MOLECULAR MODELLING AND DOCKING STUDIES OF HUMAN ACROSIN BINDING PROTEIN (ACRBP/OY-TES-1)

Objective: We have made an attempt to identify inhibitors that are bound with Acrosin binding protein (ACRBP/OY-TES-1) through In silico molecular docking studies.Methods: Modeling of ACRBP/OY-TES-1 was performed using Iterative Threading Assembly Refinement (I-TASSER) software. Docking calculations were carried out using Glide. Glide Score (GS core) was used to rank the ligands on the basis of their relative binding affinities.Results: Food and Drug Administration (FDA)-approved drugs were docked with ACRBP/OY-TES-1 to identify potent inhibitors. Leuprolide a decapeptide interacts with the protein at residues Tyr116, Gly421, Leu433, Asp480 and Gln483 with Glide score-14.188. Other compounds that showed high affinity to the protein are triptorelin, nafatarelin, goserelin and sincalide.Conclusion: The investigation concluded that these drugs could be used as potential inhibitors against ACRBP/OY-TES-1 in cancer treatment.Â

COMPUTATIONAL ANALYSIS OF MUTATIONS IN REALLY INTERESTING NEW GENE FINGER DOMAIN AND BRCA1 C TERMINUS DOMAIN OF BREAST CANCER SUSCEPTIBILITY GENE

Objective: Breast Cancer 1 (BRCA1), Early Onset and Breast Cancer 2, Early Onset (BRCA2) genes are involved in pathways important for DNA damagerecognition, double-strand break repair, checkpoint control, transcription regulation, and chromatin remodeling. These functions are essential andimportant for all cell types. Germline mutations in these genes increase the risk of breast and ovarian cancer in women. In this study, we did ananalysis of the functional and structural impact of all known single nucleotide polymorphisms (SNPs) in BRCA1 and BRCA2 using publicly availablecomputational prediction tools.Methods: We analyzed the mutations using two mutation tolerance prediction approaches: Sorting intolerant from tolerant (SIFT), and polymorphismphenotyping (PolyPhen-2). In addition, stability of the protein was analyzed by I-Mutant. Affinity and stability of really interesting new gene (RING)and BRCA1 C-terminus (BRCT) domains were also analyzed by BioLuminate tool.Results: Out of 486 SNPs in BRCA retrieved from functional SNP, a total of 10 SNPs were found to be deleterious by SIFT and PolyPhen. I-Mutant resultsindicate that C27F, A1708V could increase the stability of protein, whereas other mutations decrease the stability. Predicted changes in stability andaffinity of RING and BRCT domains of BRCA were computed using residue scanning functionality in bioluminate for all 10 SNPs. The mutation C61Rcould affect the stability of RING domain and all mutations in BRCT domain were affecting the inter subunit affinity and stability of the complex.Conclusion: The combination of computational methods provides a way in understanding the impact of deleterious mutations in altering the BRCAprotein stability and affinity. Based on our investigation, we report potential candidate SNPs for future studies of BRCA mutations.Keywords: Breast cancer susceptibility gene, BRCA1 C terminus domain, Zinc finger domain, Sorting intolerant from tolerant, Polymorphismphenotyping, I-mutant, BioLuminate

T Cell Receptor Gamma and Delta Gene Rearrangements in T-cell Acute Lymphoblastic Leukemia in South India and Quantitation of Minimal Residual Disease

Background: T cell-Acute Lymphoblastic Leukemia (T-ALL) arises by clonal proliferation of lymphoid precursors arrested at particular stage of differentiation. The incidence of T-ALL in India is 37-43% of ALL. In this study, TCR gamma (TCRG) and TCR delta (TCRD) gene rearrangements were detected in diagnostic samples of ALL. Those clonal rearrangements detected at diagnosis are used as clonal markers for the quantitation of minimal residual disease (MRD) in follow up samples. 

