Metabolic history impacts mammary tumor epithelial hierarchy and early drug response in mice

Integrated bioinformatical analysis, machine learning and in vitro experiment-identified m6A subtype, and predictive drug target signatures for diagnosing renal fibrosis

Renal biopsy is the gold standard for defining renal fibrosis which causes calcium deposits in the kidneys. Persistent calcium deposition leads to kidney inflammation, cell necrosis, and is related to serious kidney diseases. However, it is invasive and involves the risk of complications such as bleeding, especially in patients with end-stage renal diseases. Therefore, it is necessary to identify specific diagnostic biomarkers for renal fibrosis. This study aimed to develop a predictive drug target signature to diagnose renal fibrosis based on m6A subtypes. We then performed an unsupervised consensus clustering analysis to identify three different m6A subtypes of renal fibrosis based on the expressions of 21 m6A regulators. We evaluated the immune infiltration characteristics and expression of canonical immune checkpoints and immune-related genes with distinct m6A modification patterns. Subsequently, we performed the WGCNA analysis using the expression data of 1,611 drug targets to identify 474 genes associated with the m6A modification. 92 overlapping drug targets between WGCNA and DEGs (renal fibrosis vs. normal samples) were defined as key drug targets. A five target gene predictive model was developed through the combination of LASSO regression and stepwise logistic regression (LASSO-SLR) to diagnose renal fibrosis. We further performed drug sensitivity analysis and extracellular matrix analysis on model genes. The ROC curve showed that the risk score (AUC = 0.863) performed well in diagnosing renal fibrosis in the training dataset. In addition, the external validation dataset further confirmed the outstanding predictive performance of the risk score (AUC = 0.755). These results indicate that the risk model has an excellent predictive performance for diagnosing the disease. Furthermore, our results show that this 5-target gene model is significantly associated with many drugs and extracellular matrix activities. Finally, the expression levels of both predictive signature genes EGR1 and PLA2G4A were validated in renal fibrosis and adjacent normal tissues by using qRT-PCR and Western blot method.

Metabolomics and health: from nutritional crops and plant-based pharmaceuticals to profiling of human biofluids

During the past decade metabolomics has emerged as one of the fastest developing branches of “-omics” technologies. Metabolomics involves documentation, identification, and quantification of metabolites through modern analytical platforms in various biological systems. Advanced analytical tools, such as gas chromatography–mass spectrometry (GC/MS), liquid chromatography–mass spectroscopy (LC/MS), and non-destructive nuclear magnetic resonance (NMR) spectroscopy, have facilitated metabolite profiling of complex biological matrices. Metabolomics, along with transcriptomics, has an influential role in discovering connections between genetic regulation, metabolite phenotyping and biomarkers identification. Comprehensive metabolite profiling allows integration of the summarized data towards manipulation of biosynthetic pathways, determination of nutritional quality markers, improvement in crop yield, selection of desired metabolites/genes, and their heritability in modern breeding. Along with that, metabolomics is invaluable in predicting the biological activity of medicinal plants, assisting the bioactivity-guided fractionation process and bioactive leads discovery, as well as serving as a tool for quality control and authentication of commercial plant-derived natural products. Metabolomic analysis of human biofluids is implemented in clinical practice to discriminate between physiological and pathological state in humans, to aid early disease biomarker discovery and predict individual response to drug therapy. Thus, metabolomics could be utilized to preserve human health by improving the nutritional quality of crops and accelerating plant-derived bioactive leads discovery through disease diagnostics, or through increasing the therapeutic efficacy of drugs via more personalized approach. Here, we attempt to explore the potential value of metabolite profiling comprising the above-mentioned applications of metabolomics in crop improvement, medicinal plants utilization, and, in the prognosis, diagnosis and management of complex diseases.

