Aims
A variety of tissue clearing techniques have been developed to render intact tissue transparent. For thicker samples, additional partial tissue delipidation is required before immersion into the ...final refractive index (RI)‐matching solution, which alone is often inadequate to achieve full tissue transparency. However, it is difficult to determine a sufficient degree of tissue delipidation, excess of which can result in tissue distortion and protein loss. Here, we aim to develop a clearing strategy that allows better monitoring and more precise determination of delipidation progress.
Methods
We combined the detergent sodium dodecyl sulphate (SDS) with OPTIClear, a RI‐matching solution, to form a strategy termed Accurate delipidation with Optimal Clearing (Accu‐OptiClearing). Accu‐OptiClearing allows for a better preview of the final tissue transparency achieved when immersed in OPTIClear alone just before imaging. We assessed for the changes in clearing rate, protein loss, degree of tissue distortion, and preservation of antigens.
Results
Partial delipidation using Accu‐OptiClearing accelerated tissue clearing and better preserved tissue structure and antigens than delipidation with SDS alone. Despite achieving similar transparency in the final OPTIClear solution, more lipids were retained in samples cleared with Accu‐OptiClearing compared to SDS.
Conclusions
Combining the RI‐matching solution OPTIClear with detergents, Accu‐OptiClearing, can avoid excessive delipidation, leading to accelerated tissue clearing, less tissue damage and better preserved antigens.
Our new strategy of using Accurate dilapidation with Optimal Clearing combines SDS, OPTIClear and refractive index‐matching solution. The new strategy provides fast, non‐swell/shrink, and no protein loss protocol for making the brain to be semi‐transparent. This opens a new avenue of fast pathological analysis of the brain without many thin tissue sectioning.
A lanthanide-based peptide-directed bioprobe
(Ln = Eu or Yb) is designed as an impressive example of a small molecule-based dual-functional probe for the EBV oncoprotein LMP1. The peptide
...(Pra-KAhx-K-LDLALK-FWLY-K-IVMSDKW-K-RrRK) is designed to selectively bind to LMP1 by mimicking its TM1 region during oligomerization in lipid rafts while signal transduction is significantly suppressed. Immunofluorescence imaging and Western blotting results reveal that
can effectively inactivate the oncogenic cellular pathway nuclear factor κB (NF-κB) and contribute to a selective cytotoxic effect on LMP1-positive cells. By conjugation with cyclen-based europium(III) and ytterbium(III) complexes,
and
were constructed to offer visible and near-infrared LMP1-targeted imaging and cancer monitoring. In addition to the ability to target and inhibit LMP1 and to selective inhibit LMP1-positive cells, selective growth inhibition toward the LMP1-positive tumor by
is also demonstrated.
Owing to the cytotoxic effect, it is challenging for clinicians to decide whether post-operative adjuvant therapy is appropriate for a non-small cell lung cancer (NSCLC) patient. Radiomics has proven ...its promising ability in predicting survival but research on its actionable model, particularly for supporting the decision of adjuvant therapy, is limited.
Pre-operative contrast-enhanced CT images of 123 NSCLC cases were collected, including 76, 13, 16, and 18 cases from R01 and AMC cohorts of The Cancer Imaging Archive (TCIA), Jiangxi Cancer Hospital and Guangdong Provincial People's Hospital respectively. From each tumor region, 851 radiomic features were extracted and two augmented features were derived therewith to estimate the likelihood of adjuvant therapy. Both Cox regression and machine learning models with the selected main and interaction effects of 853 features were trained using 76 cases from R01 cohort, and their test performances on survival prediction were compared using 47 cases from the AMC cohort and two hospitals. For those cases where adjuvant therapy was unnecessary, recommendations on adjuvant therapy were made again by the outperforming model and compared with those by IBM Watson for Oncology (WFO).
The Cox model outperformed the machine learning model in predicting survival on the test set (C-Index: 0.765 vs. 0.675). The Cox model consists of 5 predictors, interestingly 4 of which are interactions with augmented features facilitating the modulation of adjuvant therapy option. While WFO recommended no adjuvant therapy for only 13.6% of cases that received unnecessary adjuvant therapy, the same recommendations by the identified Cox model were extended to 54.5% of cases (McNemar's test
= 0.0003).
A Cox model with radiomic and augmented features could predict survival accurately and support the decision of adjuvant therapy for bettering the benefit of NSCLC patients.
Solid evidence shows that tumor-initiating cells (T-ICs) are the root of tumor relapse and drug resistance, which lead to a poor prognosis in patients with hepatocellular carcinoma (HCC). Through an ...in vitro liver T-IC enrichment approach, we identified nuclear factor (erythroid-derived 2)-like 2 (NRF2) as a transcription regulator that is significantly activated in enriched liver T-IC populations. In human HCCs, NRF2 was found to be overexpressed, which was associated with poor patient survival. Through a lentiviral based knockdown approach, NRF2 was found to be critical for regulating liver T-IC properties, including self-renewal, tumorigenicity, drug resistance and expression of liver T-IC markers. Furthermore, we found that ROS-induced NRF2 activation regulates sorafenib resistance in HCC cells. Mechanistically, NRF2 was found to physically bind to the promoter of sonic hedgehog homolog (SHH), which triggers activation of the sonic hedgehog pathway. The effect of NRF2 knockdown was eliminated upon administration of recombinant SHH, demonstrating that NRF2 mediated T-IC function via upregulation of SHH expression. Our study suggests a novel regulatory mechanism for the canonical sonic hedgehog pathway that may function through the NRF2/SHH/GLI signaling axis, thus mediating T-IC phenotypes.
