• Asian Pacific Journal of Cancer Prevention
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• v.17 no.5
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• pp.2375-2382
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• 2016

Cancer is a major health problem in Oman. It is reported that cancer incidence in Oman is the second highest after Saudi Arabia among Gulf Cooperation Council countries. Based on GLOBOCAN estimates, Oman is predicted to face an almost two-fold increase in cancer incidence in the period 2008-2020. However, cancer research in Oman is still in its infancy. This is due to the fact that medical institutions and infrastructure that play central roles in data collection and analysis are relatively new developments in Oman. We believe the country requires an organized plan and efforts to promote local cancer research. In this paper, we discuss current research progress in cancer diagnosis using machine learning techniques to optimize computer aided cancer detection and classification (CAD). We specifically discuss CAD using two major medical data, i.e., medical imaging and microarray gene expression profiling, because medical imaging like mammography, MRI, and PET have been widely used in Oman for assisting radiologists in early cancer diagnosis and microarray data have been proven to be a reliable source for differential diagnosis. We also discuss future cancer research directions and benefits to Oman economy for entering the cancer research and treatment business as it is a multi-billion dollar industry worldwide.

• Journal of the Korea Convergence Society
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• v.8 no.12
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• pp.49-53
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• 2017

Breast cancer is the sccond most female cancer patient in the entire female cancer patient, and has emerged as the highest contributor to female cancer deaths. If breast cancer id detected early, the cure rate is 92 percent. However, if early detection fails, breast cancer has a very high rate of metastasis. The transition from cancer to cancer has become more successful as cancer progresses. Early diagnosis of cancer is an important factor in improving quality of life. Examples of breast cancer include Mammograph, ultrasound, and Momotome. Mommography is not only painful for the examiner, but also for easy access to breast cancer exam inations. In this paper, breast cancer diagnosis data mammograph data was used. In addition, the Neural Network were classified for early diagnosis of breast cancer early using NEWFM. After learning of data using NEWFM, the accuracy of the breast cancer data classification was 84.4391%.

• Journal of Korean Biological Nursing Science
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• v.25 no.2
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• pp.105-112
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• 2023

Purpose: This study aimed to understand the general characteristics and biomarkers of inflammation in adult patients who visited the emergency department with fever and to determine whether the severity of clinical symptoms varies according to cancer diagnosis. Methods: Data were collected retrospectively from 4,002 adult patients with fever who visited the emergency department at a tertiary hospital from January 2018 to December 2018 using medical records. Results: On average, cancer patients were older than non-cancer patients (p < .001), and differences were observed between cancer and non-cancer patients in the origin of fever and biomarkers associated with inflammation. A higher proportion of cancer patients than non-cancer patients had a Korean Triage and Acuity Scale level of 1 to 3 (p < .001), and more cancer patients than non-cancer patients met two or more criteria for systemic inflammatory response syndrome (p = .001). More life-saving interventions in the emergency department were required in cancer patients than in non-cancer patients (p < .001), and cancer patients spent more time in the emergency department than non-cancer patients (p < .001). Conclusion: This study showed that the general characteristics and biomarkers of inflammation differed among adult patients with fever depending on cancer diagnosis. Furthermore, among adult patients with fever, cancer patients had more severe clinical symptoms than non-cancer patients. The results of this study are hoped to be helpful as a basis of nursing knowledge for adult patients with fever in the emergency department and as evidence for the classification of severity in patients with fever according to cancer diagnosis.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.23
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• pp.10267-10272
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• 2015

