Locus-Specific Enrichment Analysis of 5-Hydroxymethylcytosine Reveals Novel Genes Associated with Breast Carcinogenesis.

An imbalance in DNA methylation is a hallmark epigenetic alteration in cancer. The conversion of 5-methylcytosine (5-mC) to 5-hydroxymethyl cytosine (5-hmC), which causes the imbalance, results in aberrant gene expression. The precise functional role of 5-hydroxymethylcytosine in breast cancer remains elusive. In this study, we describe the landscape of 5-mC and 5-hmC and their association with breast cancer development. We found a distinguishable global loss of 5-hmC in the localized and invasive types of breast cancer that strongly correlate with TET expression. Genome-wide analysis revealed a unique 5-mC and 5-hmC signature in breast cancer. The differentially methylated regions (DMRs) were primarily concentrated in the proximal regulatory regions such as the promoters and UTRs, while the differentially hydroxymethylated regions (DhMRs) were densely packed in the distal regulatory regions, such as the intergenic regions (>-5 kb from TSSs). Our results indicate 4809 DMRs and 4841 DhMRs associated with breast cancer. Validation of nine 5-hmC enriched loci in a distinct set of breast cancer and normal samples positively correlated with their corresponding gene expression. The novel 5-hmC candidates such as TXNL1, and CNIH3 implicate a pro-oncogenic role in breast cancer. Overall, these results provide new insights into the loci-specific accumulation of 5-mC and 5-hmC, which are aberrantly methylated and demethylated in breast cancer.

Fear of Cancer Recurrence 7 Scale Tamil Translation and Validation among Breast Cancer Survivors in India.

Objectives: Fear of cancer recurrence (FCR) is one of the most widely reported conditions among cancer survivors. The present study aims to translate and validate FCR7 scale into regional language tamil among breast cancer survivors (BCSv). Material and Methods: A cross-sectional study comprising a sample of 106 breast cancer survivors was carried out. FCR 7 scale, functional assessment of cancer therapy-B (FACT-B) and impact of event scale-R (IES-R) were used for establishing reliability and validity. Translation of the FCR7-T scale was done from English into Tamil following the international guidelines and a field study was performed. Results: The test-retest reliability was established for FCR 7 Tamil with a Cronbach's alpha of 0.96 and ICC value of 0.910. On Spearman's correlation, an inverse relationship was found between FCR7 and FACT-B (r = -0.259 and P = 0.01). The survivors with high FCR reported poorer quality of life. Conclusion: The Tamil version of the FCR7 tool is highly sensitive for measuring FCR.

Identification of tumor biomarkers for pathological complete response to neoadjuvant treatment in locally advanced breast cancer.

BACKGROUND: Therapeutic response predictors like age, nodal status, and tumor grade and markers, like ER/PR, HER2, and Ki67, are not reliable in predicting the response to a specific form of chemotherapy. The current study aims to identify and validate reliable markers that can predict pathological complete response (pCR) in fluorouracil, epirubicin, and cyclophosphamide (FEC)-based neoadjuvant therapy with (NACT/RT) and without concurrent radiation (NACT). MATERIALS AND METHODS: Tandem mass tag (TMT) quantitative liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to identify differentially expressed proteins from core needle breast biopsy between pCR (n = 4) and no-pCR (n = 4). Immunoblotting of shortlisted proteins with the tissue lysates confirmed the differential expression of the markers. Further, immunohistochemistry (IHC) was performed on formalin-fixed paraffin-embedded sections of treatment-naive core needle biopsies. In the NACT, 29 pCR and 130 no-pCR and in NACT/RT, 32 pCR and 71 no-pCR were used. RESULTS: 733 and 807 proteins were identified in NACT and NACT/RT groups, respectively. Ten proteins were shortlisted for validation as potential pCR-predictive markers. THBS1, TNC, and DCN were significantly overexpressed in no-pCR in both the groups. In NACT, CPA3 was significantly upregulated in the no-pCR. In NACT/RT, HnRNPAB was significantly upregulated and HMGB1 significantly downregulated in the no-pCR. HMGB1 was the only marker to show prognostic significance. CONCLUSION: Quantitative proteomics followed by IHC identified and validated potential biomarkers for predicting patient response to therapy. These markers can be used, following larger-scale validation, in combination with routine histological analysis providing vital indications of treatment response.