•NRF2 is overexpressed in human HCCs and is a potential prognostic factor for HCC patients.•NRF2 is critical for self-renewal, tumorigencity and invasiveness of HCC cells.•ROS-induced NRF2 activation regulates sorafenib resistance of HCC cells.•NRF2 regulates liver T-IC functions via SHH/GLI signaling cascade.
Anxiety disorders are common, complex psychiatric disorders with twin heritabilities of 30-60%. We conducted a genome-wide association study of Lifetime Anxiety Disorder (n
= 25 453, n
= 58 113) ...and an additional analysis of Current Anxiety Symptoms (n
= 19 012, n
= 58 113). The liability scale common variant heritability estimate for Lifetime Anxiety Disorder was 26%, and for Current Anxiety Symptoms was 31%. Five novel genome-wide significant loci were identified including an intergenic region on chromosome 9 that has previously been associated with neuroticism, and a locus overlapping the BDNF receptor gene, NTRK2. Anxiety showed significant positive genetic correlations with depression and insomnia as well as coronary artery disease, mirroring findings from epidemiological studies. We conclude that common genetic variation accounts for a substantive proportion of the genetic architecture underlying anxiety.
Hyperhomocysteinemia (HHcy) is an independent risk factor for cardiovascular diseases and increases mortality in type 2 diabetic patients. HHcy induces endoplasmic reticulum (ER) stress and oxidative ...stress to impair endothelial function. The glucagon-like peptide 1 (GLP-1) analog exendin-4 attenuates endothelial ER stress, but the detailed vasoprotective mechanism remains elusive. The present study investigated the beneficial effects of exendin-4 against HHcy-induced endothelial dysfunction. Exendin-4 pretreatment reversed homocysteine-induced impairment of endothelium-dependent relaxations in C57BL/6 mouse aortae ex vivo. Four weeks subcutaneous injection of exendin-4 restored the impaired endothelial function in both aortae and mesenteric arteries isolated from mice with diet-induced HHcy. Exendin-4 treatment lowered superoxide anion accumulation in the mouse aortae both ex vivo and in vivo. Exendin-4 decreased the expression of ER stress markers (e.g., ATF4, spliced XBP1, and phosphorylated eIF2α) in human umbilical vein endothelial cells (HUVECs), and this change was reversed by cotreatment with compound C (CC) (AMPK inhibitor). Exendin-4 induced phosphorylation of AMPK and endothelial nitric oxide synthase in HUVECs and arteries. Exendin-4 increased the expression of endoplasmic reticulum oxidoreductase (ERO1α), an important ER chaperone in endothelial cells, and this effect was mediated by AMPK activation. Experiments using siRNA-mediated knockdown or adenoviral overexpression revealed that ERO1α mediated the inhibitory effects of exendin-4 on ER stress and superoxide anion production, thus ameliorating HHcy-induced endothelial dysfunction. The present results demonstrate that exendin-4 reduces HHcy-induced ER stress and improves endothelial function through AMPK-dependent ERO1α upregulation in endothelial cells and arteries. AMPK activation promotes the protein folding machinery in endothelial cells to suppress ER stress.
This study aimed to identify radiomic features of primary tumor and develop a model for indicating extrahepatic metastasis of hepatocellular carcinoma (HCC). Contrast-enhanced computed tomographic ...(CT) images of 177 HCC cases, including 26 metastatic (MET) and 151 non-metastatic (non-MET), were retrospectively collected and analyzed. For each case, 851 radiomic features, which quantify shape, intensity, texture, and heterogeneity within the segmented volume of the largest HCC tumor in arterial phase, were extracted using Pyradiomics. The dataset was randomly split into training and test sets. Synthetic Minority Oversampling Technique (SMOTE) was performed to augment the training set to 145 MET and 145 non-MET cases. The test set consists of six MET and six non-MET cases. The external validation set is comprised of 20 MET and 25 non-MET cases collected from an independent clinical unit. Logistic regression and support vector machine (SVM) models were identified based on the features selected using the stepwise forward method while the deep convolution neural network, visual geometry group 16 (VGG16), was trained using CT images directly. Grey-level size zone matrix (GLSZM) features constitute four of eight selected predictors of metastasis due to their perceptiveness to the tumor heterogeneity. The radiomic logistic regression model yielded an area under receiver operating characteristic curve (AUROC) of 0.944 on the test set and an AUROC of 0.744 on the external validation set. Logistic regression revealed no significant difference with SVM in the performance and outperformed VGG16 significantly. As extrahepatic metastasis workups, such as chest CT and bone scintigraphy, are standard but exhaustive, radiomic model facilitates a cost-effective method for stratifying HCC patients into eligibility groups of these workups.