Patients and Methods: BM/PB from 54 T-ALL patients (34 pediatrics and 20 adults) at diagnosis, treated by MCP 841 protocol were studied. Median age of the patients was 13. The frequency of clonal TCRG and TCRD gene rearrangements were studied by Polymerase Chain Reaction (PCR) coupled with Heteroduplex analysis (HD). Allele Specific Oligos (ASO) was designed by sequencing the junctional region sequence of clonal TCRG and TCRD gene rearrangements. MRD was studied in 4 patients with follow up samples. Diagnostic DNA with almost 100% tumor involvement as standard was serially diluted (50ng to 5ng) in 500ng control DNA to give a final concentration of one leukemic cell in 101 (1 in 101) cells to one leuekemic cell in 105 (1 in 105) cells. The serially diluted diagnostic standard in triplicates was amplified with TaqMan probe for respective TCRG/TCRD gene rearrangements in Real-time PCR along with 500ng of follow up DNA samples at different time points (Unknown) in triplicates. Analysis was done to calculate the amount of leukemic cells in follow up samples. 

Results: Using PCR-HD analysis, TCRG gene rearrangements were detected in 37 of 54 cases (68.5%) and TCRD gene rearrangements in 16 of 54 cases (29.6%). VgI-Jg1.3/2.3 was more commonly rearranged in 29 cases (53.7%) of T-ALL; VgII-Jg1.3/2.3 in 14 cases (26%). Both VgIII-Jg1.3/2.3 and VgIV-Jg1.3/2.3 rearrangements were detected in 4 cases respectively and VgI-Jg1.1/2.1 was detected in 3 cases. Vd1-Jd1 rearrangement was detected in 9 cases (16.6%); Vd2-Dd3 in 5 cases and Dd2-Dd3 in 4 cases of T-ALL. Both TCRG and TCRD gene rearrangements were detected in 8 cases (14.8%). The junctional region in TCRG rearrangements ranged from 1nucleotide to 11nucleotide (average 7.6 nt) and in TCRD rearrangements ranged from 14 nucleotide to 42 nucleotide (average 27 nt). In patient 1, the initial leukeimia load of 1 (before treatment) was reduced to 3 leukemic cell in 104 cells at the lost follow up. In patient 2, the initial leukemia load was reduced to 3.7 in 104 cells. In Patient 3, the initial leukemia load 1 was reduced to 6 in 102 cells at end of M2 and disease relapsed at M5. In patient 4, the initial leukemia load was reduced to 1.6 leukemic cell in 104 cells. 

Conclusion: Real-time PCR experiments reached a reproducible sensitivity of detecting one leukemic cell in 104 normal cells. Real-time PCR analysis showed that Patient 3 was not all responded to treatment and it was detectable by Real-time PCR at RI1 stage itself though the disease was clinically evident only at M5 stage of treatment. Thus, monitoring the MRD using Real-time PCR will help to quantitate the accurate amount of residual leukemic load, predate relapse and assess the response to treatment. 
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Identification and validation of genes involved in gastric tumorigenesis

