Fingerprinting the diseased prostate: associations between BPH and prostate cancer

Two of the most common diseases which occur in ageing men relate to their prostate. BPH and prostate cancer are prevalent diseases which have an impact on most men as they age. The advent of gene expression analysis has provided an opportunity to examine these diseases in a novel fashion. These analyses, to date, have revealed associations between these two diseases which have not been previously identified. These commonalities include global genetic changes which occur throughout the prostates in individuals with these diseases. Understanding the fingerprints of these diseases is providing novel markers and treatment strategies for both BPH and prostate cancer.     

Comprehensive serum N-glycan profiling identifies a biomarker panel for early diagnosis of non-small-cell lung cancer

Aberrant serum N-glycan profiles have been observed in multiple cancers including non-small-cell lung cancer (NSCLC), yet the potential of N-glycans in the early diagnosis of NSCLC remains to be determined. In this study, serum N-glycan profiles of 275 NSCLC patients and 309 healthy controls were characterized by MALDI-TOF-MS. The levels of serum N-glycans and N-glycosylation patterns were compared between NSCLC and control groups. In addition, a panel of N-glycan biomarkers for NSCLC diagnosis was established and validated using machine learning algorithms. As a result, a total of 54 N-glycan structures were identified in human serum. Compared with healthy controls, 29 serum N-glycans were increased or decreased in NSCLC patients. N-glycan abundance in different histological types or clinical stages of NSCLC presented differentiated changes. Furthermore, an optimal biomarker panel of eight N-glycans was constructed based on logistic regression, with an AUC of 0.86 in the validation set. Notably, this model also showed a desirable capacity in distinguishing early-stage patients from healthy controls (AUC = 0.88). In conclusion, our work highlights the abnormal N-glycan profiles in NSCLC and provides supports potential application of N-glycan biomarker panel in clinical NSCLC detection.     

Novel miRNA markers for the diagnosis and prognosis of endometrial cancer

As endometrial cancer (EC) is a major threat to female health worldwide, the ability to provide an accurate diagnosis and prognosis of EC is promising to improve its treatment guidance. Since the discovery of miRNAs, it has been realized that miRNAs are associated with every cell function, including malignant transformation and metastasis. This study aimed to explore diagnostic and prognostic miRNA markers of EC. In this study, differential analysis and machine learning were performed, followed by correlation analysis of miRNA‐mRNA based on the miRNA and mRNA expression data. Nine miRNAs were identified as diagnostic markers, and a diagnostic classifier was established to distinguish between EC and normal endometrium tissue with overall correct rates >95%. Five specific prognostic miRNA markers were selected to construct a prognostic model, which was confirmed more effective in identifying EC patients at high risk of mortality compared with the FIGO staging system. This study demonstrates that the expression patterns of miRNAs may hold promise for becoming diagnostic and prognostic biomarkers and novel therapeutic targets for EC.     

细胞外微RNA:一种新型的肺癌分子生物标志物

尽管癌症的早期诊断和治疗在不断发展和进步,但寻找一种敏感、准确和微创的分子生物标志物,用于肿瘤的诊断仍是一项艰巨任务。微RNA(miRNA)是一类长约21～24个核甘酸的内源性非编码小分子RNA。细胞外miRNA作为一种新型的分子生物标志物,在癌症诊断方面具有微创、高灵敏度和高特异性等许多潜在特征。近年来,细胞外miRNA研究成果颇丰。文章就细胞外miRNA的来源、功能、检测以及作为分子标志物在肺癌诊断中的作用和目前存在的一些问题进行了综述。     

Development and validation of hub genes for lymph node metastasis in patients with prostate cancer

Lymph node metastasis is one of the most important independent risk factors that can negatively affect the prognosis of prostate cancer (PCa); however, the exact mechanisms have not been well studied. This study aims to better understand the underlying mechanism of lymph node metastasis in PCa by bioinformatics analysis. We analysed a total of 367 PCa cases from the cancer genome atlas database and performed weighted gene co‐expression network analysis to explore some modules related to lymph node metastasis. Gene Ontology analysis and pathway enrichment analysis were conducted for functional annotation, and a protein‐protein interaction network was built. Samples from the International Cancer Genomics Consortium database were used as a validation set. The turquoise module showed the most relevance with lymph node metastasis. Functional annotation showed that biological processes and pathways were mainly related to activation of the processes of cell cycle and mitosis. Four hub genes were selected: CKAP2L, CDCA8, ERCC6L and ARPC1A. Further validation showed that the four hub genes well‐distinguished tumour and normal tissues, and they were good biomarkers for lymph node metastasis of PCa. In conclusion, the identified hub genes facilitate our knowledge of the underlying molecular mechanism for lymph node metastasis of PCa.     

