92-Gene Molecular Profiling in Identification of Cancer Origin: A Retrospective Study in Chinese Population and Performance within Different Subgroups

BACKGROUND: After cancer diagnosis, therapy for the patient is largely dependent on the tumor origin, especially when a metastatic tumor is being treated. However, cases such as untypical metastasis, poorly differentiated tumors or even a limited number of tumor cells may lead to challenges in identifying the origin. Moreover, approximately 3% to 5% of total solid tumor patients will not have to have their tumor origin identified in their lifetime. The THEROS CancerTYPE ID® is designed for identifying the tumor origin with an objective, rapid and standardized procedure. METHODOLOGY AND PRINCIPAL FINDINGS: This is a blinded retrospective study to evaluate performance of the THEROS CancerTYPE ID® in a Chinese population. In total, 184 formalin-fixed paraffin-embedded (FFPE) samples of 23 tumor origins were collected from the tissue bank of Fudan University Shanghai Cancer Center (FDUSCC). A standard tumor cell enrichment process was used, and the prediction results were compared with reference diagnosis, which was confirmed by two experienced pathologists at FDUSCC. All of the 184 samples were successfully analyzed, and no tumor specimens were excluded because of sample quality issues. In total, 151 samples were correctly predicted. The agreement rate was 82.1%. A Pearson Chi-square test shows that there is no difference between this study and the previous evaluation test performed by bioTheranostics Inc. No statistically significant decrease was observed in either the metastasis group or tumors with high grades. CONCLUSIONS: A comparable result with previous work was obtained. Specifically, specimens with a high probability score (>0.85) have a high chance (agreement rate = 95%) of being correctly predicted. No performance difference was observed between primary and metastatic specimens, and no difference was observed among three tumor grades. The use of laser capture micro-dissection (LCM) makes the THEROS CancerTYPE ID® accessible to almost all of the cancer patients with different tumor statuses

An approach for the identification of targets specific to bone metastasis using cancer genes interactome and gene ontology analysis

Metastasis is one of the most enigmatic aspects of cancer pathogenesis and is a major cause of cancer-associated mortality. Secondary bone cancer (SBC) is a complex disease caused by metastasis of tumor cells from their primary site and is characterized by intricate interplay of molecular interactions. Identification of targets for multifactorial diseases such as SBC, the most frequent complication of breast and prostate cancers, is a challenge. Towards achieving our aim of identification of targets specific to SBC, we constructed a 'Cancer Genes Network', a representative protein interactome of cancer genes. Using graph theoretical methods, we obtained a set of key genes that are relevant for generic mechanisms of cancers and have a role in biological essentiality. We also compiled a curated dataset of 391 SBC genes from published literature which serves as a basis of ontological correlates of secondary bone cancer. Building on these results, we implement a strategy based on generic cancer genes, SBC genes and gene ontology enrichment method, to obtain a set of targets that are specific to bone metastasis. Through this study, we present an approach for probing one of the major complications in cancers, namely, metastasis. The results on genes that play generic roles in cancer phenotype, obtained by network analysis of 'Cancer Genes Network', have broader implications in understanding the role of molecular regulators in mechanisms of cancers. Specifically, our study provides a set of potential targets that are of ontological and regulatory relevance to secondary bone cancer.Comment: 54 pages (19 pages main text; 11 Figures; 26 pages of supplementary information). Revised after critical reviews. Accepted for Publication in PLoS ON

Factors affecting the yield of microRNAs from laser microdissectates of formalin-fixed tissue sections

<p>Abstract</p> <p>Background</p> <p>Quantification of microRNAs in specific cell populations microdissected from tissues can be used to define their biological roles, and to develop and deploy biomarker assays. In this study, a number of variables were examined for their effect on the yield of microRNAs in samples obtained from formalin-fixed paraffin-embedded tissues by laser microdissection.</p> <p>Results</p> <p>MicroRNA yield was improved by using cresyl violet instead of hematoxylin-eosin to stain tissue sections in preparation for microdissection, silicon carbide instead of glass fiber as matrix in RNA-binding columns, and overnight digestion of dissected samples with proteinase K. Storage of slides carrying stained tissue sections at room temperature for up to a week before microdissection, and storage of the microdissectates at room temperature for up to a day before RNA extraction did not adversely affect microRNA yield.</p> <p>Conclusions</p> <p>These observations should be of value for the efficient isolation of microRNAs from microdissected formalin-fixed tissues with a flexible workflow.</p

Elevated tumour interleukin-1β is associated with systemic inflammation: a marker of reduced survival in gastro-oesophageal cancer

