• Title, Summary, Keyword: Cancer prediction

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FOXA1: a Promising Prognostic Marker in Breast Cancer

  • Hu, Qing;Luo, Zhou;Xu, Tao;Zhang, Jun-Ying;Zhu, Ying;Chen, Wei-Xian;Zhong, Shan-Liang;Zhao, Jian-Hua;Tang, Jin-Hai
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.1
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    • pp.11-16
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    • 2014
  • Accurate diagnosis and proper monitoring of cancer patients remain important obstacles for successful cancer treatment. The search for cancer biomarkers can aid in more accurate prediction of clinical outcome and may also reveal novel predictive factors and therapeutic targets. One such prognostic marker seems to be FOXA1. Many studies have shown that FOXA1 is strongly expressed in a vast majority of cancers, including breast cancer, in which high expression is associated with a good prognosis. In this review, we summarize the role of this transcription factor in the development and prognosis of breast cancer in the hope of providing insights into utility of FOXA1 as a novel biomarker.

Comparison of Two Ovarian Malignancy Prediction Models Based on Age Sonographic Findings and Serum Ca125 Measurement

  • Arab, Maliheh;Yaseri, Mehdi;Ashrafganjoi, Tahereh;Maktabi, Maryam;Noghabaee, Giti;Sheibani, Kourosh
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.8
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    • pp.4199-4202
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    • 2012
  • Objective: The aim of our study is to compare an ovarian malignancy prediction model based on age and four sonographic findings (OMPS1) with a new model called OMPS2 which differs just by adding serum CA125 measurement to (OMPS1). Methods: In a cross sectional comparative study OMPS1 was validated in 830 operated ovarian masses within a 3 years period (2006-2009). Logistic regression analysis was used to construct OMPS2 based on OMPS1 adding serum CA125 findings. The area under the curve for two models was compared in 411 patients. Results: OMPS2 was calculated as follows: OMPS1 + 1.444 (if serum CA125= 36-200) or 3.842 (if serum CA125 is more than 200). AUC of OMPS2 was increased to 84.3% (CI 95% 78.1- 89.8) in comparison to OMPS1 with AUC of 78.1% (CI 95% 71.8-84.5). Conclusion: Our second model is more accurate in prediction of ovarian malignancy, compared with our first model.

Linear and Conformational B Cell Epitope Prediction of the HER 2 ECD-Subdomain III by in silico Methods

  • Mahdavi, Manijeh;Mohabatkar, Hassan;Keyhanfar, Mehrnaz;Dehkordi, Abbas Jafarian;Rabbani, Mohammad
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.7
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    • pp.3053-3059
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    • 2012
  • Human epidermal growth factor receptor 2 (HER2) is a member of the epidermal growth factor receptor family of receptor tyrosine kinases that plays important roles in all processes of cell development. Their overexpression is related to many cancers, including examples in the breast, ovaries and stomach. Anticancer therapies targeting the HER2 receptor have shown promise, and monoclonal antibodies against subdomains II and IV of the HER2 extra-cellular domain (ECD), Pertuzumab and Herceptin, are currently used in treatments for some types of breast cancers. Since anti HER2 antibodies targeting distinct epitopes have different biological effects on cancer cells; in this research linear and conformational B cell epitopes of HER2 ECD, subdomain III, were identified by bioinformatics analyses using a combination of linear B cell epitope prediction web servers such as ABCpred, BCPREDs, Bepired, Bcepred and Elliprro. Then, Discotope, CBtope and SUPERFICIAL software tools were employed for conformational B cell epitope prediction. In contrast to previously reported epitopes of HER2 ECD we predicted conformational B cell epitopes $P1_C$: 378-393 (PESFDGDPASNTAPLQ) and $P2_C$: 500-510 (PEDECVGEGLA) by the integrated strategy and P4: PESFDGD-X-TAPLQ; P5: PESFDGDP X TAPLQ; P6: ESFDGDP X NTAPLQP; P7: PESFDGDP-X-NTAPLQ; P8: ESFDG-XX-TAPLQPEQL and P9: ESFDGDP-X-NTAPLQP by SUPERFICIAL software. These epitopes could be further used as peptide antigens to actively immune mice for development of new monoclonal antibodies and peptide cancer vaccines that target different epitopes or structural domains of HER2 ECD.