Maternal obesity increases offspring's mammary cancer recurrence and impairs tumor immune response

Over 50% of women at a childbearing age in the United States are overweight or obese, and this can adversely affect their offspring. We studied if maternal obesity-inducing high fat diet (HFD) not only increases offspring's mammary cancer risk but also impairs response to antiestrogen tamoxifen. Female rat offspring of HFD and control diet-fed dams, in which estrogen receptor-positive (ER+) mammary tumors were induced with the carcinogen 7,12-dimethylbenz[a]anthracene (DMBA), exhibited similar initial responses to antiestrogen tamoxifen. However, after tamoxifen therapy was completed, almost all (91%) tumors recurred in HFD offspring, compared with only 29% in control offspring. The increase in local mammary tumor recurrence in HFD offspring was linked to an increase in the markers of immunosuppression (Il17f, Tgfβ1, VEGFR2) in the tumor microenvironment (TME). Protein and mRNA levels of the major histocompatibility complex II (MHC-II), but not MHC-I, were reduced in the recurring DMBA tumors of HFD offspring. Further, infiltration of CD8+ effector T cells and granzyme B+ (GZMB+) cells were lower in their recurring tumors. To determine if maternal HFD can pre-program similar changes in the TME of allografted E0771 mammary tumors in offspring of syngeneic mice, flow cytometry analysis was performed. E0771 mammary tumor growth was significantly accelerated in the HFD offspring, and a reduction in the numbers of GZMB and non-significant reduction of interferon γ (IFNγ) secreting CD8+ T cells in the TME was seen. Thus, consumption of a HFD during pregnancy increases susceptibility of the female rat and mouse offspring to tumor immune suppression and mammary tumor growth and recurrence.

Cardioprotective action of the aqueous extract of Terminalia arjuna bark against toxicity induced by doxorubicin

BACKGROUND

The aqueous extract of Terminalia arjuna (TA) bark (TA_AqE) has been shown to have a direct inotropic effect on ventricular myocytes. Active constituents of TA_AqE contain various flavonoids and proanthocyanidins, some of which are known to have antioxidant activities. Whether TA_AqE affords a cardioprotective action against oxidative stress (OS) remains unclear.

PURPOSE

Increased OS is one of the major mechanisms underlying cardiotoxicity induced by doxorubicin (DOX), a commonly-used anticancer agent. The aim of the present study was to investigate potential cardioprotective effect of TA_AqE against DOX-induced OS and cardiac dysfunction.

METHODS

OS and cytotoxicity were induced by 1 µM DOX for 24 h in H9c2 cells, a cardiac tissue-derived cell line, and left ventricular (LV) dysfunction was induced by intrapleural injection of DOX (accumulative 20 mg/kg body weight) to mice. Cellular oxidative levels and morphology were assessed using microscopy and oxidative-sensitive fluorescent dyes with and without co-treatment with TA_AqE. LV function was monitored weekly with echocardiography.

RESULTS

TA_AqE reduced OS and preserved mitochondria and cell growth of H9c2 cells against DOX treatment. TA_AqE (in drinking water) attenuated the decreased LV function and altered myocardial structure caused by DOX treatment.

CONCLUSION

TA_AqE exerts a protective action against cardiotoxicity caused by DOX in part via suppression of OS. Thus, TA_AqE is a promising cardiotonic in adjuvant cancer chemotherapy.

Leptin signaling and cancer chemoresistance: Perspectives

Obesity is a major health problem and currently is endemic around the world. Obesity is a risk factor for several different types of cancer, significantly promoting cancer incidence, progression, poor prognosis and resistance to anti-cancer therapies. The study of this resistance is critical as development of chemoresistance is a serious drawback for the successful and effective drug-based treatments of cancer. There is increasing evidence that augmented adiposity can impact on chemotherapeutic treatment of cancer and the development of resistance to these treatments, particularly through one of its signature mediators, the adipokine leptin. Leptin is a pro-inflammatory, pro-angiogenic and pro-tumorigenic adipokine that has been implicated in many cancers promoting processes such as angiogenesis, metastasis, tumorigenesis and survival/resistance to apoptosis. Several possible mechanisms that could potentially be developed by cancer cells to elicit drug resistance have been suggested in the literature. Here, we summarize and discuss the current state of the literature on the role of obesity and leptin on chemoresistance, particularly as it relates to breast and pancreatic cancers. We focus on the role of leptin and its significance in possibly driving these proposed chemoresistance mechanisms, and examine its effects on cancer cell survival signals and expansion of the cancer stem cell sub-populations.