Outcome modeling techniques for prostate cancer radiotherapy: Data,models, and validation

Prostate cancer is a frequently diagnosed malignancy worldwide and radiation therapy is a first-line approach in treating localized as well as locally advanced cases. The limiting factor in modern radiotherapy regimens is dose to normal structures, an excess of which can lead to aberrant radiation-induced toxicities. Conversely, dose reduction to spare adjacent normal structures risks underdosing target volumes and compromising local control. As a result, efforts aimed at predicting the effects of radiotherapy could invaluably optimize patient treatments by mitigating such toxicities and simultaneously maximizing biochemical control. In this work, we review the types of data, frameworks and techniques used for prostate radiotherapy outcome modeling. Consideration is given to clinical and dose-volume metrics, such as those amassed by the QUANTEC initiative, and also to newer methods for the integration of biological and genetic factors to improve prediction performance. We furthermore highlight trends in machine learning that may help to elucidate the complex pathophysiological mechanisms of tumor control and radiation-induced normal tissue side effects.     

Genetic characterization of breast cancer and implications for clinical management

Breast cancer is a genetic disease caused by the accumulation of mutations in neoplastic cells. In the last few years, high-throughput microarray-based molecular analysis has provided increasingly more coherent information about the genetic aberrations in breast cancer. New biomarkers and molecular techniques are slowly becoming part of the diagnostic and prognostic armamentarium available for pathologists and oncologists to tailor the therapy for breast cancer patients. In this review, we will focus on the contribution of breast cancer somatic genetics to our understanding of breast cancer biology and its impact on breast cancer patient management.     

Molecular profile of androgen-independent prostate cancer xenograft LuCaP 23.1

After castration or therapeutic hormone deprivation, most cancer of the prostate (CaP) cells develop androgen-independent (AI) growth. In this work, we studied the effect of androgen depletion (castration) on the growth of experimental model LuCaP 23.1 xenograft. A total of 101 nude mice were implanted and analysed for their growth profile before experimental period 1 (11 weeks) and after castration experimental period 2 (15 weeks). For specific periods, tumors were harvested and assessed for molecular marker expression specific for CaP. Taking into account tumor dynamic growth, prior to castration we found 37 fast growing (FG) tumors (948.9 ± 76.9 mm³) and 63 slow growing (SG) tumors (229.6 ± 18.4 mm³). Real-time quantitative RT-PCR showed that in comparison to SGs, FGs contained elevated expression of epidermal growth factor receptor type 1 (HER1), urokinase plasminogen activator (uPA), thymidine phosphorylase (TP) and thymidilate synthase (TS) mRNAs expression and low levels of 5-reductase 2 (5-R2) mRNA. After castration all FG tumors progressed rapidly (by 5 weeks) to AI growth (FG-P). In SG castrated tumors, 66% of tumors showed retarded progression (by 12 weeks) to AI (SG-P), whereas 34% responded to castration (SG-R). Molecular analysis demonstrated distinct molecular profiles integrating different pathways associated with AI progression. The progressive tumors FG-P, and some tumors of SG-P subgroup, presented significantly high levels of HER1, epidermal growth factor receptor type 2 (HER2), TS, uPA, TP, tumor necrosis factor superfamily member 6 (FAS) and peptidylglycine -amidating mono-oxygenase (PAM) mRNA all of which correlated with androgen receptor (AR) mRNA. The second subgroup of SG-P tumors showed a high expression of the anti-apoptotic gene Bcl-2. A third subgroup of SG-P tumors showed significant expression of hypoxia-related genes such as adrenomedullin (AM) after castration. LuCaP 23.1 xenograft represent a useful dynamic model to study pre-clinically new therapeutic molecules and evaluate non-randomized therapeutics protocols combining different target inhibition specific to each AI pathways.     

Unsaturated free fatty acids: a potential biomarker panel for early detection of gastric cancer

Abstract

Changes in the levels of free fatty acids (FFAs) are closely associated with physiological status. Serum levels of C_16:1, C_18:3, C_18:2, C_18:1, C_20:4, and C_22:6 in 164 gastric cancer (GC) patients and 111 benign gastric disease (BGD) patients were significantly decreased compared with 252 healthy controls. Receiver operating characteristic analysis showed that the biomarker panel including C_16:1, C_18:3, C_18:2, C_20:4, and C_22:6 presents a high diagnostic ability to differentiate early-stage GC patients from healthy controls plus BGD patients, with a sensitivity of 80.6% and a specificity of 72.7%.     

