Reliable microRNA profiling in routinely processed formalin-fixed paraffin-embedded breast cancer specimens using fluorescence labelled bead technology

Background  

During the last years the analysis of microRNA expression patterns has led to completely new insights into cancer biology. Furthermore, these patterns are a very promising tool for the development of new diagnostic and prognostic markers. However, most human tumour samples for which long term clinical records are available exist only as formalin-fixed paraffin-embedded specimens. Therefore, the aim of this study was to examine the feasibility of microRNA profiling studies in routinely processed formalin-fixed paraffin-embedded human breast cancer specimens using fluorescence labelled bead technology.     

Periostin identified as a potential biomarker of prostate cancer by iTRAQ-proteomics analysis of prostate biopsy

Background  

Proteomics may help us better understand the changes of multiple proteins involved in oncogenesis and progression of prostate cancer(PCa) and identify more diagnostic and prognostic biomarkers. The aim of this study was to screen biomarkers of PCa by the proteomics analysis using isobaric tags for relative and absolute quantification(iTRAQ).     

Early detection of gastric cancer after Helicobacter pylori eradication due to endoscopic surveillance

Background

Helicobacter pylori eradication therapy is commonly performed to reduce the incidence of gastric cancer. However, gastric cancer is occasionally discovered even after successful eradication therapy. Therefore, we examined the prognosis of gastric cancer patients, diagnosed after successful H. pylori eradication therapy.

Materials and Methods

All‐cause death rates and gastric cancer‐specific death rates in gastric cancer patients who received successful H. pylori eradication treatment was tracked and compared to rates in patients who did not receive successful eradication therapy.

Results

In total, 160 gastric cancer patients were followed‐up for up to 11.7 years (mean 3.5 years). Among them, 53 gastric cancer patients received successful H. pylori eradication therapy prior to gastric cancer diagnosis. During the follow‐up period, 11 all‐cause deaths occurred. In the successful eradication group, the proportion of patients with cancer stage I was higher. The proportions of patients who received curative endoscopic therapy and endoscopic examination in the 2 years prior to gastric cancer diagnosis were also higher in the successful eradication group. Kaplan–Meier analysis of all‐cause death and gastric cancer‐specific death revealed a lower death rate in patients in the successful eradication group (P = .0139, and P = .0396, respectively, log‐rank test). The multivariate analysis showed that endoscopy within 2 years before cancer diagnosis is associated with stage I cancer.

Conclusions

Possible early discovery of gastric cancer after H. pylori eradication due to regular endoscopic surveillance may contribute to better prognosis of patients with gastric cancer.     

The biological sense of cancer: a hypothesis

Background  

Most theories about cancer proposed during the last century share a common denominator: cancer is believed to be a biological nonsense for the organism in which it originates, since cancer cells are believed to be ones evading the rules that control normal cell proliferation and differentiation. In this essay, we have challenged this interpretation on the basis that, throughout the animal kingdom, cancer seems to arise only in injured organs and tissues that display lost or diminished regenerative ability.     

Meta-analysis of breast cancer microarray studies in conjunction with conserved <Emphasis Type="Italic">cis</Emphasis>-elements suggest patterns for coordinate regulation

Background  

Gene expression measurements from breast cancer (BrCa) tumors are established clinical predictive tools to identify tumor subtypes, identify patients showing poor/good prognosis, and identify patients likely to have disease recurrence. However, diverse breast cancer datasets in conjunction with diagnostic clinical arrays show little overlap in the sets of genes identified. One approach to identify a set of consistently dysregulated candidate genes in these tumors is to employ meta-analysis of multiple independent microarray datasets. This allows one to compare expression data from a diverse collection of breast tumor array datasets generated on either cDNA or oligonucleotide arrays.     

Levels of certain tumor markers as differential factors between bilharzial and non-biharzial bladder cancer among Egyptian patients

Background/Objective  

Bladder cancer is the commonest type of malignant tumors as a result of schistosomaisis which is a major healthy problem in many subtropical developing countries. The aim of this study is to comparatively elucidate the underlying biochemical tumor markers in schistosomal bladder cancer versus non-schistosomal bladder cancer when compared to normal healthy ones.     

