• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.71-75
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• 2016

Pancreatic cancer is a leading cause of fatality worldwide. Several population studies have been conducted on genetic diagnosis of pancreatic cancer but the results from epidemiologic studies are very limited. CYP17A gene has a role in disease formation but its influence on pancreatic cancer is unclear. A polymorphism in the 5'UTR promoter region of CYP17A1-34T/C (A1/A2) has been associated with multiple cancers. The aim of the current study was to assess associations of this polymorphism and socio-demographic risk factors with pancreatic cancer. A total of 255 and 320 controls were enrolled in the study, and were genetically analyzed through PCR-RFLP. Statistical analysis was conducted with observed genotype frequencies and odds ratios (ORs) and 95% CIs were estimated using unconditional logistic regression. The impact of socio-demographic factors was accessed through Kaplen-Meir analysis. According to our results, the A2/A2 genotype was significantly associated with pancreatic cancer (OR=2.1, 95%CI = 1.3-3.5). Gender female (OR=2.6, 95%CI=1.8-3.7), age group 80s/80+ years (OR=2.2, 95% CI=1.2-4), smoking both former (OR=4.6, 95% CIs=2.5-8.8) and current (OR=3.6, 95% CI=2-6.7), and family history (OR=7.1; 95%CI = 4.6-11.4) were also found associated with increased risk. Current study suggests that along with established risk factors for pancreatic cancer CYP17A1-34T/C may play a role. However, on the basis of small sample size the argument cannot be fully endorsed and larger scale studies are recommended.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.65-70
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• 2016

Lung cancer is one of the most common malignancies in the world. Its incidence and mortality rates are on the rise in Pakistan. However, epidemiological studies to identify common lung cancer determinants in the Pakistani population have been limited. In this study, data of 440 cases and 323 controls were collected from different hospitals in Peshawar and Islamabad, along with information about socio-demographic factors including age, sex and smoking. Univariate and multi-factorial analyses of socio-demographic factors in association with each other were also performed. Overall survival analysis highlighted that, out of 440 patients in the lung cancer dataset, 204 people were uncensored with a median survival time of 13 months (95% CI=12-18). There were 41 femaleand 399 male patients. Differences were observed between length of survival in the males and females (${\chi}12$ = 6.1; p-value = 0.01). Gender was observed to be significantly related to survival (p-value< 0.01), with better survival in females (hazard ratio=2). Cox regression was extended to adjust for the covariate age (z = 2.5; p-value = 0.02). Survival analysis was also performed on the basis of smoking groups (current smokers, former smokers and never smoked individuals) and smoking duration (smoking duration >10 years, <10 years and never smoked). Smoking duration was significantly associated with survival (p-value < 0.01), with better survival in never smokers in comparison to both smoking for greater or less than 10 years. Strong associations were observed for smoking group with duration greater than 10 years, OR=6.1(3.9-9.5) on univariate and multifactorial analysis OR=11.3(CI=6.8-19.3).

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.1003-1008
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• 2016

Breast cancer is now the leading cause of cancer death in women worldwide. Cancer progression is driven not only by cancer cell intrinsic alterations and interactions with tumor microenvironment, but also by systemic effects. Integration of multiple profiling data may provide insights into the underlying molecular mechanisms of complex systemic processes. We performed a bioinformatic analysis of two public available microarray datasets for breast tumor stroma and peripheral blood mononuclear cells, featuring integrated transcriptomics data, protein-protein interactions (PPIs) and protein subcellular localization, to identify genes and biological pathways that contribute to dialogue between tumor stroma and the peripheral circulation. Genes of the integrin family as well as CXCR4 proved to be hub nodes of the crosstalk network and may play an important role in response to stroma-derived chemoattractants. This study pointed to potential for development of therapeutic strategies that target systemic signals travelling through the circulation and interdict tumor cell recruitment.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.8
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• pp.3763-3766
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• 2014

Human mammary epithelial cells have different proliferative statuses and demonstrate a close relationship with age and cell proliferation. Research on this topic could help understand the occurrence, progression and prognosis of breast cancer. In this article, using significance analysis of a microarray algorithm, we analyzed gene expression profiles of human mammary epithelial cells of different proliferative statuses and different age groups. The results showed there were significant differences in gene expression in the same proliferation status between elderly and young groups. Three common differentially expressed genes were found to dynamically change with the proliferation status and to be closely related to tumorigenesis. We also found elderly group had less status-related differential genes from actively proliferating status to intermediate status and more statusrelated differential genes from intermediate status than the young group. Finally, functional enrichment analyses allowed evaluation of the detailed roles of these differentially-expressed genes in tumor progression.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.19
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• pp.8155-8159
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• 2014

Background: Breast cancer is the serious health concern in India causing the highest mortality rate in females, which occurs due to uncontrolled cell division and can be metastasize to other parts of the human body. Interactions with estrogen receptor (ER) alpha are mainly responsible for the malignant tumors with regulation of the transcription of various genes as a transcription factor. Most of the drugs currently used for the breast cancer treatment produce various side effects and hence we focused on natural compounds which do not exhibit any toxic effect against normal human cells. Materials and Methods: Structure of human ER was retrieved from the Protein Data Bank and the structures of flavonoid compounds have been collected from PubChem database. Molecular docking and drug likeness studies were performed for those natural compounds to evaluate and analyze the anti-breast cancer activity. Results: Finally two compounds satisfying the Lipinski's rule of five were reported. The two compounds also exhibited highest binding affinity with human ER greater than 10.5 Kcal/mol. Conclusions: The results of this study can be implemented in the drug designing pipeline.