An electrochemical biosensor for prostate cancer biomarker detection using graphene oxide–gold nanostructures

In this paper, a most sensitive electrochemical biosensor for detection of prostate‐specific antigen (PSA) was designed. To reach the goal, a sandwich type electrode composed of reduced graphene oxide/ gold nanoparticles (GO/AuNPs), Anti‐Total PSA monoclonal antibody, and anti‐Free PSA antibody was assembled. The functionalized materials were thoroughly characterized by atomic force microscope spectroscopy, transmission electron microscopy, and X‐ray diffraction techniques. The electrochemical properties of each of the modification step were evaluated by cyclic voltammetry and electrochemical impedance spectroscopy. The results presented that the proposed biosensor possesses high sensitivity toward total and free PSA. Furthermore, the fabricated biosensor revealed an excellent selectivity for PSA in comparison to the other tumor markers such as BHCG, Alb, CEA, CA125, and CA19‐9. The limit of detection for the proposed electrochemical biosensor was estimated to be around 0.2 and 0.07 ng/mL for total and free PSA antigen, respectively.     

Proton beam and prostate cancer: An evolving debate

This paper evaluates the reasons behind the rise in the use of proton beam for prostate cancer, the economics drivers behind it, and the evidence that exists to support it. It concludes that clinical outcome data underlying the notion that this is a superior treatment remains sparse and discusses what is needed to fill in the gaps.     

MicroRNA‐guided gene expression in prostate cancer: Literature and database overview

Insight into the aberrant expression of microRNAs (miRNAs) and the genes that they regulate during the progression of cancer in general and prostate cancer (PCa) in particular is one of the most important issues in current molecular biomedicine and allows for the discovery of therapeutic or diagnostic miRNA targets. The present study aimed to analyze the available data regarding the direct or indirect effects of miRNAs on the expression of the mRNAs involved in carcinogenesis and to enable updating and optimizing the selection of the corresponding targets. The present review focuses on the data related to the genes with miRNA‐dependent expression during the development of PCa. The data used in this review have been extracted from research papers and the databases STRING, PANTHER and TargetScan, with a special focus on the genes directly associated with cell transformation and the maintenance of the transformed genotype, as well as tumor invasion and spread. The search for miRNA markers of PCa and therapeutically active molecules should rely on bioinformatics resources, such as data from recent experimental studies, as well as meta‐analysis and cross‐analysis of the data on the state of the tumor, patient status, histological/immunohistological data and data on mRNA–miRNA coexpression.     

Random forest for gene selection and microarray data classification

A random forest method has been selected to perform both gene selection and classification of the microarray data. In this embedded method, the selection of smallest possible sets of genes with lowest error rates is the key factor in achieving highest classification accuracy. Hence, improved gene selection method using random forest has been proposed to obtain the smallest subset of genes as well as biggest subset of genes prior to classification. The option for biggest subset selection is done to assist researchers who intend to use the informative genes for further research. Enhanced random forest gene selection has performed better in terms of selecting the smallest subset as well as biggest subset of informative genes with lowest out of bag error rates through gene selection. Furthermore, the classification performed on the selected subset of genes using random forest has lead to lower prediction error rates compared to existing method and other similar available methods.     

Nuclear microenvironment in cancer diagnosis and treatment

The nuclear architecture plays an important role in the temporal and spatial control of complex functional processes within the nucleus. Alterations in nuclear structures are characteristic of cancer cells and the mechanisms underlying these perturbations may directly contribute to tumor development and progression. In this review, we will highlight aspects of the nuclear microenvironment that are perturbed during tumorigenesis and discuss how a greater understanding of the role of nuclear structure in the control of gene expression can provide new options for cancer diagnosis and treatment.     

Universal and cross-cancer prognostic biomarkers for predicting survival risk of cancer patients from expression profile of apoptotic pathway genes

Numerous cancer-specific prognostic models have been developed in the past, wherein one model is applicable for only one type of cancer. In this study, an attempt has been made to identify universal or multi-cancer prognostic biomarkers and develop models for predicting survival risk across different types of cancer patients. In order to accomplish this, we gauged the prognostic role of mRNA expression of 165 apoptosis-related genes across 33 cancers in the context of patient survival. Firstly, we identified specific prognostic biomarker genes for 30 cancers. The cancer-specific prognostic models achieved a minimum Hazard Ratio, HR_SKCM = 1.99 and maximum HR_THCA = 41.59. Secondly, a comprehensive analysis was performed to identify universal biomarkers across many cancers. Our best prognostic model consisted of 11 genes (TOP2A, ISG20, CD44, LEF1, CASP2, PSEN1, PTK2, SATB1, SLC20A1, EREG, and CD2) and stratified risk groups across 27 cancers (HR_OV = 1.53-HR_UVM = 11.74). The model was validated on eight independent cancer cohorts and exhibited a comparable performance. Further, we clustered cancer-types on the basis of shared survival related apoptosis genes. This approach proved helpful in development of cross-cancer prognostic models. To show its efficacy, a prognostic model consisting of 15 genes was thereby developed for LGG-KIRC pair (HR_KIRC = 3.27, HR_LGG = 4.23). Additionally, we predicted potential therapeutic candidates for LGG-KIRC high risk patients.