A Novel Inflammation-Based Risk Score Predicts Mortality in Acute Type A Aortic Dissection Surgery: The Additive Anti-inflammatory Action for Aortopathy and Arteriopathy Score.

Objective: To develop an inflammation-based risk stratification tool for operative mortality in patients with acute type A aortic dissection. Methods: Between January 1, 2016 and December 31, 2021, 3124 patients from Beijing Anzhen Hospital were included for derivation, 571 patients from the same hospital were included for internal validation, and 1319 patients from other 12 hospitals were included for external validation. The primary outcome was operative mortality according to the Society of Thoracic Surgeons criteria. Least absolute shrinkage and selection operator regression were used to identify clinical risk factors. A model was developed using different machine learning algorithms. The performance of the model was determined using the area under the receiver operating characteristic curve (AUC) for discrimination, calibration curves, and Brier score for calibration. The final model (5A score) was tested with respect to the existing clinical scores. Results: Extreme gradient boosting was selected for model training (5A score) using 12 variables for prediction-the ratio of platelet to leukocyte count, creatinine level, age, hemoglobin level, prior cardiac surgery, extent of dissection extension, cerebral perfusion, aortic regurgitation, sex, pericardial effusion, shock, and coronary perfusion-which yields the highest AUC (0.873 [95% confidence interval (CI) 0.845-0.901]). The AUC of 5A score was 0.875 (95% CI 0.814-0.936), 0.845 (95% CI 0.811-0.878), and 0.852 (95% CI 0.821-0.883) in the internal, external, and total cohort, respectively, which outperformed the best existing risk score (German Registry for Acute Type A Aortic Dissection score AUC 0.709 [95% CI 0.669-0.749]). Conclusion: The 5A score is a novel, internally and externally validated inflammation-based tool for risk stratification of patients before surgical repair, potentially advancing individualized treatment. Trial Registration: clinicaltrials.gov Identifier: NCT04918108.

Circulating biomarker-based risk stratifications individualize arch repair strategy of acute Type A aortic dissection via the XGBoosting algorithm.

Aims: The incremental usefulness of circulating biomarkers from different pathological pathways for predicting mortality has not been evaluated in acute Type A aortic dissection (ATAAD) patients. We aim to develop a risk prediction model and investigate the impact of arch repair strategy on mortality based on distinct risk stratifications. Methods and results: A total of 3771 ATAAD patients who underwent aortic surgery retrospectively included were randomly divided into training and testing cohorts at a ratio of 7:3 for the development and validation of the risk model based on multiple circulating biomarkers and conventional clinical factors. Extreme gradient boosting was used to generate the risk models. Subgroup analyses were performed by risk stratifications (low vs. middle-high risk) and arch repair strategies (proximal vs. extensive arch repair). Addition of multiple biomarkers to a model with conventional factors fitted an ABC risk model consisting of platelet-leucocyte ratio, mean arterial pressure, albumin, age, creatinine, creatine kinase-MB, haemoglobin, lactate, left ventricular end-diastolic dimension, urea nitrogen, and aspartate aminotransferase, with adequate discrimination ability {area under the receiver operating characteristic curve (AUROC): 0.930 [95% confidence interval (CI) 0.906-0.954] and 0.954, 95% CI (0.930-0.977) in the derivation and validation cohort, respectively}. Compared with proximal arch repair, the extensive repair was associated with similar mortality risk among patients at low risk [odds ratio (OR) 1.838, 95% CI (0.559-6.038); P = 0.316], but associated with higher mortality risk among patients at middle-high risk [OR 2.007, 95% CI (1.460-2.757); P < 0.0001]. Conclusion: In ATAAD patients, the simultaneous addition of circulating biomarkers of inflammatory, cardiac, hepatic, renal, and metabolic abnormalities substantially improved risk stratification and individualized arch repair strategy.

GRP78 facilitates M2 macrophage polarization and tumour progression.

This study investigated the regulation of GRP78 in tumour-associated macrophage polarization in lung cancer. First, our results showed that GRP78 was upregulated in macrophages during M2 polarization and in a conditioned medium derived from lung cancer cells. Next, we found that knocking down GRP78 in macrophages promoted M1 differentiation and suppressed M2 polarization via the Janus kinase/signal transducer and activator of transcription signalling. Moreover, conditioned medium from GRP78- or insulin-like growth factor 1-knockdown macrophages attenuated the survival, proliferation, and migration of lung cancer cells, while conditioned medium from GRP78-overexpressing macrophages had the opposite effects. Additionally, GRP78 knockdown reduced both the secretion of insulin-like growth factor 1 and the phosphorylation of the insulin-like growth factor 1 receptor. Interestingly, insulin-like growth factor 1 neutralization downregulated GRP78 and suppressed GRP78 overexpression-induced M2 polarization. Mechanistically, insulin-like growth factor 1 treatment induced the translocation of GRP78 to the plasma membrane and promoted its association with the insulin-like growth factor 1 receptor. Finally, IGF-1 blockade and knockdown as well as GRP78 knockdown in macrophages inhibited M2 macrophage-induced survival, proliferation, and migration of lung cancer cells both in vitro and in vivo.

Long non-coding RNAs: a rising biotarget in colorectal cancer.

Colorectal cancer (CRC) is a common gastrointestinal cancer, with a high incidence and high mortality. Long non-coding RNAs (lncRNAs) are involved in the development, invasion and metastasis, early diagnosis, prognosis, the chemoresistance and radioresistance of CRC through interference with mRNA activity, directly combining with proteins to regulate their activity or alter their localization, influencing downstream gene expression by inhibiting RNA polymerase and regulating gene expression as competing endogenous RNAs. Recent progress in next generation sequencing and transcriptome analysis has revealed that tissue and cancer-type specific lncRNAs could be useful prognostic markers. Here, the CRC-associated lncRNAs from recent studies until October 2016 are reviewed and multiple studies that have confirmed CRC-associated lncRNAs are summarized. This review may be helpful in understanding the overall relationships between the lncRNAs involved in CRC.