Real-time Quantitative RT-PCR for CT9 Level in Human Cancer

Introduction Malignantdiseasesarecharacterizedbytheunreg ulatedgrowthoftransformedcells.Inrecentyears,dramaticinsightsintothemolecularmechanismsofthis phenomenonhavebeenachievedfrombasiccancerre search.Manycellularfunctionsareregulatedbychan gesingeneexpr…     

Delimitation of squamous cell cervical carcinoma using infrared microspectroscopic imaging

Infrared (IR) spectroscopic imaging coupled with microscopy has been used to investigate thin sections of cervix uteri encompassing normal tissue, precancerous structures, and squamous cell carcinoma. Methods for unsupervised distinction of tissue types based on IR spectroscopy were developed. One-hundred and twenty-two images of cervical tissue were recorded by an FTIR spectrometer with a 64×64 focal plane array detector. The 499,712 IR spectra obtained were grouped by an approach which used fuzzy C-means clustering followed by hierarchical cluster analysis. The resulting false color maps were correlated with the morphological characteristics of an adjacent section of hematoxylin and eosin-stained tissue. In the first step, cervical stroma, epithelium, inflammation, blood vessels, and mucus could be distinguished in IR images by analysis of the spectral fingerprint region (950–1480 cm⁻¹). In the second step, analysis in the spectral window 1420–1480 cm⁻¹ enables, for the first time, IR spectroscopic distinction between the basal layer, dysplastic lesions and squamous cell carcinoma within a particular sample. The joint application of IR microspectroscopic imaging and multivariate spectral processing combines diffraction-limited lateral optical resolution on the single cell level with highly specific and sensitive spectral classification on the molecular level. Compared with previous reports our approach constitutes a significant progress in the development of optical molecular spectroscopic techniques toward an additional diagnostic tool for the early histopathological characterization of cervical cancer.     

Expression Levels of RFP in Normal and Cancer Human Tissues via Real-time RT-PCR Detection

IntroductionRet finger protein(RFP) was first identified as apart of the human recombined transforming gene, ret,and was a member of the tripartite motif(TRIM) pro-tein family. Itwas postulated thatmultimeric complexesmade of TRIM proteins defined differe…     

Synchronous Fluorescence Spectroscopy for the Detection and Characterization of Cervical Cancers In Vitro

The objective of this study was to assess the diagnostic potential of synchronous fluorescence (SF) spectroscopy (SFS) technique for the detection and characterization of normal and different malignancy stages of moderately differentiated squamous cell carcinoma (MDSCC), poorly differentiated squamous cell carcinoma (PDSCC) cervical tissues. SF spectra were measured from 45 biopsies from 30 patients in vitro . Characteristic, highly resolved peaks and significant spectral differences between normal and MDSCC, PDSCC cervical tissues were obtained. Nine potential ratios were calculated and used as input variables for a discriminant analysis across different groups. The potentiality of the SFS technique was estimated by two discriminant analyses. Discriminant analysis I performed across normal and abnormal (including MDSCC and PDSCC) cervical tissues classified as 100% both original and the cross-validated grouped cases. In discriminant analysis II performed across the three groups, normal, MDSCC and PDSCC, 100% of both original and the cross-validated grouped cases were correctly classified. Using the SFS technique, one can obtain all the key biochemical markers such as tryptophan, collagen, hemoglobin, reduced form of nicotinamide adenine dinucleotide and flavin adenine dinucleotide in a single scan and hence they can be targeted as tumor markers in the detection of normal from abnormal cervical tissues.     

Multi-class classification algorithm for optical diagnosis of oral cancer

We report development of a direct multi-class spectroscopic diagnostic algorithm for discrimination of high-grade cancerous tissue sites from low-grade as well as precancerous and normal squamous tissue sites of human oral cavity. The algorithm was developed making use of the recently formulated theory of total principal component regression (TPCR). The in vivo autofluorescence spectral data acquired from patients screened for neoplasm of oral cavity at the Government Cancer Hospital, Indore, was used to train and validate the algorithm. The diagnostic algorithm based on TPCR was found to provide satisfactory performance in classifying the tissue sites in four different classes - high-grade squamous cell carcinoma, low-grade squamous cell carcinoma, leukoplakia, and normal squamous tissue. The classification accuracy for these four classes was observed to be approximately 94%, 100%, 100% and 91% for the training data set (based on leave-one-out cross-validation), and was approximately 90%, 90%, 85% and 88%, respectively for the corresponding classes for the independent validation data set.     