To evaluate the value of combined detection of serum CEA, CA19-9, CA24-2, AFP, CA72-4, SCC, TPA and TPS for the clinical diagnosis of upper gastrointestinal tract (GIT) cancer and to analyze the efficacy of these tumor markers (TMs) in evaluating curative effects and prognosis. A total of 573 patients with upper GIT cancer between January 2004 and December 2007 were enrolled in this study. Serum levels of CEA, CA19-9, CA24-2, AFP, CA72-4, SCC, TPA and TPS were examined preoperatively and every 3 months postoperatively by ELISA. The sensitivity of CEA, CA19-9, CA24-2, AFP, CA72-4, SCC, TPA and TPS were 26.8%, 36.2%, 42.9%, 2.84%, 25.4%, 34.6%, 34.2% and 30.9%, respectively. The combined detection of CEA+CA199+CA242+CA724 had higher sensitivity and specificity in gastric cancer (GC) and cardiac cancer, while CEA+CA199+CA242+SCC was the best combination of diagnosis for esophageal cancer (EC). Elevation of preoperative CEA, CA19-9 and CA24-2, SCC and CA72-4 was significantly associated with pathological types (p<0.05) and TNM staging (p<0.05). Correlation analysis showed that CA24-2 was significantly correlated with CA19-9 (r=0.810, p<0.001). The levels of CEA, CA19-9, CA24-2, CA72-4 and SCC decreased obviously 3 months after operations. When metastasis and recurrence occurred, the levels of TMs significantly increased. On multivariate analysis, high preoperative CA72-4, CA24-2 and SCC served as prognostic factors for cardiac carcinoma, GC and EC, respectively. combined detection of CEA+CA199+CA242+SCC proved to be the most economic and practical strategy in diagnosis of EC; CEA+CA199+CA242+CA724 proved to be a better evaluation indicator for cardiac cancer and GC. CEA and CA19-9, CA24-2, CA72-4 and SCC, examined postoperatively during follow-up, were useful to find early tumor recurrence and metastasis, and evaluate prognosis. AFP, TPA and TPS have no significant value in diagnosis of patients with upper GIT cancer.

• The KIPS Transactions:PartB
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• v.16B no.2
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• pp.165-172
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• 2009

According to the American Cancer Society, breast cancer is the second largest cause of cancer deaths and most frequently diagnosed cancer in women. The currently most popular method for early detection of breast cancer is the digital mammography. A mass or calcification lesion has been known as the most important clue for the diagnosis. In this paper, we propose a diagnosis approach based on fuzzy cluster knowledge base. We combine different two sources of feature data in duel OFUN-NET and produce the diagnosis result with possibility degree. We also present the experimental results on the dataset of mass and calcification lesions extracted from the public real world mammogram database DDSM. These results show higher classification accuracy than conventional methods and the feasibility as a decision supporting tool for diagnosis of digital mammogram.

• BMB Reports
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• v.51 no.11
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• pp.563-571
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• 2018

Colorectal cancer (CRC), the third most common cancer in the world, has no specific biomarkers that facilitate its diagnosis and subsequent treatment. The miRNAs, small single-stranded RNAs that repress the mRNA translation and trigger the mRNA degradation, show aberrant levels in the CRC, by which these molecules have been related with the initiation, progression, and drug-resistance of this cancer type. Numerous studies show the microRNAs influence the cellular mechanisms related to the cell cycle, differentiation, apoptosis, and migration of the cancer cells through the post-transcriptionally regulated gene expression. Specific patterns of the upregulated and down-regulated miRNA have been associated with the CRC diagnosis, prognosis, and therapeutic response. Concretely, the downregulated miRNAs represent attractive candidates, not only for the CRC diagnosis, but for the targeted therapies via the tumor-suppressing microRNA replacement. This review shows a general overview of the potential uses of the miRNAs in the CRC diagnosis, prognosis, and treatment with a special focus on the downregulated ones.

• Archives of Pharmacal Research
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• v.11 no.2
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• pp.134-138
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• 1988

Urine measurements by MNR were made for 25 persons including cancer and non-cancer patients. The aromatic proton signals of NMR wer observed much more often in cancer patients' urine than non-cancer patients' one. To compare the amount of the phenolic compounds excreted in urine between cancer and non-cancer patient, urine analysis by HPLC with UV detector was performed. Total peak area and major peak areas of cancer patients' urine wer emuch greater than those of non-cancer patients' one. To check the phenolic compound excreted in urine, a new jellied reagent named Gift reagent which was based on Millon's reagent, was developed for urine color reaction. When the reagent was tested, the sensitivity and specificity for urine samples of 69 persons including cancer and non-cancer patients were measured by 85.3% and 91.4%, respectively, indicating that the Gift reagent afford a possibility of cancer diagnosis.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.6
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• pp.2895-2899
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• 2016