The multifaceted role of Matricellular Proteins in health and cancer, as biomarkers and therapeutic targets.

The extracellular matrix (ECM) is composed of a mesh of proteins, proteoglycans, growth factors, and other secretory components. It constitutes the tumor microenvironment along with the endothelial cells, cancer-associated fibroblasts, adipocytes, and immune cells. The proteins of ECM can be functionally classified as adhesive proteins and matricellular proteins (MCP). In the tumor milieu, the ECM plays a major role in tumorigenesis and therapeutic resistance. The current review encompasses thrombospondins, osteonectin, osteopontin, tenascin C, periostin, the CCN family, laminin, biglycan, decorin, mimecan, and galectins. The matrix metalloproteinases (MMPs) are also discussed as they are an integral part of the ECM with versatile functions in the tumor stroma. In this review, the role of these proteins in tumor initiation, growth, invasion and metastasis have been highlighted, with emphasis on their contribution to tumor therapeutic resistance. Further, their potential as biomarkers and therapeutic targets based on existing evidence are discussed. Owing to the recent advancements in protein targeting, the possibility of agents to modulate MCPs in cancer as therapeutic options are discussed.

RP-HPLC-UV Method for Estimation of Fluorouracil-Epirubicin-Cyclophosphamide and Their Metabolite Mixtures in Human Plasma (Matrix).

A combination of 5-fluorouracil (FU), epirubicin (EP) and cyclophosphamide (CP) is routinely employed in the treatment of breast cancer. The objective of this study was to develop a reverse phase high-performance liquid chromatography (HPLC)-UV method for simultaneous quantitative analysis of the triple-drug and their metabolites in plasma. RP-HPLC system with a C18 column and a diode array detector was employed. The plasma samples were precipitated with acetonitrile and the supernatant was dried under a flow of nitrogen gas. The mobile phase comprised of two combinations, water (pH 4.0) and methanol (98:2 v/v), and water (pH 4.0):methanol:acetonitrile (70:13:17 v/v/v). The retention times for the compounds were determined and the parameters of validation established in plasma indicated the robustness and reliability. The corresponding HPLC peaks were confirmed using electron spray ionization mass spectrometry. FU and metabolites had a recovery of >93%; EP, epirubicinol and CP were >78% from plasma. Stability at 28-30°C in water (pH 4.0) of FU, 5,6-dihydro-5-fluorouracil and EP were higher followed by CP, EPol, fluorodeoxyuridine and fluorouridine (FUR). Storage of the drug-spiked plasma at -80°C assessed for 72 h showed a small but significant (P < 0.05) change in the recovery of FUR and EP. The method was validated in patient's plasma samples (n = 6).

Identification of candidate biomarker mass (m/z) ranges in serous ovarian adenocarcinoma using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry profiling.

OBJECTIVE: To differentiate plasma from ovarian cancer and healthy individuals using MALDI-TOF mass spectroscopy. MATERIALS AND METHODS: MALDI-TOF was used to generate profiles of immuno-depleted plasma samples (89 cancers and 199 healthy individuals) that were fractionated using three types of magnetic beads (HIC8, WCX and IMAC-Cu). RESULTS: Differentially expressed mass ranges showing >1.5-2-fold change in expression from HIC8 (30), WCX (12) and IMAC-Cu (6) fractions were identified. Cross validation and recognition capability scores for the models indicated discrimination between the classes. CONCLUSIONS: Spectral profiles can differentiate plasma samples of ovarian cancer patients from healthy individuals.