IUAs and provides a new theoretical basis upon which clinicians can make appropriate clinical decisions.

Artificial intelligence identified peptides modulate inflammation in healthy adults

Dietary bioactive peptides have been, among many functionalities, associated with immune modulation and thereby may improve resolution of inflammation. The goals of this research were to assess (1) whether specific peptides with immune-modulating activity consumed as part of a rice protein hydrolysate could be absorbed into blood and (2) whether they modulate inflammation markers. Artificial intelligence algorithms were applied to target, predict and unlock inflammation-modulating peptides from rice protein. A food application was developed containing four bioactive peptides. Protein docking simulation studies revealed high binding energies of these peptides with inflammation markers. In a small kinetic study 10 healthy subjects consumed the peptides with a single bolus of 20 g protein hydrolysate. Although absorption of the four predicted peptides at plasma concentrations deemed biologically relevant could not be confirmed (quantitative LC-MS/MS), several cytokines responded (ELISA kits). The 24-hour kinetic study revealed a slight suppression of pro-inflammatory TNF-α, IP-10 and NOx, whereas IL-6 increased temporarily (timepoints 2-12 hours). These markers returned to the baseline after 24 hours whereas others were not affected significantly (IL-10, hs-CRP, IL-8, and MCP-1). Consumption of a single dose protein hydrolysate containing immune modulatory peptides induced a mild temporary response most likely through intestinal signaling. Forthcoming studies will examine dietary supplementation in situations of stress.

Protein calorie malnutrition, nutritional intervention and personalized cancer care

Cancer patients often experience weight loss caused by protein calorie malnutrition (PCM) during the course of the disease or treatment. PCM is expressed as severe if the patient has two or more of the following characteristics: obvious significant muscle wasting, loss of subcutaneous fat; nutritional intake of <50% of recommended intake for 2 weeks or more; bedridden or otherwise significantly reduced functional capacity; weight loss of >2% in 1 week, 5% in 1 month, or 7.5% in 3 months. Cancer anorexia-cachexia syndrome (CACS) is a multifactorial condition of advanced PCM associated with underlying illness (in this case cancer) and is characterized by loss of muscle with or without loss of fat mass. Cachexia is defined as weight loss of more than 5% of body weight in 12 months or less in the presence of chronic disease. Hence with a chronic illness on board even a small amount of weight loss can open the door to cachexia. These nutritional challenges can lead to severe morbidity and mortality in cancer patients. In the clinic, the application of personalized medicine and the ability to withstand the toxic effects of anti-cancer therapies can be optimized when the patient is in nutritional homeostasis and is free of anorexia and cachexia. Routine assessment of nutritional status and appropriate intervention are essential components of the effort to alleviate effects of malnutrition on quality of life and survival of patients.

Systemic effects of ionizing radiation at the proteome and metabolome levels in the blood of cancer patients treated with radiotherapy: the influence of inflammation and radiation toxicity

PURPOSE

Blood is the most common replacement tissue used to study systemic responses of organisms to different types of pathological conditions and environmental insults. Local irradiation during cancer radiotherapy induces whole body responses that can be observed at the blood proteome and metabolome levels. Hence, comparative blood proteomics and metabolomics are emerging approaches used in the discovery of radiation biomarkers. These techniques enable the simultaneous measurement of hundreds of molecules and the identification of sets of components that can discriminate different physiological states of the human body. Radiation-induced changes are affected by the dose and volume of irradiated tissues; hence, the molecular composition of blood is a hypothetical source of biomarkers for dose assessment and the prediction and monitoring of systemic responses to radiation. This review aims to provide a comprehensive overview on the available evidence regarding molecular responses to ionizing radiation detected at the level of the human blood proteome and metabolome. It focuses on patients exposed to radiation during cancer radiotherapy and emphasizes effects related to radiation-induced toxicity and inflammation.

CONCLUSIONS

Systemic responses to radiation detected at the blood proteome and metabolome levels are primarily related to the intensity of radiation-induced toxicity, including inflammatory responses. Thus, several inflammation-associated molecules can be used to monitor or even predict radiation-induced toxicity. However, these abundant molecular features have a rather limited applicability as universal biomarkers for dose assessment, reflecting the individual predisposition of the immune system and tissue-specific mechanisms involved in radiation-induced damage.

Application of 1H NMR spectroscopy-based metabonomics to feces of cervical cancer patients with radiation-induced acute intestinal symptoms

OBJECTIVE

Radiation-induced acute intestinal symptoms (RIAISs) are a common complication of radiotherapy for cervical cancer. The aim of this study was to use (1)H nuclear magnetic resonance ((1)H NMR) combined with chemometric analysis to develop a metabolic profile of patients with RIAISs.

METHODS

Fecal samples were collected from 66 patients with cervical cancer before and after pelvic radiotherapy. After radiotherapy, RIAISs occurred in eleven patients. We selected another 11 patients from participants without RIAISs whose age, stage, histological type and treatment methods are matched with RIAIS patients as the control group. (1)H NMR spectroscopy combined with multivariate pattern recognition analysis was used to generate metabolic profile data, as well as to establish a RIAIS-specific metabolic phenotype.

RESULTS

Orthogonal partial least-squares discriminant analysis was used to distinguish samples between the pre- and post-radiotherapy RIAIS patients and between RIAIS patients and controls. Fecal samples from RIAIS patients after pelvic radiotherapy were characterized by increased concentrations of α-ketobutyrate, valine, uracil, tyrosine, trimethylamine N-oxide, phenylalanine, lysine, isoleucine, glutamine, creatinine, creatine, bile acids, aminohippurate, and alanine, accompanied by reduced concentrations of α-glucose, n-butyrate, methylamine, and ethanol relative to samples from RIAIS patients before pelvic radiotherapy, while in RIAIS patients relative to controls, trimethylamine, n-butyrate, fumarate and acetate were down-regulated and valine, TMAO, taurine, phenylalanine, lactate, isoleucine and creatinine were up-regulated.

CONCLUSIONS

We obtained the metabolic profile of RIAIS patients from fecal samples using NMR-based metabonomics. This profile has the potential to be developed into a novel clinical tool for RIAIS diagnosis or therapeutic monitoring, and could contribute to an improved understanding of the disease mechanism. However, because of the limitations of methods, technique, bacterial contamination of feces and small sample size, further research and verification are needed.