DUSP12 regulates the tumorigenesis and prognosis of hepatocellular carcinoma

An engineered niche delineates metastatic potential of breast cancer

Metastatic breast cancer is often not diagnosed until secondary tumors have become macroscopically visible and millions of tumor cells have invaded distant tissues. Yet, metastasis is initiated by a cascade of events leading to formation of the pre-metastatic niche, which can precede tumor formation by a matter of years. We aimed to distinguish the potential for metastatic disease from nonmetastatic disease at early times in triple-negative breast cancer using sister cell lines 4T1 (metastatic), 4T07 (invasive, nonmetastatic), and 67NR (nonmetastatic). We used a porous, polycaprolactone scaffold, that serves as an engineered metastatic niche, to identify metastatic disease through the characteristics of the microenvironment. Analysis of the immune cell composition at the scaffold was able to distinguish noninvasive 67NR tumor-bearing mice from 4T07 and 4T1 tumor-bearing mice but could not delineate metastatic potential between the two invasive cell lines. Gene expression in the scaffolds correlated with the up-regulation of cancer hallmarks (e.g., angiogenesis, hypoxia) in the 4T1 mice relative to 4T07 mice. We developed a 9-gene signature (Dhx9, Dusp12, Fth1, Ifitm1, Ndufs1, Pja2, Slc1a3, Soga1, Spon2) that successfully distinguished 4T1 disease from 67NR or 4T07 disease throughout metastatic progression. Furthermore, this signature proved highly effective at distinguishing diseased lungs in publicly available datasets of mouse models of metastatic breast cancer and in human models of lung cancer. The early and accurate detection of metastatic disease that could lead to early treatment has the potential to improve patient outcomes and quality of life.

Dual-specificity phosphatase 12 attenuates oxidative stress injury and apoptosis in diabetic cardiomyopathy via the ASK1-JNK/p38 signaling pathway

Diabetic cardiomyopathy (DCM) is ventricular dysfunction that occurs in patients with diabetes mellitus (DM), independent of recognized risk factors, such as coronary artery disease, hypertension, and valvular heart disease. Dual-specificity phosphatase 12 (DUSP12) is a dual-specificity phosphatase expressed in all tissues. Genome-wide linkage studies have found an association between DUSP12 and type 2 diabetes (T2D). However, the role of DUSP12 in DCM remains largely unknown. Ubiquitously expressed DUSP12 is involved in nonalcoholic fatty liver disease, bacterial infection, and myocardial hypertrophy and plays a critical role in tumorigenesis. Herein, we observed an increased expression of DUSP12 in a hyperglycemia cell model and a high-fat diet (HFD) mouse model. Heart-specific DUSP12-deficient mice showed severe cardiac dysfunction and remodeling induced by an HFD. DUSP12 deficiency exacerbated oxidative stress injury and apoptosis, whereas DUSP12 overexpression had the opposite effect. At the molecular level, DUSP12 physically bound to apoptotic signal-regulated kinase 1 (ASK1), promoted its dephosphorylation, and inhibited its action on c-Jun N-terminal kinase and p38 mitogen-activated protein kinase. Rescue experiments have shown that oxidative stress injury and apoptosis, exacerbated by DUSP12 deficiency, are alleviated by ASK1 inhibition. Therefore, we consider DUSP12 an important signaling pathway in DCM.

A Potential Prognostic Marker for Recognizing VEGF-Positive Hepatocellular Carcinoma Based on Magnetic Resonance Radiomics Signature

Objectives

The objective of our project is to explore a noninvasive radiomics model based on magnetic resonance imaging (MRI) that could recognize the expression of vascular endothelial growth factor (VEGF) in hepatocellular carcinoma before operation.

Methods

202 patients with proven single HCC were enlisted and stochastically distributed into a training set (n = 142) and a test set (n = 60). Arterial phase, portal venous phase, balanced phase, delayed phase, and hepatobiliary phase images were used to radiomics features extraction. We retrieved 1906 radiomic features from each phase of every participant’s MRI images. The F-test was applied to choose the crucial features. A logistic regression model was adopted to generate a radiomics signature. By combining independent risk indicators from the fusion radiomics signature and clinico-radiological features, we developed a multivariable logistic regression model that could predict the VEGF status preoperatively through calculating the area under the curve (AUC).

Results

The entire group comprised 108 VEGF-positive individuals and 94 VEGF-negative patients. AUCs of 0.892 (95% confidence interval [CI]: 0.839 - 0.945) in the training dataset and 0.800 (95% CI: 0.682 - 0.918) in the test dataset were achieved by utilizing radiomics features from two phase images (8 features from the portal venous phase and 5 features from the hepatobiliary phase). Furthermore, the nomogram relying on a combined model that included the clinical factors α-fetoprotein (AFP), irregular tumor margin, and the fusion radiomics signature performed well in both the training (AUC = 0.936, 95% CI: 0.898-0.974) and test (AUC = 0.836, 95% CI: 0.728-0.944) datasets.

Conclusions

The combined model acquired from two phase (portal venous and hepatobiliary phase) pictures of gadolinium-ethoxybenzyl-diethylenetriamine-pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI could be considered as a credible prognostic marker for the level of VEGF in HCC.

Insights into the Association Between QSER1 and M2 Macrophages and Remarkable Malignancy Characteristics in Hepatocellular Carcinoma

Purpose

Glutamine and serine rich 1 (QSER1), as a DNA methylation modulator, play a crucial role in transforming tumor cells. Previous studies have shown that QSER1 plays a role in regulating the progression of various malignancies and that QSER1 dysfunction is connected with precancerous lesions of hepatocellular carcinoma (HCC) as well as HCC prognosis. However, little is known about the detailed contribution of QSER1 in HCC.

Patients and Methods

Various statistical methods such as Kaplan–Meier method, AUC analysis, GSEA, and immune-infiltration analysis were used to evaluate the relationship between QSER1 expression and clinical features, prognostic factors, and potential functional mechanisms of QSER1.

Results

QSER1 expression was negatively correlated with clinicopathological features (clinical stage, pathological grade, TP53 mutation, lymph node metastasis) and clinical outcome (overall survival versus recurrence). Functional enrichment analysis further suggested that QSER1 is involved in multiple pathways related to DNA replication and tumor immunity. TIMER analysis indicated that high QSER1 expression was significantly associated with higher macrophage infiltration and poorer macrophage-related outcomes. In particular, QSER1 was significantly more associated with M2 macrophages than M1 macrophages.

Conclusion

Overall, elevated QSER1 is a potential prognostic marker for HCC and is associated with immune infiltration in HCC.