• Title/Summary/Keyword: Cancer prediction

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Breast Cancer in Morocco: A Literature Review

  • Slaoui, Meriem;Razine, Rachid;Ibrahimi, Azeddine;Attaleb, Mohammed;El Mzibri, Mohammed;Amrani, Mariam
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.3
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    • pp.1067-1074
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    • 2014
  • In Morocco, breast cancer is the most prevalent cancer in women and a major public health problem. Several Moroccan studies have focused on studying this disease, but more are needed, especially at the genetic and molecular levels. It is therefore interesting to establish the genetic and molecular profile of Moroccan patients with breast cancer. In this paper, we will highlight some pertinent hypotheses that may enhance breast cancer care in Moroccan patients. This review will give a precise description of breast cancer in Morocco and propose some new markers for detection and prediction of breast cancer prognosis.

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.

Self-Assembled Nanoparticles of Bile Acid-Modified Glycol Chitosans and Their Applications for Cancer Therapy

  • Kim Kwangmeyung;Kim Jong-Ho;Kim Sungwon;Chung Hesson;Choi Kuiwon;Kwon Ick Chan;Park Jae Hyung;Kim Yoo-Shin;Park Rang-Won;Kim In-San;Jeong Seo Young
    • Macromolecular Research
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    • v.13 no.3
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    • pp.167-175
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    • 2005
  • This review explores recent works involving the use of the self-assembled nanoparticles of bile acid-modified glycol chitosans (BGCs) as a new drug carrier for cancer therapy. BGC nanoparticles were produced by chemically grafting different bile acids through the use of l-ethyl-3-(3-dimethylaminopropyl)-carbodiimide (EDC). The precise control of the size, structure, and hydrophobicity of the various BGC nanoparticles could be achieved by grafting different amounts of bile acids. The BGC nanoparticles so produced formed nanoparticles ranging in size from 210 to 850 nm in phosphate-buffered saline (PBS, pH=7.4), which exhibited substantially lower critical aggregation concentrations (0.038-0.260 mg/mL) than those of other low-molecular-weight surfactants, indicating that they possess high thermodynamic stability. The SOC nanoparticles could encapsulate small molecular peptides and hydrophobic anticancer drugs with a high loading efficiency and release them in a sustained manner. This review also highlights the biodistribution of the BGC nanoparticles, in order to demonstrate their accumulation in the tumor tissue, by utilizing the enhanced permeability and retention (EPR) effect. The different approaches used to optimize the delivery of drugs to treat cancer are also described in the last section.

Two-Stage Logistic Regression for Cancer Classi cation and Prediction from Copy-Numbe Changes in cDNA Microarray-Based Comparative Genomic Hybridization

  • Kim, Mi-Jung
    • The Korean Journal of Applied Statistics
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    • v.24 no.5
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    • pp.847-859
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    • 2011
  • cDNA microarray-based comparative genomic hybridization(CGH) data includes low-intensity spots and thus a statistical strategy is needed to detect subtle differences between different cancer classes. In this study, genes displaying a high frequency of alteration in one of the different classes were selected among the pre-selected genes that show relatively large variations between genes compared to total variations. Utilizing copy-number changes of the selected genes, this study suggests a statistical approach to predict patients' classes with increased performance by pre-classifying patients with similar genetic alteration scores. Two-stage logistic regression model(TLRM) was suggested to pre-classify homogeneous patients and predict patients' classes for cancer prediction; a decision tree(DT) was combined with logistic regression on the set of informative genes. TLRM was constructed in cDNA microarray-based CGH data from the Cancer Metastasis Research Center(CMRC) at Yonsei University; it predicted the patients' clinical diagnoses with perfect matches (except for one patient among the high-risk and low-risk classified patients where the performance of predictions is critical due to the high sensitivity and specificity requirements for clinical treatments. Accuracy validated by leave-one-out cross-validation(LOOCV) was 83.3% while other classification methods of CART and DT performed as comparisons showed worse performances than TLRM.

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.

A Panel of Serum Biomarkers for Diagnosis of Prostate Cancer (전립선암 진단을 위한 바이오마커 패널)

  • Cho, Jung Ki;Kim, Younghee
    • Journal of Biomedical Engineering Research
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    • v.38 no.5
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    • pp.271-276
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    • 2017
  • Cancer biomarkers are using in the diagnosis, staging, prognosis and prediction of disease progression. But, there are not sufficiently profiled and validated in early detection and risk classification of prostate cancer. In this study, we have devoted to finding a panel of serum biomarkers that are able to detect the diagnosis of prostate cancer. The serum samples were consisted of 111 prostate cancer and 343 control samples and examined. Eleven biomarkers were constructed in this study, and then nine biomarkers were relevant to candidate biomarkers by using t test. Finally, four biomarkers, PSA, ApoA2, CYFRA21.1 and TTR, were selected as the prostate cancer biomarker panel, logistic regression was used to identify algorithms for diagnostic biomarker combinations(AUC = 0.9697). A panel of combination biomarkers is less invasive and could supplement clinical diagnostic accuracy.

Prediction and Analysis of Breast Cancer Related Deleterious Non-Synonymous Single Nucleotide Polymorphisms in the PTEN Gene

  • Naidu, C Kumaraswamy;Suneetha, Y
    • Asian Pacific Journal of Cancer Prevention
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    • v.17 no.4
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    • pp.2199-2203
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    • 2016
  • One of the most common cancer types faced by the women around the world is breast cancer. Among the several low, moderate and high penetrance genes conferring susceptibility to breast cancer, PTEN is one which is known to be mutated in many tumor types. In this study, we predicted and analyzed the impact of three deleterious coding non-synonymous single nucleotide polymorphisms rs121909218 (G129E), rs121909229 (R130Q) and rs57374291 (D107N) in the PTEN gene on the phenotype of breast tumors using computational tools SIFT, Polyphen-2, PROVEAN, MUPro, POPMusic and the GETAREA server.