Bladder squamous cell carcinoma biomarkers derived from proteomics

Proteomics provide powerful technology for analyzing the expression levels of thousands of proteins simultaneously both in health and disease. Here, we review proteomic strategies that we have developed to identify metaplastic lesions in bladder squamous cell carcinomas as well as biomarkers in the urine for follow-up studies of squamous cell carcinoma (SCC)-bearing patients.     

Clinical evaluation of gallium-67 scintigraphy in comparison with autopsy findings in the elderly, with particular reference to histological findings and classification of pulmonary cancer

A correlative study of autopsy findings and retrospective review of gallium scintigrams were performed in 106 elderly patients. Of the cases studied, 57% demonstrated positive gallium study in the present series. Histological correlation was undertaken in cases of lung cancer. Among them, squamous cell carcinoma showed the highest incidence of positive results (83%), whereas adenocarcinoma was the lowest (35%). There is no apparent correlation between subtypes of histological classification of adenocarcinoma and abnormal accumulation of gallium. However, abnormal accumulation of the nuclide seems to be rather related with interstitial reactions, namely fibrotic changes, lymphocyte infiltration and vascularization.     

Basic and clinical evaluation of a new assay procedure "SCC RIABEAD" for estimation of squamous cell carcinoma related antigen

We examined the efficacy of a new commercial assay procedure (SCC RIABEAD) for estimation of squamous cell carcinoma related antigen (SCC). Intraassay and interassay variance were 4.0-14.6% and 4.6-17.0% respectively. Recovery and dilution tests gave satisfactory results. The normal range was under the level of 1.63 ng/ml. The patients with uterine cervical cancer or squamous cell carcinoma of the lung showed high positive rates. The values of SCC measured by SCC RIABEAD were well-correlated to those by SCC RIAKIT. However, SCC RIABEAD showed lower values in low SCC level and higher values in high SCC level than SCC RIAKIT.     

Fourier transform infrared imaging analysis in discrimination studies of squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) of the oral cavity and oropharynx represents more than 95% of all malignant neoplasms in the oral cavity. Histomorphological evaluation of this cancer type is invasive and remains a time consuming and subjective technique. Therefore, novel approaches for histological recognition are necessary to identify malignancy at an early stage. Fourier transform infrared (FTIR) imaging has become an essential tool for the detection and characterization of the molecular components of biological processes, such as those responsible for the dynamic properties of tumor progression. FTIR imaging is a modern analytical technique enabling molecular imaging of a complex biological sample and is based on the absorption of IR radiation by vibrational transitions in covalent bonds. One major advantage of this technique is the acquisition of local molecular expression profiles, while maintaining the topographic integrity of the tissue and avoiding time-consuming extraction, purification, and separation steps. With this imaging technique, it is possible to obtain unique images of the spatial distribution of proteins, lipids, carbohydrates, cholesterols, nucleic acids, phospholipids, and small molecules with high spatial resolution. Analysis and visualization of FTIR imaging datasets are challenging and the use of chemometric tools is crucial in order to take advantage of the full measurement. Therefore, methodologies for this task based on the novel developed algorithm for multivariate image analysis (MIA) are often necessary. In the present study, FTIR imaging and data analysis methods were combined to optimize the tissue measurement mode after deparaffinization and subsequent data evaluation (univariate analysis and MIAs). We demonstrate that it is possible to collect excellent IR spectra from formalin-fixed paraffin-embedded (FFPE) tissue microarrays (TMAs) of OSCC tissue sections employing an optimised analytical protocol. The correlation of FTIR imaging to the morphological tissue features obtained by histological staining of the sections demonstrated that many histomorphological tissue patterns can be visualized in the colour images. The different algorithms used for MIAs of FTIR imaging data dramatically increased the information content of the IR images from squamous cell tissue sections. These findings indicate that intra-operative and surgical specimens of squamous cell carcinoma tissue can be characterized by FTIR imaging.     

