Incorporating Genetic Biomarkers into Predictive Models of Normal Tissue Toxicity.

There is considerable variation in the level of toxicity patients experience for a given dose of radiotherapy, which is associated with differences in underlying individual normal tissue radiosensitivity. A number of syndromes have a large effect on clinical radiosensitivity, but these are rare. Among non-syndromic patients, variation is less extreme, but equivalent to a ±20% variation in dose. Thus, if individual normal tissue radiosensitivity could be measured, it should be possible to optimise schedules for individual patients. Early investigations of in vitro cellular radiosensitivity supported a link with tissue response, but individual studies were equivocal. A lymphocyte apoptosis assay has potential, and is currently under prospective validation. The investigation of underlying genetic variation also has potential. Although early candidate gene studies were inconclusive, more recent genome-wide association studies are revealing definite associations between genotype and toxicity and highlighting the potential for future genetic testing. Genetic testing and individualised dose prescriptions could reduce toxicity in radiosensitive patients, and permit isotoxic dose escalation to increase local control in radioresistant individuals. The approach could improve outcomes for half the patients requiring radical radiotherapy. As a number of patient- and treatment-related factors also affect the risk of toxicity for a given dose, genetic testing data will need to be incorporated into models that combine patient, treatment and genetic data.NGB is supported by the NIHR Cambridge Biomedical Research Centre.This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.clon.2015.06.01

Fine-Scale mapping of the 11q13 breast cancer susceptibility locus

The Cancer Genetic Markers of Susceptibility genome-wide association study (GWAS) originally identified a single nucleotide polymorphism (SNP) rs11249433 at 1p11.2 associated with breast cancer risk. To fine-map this locus, we genotyped 92 SNPs in a 900kb region (120,505,799–121,481,132) flanking rs11249433 in 45,276 breast cancer cases and 48,998 controls of European, Asian and African ancestry from 50 studies in the Breast Cancer Association Consortium. Genotyping was done using iCOGS, a custom-built array. Due to the complicated nature of the region on chr1p11.2: 120,300,000–120,505,798, that lies near the centromere and contains seven duplicated genomic segments, we restricted analyses to 429 SNPs excluding the duplicated regions (42 genotyped and 387 imputed). Perallelic associations with breast cancer risk were estimated using logistic regression models adjusting for study and ancestry-specific principal components. The strongest association observed was with the original identified index SNP rs11249433 (minor allele frequency (MAF) 0.402; per-allele odds ratio (OR) = 1.10, 95% confidence interval (CI) 1.08–1.13, $\small \textit{P}$ = 1.49 x 10$^{-21}$). The association for rs11249433 was limited to ER-positive breast cancers (test for heterogeneity $\small \textit{P}$ $\leq$ 8.41 x 10$^{-5}$). Additional analyses by other tumor characteristics showed stronger associations with moderately/well differentiated tumors and tumors of lobular histology. Although no significant eQTL associations were observed, in silico analyses showed that rs11249433 was located in a region that is likely a weak enhancer/promoter. Fine-mapping analysis of the 1p11.2 breast cancer susceptibility locus confirms this region to be limited to risk to cancers that are ER-positive.Cancer Research UK (Grant IDs: C1287/A10118, C1287/A12014, C490/A10124, C1287/A10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/A16565), European Community's Seventh Framework Programme (Grant ID: HEALTH-F2-2009-223175), National Institutes of Health (Grant IDs: CA128978, CA116167, CA176785, CA116201, CA63464, CA54281, CA098758, CA132839, R01CA100374, R01CA64277, R01CA148667, R37CA70867, R01CA092447), National Institute for Health Research. See also Table K via http://dx.doi.org/10.1371/journal.pone.0160316.s003This is the final version of the article. It first appeared from the Public Library of Science via http://dx.doi.org/10.1371/journal.pone.016031

Firm-specific, country-specific and region-specific competitive advantages: the case of emerging economy MNEs - Thailand

Increasing levels of regional economic integration have created a new source of international competitiveness for MNEs from an emerging economy, Thailand, in the context of ASEAN economic integration. Building on the theoretical framework of firm-specific advantages (FSAs) and country-specific advantages (CSAs) grounded in internalization theory, we introduce region-specific advantages (RSAs) and advance a novel regional dual-double-diamond model to analyse regional competitiveness. Using both primary and secondary data we find that most Thai firms derive their international competitiveness from CSAs rather than FSAs, and will benefit from ASEAN RSAs. Our study significantly advances the literature on international competitiveness of emerging-economy MNEs

A genome-wide association study to identify genetic markers associated with endometrial cancer grade

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Identification and validation of DOCK4 as a potential biomarker for risk of bone metastasis development in patients with early breast cancer.

Skeletal metastasis occurs in around 75% of advanced breast cancers, with the disease incurable once cancer cells disseminate to bone, but there remains an unmet need for biomarkers to identify patients at high risk of bone recurrence. This study aimed to identify such a biomarker and to assess its utility in predicting response to adjuvant zoledronic acid. We used quantitative proteomics (SILAC-MS), to compare protein expression in a bone-homed variant (BM1) of the human breast cancer cell line MDA-MB-231 with parental non-bone-homing cells to identify novel biomarkers for risk of subsequent bone metastasis in early breast cancer. SILAC-MS showed that Dedicator of cytokinesis protein 4 (DOCK4) was upregulated in bone-homing BM1 cells, confirmed by Western blotting. BM1 cells also had enhanced invasive ability compared with parental cells which could be reduced by DOCK4-shRNA. In a training Tissue Microarray (TMA) comprising 345 patients with early breast cancer, immunohistochemistry followed by Cox regression revealed that high DOCK4 expression correlated with histological grade (p=0.004) but not oestrogen receptor status (p=0.19) or lymph node involvement (p=0.15). A clinical validation TMA used tissue samples and the clinical database from the large AZURE adjuvant study (n=689). Adjusted Cox regression analyses showed that high DOCK4 expression in the control arm (no zoledronic acid) was significantly prognostic for first recurrence in bone (HR 2.13, 95%CI 1.06-4.30, p=0.034). No corresponding association was found in patients who received zoledronic acid (HR 0.812, 95%CI 0.176-3.76, p=0.790), suggesting that treatment with zoledronic acid may counteract the higher risk for bone relapse from high DOCK4-expressing tumours. High DOCK4 expression was not associated with metastasis to non-skeletal sites when these were assessed collectively. In conclusion, high DOCK4 in early breast cancer is significantly associated with aggressive disease and with future bone metastasis and is a potentially useful biomarker for subsequent bone metastasis risk