• Journal of Computing Science and Engineering
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• v.11 no.4
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• pp.111-120
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• 2017

Post-translational modifications (PTMs) of proteins play substantial roles in the gene regulation of cell physiological functions and in the generation of major diseases. However, the majority of existing studies only explored a certain PTM of proteins, while very few have investigated the PTMs of two or more domains and the effects of their interactions. In this study, after collecting data regarding a large number of breast cancer-related and validated PTMs, a sequence and domain analysis of breast cancer proteins was carried out using bioinformatics methods. Then, protein-protein interaction network-related tools were applied in order to determine the crosstalks between the PTMs of the proteins. Finally, statistical and functional analyses were conducted to identify more modification sites of domains and proteins that may interact with at least two or more PTMs. In addition to exploring the associations between the interactive effects of PTMs, the present study also provides important information that would allow biologists to further explore the regulatory pathways of biological functions and related diseases.

• Genomics & Informatics
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• v.11 no.4
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• pp.239-244
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• 2013

Somatic mutation is a major cause of cancer progression and varied responses of tumors against anticancer agents. Thus, we must obtain and characterize genome-wide mutational profiles in individual cancer subtypes. The Cancer Genome Atlas database includes large amounts of sequencing and omics data generated from diverse human cancer tissues. In the present study, we integrated and analyzed the exome sequencing data from ~3,000 tissue samples and summarized the major mutant genes in each of the diverse cancer subtypes and stages. Mutations were observed in most human genes (~23,000 genes) with low frequency from an analysis of 11 major cancer subtypes. The majority of tissue samples harbored 20-80 different mutant genes, on average. Lung cancer samples showed a greater number of mutations in diverse genes than other cancer subtypes. Only a few genes were mutated with over 5% frequency in tissue samples. Interestingly, mutation frequency was generally similar between non-metastatic and metastastic samples in most cancer subtypes. Among the 12 major mutations, the TP53, USH2A, TTN, and MUC16 genes were found to be frequent in most cancer types, while BRAF, FRG1B, PBRM1, and VHL showed lineage-specific mutation patterns. The present study provides a useful resource to understand the broad spectrum of mutation frequencies in various cancer types.

• Journal of Microbiology and Biotechnology
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• v.15 no.4
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• pp.734-739
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• 2005

Myxobacterium sp. HK1, isolated from Korean soil, degrades cellulose, differentiates to fruiting body, and its 16s rDNA has $95\%$ similarity to Polyangium sp. An anticancer molecule, CDMHK, was identified from culture broth of Myxobacterium sp. HK1, and purified by Diaion HP20, Silica gel, Sephadex LH-20 chromatography, and preparative HPLC using an YMC OSD-A C18 column. The molecular structure and formula were determined to be $C_{l2}H_{l9}N_3O_2$ (M.W 237) by MS spectrometry, 300 MHz $^{1}H\;and\;^{13}C$ NMR. The CDMHK was not active against Escherichia coli, Staphylococcus aureus, and Candida albicans. However, this molecule inhibited the growth of various cancer cell lines. The $ED_{50}$ values of CDMHK were determined to be 0.147, 0.086, 0.18, 0.166, and 0.142 $\mu$g/ml against A549, SK-OV-3, SK-MEL-2, VF498, and HCTl5 cancer cell lines, respectively. In addition, the CDMHK was able to induce apoptosis of the CCRF-CEM cancer cell line, evidenced by DNA fragmentation assay and DAPI staining.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.23-28
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• 2005

The high-dimensionality and insufficiency of gene expression profiles and proteomic profiles makes feature selection become a critical step in efficiently building accurate models for cancer problems based on such data sets. In this paper, we use a method, called Discrete Function Learning algorithm, to find discriminatory feature vectors based on information theory. The target feature vectors contain all or most information (in terms of entropy) of the class attribute. Two data sets are selected to validate our approach, one leukemia subtype gene expression data set and one ovarian cancer proteomic data set. The experimental results show that the our method generalizes well when applied to these insufficient and high-dimensional data sets. Furthermore, the obtained classifiers are highly understandable and accurate.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.9
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• pp.4307-4312
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• 2016

Background: Breast cancer is the most common female malignancy worldwide and its incidence is on the rise in Pakistan. The aim of this case-control study was to quantify the association of various risk factors with breast cancer risk among Pakistani women. Materials and Methods: A total of 2,246 women were studied, including 1,238 women with histologically confirmed breast cancer patients and age matched control subjects (N=1008) without breast cancer and other chronic diseases. Subjects were interviewed using a specifically designed questionnaire. Unconditional logistic regression was applied. Subsequent disease-specific mortality was also measured. Results: In this study, majority of the breast cancer patients (69.59%) were in age ranges of 40s and 50s. BMI greater than 25kg/m2 (OR=1.57; 95%CI, 1.26-1.90 and OR=1.60; 95%CI, 1.26-2.03), marital status of unmarried (OR=2.03; 95%CI, 1.69-2.44), lack of breast feeding, smoking (current or ever), lack of physical activity and post-menopausal status were found to have significant positive associations with breast cancer. It was also observed that increased parity reduced the disease risk. A larger number of cases (58.1%) had their right breast affected while 22.8% had other complications as well. Conclusions: This exploratory analysis indicated a number of risk factors to be associated with increased risk of breast cancer. It was also observed that mean age at diagnosis is a decade earlier than in western countries. It is hoped that our findings will facilitate establishment of adequate evidence-based awareness and preventive measures for Pakistani women.