Preliminary study on proteomics of gastric carcinoma and its clinical significance

AIM: To explore the preliminary identification of serum protein pattern models that may be novel potential biomarkers in the detection of gastric cancer.METHODS: A total of 130 serum samples, including 70 from patients with gastric cancer and 60 from healthy adults, were detected by surface-enhanced laser desorption and ionization time-of-flight mass spectrometry (SELDI-TOF-MS). The data of spectra were analyzed by Biomarker Patterns Software (BPS). Thirty serum samples of gastric cancer patients and 30 serum samples of healthy adults were grouped into the training group to build models, and the other 70 samples were used to test and evaluate the models. The samples of the test group were judged only with their peaks'height and were separated into cancer group or healthy control group by BPS automatically and the judgments were checked with the histopathologic diagnosis of the samples.RESULTS: Sixteen mass peaks were found to be potential biomarkers with a significant level of P＜0.01.Among them, nine mass peaks showed increased expression in patients with gastric cancer. Analyzed by BPS, two peaks were chosen to build the model for gastric cancer detection. The sensitivity, specificity, and accuracy of the model were 90%, 36/40, 86.7%, 26/30,and 88.6%, 62/70, respectively, which were greatly higher than those of clinically used serum biomarkers CEA (carcinoembryonic antigen), CA19-9 and CA72-4.Stage Ⅰ/Ⅱ gastric cancer samples of the test group were all judged correctly.CONCLUSION: The novel biomarkers in serum and the established model could be potentially used in the detection of gastric cancer. However, large-scale studies should be carried on to further explore the clinical impact on the model.

Effect of Traditional Chinese Medicine inImproving Hot Flashes Symptom ofBreast Cancer

Breast cancer (BC) is the most common malignant tumor in women. Around 50% of BC receptor-positive patients are hormone-dependent cases, and it is necessary for them to use endocrine after operation. Through inhibition of estrogen level

Investigation of Common Symptoms of Cancer and Reliability Analysis

Objective： To identify cancer distribution and treatment requirements, a questionnaire on cancer patients was conducted. It was our objective to validate a series of symptoms commonly used in traditional Chinese medicine （TCM）. Methods： The M. D. Anderson Symptom Assessment Inventory （MDASI） was used with 10 more TCM items added. Questions regarding TCM application requested in cancer care were also asked. A multi-center, cross-sectional study was conducted in 340 patients from 4 hospitals in Beijing and Dalian. SPSS and Excel software were adopted for statistical analysis. The questionnaire was self-evaluated with the Cronbach＇s alpha score. Results： The most common symptoms were fatigue 89.4%, sleep disturbance 74.4%, dry mouth 72.9%, poor appetite 72.9%, and difficulty remembering 71.2%. These symptoms affected work （89.8%）, mood （82.6%）, and activity （76.8%）, resulting in poor quality of life. Eighty percent of the patients wanted to regulate the body with TCM. Almost 100% of the patients were interested in acquiring knowledge regarding the integrated traditional Chinese medicine （TCM） and Western medicine （WM） in the treatment and rehabilitation of cancer. Cronbach＇s alpha score indicated that there was acceptable internal consistency within both the MDASI and TCM items, 0.86 for MDASI, 0.78 for TCM, and 0.90 for MDASI-TCM （23 items）. Conclusions： Fatigue, sleep disturbance, dry mouth, poor appetite, and difficulty remembering are the most common symptoms in cancer patients. These greatly affect the quality of life for these patients. Patients expressed a strong desire for TCM holistic regulation. The MDASI and its TCM-adapted model could be a critical tool for the quantitative study of TCM symptoms.