[Clinical Characteristics and Risk Factors of ESKAPE Pathogens Bloodstream Infection in Cancer Patients].

OBJECTIVE: To identify the risk factors of ESKAPE pathogens infection and related death in cancer patients, and to supply evidence for clinical precaution and diagnosis. METHODS: A retrospective study of clinical and experimental data of cancer patients with bloodstream infection were carried out in Sichuan Cancer Hospital from 2013 to 2018. The clinical feature, predisposing factors and risk factors of death in ESKAPE group and non-ESKAPE group were analyzed by univariate analysis and multivariate logistic regression. RESULTS: A total of 753 patients were enrolled in the study. Totally 795 pathogenic bacteria strains were isolated from blood culture and there were 278 ESKAPE strains, which took up 34.97% of isolated strains. Univariate analysis and multivariate logistic regression analysis showed that gender of male, multiple pathogens, history of exposure to enzyme inhibitors and agranulocytosis were independent risk factors of ESKAPE pathogens bloodstream infection. Peritoneal infection and combined fungal infection were independent risk factors of ESKAPE bloodstream infection related death. CONCLUSION: The bloodstream infection of ESKAPE pathogens is a problem worthy of clinical attention for cancer patients with neutrophil deficiency, previous antibiotic exposure, and fungal infection and peritoneal infection.

Preoperative high c-reactive protein/albumin ratio is a poor prognostic factor of oral squamous cell carcinoma.

Aim: To explore whether c-reactive protein/albumin (CRP/Alb) ratio is a poor prognostic factor for patients with oral squamous cell carcinoma (OSCC). Patients & methods: Receiver-operating characteristic analysis was performed to evaluate the optimal cut-off value of CRP/Alb ratio in 240 patients with OSCC. The Kaplan-Meier method was used to plot the overall survival and disease-free survival curves. Cox proportional hazards model was used to implement univariate and multivariate analyses. Results: Preoperative high CRP/Alb ratio was associated with age, advanced stage, lymphatic metastasis, platelet-to-lymphocyte ratio and neutrophil-to-lymphocyte ratio (all p < 0.05). Elevated CRP/Alb ratio independently predicts worse overall survival and disease-free survival of patients with OSCC. Conclusion: Preoperative high CRP/Alb ratio was a poor independent prognostic marker of OSCC.

Identification and panoramic analysis of drug response-related genes in triple negative breast cancer using as an example NVP-BEZ235.

Taking NVP-BEZ235 (BEZ235) as an example to screen drug response-related genes (DRRGs) and explore their potential value in triple-negative breast cancer (TNBC). Through high-throughput technique, multidimensional transcriptome expression data (mRNA, miRNA and lncRNA) of BEZ235-treated and -untreated MDA-MB-468 cell lines were obtained. Combined with transcriptome data of the MDA-MB-468 cells and TCGA-TNBC tissues, differential gene expression analysis and WGCNA were performed to identify DRRGs associated with tumor trait by simulating the drug response microenvironment (DRM) of BEZ235-treated patients. Based on DRRGs, we constructed a ceRNA network and verified the expression levels of three key molecules by RT-qPCR, which not only demonstrated the successful construction of a BEZ235-treated cell line model but also explained the antitumor mechanism of BEZ235. Four molecular subtypes related to the DRM with survival difference were proposed using cluster analysis, namely glycolysis subtype, proliferation depression subtype, immune-suppressed subtype, and immune-activated subtype. A novel prognostic signature consisting of four DRRGs was established by Lasso-Cox analysis, which exhibited outstanding performance in predicting overall survival compared with several excellent reported signatures. The high- and low-risk groups were characterized by enrichment of metabolism-related pathways and immune-related pathways, respectively. Of note, the low-risk group had a better response to immune checkpoint blockade. Besides, pRRophetic analysis found that patients in the low-risk group were more sensitive to methotrexate and cisplation, whereas more resistant to BEZ235, docetaxel and paclitaxel. In conclusion, the DRRGs exemplified by BEZ235 are potential biomarkers for TNBC molecular typing, prognosis prediction and targeted therapy. The novel DRRGs-guided strategy for predicting the subtype, survival and therapy efficacy, might be also applied to more cancers and drugs other than TNBC and BEZ235.

Machine learning­based prediction of survival prognosis in esophageal squamous cell carcinoma.

