METHODS: RNA was isolated from peripheral whole blood samples (2 x 10 ml) collected from NPC patients/controls (EDTA vacutainer). Gene expression patterns from 99 samples (66 NPC; 33 controls) were assessed using the Affymetrix array. We also collected expression data from 447 patients with other cancers (201 patients) and non-cancer conditions (246 patients). Multivariate logistic regression analysis was used to obtain biomarker signatures differentiating NPC samples from controls and other diseases. Differences were also analysed within a subset (n=28) of a pre-intervention case cohort of patients whom we followed post-treatment.
RESULTS: A blood-based gene expression signature composed of three genes - LDLRAP1, PHF20, and LUC7L3 - is able to differentiate NPC from various other diseases and from unaffected controls with significant accuracy (area under the receiver operating characteristic curve of over 0.90). By subdividing our NPC cohort according to the degree of patient response to treatment we have been able to identify a blood gene signature that may be able to guide the selection of treatment.
CONCLUSION: We have identified a blood-based gene signature that accurately distinguished NPC patients from controls and from patients with other diseases. The genes in the signature, LDLRAP1, PHF20, and LUC7L3, are known to be involved in carcinoma of the head and neck, tumour-associated antigens, and/or cellular signalling. We have also identified blood-based biomarkers that are (potentially) able to predict those patients who are more likely to respond to treatment for NPC. These findings have significant clinical implications for optimizing NPC therapy.
RESULTS: Remarkably, modules could be grouped into just four functional themes: transcription regulation, immunological, extracellular, and neurological, with module generation frequently driven by lncRNA tissue specificity. Notably, three modules associated with the extracellular matrix represented potential networks of lncRNAs regulating key events in tumour progression. These included a tumour-specific signature of 33 lncRNAs that may play a role in inducing epithelial-mesenchymal transition through modulation of TGFβ signalling, and two stromal-specific modules comprising 26 lncRNAs linked to a tumour suppressive microenvironment and 12 lncRNAs related to cancer-associated fibroblasts. One member of the 12-lncRNA signature was experimentally supported by siRNA knockdown, which resulted in attenuated differentiation of quiescent fibroblasts to a cancer-associated phenotype.
CONCLUSIONS: Overall, the study provides a unique pan-cancer perspective on the lncRNA functional landscape, acting as a global source of novel hypotheses on lncRNA contribution to tumour progression.
METHODS: Colon tissues (normal and cancerous) were homogenized and the proteins were extracted using three protein extraction buffers. The extraction buffers were used in an orderly sequence of increasing extraction strength for proteins with hydrophobic properties. The protein extracts were separated using the SDS-PAGE method and the images were captured and analyzed using Quantity One software. The target protein bands were subjected to in-gel digestion with trypsin and finally analyzed using an ESI-ion trap mass spectrometer.
RESULTS: A total of 50 differentially expressed proteins in colonic cancerous and normal tissues were identified.
CONCLUSION: Many of the identified proteins have been reported to be involved in the progression of similar or other types of cancers. However, some of the identified proteins have not been reported before. In addition, a number of hypothetical proteins were also identified.
CONCLUSIONS: HMGB1 plays multiple roles in promoting the pathogenesis of colorectal cancer, despite a few contradicting studies. HMGB1 may differentially regulate disease-related processes, depending on the redox status of the protein in colorectal cancer. Binding of HMGB1 to various protein partners may alter the impact of HMGB1 on disease progression. As HMGB1 is heavily implicated in the pathogenesis of colorectal cancer, it is crucial to further improve our understanding of the functional roles of HMGB1 not only in colorectal cancer, but ultimately in all types of cancers.
METHODS: In this study, plasma miRNA profiles from eight early-stage breast cancer patients and nine age-matched (± 2 years) healthy controls were characterized by miRNA array-based approach, followed by differential gene expression analysis, Independent T-test and construction of Receiver Operating Characteristic (ROC) curve to determine the capability of the assays to discriminate between breast cancer and the healthy control.
RESULTS: Based on the 372-miRNAs microarray profiling, a set of 40 differential miRNAs was extracted regarding to the fold change value at 2 and above. We further sub grouped 40 miRNAs of breast cancer patients that were significantly expressed at 2-fold change and higher. In this set, we discovered that 24 miRNAs were significantly upregulated and 16 miRNAs were significantly downregulated in breast cancer patients, as compared to the miRNA expression of healthy subjects. ROC curve analysis revealed that seven miRNAs (miR-125b-5p, miR-142-3p, miR-145-5p, miR-193a-5p, miR-27b-3p, miR-22-5p and miR-423-5p) had area under curve (AUC) value > 0.7 (AUC p-value < 0.05). Overlapping findings from differential gene expression analysis, ROC analysis, and Independent T-Test resulted in three miRNAs (miR-27b-3p, miR-22-5p, miR-145-5p). Cohen's effect size for these three miRNAs was large with d value are more than 0.95.
CONCLUSION: miR-27b-3p, miR-22-5p, miR-145-5p could be potential biomarkers to distinguish breast cancer patients from healthy controls. A validation study for these three miRNAs in an external set of samples is ongoing.
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MAIN BODY: This review highlights the roles of CSCs in tumour initiation, progression and metastasis with a focus on the cellular and molecular regulators that influence their phenotypical changes and behaviours in the different stages of cancer progression. We delineate the cross-talks between CSCs with the tumour microenvironment that support their intrinsic properties including survival, stemness, quiescence and their cellular and molecular adaptation in response to therapeutic pressure. An insight into the distinct roles of CSCs in promoting angiogenesis and metastasis has been captured based on in vitro and in vivo evidences.
CONCLUSION: Given dynamic cellular events along the cancer progression and contributions of resistance nature by CSCs, understanding their molecular and cellular regulatory mechanism in a heterogeneous nature, provides significant cornerstone for the development of CSC-specific therapeutics.