Background: Increasing breast cancer (BC) incidence rates have been reported from India; causal factors for this increased incidence are not understood and diagnosis is mostly in advanced stages. Trivandrum exhibits the highest BC incidence rates in India. This study aimed to estimate trends in incidence by age from 2005-2014, to predict rates through 2020 and to assess the stage at diagnosis of BC in Trivandrum. Materials and Methods: BC cases were obtained from the Population Based Cancer Registry, Trivandrum. Distribution of stage at diagnosis and incidence rates of BC [Age-specific (ASpR), crude (CR) and age-standardized (ASR)] are described and employed with a joinpoint regression model to estimate average annual percent changes (AAPC) and a Bayesian model to estimate predictive rates. Results: BC accounts for 31% (2681/8737) of all female cancers in Trivandrum. Thirty-five percent (944/2681) are <50 years of age and only 9% present with stage I disease. Average age increased from 53 to 56.4 years (p=0.0001), CR (per $10^5$ women) increased from 39 (ASR: 35.2) to 55.4 (ASR: 43.4), AAPC for CR was 5.0 (p=0.001) and ASR was 3.1 (p=0.001). Rates increased from 50 years. Predicted ASpR is 174 in 50-59 years, 231 in > 60 years and overall CR is 80 (ASR: 57) for 2019-20. Conclusions: BC, mostly diagnosed in advanced stages, is rising rapidly in South India with large increases likely in the future; particularly among post-menopausal women. This increase might be due to aging and/or changes in lifestyle factors. Reasons for the increased incidence and late stage diagnosis need to be studied.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.3
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• pp.1047-1049
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• 2015

Background: This systematic analysis was conducted to investigate pathological diagnosis of vertebral tumor metastasis with unknown primaries. Methods: Clinical studies conducted to pathologically investigate vertebral tumor metastasis were identified using a predefined search strategy. Pooled diagnosis (PD) of each pathological confirmation was calculated. Results: For vertebral tumor metastasis, 5 clinical studies which included 762 patients were considered eligible for inclusion. Systematic analysis suggested that, for all patients with vertebral tumor metastasis, dominant PD was pathologically confirmed with lung cancer in 21.7% (165/762), with breast cancer in 26.6% (203/762) and with prostate cancer in 19.2% (146/762). Other diagnosis that could be confirmed included lymphoma, multiple myeloma, renal cancer, for example, in this cohort of patients. Conclusions: This systemic analysis suggested that breast, lung and prostate lesions could be the most common pathological types of cancer for vertebral tumor metastasis formunknown primaries, and other common diagnoses could include lymphoma, multiple myeloma, renal cancer.

• BMB Reports
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• v.41 no.9
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• pp.615-625
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• 2008

Over a last decade, intense interest has been focused on biomarker discovery and their clinical uses. This interest is accelerated by the completion of human genome project and the progress of techniques in proteomics. Especially, cancer biomarker discovery is eminent in this field due to its anticipated critical role in early diagnosis, therapy guidance, and prognosis monitoring of cancers. Among cancers, lung cancer, one of the top three major cancers, is the one showing the highest mortality because of failure in early diagnosis. Numerous potential DNA biomarkers such as hypermethylations of the promoters and mutations in K-ras, p53, and protein biomarkers; carcinoembryonic antigen (CEA), CYFRA21-1, plasma kallikrein B1 (KLKB1), Neuron-specific enolase, etc. have been discovered as lung cancer biomarkers. Despite extensive studies thus far, few are turned out to be useful in clinic. Even those used in clinic do not show enough sensitivity, specificity and reproducibility for general use. This review describes what the cancer biomarkers are for, various types of lung cancer biomarkers discovered at present and predicted future advance in lung cancer biomarker discovery with proteomics technology.