Raman spectroscopic study on classification of cervical cell specimens

Cervix-cancer is the third most common female cancer worldwide. Papanicolaou (Pap) test, a well-recognized screening tool, is labor intensive, time consuming and prone to subjective interpretations. Optical spectroscopic methods, sensitive to molecular changes are being pursued as potential diagnostics tool. In this study we have explored Raman spectroscopic approach to differentiate exfoliated cell pellets using 94 cervical cell specimens (45-normal and 49-abnormal specimens). Study was carried out by two approaches. In the first approach, spectral data from 37 cell specimens were acquired and analyzed by Principal Component-Linear Discriminant Analysis (PC-LDA), which yielded classification efficiencies of 86% and 84% for normal and abnormal specimens, respectively. Mean and difference spectra suggest presence of blood in abnormal specimen as a major cause of discrimination. However, as tumor is vascular, bleeding was observed during abnormal sample collection. Hence, spectra of abnormal specimens show heme and fibrin features, and this can lead to false interpretations, as bleeding also occur in several non-cancerous conditions. Therefore, remaining 57 specimens were treated with Red Blood Corpuscles (RBC) lysis buffer in order to remove the RBC influence. PC-LDA resulted classification efficiency of about 79% and 78% for normal and abnormal smear, respectively – comparable to Pap test. Thus finding of the study suggests feasibility of Raman spectroscopic classification of normal and cancerous exfoliated cervical cell specimens.     

How to winnow actives from inactives: introducing molecular orthogonal sparse bigrams (MOSBs) and multiclass Winnow

In the present paper we combine the Winnow algorithm and an advanced scheme for feature generation into a tool for multiclass classification. The Winnow algorithm, specifically designed in the late 1980s to work well with high-dimensional data, by design ignores most of the irrelevant features for the scoring of each single training/test case. To augment the pool of available molecular features we use the Winnow algorithm in conjunction with a process that creates additional features from a set of given ones. We adapt a technique formerly employed in text classification termed "orthogonal sparse bigrams" and extend the use of that method to the domain of cheminformatics. Using circular molecular fingerprints as initial features, we create "molecular orthogonal sparse bigrams" (MOSBs) and report their successful application to the task of classification of bioactive molecules. Additionally, we introduce a memory-efficient way of bagging individual classifiers, avoiding the need to hold the complete training data set in memory. To compare the performance of our method with published results, we use the Hert data set of 8293 active molecules in 11 classes. We compare our method to Random Forest and find that our method not only is comparable or better in classification accuracy (up to 50% higher in MCC [Matthews correlation coefficient], 98% higher in fraction of correct predictions) but also is quicker to train (by a factor between 2 and 18, depending on the feature generation), more memory efficient, and able to cope more easily with large data sets when we seeded the actives into a pool of 94290 inactive molecules. It is shown that this method can be used with different fingerprints.     

Enzyme-conjugated hybridization chain reaction for magneto-controlled immunoassay of squamous cell carcinoma antigen with pH meter

A nanoparticle-based potentiometric immunoassay was designed for sensitive detection of squamous cell carcinoma antigen on a portable pH meter by coupling enzyme-labeled hybridization chain reaction with two alternating hairpin DNA probes for the signal amplification.     

Ezrin Modulates the Cell Surface Expression of Programmed Cell Death Ligand-1 in Human Cervical Adenocarcinoma Cells

Cancer cells employ programmed cell death ligand-1 (PD-L1), an immune checkpoint protein that binds to programmed cell death-1 (PD-1) and is highly expressed in various cancers, including cervical carcinoma, to abolish T-cell-mediated immunosurveillance. Despite a key role of PD-L1 in various cancer cell types, the regulatory mechanism for PD-L1 expression is largely unknown. Understanding this mechanism could provide a novel strategy for cervical cancer therapy. Here, we investigated the influence of ezrin/radixin/moesin (ERM) family scaffold proteins, crosslinking the actin cytoskeleton and certain plasma membrane proteins, on the expression of PD-L1 in HeLa cells. Our results showed that all proteins were expressed at mRNA and protein levels and that all ERM proteins were highly colocalized with PD-L1 in the plasma membrane. Interestingly, immunoprecipitation assay results demonstrated that PD-L1 interacted with ERM as well as actin cytoskeleton proteins. Furthermore, gene silencing of ezrin, but not radixin and moesin, remarkably decreased the protein expression of PD-L1 without affecting its mRNA expression. In conclusion, ezrin may function as a scaffold protein for PD-L1; regulate PD-L1 protein expression, possibly via post-translational modification in HeLa cells; and serve as a potential therapeutic target for cervical cancer, improving the current immune checkpoint blockade therapy.     