Systemic inflammation is associated with adverse prognosis cancer but its aetiology remains unclear. We investigated the expression of proinflammatory cytokines within normal mucosa from healthy controls and tumour tissue in cancer patients and related these levels with markers of systemic inflammation and with the presence of a tumour inflammatory infiltrate. Tissue was collected from 56 patients with gastro-oesophageal cancer and from 12 healthy controls. Tissue cytokine mRNA concentrations were measured by real-time PCR and tissue protein concentrations by cytometric bead array. The degree of chronic inflammatory cell infiltrate was recorded. Serum cytokine and acute phase protein concentrations (including C-reactive protein (CRP)) were measured by enzyme-linked immunosorbent assay. Proinflammatory cytokines were significantly overexpressed (interleukin (IL)-1β, IL-6, IL-8 and tumour necrosis factor-α) both at mRNA and protein levels in the cancer specimens compared with mucosa from controls. Interleukin-1β was expressed in greatest (10–100-fold) concentration and protein levels correlated significantly with systemic inflammation (CRP) (P=0.05, r=0.31). A chronic inflammatory infiltrate was observed in 75% of the cancer specimens and was associated with systemic inflammation (CRP: P=0.01). However, the presence of chronic inflammation per se was not associated with altered cytokine expression within the tumour. Both a chronic inflammatory infiltrate and systemic inflammation (CRP) were associated with reduced survival (P=0.05 and P=0.03, respectively). Tumour chronic inflammatory infiltrate and tumour tissue IL-1β overexpression are potential independent factors influencing systemic inflammation in oesophagogastric cancer patients

Cystatin E/M suppresses legumain activity and invasion of human melanoma

<p>Abstract</p> <p>Background</p> <p>High activity of cysteine proteases such as legumain and the cathepsins have been shown to facilitate growth and invasion of a variety of tumor types. In breast cancer, several recent studies have indicated that loss of the cysteine protease inhibitor cystatin E/M leads to increased growth and metastasis. Although cystatin E/M is normally expressed in the skin, its role in cysteine protease regulation and progression of malignant melanoma has not been studied.</p> <p>Methods</p> <p>A panel of various non-melanoma and melanoma cell lines was used. Cystatin E/M and C were analyzed in cell media by immunoblotting and ELISA. Legumain, cathepsin B and L were analyzed in cell lysates by immunoblotting and their enzymatic activities were analyzed by peptide substrates. Two melanoma cell lines lacking detectable secretion of cystatin E/M were transfected with a cystatin E/M expression plasmid (pCST6), and migration and invasiveness were studied by a Matrigel invasion assay.</p> <p>Results</p> <p>Cystatin E/M was undetectable in media from all established melanoma cell lines examined, whereas strong immunobands were detected in two of five primary melanoma lines and in two of six lines derived from patients with metastatic disease. Among the four melanoma lines secreting cystatin E/M, the glycosylated form (17 kD) was predominant compared to the non-glycosylated form (14 kD). Legumain, cathepsin B and L were expressed and active in most of the cell lines, although at low levels in the melanomas expressing cystatin E/M. In the melanoma lines where cystatin E/M was secreted, cystatin C was generally absent or expressed at a very low level. When melanoma cells lacking secretion of cystatin E/M were transfected with pCST6, their intracellular legumain activity was significantly inhibited. In contrast, cathepsin B activity was not affected. Furthermore, invasion was suppressed in cystatin E/M over-expressing melanoma cell lines as measured by the transwell Matrigel assay.</p> <p>Conclusions</p> <p>These results suggest that the level of cystatin E/M regulates legumain activity and hence the invasive potential of human melanoma cells.</p

Identification of a gene signature for discriminating metastatic from primary melanoma using a molecular interaction network approach

Understanding the biological factors that are characteristic of metastasis in melanoma remains a key approach to improving treatment. In this study, we seek to identify a gene signature of metastatic melanoma. We configured a new network-based computational pipeline, combined with a machine learning method, to mine publicly available transcriptomic data from melanoma patient samples. Our method is unbiased and scans a genome-wide protein-protein interaction network using a novel formulation for network scoring. Using this, we identify the most influential, differentially expressed nodes in metastatic as compared to primary melanoma. We evaluated the shortlisted genes by a machine learning method to rank them by their discriminatory capacities. From this, we identified a panel of 6 genes, ALDH1A1, HSP90AB1, KIT, KRT16, SPRR3 and TMEM45B whose expression values discriminated metastatic from primary melanoma (87% classification accuracy). In an independent transcriptomic data set derived from 703 primary melanomas, we showed that all six genes were significant in predicting melanoma specific survival (MSS) in a univariate analysis, which was also consistent with AJCC staging. Further, 3 of these genes, HSP90AB1, SPRR3 and KRT16 remained significant predictors of MSS in a joint analysis (HR = 2.3, P = 0.03) although, HSP90AB1 (HR = 1.9, P = 2 × 10−4) alone remained predictive after adjusting for clinical predictors

Toward an Open-Access Global Database for Mapping, Control, and Surveillance of Neglected Tropical Diseases

There is growing interest in the scientific community, health ministries, and other organizations to control and eventually eliminate neglected tropical diseases (NTDs). Control efforts require reliable maps of NTD distribution estimated from appropriate models and survey data on the number of infected people among those examined at a given location. This kind of data is often available in the literature as part of epidemiological studies. However, an open-access database compiling location-specific survey data does not yet exist. We address this problem through a systematic literature review, along with contacting ministries of health, and research institutions to obtain disease data, including details on diagnostic techniques, demographic characteristics of the surveyed individuals, and geographical coordinates. All data were entered into a database which is freely accessible via the Internet (http://www.gntd.org). In contrast to similar efforts of the Global Atlas of Helminth Infections (GAHI) project, the survey data are not only displayed in form of maps but all information can be browsed, based on different search criteria, and downloaded as Excel files for further analyses. At the beginning of 2011, the database included over 12,000 survey locations for schistosomiasis across Africa, and it is continuously updated to cover other NTDs globally