Abstract
Background: Glutathione S-transferases (GSTs) are an enzyme family responsible for the metabolism of toxins and carcinogens in the phase II detoxification pathway. Among the 5 alpha class ...isoforms, GSTA1 and GSTA3 are involved in metabolizing several active carcinogenic substrates generated from benzo-a-pyrene mainly found in grilled meats and burnt coal. The expression of GSTA1 and GSTA3 in gastrointestinal (GI) tract may be implicated with cancer development associated with the intake of xenobiotic substances.
Methods: Formalin-fixed and paraffin-embedded tissue cores of esophagus (190), stomach (180), small intestine (372), colon (120) and rectum (142) were stained with a multiplex tyramide-immunofluorescence (T-IMF) technique for the simultaneous demonstration of cytokeratin AE1/AE3, GSTA1 and GSTA3. The tissue types range from normal to cancer progression spectrum. All tissue cores were screened for AE1/AE3 expression to confirm the epithelial cell lineage before scoring for GSTA1 and GSTA3 positivity. A p-value <0.05 by Chi-squared test is considered significant.
Results: T-IMF is useful in studying the interaction of multi-markers in a single slide. This technique is superior to chromogenic immunohistochemical application in multi-color presentation. This highly sensitive and handy technique will save multiple sectionings and precious tissues. We found a significant down-regulation of two alpha class GSTs in the malignancies of GI tract (Table 1).
Table 1. Positive percentages of glutathione S-transferases markersMarkerEsophagusStomachSmall intestineColonRectumNMNMNMNMNMGSTA141%24%99%40%90%15%22%3%43%21%p-value0.0603<0.0001<0.00010.0010.0194GSTA378%35%99%54%96%64%100%39%88%40%p-value<0.0001<0.0001<0.0001<0.0001<0.0001Abbreviation: N= normal; M= malignant
Conclusion: The differential expression of these detoxification enzymes in normal epithelium vs GI cancer may shed some light on their role in protecting normal tissue from cancer development. This finding may provide a potential target for the development of intervention strategies against GI cancer. Further investigations will be conducted to decipher the mechanism underlying this observation.
Citation Format: Victor Wan-San Ma, Goretti Hoi-Yan Cheung, Eunice Yuen-Ting Lau, William Chi-Shing Cho. Xenobiotic detoxification enzymes and cancer risk: A multiplex immunofluorescence detection of AE1/AE3, GSTA1 and GSTA3 in the tissue microarrays of gastrointestinal tract abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3597.
Abstract
Lung adenocarcinoma (LUAD), the most common histological subtype of lung cancer, remains one of the leading causes of cancer-related deaths worldwide. With improving knowledge in the ...molecular aberrations underlying lung carcinogenesis, a large number of targeted therapies are being developed to better patient's survival. EGFR-activating mutations are one of the most frequent genetic alterations in advanced lung adenocarcinoma, and patients harbouring certain types of EGFR activating mutation confer sensitivity to EGFR tyrosine kinase inhibitors (TKIs). Despite promising initial responses, majority of patients develop resistance to treatment and the mechanism of resistance remains unknown in up to 30% of patients. Recent studies revealed that cancer stem cells (CSCs) endowed with stem cell-like properties confer resistance to EGFR-TKI treatment. Identification of pathways maintaining stemness properties potentially provide novel drug targets to overcome treatment resistance. Protein phosphorylation is the most common form of reversible post-translational modification and is frequently involved in the deregulation of signal transductions associated with cancer development and progression. In this study, we have identified Serine/Threonine Kinase 31 (STK31) to be upregulated in enriched lung CSC populations, as well as in the erlotinib resistant derivatives from two LUAD cell lines. Through analysing The Cancer Genome Atlas (TCGA) data, mRNA expression of STK31 is observed to be higher in LUAD tumor when compared with paired normal tissues (p<0.001). High mRNA expression of STK31 was also found to be associated with poorer disease-free survival (p=0.0324) and overall survival (p=0.0012) in LUAD patients. Functional studies using shRNA based knockdown of STK31 in lung cancer cell lines revealed its regulatory role on cancer and stem cell-like properties in vitro and in vivo including tumorigenicity, self-renewal, drug resistance and metastasis. Repressing the expression of STK31 in erlotinib resistant cells re-sensitized the cells to drug treatment. Further studies will be done to delineate the downstream mechanism by which STK31 regulates lung CSCs and erlotinib resistance.
Citation Format: Eunice Yuen-Ting Lau, Isabella Kit-Nam Chin, Alvin Hong-Wai Fong, Victor Wan-San Ma, William Chi-Shing Cho. STK31 contributes to lung carcinogenesis through induction of stemness and resistance to EGFR-TKI therapy abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1142.
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