Alterations of HLA class I and II antigen expression in preinvasive, invasive and metastatic cervical cancers

HLA expression is altered in a large variety of human cancers. We performed immunohistochemical staining on tissues from normal, preinvasive, invasive and metastatic cervical cancer tissues using anti-HLA class I or class II antibody. In tissues from normal squamous epithelium, carcinoma in situ (CIS) and microinvasive carcinoma (MIC), the expressions of HLA-B, C heavy chains and class II heavy chain were significantly decreased as disease progressed. When the expression patterns were compared between primary and metastatic squamous cell carcinoma (SCC) lesions, statistically significant down-regulation of HLA class I and class II antigen in metastatic lesions was observed. The rates of HLA-B, C heavy chains and class II heavy chain expressions were all significantly down-regulated compared to the down-regulation rate of class I beta2-microglobulin (beta2m) in invasive squamous lesions, and the expressions of class II heavy chain in metastatic lesions was decreased further than that in primary lesions. Unlike SCC, the degree of HLA class I and class II loss was not evident as disease progressed in early stage of adenocarcinoma. In invasive adenocarcinoma lesions, only the expression of HLA-B, C heavy chains was decreased and no differences were seen in HLA-B, C heavy chain expression patterns between primary and metastatic lesions. These results suggest that alterations of HLA class I and II expressions seem to occur at a particular step in cervical cancer development and depend on tissue types: when the tumor becomes invasive and starts to metastasize.     

Expression of high-abundance proteins in sera of patients with endometrial and cervical cancers: analysis using 2-DE with silver staining and lectin detection methods

The expression of high-abundance serum proteins in newly diagnosed patients with endometrial adenocarcinoma (EACa), squamous cell cervical carcinoma (SCCa) and cervical adenocarcinoma (ACCa), relative to control female subjects, was analyzed by subjecting serum samples to 2-DE followed by image analysis of the silver-stained protein profiles. The three cohorts of cancer patients demonstrated different altered expression of serum high-abundance proteins compared to negative control women. The expression of alpha1-antitrypsin, alpha1-B glycoprotein, cleaved high-molecular-weight kininogen (light chain) and antithrombin III were consistently altered in all the patients. However, clusterin was upregulated only in the patients with EACa, while those with SCCa and ACCa were typically characterized by the upregulated expression of zinc alpha-2-glycoprotein. The aberrant expression of selective serum proteins in the various cohorts of cancer patients was validated by competitive ELISA as well as by lectin detection. Analysis by using the champedak galactose binding lectin further highlighted an unidentified protein that may be differently glycosylated in the sera of the EACa patients that were studied.     

Enzyme-conjugated hybridization chain reaction for magneto-controlled immunoassay of squamous cell carcinoma antigen with pH meter

A nanoparticle-based potentiometric immunoassay was designed for the sensitive detection of squamous cell carcinoma antigen (SCCA; cervical carcinoma marker) on a portable pH meter coupling enzyme-labeled hybridization chain reaction (HCR) with two alternating hairpin DNA probes for the signal amplification. Initially, a sandwich-type immunoreaction was carried out between anti-SCCA capture antibody-conjugated magnetic bead and detection antibody/initiator strand-coated gold nanoparticle (AuNP). Then, the HCR reaction was readily executed between two glucose oxidase (GOx)-labeled hairpins through the initiator strand to form numerous GOx concatamers on the AuNP via the long nicked double-helix. The concatenated GOx oxidized glucose into gluconic acid and hydrogen peroxide, thus resulting in the pH change of the detection solution on a handheld pH meter. Several labeling protocols including GOx-antibody, GOx-AuNP-antibody and GOx-HCR-AuNP-antibody were investigated for detection of target SCCA, and improved analytical features were obtained with the immune-HCR assay. Under optimum conditions, the immune-HCR assay exhibited good pH responses for the determination of SCCA at a concentration as low as 5.7 pg/mL. Additionally, the immune-HCR assay had good precision and reproducibility, high specificity, and acceptable accuracy for analyzing human serum specimens.     