A Stochastic Approach for Prediction of Partially Measured Concentrations of Benzo[a]pyrene in the Ambient Air in Korea

  • Kim, Yongku;Seo, Young-Kyo;Baek, Kyung-Min;Kim, Min-Ji;Baek, Sung-Ok
    • Asian Journal of Atmospheric Environment
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    • v.10 no.4
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    • pp.197-207
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    • 2016
  • Large quantities of air pollutants are released into the atmosphere and hence, must be monitored and routinely assessed for their health implications. This paper proposes a stochastic technique to predict unobserved hazardous air pollutants (HAPs), especially Benzo[a]pyrene (BaP), which can have negative effects on human health. The proposed approach constructs a nearest-neighbor structure by incorporating the linkage between BaP and meteorology and meteorological effects. This approach is adopted in order to predict unobserved BaP concentrations based on observed (or forecasted) meteorological conditions, including temperature, precipitation, wind speed, and air quality. The effects of BaP on human health are examined by characterizing the cancer risk. The efficient prediction provides useful information relating to the optimal monitoring period and projections of future BaP concentrations for both industrial and residential areas within Korea.

Sex-Biased Molecular Signature for Overall Survival of Liver Cancer Patients

  • Kim, Sun Young;Song, Hye Kyung;Lee, Suk Kyeong;Kim, Sang Geon;Woo, Hyun Goo;Yang, Jieun;Noh, Hyun-Jin;Kim, You-Sun;Moon, Aree
    • Biomolecules & Therapeutics
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    • v.28 no.6
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    • pp.491-502
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    • 2020
  • Sex/gender disparity has been shown in the incidence and prognosis of many types of diseases, probably due to differences in genes, physiological conditions such as hormones, and lifestyle between the sexes. The mortality and survival rates of many cancers, especially liver cancer, differ between men and women. Due to the pronounced sex/gender disparity, considering sex/gender may be necessary for the diagnosis and treatment of liver cancer. By analyzing research articles through a PubMed literature search, the present review identified 12 genes which showed practical relevance to cancer and sex disparities. Among the 12 sex-specific genes, 7 genes (BAP1, CTNNB1, FOXA1, GSTO1, GSTP1, IL6, and SRPK1) showed sex-biased function in liver cancer. Here we summarized previous findings of cancer molecular signature including our own analysis, and showed that sex-biased molecular signature CTNNB1High, IL6High, RHOAHigh and GLIPR1Low may serve as a female-specific index for prediction and evaluation of OS in liver cancer patients. This review suggests a potential implication of sex-biased molecular signature in liver cancer, providing a useful information on diagnosis and prediction of disease progression based on gender.

Cohort Analysis of Incidence/Mortality of Liver Cancer in Japan through Logistic Curve Fitting

  • Okamoto, Etsuji
    • Asian Pacific Journal of Cancer Prevention
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    • v.14 no.10
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    • pp.5891-5893
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    • 2013
  • Incidence/mortality of liver cancer follow logistic curves because there is a limit reflecting the prevalence of hepatitis virus carriers in the cohort. The author fitted logistic curves to incidence/mortality data covering the nine five-year cohorts born in 1911-1955 of both sexes. Goodness-of-fit of logistic curves was sufficiently precise to be used for future predictions. Younger cohorts born in 1936 or later were predicted to show constant decline in incidence/mortality in the future. The male cohort born in 1931-35 showed an elevated incidence/mortality of liver cancer early in their lives supporting the previous claim that this particular cohort had suffered massive HCV infection due to nation-wide drug abuse in the 1950s. Declining case-fatality observed in younger cohorts suggested improved treatment of liver cancer. This study demonstrated that incidence/mortality of liver cancer follow logistic curves and fitted logistic formulae can be used for future prediction. Given the predicted decline of incidence/mortality in younger cohorts, liver cancer is likely to be lost to history in the not-so-distant future.

The Identification of the Characteristics of Cancer Patients Who Defected to Other Medical Institutions (타 의료기관으로 이탈한 암환자의 특성 파악)

  • Cha, Jae-Bin;Nam, Jung-He;Ahn, Sung-Sik
    • The Korean Journal of Health Service Management
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    • v.7 no.1
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    • pp.1-9
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    • 2013
  • This study intends to identify the characteristics of cancer in-patients and those of cancer patients who defected to other medical institutions based on the summary of hospital discharge information of a university hospital for the purpose of improving work efficiency and maximizing the number of patients. The study used data on cancer patients registered in the database of C University Hospital in Gyeonggi Province for a period of one year between January 1 and December 31. The analysis results suggest that the commonalities of the cancer patients who defected to other medical institutions include no specific job, old age, and hospitalization through emergency room. In conclusion, hospitals need to identify the characteristics of cancer patients classified as patients who are prone to defect and the defection factors through this prediction model.