Long noncoding RNA LINC00978 promotes cancer growth and acts as a diagnostic biomarker in gastric cancer

Objectives

Long noncoding RNAs (lncRNAs) play important roles in cancer development and progression. The deregulated expression of LINC00978 has been reported in human cancers. However, the expression pattern and biological roles of LINC00978 in gastric cancer (GC) remain unclear. In this study, we investigated the potential roles and clinical value of LINC00978 in gastric cancer.

Materials and methods

QRT‐PCR was performed to investigate the expression of LINC00978 in gastric cancer cell lines, tissues and serum samples. Cell counting, colony formation, transwell migration and matrigel invasion assays were performed to determine the effects of shRNA‐mediated knockdown of LINC00978 on gastric cancer cell functions. In vivo tumour growth assay was also conducted. Flow cytometry, immunohistochemistry, western blot and qRT‐PCR were used for potential mechanism study.

Results

LINC00978 expression level was elevated in GC tumour tissues, serum samples and cell lines. The expression level of LINC00978 was significantly correlated with tumour size (P = 0.02), lymphatic metastasis (P = 0.009) and TNM stage (P = 0.009). LINC00978 knockdown inhibited the proliferation of GC cells by suppressing cell cycle progression and inducing apoptosis. LINC00978 knockdown also inhibited the migration and invasion of GC cells. In addition, LINC00978 knockdown inhibited the activation of TGF‐β/SMAD signalling pathway and the process of epithelial‐mesenchymal transition (EMT) in GC cells. Moreover, the in vivo tumorigenicity of LINC00978 knockdown GC cells in mice was significantly decreased.

Conclusions

LINC00978 promotes gastric cancer progression and may serve as a potential biomarker for GC.     

Comparative proteome analysis of human epithelial ovarian cancer

Background  

Epithelial ovarian cancer is a devastating disease associated with low survival prognosis mainly because of the lack of early detection markers and the asymptomatic nature of the cancer until late stage. Using two complementary proteomics approaches, a differential protein expression profile was carried out between low and highly transformed epithelial ovarian cancer cell lines which realistically mimic the phenotypic changes observed during evolution of a tumour metastasis. This investigation was aimed at a better understanding of the molecular mechanisms underlying differentiation, proliferation and neoplastic progression of ovarian cancer.     

Predicting cancer involvement of genes from heterogeneous data

Background  

Systematic approaches for identifying proteins involved in different types of cancer are needed. Experimental techniques such as microarrays are being used to characterize cancer, but validating their results can be a laborious task. Computational approaches are used to prioritize between genes putatively involved in cancer, usually based on further analyzing experimental data.     

Best serum biomarker combination for ovarian cancer classification

Background

Screening test using CA-125 is the most common test for detecting ovarian cancer. However, the level of CA-125 is diverse by variable condition other than ovarian cancer. It has led to misdiagnosis of ovarian cancer.

Methods

In this paper, we explore the 16 serum biomarker for finding alternative biomarker combination to reduce misdiagnosis. For experiment, we use the serum samples that contain 101 cancer and 92 healthy samples. We perform two major tasks: Marker selection and Classification. For optimal marker selection, we use genetic algorithm, random forest, T-test and logistic regression. For classification, we compare linear discriminative analysis, K-nearest neighbor and logistic regression.

Results

The final results show that the logistic regression gives high performance for both tasks, and HE4-ELISA, PDGF-AA, Prolactin, TTR is the best biomarker combination for detecting ovarian cancer.

Conclusions

We find the combination which contains TTR and Prolactin gives high performance for cancer detection. Early detection of ovarian cancer can reduce high mortality rates. Finding a combination of multiple biomarkers for diagnostic tests with high sensitivity and specificity is very important.