PROMOTIONAL EFFECTS OF ULTRAVIOLET RADIATION ON HUMAN BASAL AND SQUAMOUS CELL CARCINOMA

Abstract— Recent data on the incidence of basal and squamous cell skin cancer among Caucasians in eight regions of the United States have been analyzed. Principal conclusions are that (1) ultraviolet radiation is an effective promoter of non-melanoma skin tumors; (2) the probability of a skin tumor becoming observable in an individual of some given age is well described by the log-normal distribution: (3) the fluence-response relation for both basal and squamous cell tumors is linear with a positive intercept, although the parameter values are clearly different for the two types; (4) a 1% ozone layer depletion would lead to an eventual 1.7% increase in basal cell carcinoma, and a 2.3% increase in squamous cell carcinoma.     

Time-dependent biodistribution of tetra(m-hydroxyphenyl)chlorin and benzoporphyrin derivative monoacid ring A in the hamster model: comparative fluorescence microscopy study

The pharmacokinetics of the photosensitizer used play a key role in the understanding of the mechanism of photodynamic therapy-induced damage. Fluorescence microscopy was used to compare time-dependent biodistribution of tetra(m-hydroxyphenyl)chlorin (mTHPC) and benzoporphyrin derivative monoacid ring A (BPD-MA) in different hamster tissues, including an early, chemically induced, squamous cell carcinoma. Following injection of 0.5 mg/kg body weight of mTHPC and 2.0 mg/kg BPD-MA, groups of three animals were sacrificed at different time points and a series of fluorescence micrographs from different excised organs were analyzed. The highest fluorescence intensities of mTHPC were observed at 96 h for squamous epithelia and skin and at 48 h for smooth muscle. There is no real peak of BPD-MA fluorescence between 30 min and 3 h in the basal epithelial layers, fibroconnective tissue, muscles or blood vessels. At 4 h after injection, the fluorescence level of BPD-MA decreased and at 24 h it had returned to background level in all observed tissues. The significantly faster clearance of BPD-MA is the principal advantage as compared to mTHPC. However, similar localization patterns in different tissues with essentially vascular affinity represent a possible disadvantage for treating early malignancies with BPD-MA as compared to mTHPC, which is mainly localized in various epithelia. For both photosensitizers no significant selectivity between early squamous cell carcinoma and healthy mucosae is seen. Pharmacokinetic studies of different photosensitizers in an appropriate animal model are essential for selecting new-generation photosensitizers with the most favorable localization for photodynamic therapy of early malignancies in hollow organs.     

A new fatty acid ester of triterpenoid from Celastrus rosthornianus with anti-tumor activitives

The methanol extract of the stalks of Celastrus rosthornianus Loes. afforded a new fatty acid ester of triterpene: 1beta,3beta-dihydroxy-olean-9(11),12-dienyl-3-palmitate (1), and three known compounds beta-amyrin palmitate (2), 3beta-hydroxy-11-oxo-olean-12-enyl-3-palmitate (3) and lupeol palmitate (4). Their structures were established by HRMS, 1D and 2D NMR experiments, as well as, by chemical degradation. The new compound showed cytotoxicity against human cervical squamous carcinoma (Hela) cells.     

Recognition of protein allosteric states and residues: Machine learning approaches

Allostery is a process by which proteins transmit the effect of perturbation at one site to a distal functional site upon certain perturbation. As an intrinsically global effect of protein dynamics, it is difficult to associate protein allostery with individual residues, hindering effective selection of key residues for mutagenesis studies. The machine learning models including decision tree (DT) and artificial neural network (ANN) models were applied to develop classification model for a cell signaling allosteric protein with two states showing extremely similar tertiary structures in both crystallographic structures and molecular dynamics simulations. Both DT and ANN models were developed with 75% and 80% of predicting accuracy, respectively. Good agreement between machine learning models and previous experimental as well as computational studies of the same protein validates this approach as an alternative way to analyze protein dynamics simulations and allostery. In addition, the difference of distributions of key features in two allosteric states also underlies the population shift hypothesis of dynamics‐driven allostery model. © 2018 Wiley Periodicals, Inc.