Application of Cancer Genomics to Solve Unmet Clinical Needs

  • Lee, Se-Hoon;Sim, Sung Hoon;Kim, Ji-Yeon;Cha, SooJin;Song, Ahnah
    • Genomics & Informatics
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    • v.11 no.4
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    • pp.174-179
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    • 2013
  • The large amount of data on cancer genome research has contributed to our understanding of cancer biology. Indeed, the genomics approach has a strong advantage for analyzing multi-factorial and complicated problems, such as cancer. It is time to think about the actual usage of cancer genomics in the clinical field. The clinical cancer field has lots of unmet needs in the management of cancer patients, which has been defined in the pre-genomic era. Unmet clinical needs are not well known to bioinformaticians and even non-clinician cancer scientists. A personalized approach in the clinical field will bring potential additional challenges to cancer genomics, because most data to now have been population-based rather than individualbased. We can maximize the use of cancer genomics in the clinical field if cancer scientists, bioinformaticians, and clinicians think and work together in solving unmet clinical needs. In this review, we present one imaginary case of a cancer patient, with which we can think about unmet clinical needs to solve with cancer genomics in the diagnosis, prediction of prognosis, monitoring the status of cancer, and personalized treatment decision.

Molecular Diagnosis for Personalized Target Therapy in Gastric Cancer

  • Cho, Jae Yong
    • Journal of Gastric Cancer
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    • v.13 no.3
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    • pp.129-135
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    • 2013
  • Gastric cancer is the second leading cause of cancer-related deaths worldwide. In advanced and metastatic gastric cancer, the conventional chemotherapy with limited efficacy shows an overall survival period of about 10 months. Patient specific and effective treatments known as personalized cancer therapy is of significant importance. Advances in high-throughput technologies such as microarray and next generation sequencing for genes, protein expression profiles and oncogenic signaling pathways have reinforced the discovery of treatment targets and personalized treatments. However, there are numerous challenges from cancer target discoveries to practical clinical benefits. Although there is a flood of biomarkers and target agents, only a minority of patients are tested and treated accordingly. Numerous molecular target agents have been under investigation for gastric cancer. Currently, targets for gastric cancer include the epidermal growth factor receptor family, mesenchymal-epithelial transition factor axis, and the phosphatidylinositol 3-kinase-AKT-mammalian target of rapamycin pathways. Deeper insights of molecular characteristics for gastric cancer has enabled the molecular classification of gastric cancer, the diagnosis of gastric cancer, the prediction of prognosis, the recognition of gastric cancer driver genes, and the discovery of potential therapeutic targets. Not only have we deeper insights for the molecular diversity of gastric cancer, but we have also prospected both affirmative potentials and hurdles to molecular diagnostics. New paradigm of transdisciplinary team science, which is composed of innovative explorations and clinical investigations of oncologists, geneticists, pathologists, biologists, and bio-informaticians, is mandatory to recognize personalized target therapy.

Hepatocellular Carcinoma Prediction Models for Patients with Chronic Hepatitis B Virus Infection in the Era of Potent Antiviral Therapy (강력한 항바이러스 치료가 보편적으로 가능한 시대에서 만성 B형간염 환자의 간암 발생 예측 모델)

  • Lee, Hye Won;Kim, Beom Kyung
    • Journal of Liver Cancer
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    • v.18 no.2
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    • pp.87-93
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    • 2018
  • Appropriate prediction of hepatocellular carcinoma (HCC) development is of paramount importance in terms of decision on antiviral therapy and HCC surveillance. To date, many HCC risk prediction models had been derived based on well-known risk factors such as age, male gender, the degree of fibrosis, and serum hepatitis B virus (HBV)-DNA load. Overall, such models showed high negative predictive values of approximately >90%, excluding the possibility of HCC development in 3 to 10 years with considerable accuracy. On the other hands, on the basis that potent antiviral therapy can substantially reduce the risk of HCC, its indications are steadily getting expanded for prevention of disease progression. Since antiviral therapy is a very strong disease modifier, the uniform application of HCC risk scores developed before the era of potent antiviral therapy would overestimate the risk of HCC. Furthermore, the tools to assess the fibrotic burden have remarkably evolved, from subjective determination based upon clinical symptom sign and ultrasonographic finding to more objective and delicate non-invasive tests based upon imaging and/or serological methods. Therefore, in the current era of potent antiviral therapy, the clinical significance of recently developed HCC risk models for patients with chronic HBV infection should be reappraised further.