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The microRNA 21 (miR-21) is upregulated in almost all known human cancers and is considered a highly potent oncogene and potential therapeutic target for cancer treatment. In the liver, miR-21 was reported to promote hepatic steatosis and inflammation, but whether miR-21 also drives hepatocarcinogenesis remains poorly investigated in vivo. Here we show using both carcinogen (Diethylnitrosamine, DEN) or genetically (PTEN deficiency)-induced mouse models of hepatocellular carcinoma (HCC), total or hepatocyte-specific genetic deletion of this microRNA fosters HCC development-contrasting the expected oncogenic role of miR-21. Gene and protein expression analyses of mouse liver tissues further indicate that total or hepatocyte-specific miR-21 deficiency is associated with an increased expression of oncogenes such as Cdc25a, subtle deregulations of the MAPK, HiPPO, and STAT3 signaling pathways, as well as alterations of the inflammatory/immune anti-tumoral responses in the liver. Together, our data show that miR-21 deficiency promotes a pro-tumoral microenvironment, which over time fosters HCC development via pleiotropic and complex mechanisms. https://www.selleckchem.com/products/Obatoclax-Mesylate.html These results question the current dogma of miR-21 being a potent oncomiR in the liver and call for cautiousness when considering miR-21 inhibition for therapeutic purposes in HCC.Metastasis-directed therapy (MDT) in oligometastatic prostate cancer has the potential of delaying the start of androgen deprivation therapy (ADT) and disease progression. We aimed to analyze the efficacy of PSMA-PET/CT in detecting oligometastatic disease (OMD), to look for predictive factors of OMD, and to evaluate the impact of PSMA-PET/CT findings on clinical management. We retrospectively analyzed a homogeneous population of 196 hormone-sensitive prostate cancer patients (HSPC), considered potential candidates for MDT, with a PSMA-PET/CT performed at biochemical recurrence (BCR) after radical prostatectomy (RP). Multivariable logistic regression analysis was performed based on several clinico-pathological factors. Changes in clinical management before and after PSMA-PET/CT were analyzed. The OMD detection rate was 44% for a total positivity rate of 60%. PSMA-PET/CT positivity was independently related to PSA (OR (95% CI), p) (1.7 (1.3-2.3), p less then 0.0001) and PSAdt (0.4 (0.2-0.8), p = 0.013), and OMD detection was independently related to PSA (1.6 (1.2-2.2), p = 0.001) and no previous salvage therapy (0.3 (0.1-0.9), p = 0.038). A treatment change was observed in 58% of patients, mostly to perform MDT after OMD detection (60% of changes). This study showed that PSMA-PET/CT is an excellent imaging technique to detect OMD early in HSPC patients with BCR after RP, changing therapeutic management mostly into MDT.Hepatocellular carcinoma (HCC) is the most common type of liver cancer. The majority of HCC cases are associated with liver fibrosis or cirrhosis developing from chronic liver injuries. The immune system of the liver contributes to the severity of tissue damage, the establishment of fibrosis and the disease's progression towards HCC. Herein, we provide a detailed characterization of the DEN-induced HCC rat model during fibrosis progression and HCC development with a special focus on the liver's inflammatory microenvironment. Fischer 344 male rats were treated weekly for 14 weeks with intra-peritoneal injections of 50 mg/kg DEN. The rats were sacrificed before starting DEN-injections at 0 weeks, after 8 weeks, 14 weeks and 20 weeks after the start of DEN-injections. We performed histopathological, immunohistochemical, RT-qPCR, RNA-seq and flow cytometry analysis. Data were compared between tumor and non-tumor samples from the DEN-treated versus untreated rats, as well as versus human HCCs. Chronic DEN injections lead to liver damage, hepatocytes proliferation, liver fibrosis and cirrhosis, disorganized vasculature, and a modulated immune microenvironment that mimics the usual events observed during human HCC development. The RNA-seq results showed that DEN-induced liver tumors in the rat model shared remarkable molecular characteristics with human HCC, especially with HCC associated with high proliferation. In conclusion, our study provides detailed insight into hepatocarcinogenesis in a commonly used model of HCC, facilitating the future use of this model for preclinical testing.Dickkopf-related protein 1 (DKK1), an antagonist of the canonical Wnt pathway, has received tremendous attention over the past years as its dysregulation is said to be critically involved in a wide variety of gastrointestinal cancers. However, the potential clinical implications of DKK1 remain poorly understood. Although multimodal treatment options have been implemented over the past years, esophageal cancer (EC) patients still suffer from poor five-year overall survival rates ranging from 15% to 25%. Especially prognostic factors and biomarkers for risk stratification are lacking to choose the most beneficial treatment out of the emerging landscape of different treatment options. In this study, we analyzed the serum DKK1 (S-DKK1) levels of 91 EC patients prior to surgery in a single center study at the University Medical Center Hamburg-Eppendorf by enzyme-linked immunosorbent assay. High levels of S-DKK1 could be especially observed in patients suffering from esophageal adenocarcinoma which may promote the hypothesis of a crucial role of DKK1 in inflammation. S-DKK1 levels of ≥5800 pg/mL were shown to be associated with unfavorable five-year survival rates and the presence of CTCs. Interestingly, significantly lower S-DKK1 levels were detected in patients after neoadjuvant treatment, implying that S-DKK1 may serve as a useful biomarker for treatment monitoring. Multivariate analysis identified S-DKK1 as an independent prognostic marker with respect to overall survival in EC patients with a hazard ratio of 2.23. In conclusion, our data implicate a negative prognostic role of DKK1 with respect to the clinical outcome in EC patients. Further prospective studies should be conducted to implement S-DKK1 into the clinical routine for risk stratification and treatment monitoring.Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal solid malignancies. While immortalized cancer cell lines and genetically engineered murine models have increased our understanding of PDAC tumorigenesis, they do not recapitulate inter- and intra-patient heterogeneity. PDAC patient derived organoid (PDO) biobanks have overcome this hurdle, and provide an opportunity for the high throughput screening of potential new therapies. This review provides a summary of the PDAC PDO biobanks established to date, and discusses how they have advanced our understanding of PDAC biology. Looking forward, the development of coculturing techniques for specific immune or stromal cell populations will enable a better understanding of the crosstalk that occurs within the tumor microenvironment, and the impact of this crosstalk on treatment response.Relapsed/refractory (RR) multiple myeloma (MM) patients are a fragile population because of prolonged drug exposure and advanced age. Preserving a good quality of life is of high priority for these patients and the treatment of disease- and treatment-related complications plays a key role in their management. By preventing and limiting MM-induced complications, supportive care improves patients' outcome. Erythropoietin-stimulating agents and bisphosphonates are well-established supportive strategies, yet novel agents are under investigation, such as anabolic bone agents and activin receptor-like kinase (ALK) inhibitors. The recent dramatic changes in the treatment landscape of MM pose an additional challenge for the routine care of RRMM patients. Multidrug combinations in first and later lines increase the risk for long-lasting toxicities, including adverse cardiovascular and neurological events. Moreover, recently approved first-in-class drugs have unique side-effect profiles, such as ocular toxicity of belantamab mafodotin or gastrointestinal toxicity of selinexor. This review discusses current standards in supportive treatment of RRMM patients, including recommendations in light of the recent SARS-CoV-19 pandemic, and critically looks at the incidence and management of side effects of standard as well as next generation anti-MM agents.Immune checkpoint inhibitor (ICI) therapy has been a paradigm shift in the treatment of cancer. ICI therapy results in durable responses and survival benefit for a large number of tumor types. Osimertinib, a third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) has shown great efficacy treating EGFR mutant lung cancers; however, all patients eventually develop resistance. ICI therapy has not benefitted EGFR mutant lung cancer. Herein, we employed stable isotope labeling by amino acids in cell culture (SILAC) quantitative mass spectrometry-based proteomics to investigate potential immune escape molecular mechanisms in osimertinib resistant EGFR mutant lung adenocarcinoma by interrogating the alterations in the human leukocyte antigen (HLA) Class I-presented immunopeptidome, Class I-interactome, and the whole cell proteome between isogenic osimertinib-sensitive and -resistant human lung adenocarcinoma cells. Our study demonstrates an overall reduction in HLA class I-presented immunopeptidome and downregulation of antigen presentation core complex (e.g., TAP1 and ERAP1/2) and immunoproteasome in osimertinib resistant lung adenocarcinoma cells. Several key components in autophagy pathway are differentially altered. S100 proteins and SLC3A2 may play critical roles in reduced antigen presentation. Our dataset also includes ~1000 novel HLA class I interaction partners and hundreds of Class I-presented immunopeptides in EGFR mutant lung adenocarcinoma. This large-scale unbiased proteomics study provides novel insights and potential mechanisms of immune evasion of EGFR mutant lung adenocarcinoma.Despite advances in tumor treatment, the inconsistent response is a major challenge among glioblastoma multiform (GBM) that lead to different survival time. Our aim was to integrate multimodal MRI with non-supervised and supervised machine learning methods to predict GBM patients' survival time. To this end, we identified different compartments of the tumor and extracted their features. Next, we applied Random Forest-Recursive Feature Elimination (RF-RFE) to identify the most relevant features to feed into a GBoost machine. This study included 29 GBM patients with known survival time. RF-RFE GBoost model was evaluated to assess the survival prediction performance using optimal features. Furthermore, overall survival (OS) was analyzed using univariate and multivariate Cox regression analyses, to evaluate the effect of ROIs and their features on survival. The results showed that a RF-RFE Gboost machine was able to predict survival time with 75% accuracy. The results also revealed that the rCBV in the low perfusion area was significantly different between groups and had the greatest effect size in terms of the rate of change of the response variable (survival time). In conclusion, not only integration of multi-modality MRI but also feature selection method can enhance the classifier performance.

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