The current prognostic tools for esophageal squamous cell carcinoma (ESCC) lack the necessary accuracy to facilitate individualized patient management strategies. To address this issue, this study was conducted to develop a machine learning (ML) prediction model for ESCC patients' survival management. Six ML approaches, including Rpart, Elastic Net, GBM, Random Forest, GLMboost, and the machine learning-extended CoxPH method, were employed to develop risk prediction models. The model was trained on a dataset of 1954 ESCC patients with 27 clinical features and validated on a dataset of 487 ESCC patients. The discriminative performance of the models was assessed using the concordance index (C-index). The best performing model was used for risk stratification and clinical evaluation. The study found that N stage, T stage, surgical margin, tumor grade, tumor length, sex, MPV, AST, FIB, and Mg are the important feature for ESCC patients' survival. The machine learning-extended CoxPH model, Elastic Net, and Random Forest had similar performance in predicting the mortality risk of ESCC patients, and outperformed GBM, GLMboost, and Rpart. The risk scores derived from the CoxPH model effectively stratified ESCC patients into low-, intermediate-, and high-risk groups with distinctly different 3-year overall survival (OS) probabilities of 80.8%, 58.2%, and 29.5%, respectively. This risk stratification was also observed in the validation cohort. Furthermore, the risk model demonstrated greater discriminative ability and net benefit than the AJCC8th stage, suggesting its potential as a prognostic tool for predicting survival events and guiding clinical decision-making. The classical algorithm of the CoxPH method was also found to be sufficiently good for interpretive studies.

Platelet-Based Nanoparticles with Stimuli-Responsive for Anti-Tumor Therapy.

In addition to hemostasis and coagulation, years of studies have proved that platelets are involved in the whole process of tumor progression, including tumor invasion, intravasation, extravasation, and so on. It means that this property of platelets can be used in anti-tumor therapy. However, traditional platelet-based antitumor drugs often cause autologous platelet damage due to lack of targeting, resulting in serious side effects. Therefore, the researchers designed a variety of anti-tumor drug delivery systems based on platelets by targeting platelets or platelet membrane coating. The drug delivery systems have special response modes, which is crucial in the design of nanoparticles. These modes enhance the targeting and improve the anti-tumor effect. Here, we present a review of recent discoveries in the field of the crosstalk between platelets and tumors and the progress of platelet-based anti-tumor nanoparticles.

A novel prognostic model for malignant patients with Gram-negative bacteremia based on real-world research.

Gram-negative bacteremia (GNB) is a common complication in malignant patients. Identifying risk factors and developing a prognostic model for GNB might improve the survival rate. In this observational and real-world study, we retrospectively analyzed the risk factors and outcomes of GNB in malignant patients. Multivariable regression was used to identify risk factors for the incidence of GNB, while Cox regression analysis was performed to identify significant prognostic factors. A prognostic model was constructed based on Cox regression analysis and presented on a nomogram. ROC curves, calibration plots, and Kaplan-Meier analysis were used to estimate the model. It comprised 1004 malignant patients with Bloodstream infection (BSI) in the study cohort, 65.7% (N = 660) acquired GNB. Multivariate analysis showed gynecologic cancer, hepatobiliary cancer, and genitourinary cancer were independent risk factors related to the incidence of GNB. Cox regression analysis raised that shock, admission to ICU before infection, pulmonary infection, higher lymphocyte counts, and lower platelet counts were independent risk factors for overall survival (OS). The OS was significantly different between the two groups classified by optimal cut-off value (log-rank, p < 0.001). Above all, a nomogram was created based on the prognostic model, which was presented on a website freely. This real-world study was concentrated on the malignant patients with GNB and proved that shock, admission to ICU before infection, pulmonary infection, higher lymphocyte counts, and lower platelet counts were related to the death of these patients. And a prognostic model was constructed to estimate the risk score of mortality, further to reduce the risk of death.

Prognostic value of nutritional and inflammatory indicators in females with esophageal squamous cell cancer: A propensity score matching study.

Background: Esophageal squamous cell cancer (ESCC) is a disease with a male predominance. Accordingly, the applicability of prognostic indicators values previously set for the general population with ESCC has not been reported for determining the physical state in females. Methods: Patients with ESCC were pooled from 2009 to 2017 at Sichuan Cancer Hospital. We determined the differences in the nutritional and inflammatory indicators between gender by sex-stratified survival analysis in all cohorts (n = 2,660) and matching cohorts (n = 483 pairs) separately. Propensity score matching (PSM) was employed to eliminate selection bias between genders. We further performed the prognostic value of total cholesterol (TC) by subgroup analysis in the female cohort. The area ROC curve was used to assess the predictive performance of TC in females. Results: There were a total of 2,660 patients with ESCC, of whom 2,173 (81.7%) were male and 487 (18.3%) were female. Before PSM, the prognostic nutritional index was an independent factor for OS in males but not in females. For cohort with or without matching, TC was an independent prognostic factor in females not for males. Furthermore, female patients with high TC level had significant poor OS in stages III and IV. The AUCs of TC were 0.63 and 0.70 for predicting 3- and 5-year OS, respectively. Conclusion: Based on a much larger cohort, we confirmed that gender was a significant prognostic factor for ESCC patients. Interestingly, we found a significant difference in TC related to ESCC prognosis between genders. Collectively, TC might be an independent prognostic factor in females with ESCC.