Colorectal cancer (CRC) remains as one of the most common cause of worldwide cancer morbidity and mortality. Improvements in surgical modalities and adjuvant chemotherapy have increased the cure rates in early stage disease, but a significant portion of the patients will develop recurrence or advanced disease. The efficacy of chemotherapy of recurrence and advanced CRC has improved significantly over the last decade. Previously, the historical drug 5-fluorouracil was used as single chemotherapeutic agent. Now with the addition of other drugs such as capecitabine, irinotecan, oxaliplatin, bevacizumab, cetuximab, panitumumab, vemurafenib, and dabrafenib, the median survival of patients with advanced CRC has significantly improved from less than a year to the current standard of almost 2 years. However, the side effects of systemic therapy such as toxicity may cause fatal complications and have a major consequences on the patients' quality of life. Hence, there is an urgent need for key biomarkers which will enable the selection of optimal drug singly or in combination for an individual patient. The application of personalized therapy based on DNA testing could aid the clinicians in providing the most effective chemotherapy agents and dose modifications for each patient. Yet, some of the current findings are controversial and the evidences are conflicting. This review aims at summarizing the current state of knowledge about germline pharmacogenomics DNA variants that are currently used to guide therapeutic decisions and variants that have the potential to be clinically useful in the future. In addition, current updates on germline variants conferring treatment sensitivity, drug resistance to existing chemotherapy agents and variants affecting prognosis and survival will also be emphasized. Different alteration in the same gene might confer resistance or enhanced sensitivity; and while most of other published reviews generally stated only the gene name and codon location, we will specifically discuss the exact variants to offer more accurate information in this mini review.
Malaysia has experienced several haze events since the 1980s as a consequence of the transboundary movement of air pollutants emitted from forest fires and open burning activities. Hazy episodes can result from local activities and be categorized as "localized haze". General probability distributions (i.e., gamma and log-normal) were chosen to analyze the PM(10) concentrations data at two different types of locations in Malaysia: industrial (Johor Bahru and Nilai) and residential (Kota Kinabalu and Kuantan). These areas were chosen based on their frequently high PM(10) concentration readings. The best models representing the areas were chosen based on their performance indicator values. The best distributions provided the probability of exceedances and the return period between the actual and predicted concentrations based on the threshold limit given by the Malaysian Ambient Air Quality Guidelines (24-h average of 150 μg/m(3)) for PM(10) concentrations. The short-term prediction for PM(10) exceedances in 14 days was obtained using the autoregressive model.
There are many factors that influence PM(10) concentration in the atmosphere. This paper will look at the PM(10) concentration in relation with the wet season (north east monsoon) and dry season (south west monsoon) in Seberang Perai, Malaysia from the year 2000 to 2004. It is expected that PM(10) will reach the peak during south west monsoon as the weather during this season becomes dry and this study has proved that the highest PM(10) concentrations in 2000 to 2004 were recorded in this monsoon. Two probability distributions using Weibull and lognormal were used to model the PM(10) concentration. The best model used for prediction was selected based on performance indicators. Lognormal distribution represents the data better than Weibull distribution model for 2000, 2001, and 2002. However, for 2003 and 2004, Weibull distribution represents better than the lognormal distribution. The proposed distributions were successfully used for estimation of exceedences and predicting the return periods of the sequence year.
Analysis and forecasting of air quality parameters are important topics of atmospheric and environmental research today due to the health impact caused by air pollution. This study examines transformation of nitrogen dioxide (NO(2)) into ozone (O(3)) at urban environment using time series plot. Data on the concentration of environmental pollutants and meteorological variables were employed to predict the concentration of O(3) in the atmosphere. Possibility of employing multiple linear regression models as a tool for prediction of O(3) concentration was tested. Results indicated that the presence of NO(2) and sunshine influence the concentration of O(3) in Malaysia. The influence of the previous hour ozone on the next hour concentrations was also demonstrated.
The incidences of colorectal cancer (CRC) are continuously increasing in some areas of the world, including Malaysia. In this study, we aimed to characterize the landscape of somatic mutations using the whole-genome sequencing approach and identify druggable somatic mutations specific to Malaysian patients. Whole-genome sequencing was performed on the genomic DNA obtained from 50 Malaysian CRC patients' tissues. We discovered the top significantly mutated genes were APC, TP53, KRAS, TCF7L2 and ACVR2A. Four novel, non-synonymous variants were identified in three genes, which were KDM4E, MUC16 and POTED. At least one druggable somatic alteration was identified in 88% of our patients. Among them were two frameshift mutations in RNF43 (G156fs and P192fs) predicted to have responsive effects against the Wnt pathway inhibitor. We found that the exogenous expression of this RNF43 mutation in CRC cells resulted in increased cell proliferation and sensitivity against LGK974 drug treatment and G1 cell cycle arrest. In conclusion, this study uncovered our local CRC patients' genomic landscape and druggable alterations. It also highlighted the role of specific RNF43 frameshift mutations, which unveil the potential of an alternative treatment targeting the Wnt/β-Catenin signalling pathway and could be beneficial, especially to Malaysian CRC patients.