<p>Abstract</p> <p>Background</p> <p>Gastric cancer is one of the common cancers seen in south India. Unfortunately more than 90% are advanced by the time they report to a tertiary centre in the country. There is an urgent need to characterize these cancers and try to identify potential biomarkers and novel therapeutic targets.</p> <p>Materials and methods</p> <p>We used 24 gastric cancers, 20 Paired normal (PN) and 5 apparently normal gastric tissues obtained from patients with non-gastric cancers (Apparently normal - AN) for the microarray study followed by validation of the significant genes (n = 63) by relative quantitation using Taqman Low Density Array Real Time PCR. We then used a custom made Quantibody protein array to validate the expression of 15 proteins in gastric tissues (4 AN, 9 PN and 9 gastric cancers). The same array format was used to study the plasma levels of these proteins in 58 patients with gastric cancers and 18 from patients with normal/non-malignant gastric conditions.</p> <p>Results</p> <p>Seventeen genes (ASPN, CCL15/MIP-1δ, MMP3, SPON2, PRSS2, CCL3, TMEPAI/PMEPAI, SIX3, MFNG, SOSTDC1, SGNE1, SST, IGHA1, AKR1B10, FCGBP, ATP4B, NCAPH2) were shown to be differentially expressed between the tumours and the paired normal, for the first time. EpCAM (p = 0.0001), IL8 (p = 0.0003), CCL4/MIP-1β (p = 0.0026), CCL20/MIP-3α (p = 0.039) and TIMP1 (p = 0.0017) tissue protein levels were significantly different (Mann Whitney U test) between tumours versus AN & PN. In addition, median plasma levels of IL8, CXCL9/MIG, CCL3/MIP-1α, CCL20/MIP-3α, PDGFR-B and TIMP1 proteins were significantly different between the non-malignant group and the gastric cancer group. The post-surgical levels of EpCAM, IGFBP3, IL8, CXCL10/IP10, CXCL9/MIG, CCL3/MIP-1α, CCL20/MIP-3α, SPP1/OPN and PDGFR-B showed a uniform drop in all the samples studied.</p> <p>Conclusions</p> <p>Our study has identified several genes differentially expressed in gastric cancers, some for the first time. Some of these have been confirmed at the protein level, as well. Some of these proteins will need to be evaluated further for their potential as diagnostic biomarkers in gastric cancers and some could be useful as follow-up markers in gastric cancer.</p

A rare truncating BRCA2 variant and genetic susceptibility to upper aerodigestive tract cancer

© The Author 2015. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact [email protected] Funding This work was supported the National Institutes of Health (R01CA092039 05/05S1) and the National Institute of Dental and Craniofacial Research (1R03DE020116). Notes The authors thank all of the participants who took part in this research and the funders and technical staff who made this study possible. We acknowledge and thank Simone Benhamou (INSERM, France) for sample contributions. We also acknowledge and thank The Cancer Genome Atlas initiative, whose data contributed heavily to this study.Peer reviewedPublisher PD

The 12p13.33/RAD52 locus and genetic susceptibility to squamous cell cancers of upper aerodigestive tract

Acknowledgments: The authors thank all of the participants who took part in this research and the funders and support and technical staff who made this study possible. We also acknowledge and thank The Cancer Genome Atlas initiative whose data contributed heavily to this study. Funding: Funding for study coordination, genotyping of replication studies and statistical analysis was provided by the US National Institutes of Health (R01 CA092039 05/05S1) and the National Institute of Dental and Craniofacial Research (1R03DE020116). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Repeated dose studies with pure Epigallocatechin-3-gallate demonstrated dose and route dependant hepatotoxicity with associated dyslipidemia

EGCG (Epigallocatechin-3-gallate) is the major active principle catechin found in green tea. Skepticism regarding the safety of consuming EGCG is gaining attention, despite the fact that it is widely being touted for its potential health benefits, including anti-cancer properties. The lack of scientific data on safe dose levels of pure EGCG is of concern, while EGCG has been commonly studied as a component of GTE (Green tea extract) and not as a single active constituent. This study has been carried out to estimate the maximum tolerated non-toxic dose of pure EGCG and to identify the treatment related risk factors. In a fourteen day consecutive treatment, two different administration modalities were compared, offering an improved [i.p (intraperitoneal)] and limited [p.o (oral)] bioavailability. A trend of dose and route dependant hepatotoxicity was observed particularly with i.p treatment and EGCG increased serum lipid profile in parallel to hepatotoxicity. Fourteen day tolerable dose of EGCG was established as 21.1 mg/kg for i.p and 67.8 mg/kg for p.o. We also observed that, EGCG induced effects by both treatment routes are reversible, subsequent to an observation period for further fourteen days after cessation of treatment. It was demonstrated that the severity of EGCG induced toxicity appears to be a function of dose, route of administration and period of treatment. Keywords: EGCG, Green tea, Serum lipids, Dose dependant toxicity, Route dependant toxicity, Liver toxicity, Dyslipidemi