     

The association of garlic with Helicobacter pylori infection and gastric cancer risk: A systematic review and meta‐analysis

Background

Garlic may be protective against Helicobacter pylori infection and gastric cancer development. We conducted this study to quantitatively update evidence on garlic intake and gastric cancer with the inclusion of most recent cohort studies and qualitatively summarize epidemiological studies of garlic consumption and Helicobacter pylori infection.

Materials and Methods

PubMed, Embase, MEDLINE, and Cochrane Library were searched on April 2018. We conducted a meta‐analysis to determine whether garlic intake reduced gastric cancer risk using random‐effect models and a systematic review to summarize evidence on the association between garlic consumption and Helicobacter pylori infection. Risk of bias was assessed using tools of Cochrane risk of bias and Robins‐I for randomized and nonrandomized studies, respectively.

Results

Meta‐analysis of 18 studies (142 921 subjects) demonstrated high garlic consumption (as comparing the highest category to the lowest) was associated with a reduced gastric cancer risk (OR = 0.51, 95% CI = 0.44‐0.57). This association became nonsignificant if only derived from the prospective studies (OR = 0.95, 95% CI = 0.66‐1.24). Thirteen studies (4889 participants) were included in the systematic review for garlic consumption and Helicobacter pylori infection; ten of which found no significant results. The majority of these studies were poor in quality given the small sample size and high risk of bias.

Conclusions

Pooled evidence, mainly from case‐control studies, suggested a significant inverse association of garlic intake with gastric cancer risk. Given the limitations of included studies, current epidemiological evidence is not sufficient to reach any definite conclusion regarding the association of garlic with Helicobacter pylori infection.     

Seroma formation after surgery for breast cancer

Background  

Seroma formation is the most frequent postoperative complication after breast cancer surgery. We carried out a study to investigate the effect of various demographic, clinical and therapeutic variables on seroma formation.     

Aberrant glycosylation associated with enzymes as cancer biomarkers

Background  

One of the new roles for enzymes in personalized medicine builds on a rational approach to cancer biomarker discovery using enzyme-associated aberrant glycosylation. A hallmark of cancer, aberrant glycosylation is associated with differential expressions of enzymes such as glycosyltransferase and glycosidases. The aberrant expressions of the enzymes in turn cause cancer cells to produce glycoproteins with specific cancer-associated aberrations in glycan structures.     

A simple method to combine multiple molecular biomarkers for dichotomous diagnostic classification

Background  

In spite of the recognized diagnostic potential of biomarkers, the quest for squelching noise and wringing in information from a given set of biomarkers continues. Here, we suggest a statistical algorithm that – assuming each molecular biomarker to be a diagnostic test – enriches the diagnostic performance of an optimized set of independent biomarkers employing established statistical techniques. We validated the proposed algorithm using several simulation datasets in addition to four publicly available real datasets that compared i) subjects having cancer with those without; ii) subjects with two different cancers; iii) subjects with two different types of one cancer; and iv) subjects with same cancer resulting in differential time to metastasis.     

Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clustering

Background  

The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell tumor (SRBCT) and thus often leads to misdiagnosis. Identification of biomarkers for distinguishing these cancers is a well studied problem. Existing methods typically evaluate each gene separately and do not take into account the nonlinear interaction between genes and the tools that are used to design the diagnostic prediction system. Consequently, more genes are usually identified as necessary for prediction. We propose a general scheme for finding a small set of biomarkers to design a diagnostic system for accurate classification of the cancer subgroups. We use multilayer networks with online gene selection ability and relational fuzzy clustering to identify a small set of biomarkers for accurate classification of the training and blind test cases of a well studied data set.     

The Estradiol-Dihydrotestosterone model of prostate cancer

Background  

The exact relationship between hormonal activity and prostate cancer(PCa) has not yet been clearly defined. One of the key hormones associated with PCa is testosterone(T). However, both in vitro and in vivo studies have shown that under some conditions T is capable of either promoting PCa growth or death. This article proposes a theory which resolves this apparent paradox.