Dataset Information

Two predictive precision medicine tools for hepatocellular carcinoma.

ABSTRACT: Background:Hepatocellular carcinoma (HCC) is a serious threat to public health due to its poor prognosis. The current study aimed to develop and validate a prognostic nomogram to predict the overall survival of HCC patients. Methods:The model cohort consisted of 24,991 mRNA expression data points from 348 HCC patients. The least absolute shrinkage and selection operator method (LASSO) Cox regression model was used to evaluate the prognostic mRNA biomarkers for the overall survival of HCC patients. Results:Using multivariate Cox proportional regression analyses, a prognostic nomogram (named Eight-mRNA prognostic nomogram) was constructed based on the expression data of N4BP3, -ADRA2B, E2F8, MAPT, PZP, HOXD9, COL15A1, and -NDST3. The C-index of the Eight-mRNA prognostic nomogram was 0.765 (95% CI 0.724-0.806) for the overall survival in the model cohort. The Harrell's concordance-index of the Eight-mRNA prognostic nomogram was 0.715 (95% CI 0.658-0.772) in the validation cohort. The survival curves demonstrated that the HCC patients in the high risk group had a significantly poorer overall survival than the patients in the low risk group. Conclusion:In the current study, we have developed two convenient and efficient predictive precision medicine tools for hepatocellular carcinoma. These two predictive precision medicine tools are helpful for predicting the individual mortality risk probability and improving the personalized comprehensive treatments for HCC patients. The Smart Cancer Predictive System can be used by clicking the following URL: https://zhangzhiqiao2.shinyapps.io/Smart_cancer_predictive_system_HCC_2/. The Gene Survival Analysis Screen System is available at the following URL: https://zhangzhiqiao5.shinyapps.io/Gene_Survival_Analysis_A1001/.

SUBMITTER: Zhang Z

PROVIDER: S-EPMC6854692 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Two predictive precision medicine tools for hepatocellular carcinoma.

Zhang Zhiqiao Z Li Jing J He Tingshan T Ouyang Yanling Y Huang Yiyan Y Liu Qingbo Q Wang Peng P Ding Jianqiang J

Cancer cell international 20191114

<h4>Background</h4>Hepatocellular carcinoma (HCC) is a serious threat to public health due to its poor prognosis. The current study aimed to develop and validate a prognostic nomogram to predict the overall survival of HCC patients.<h4>Methods</h4>The model cohort consisted of 24,991 mRNA expression data points from 348 HCC patients. The least absolute shrinkage and selection operator method (LASSO) Cox regression model was used to evaluate the prognostic mRNA biomarkers for the overall survival ...[more]

PMID: 31754347

Similar Datasets

Project description:Patients who develop chronic fibrotic liver disease, caused by viral or metabolic aetiologies, are at a high risk of developing hepatocellular carcinoma (HCC). Even after complete HCC tumour resection or ablation, the carcinogenic tissue microenvironment in the remnant liver can give rise to recurrent de novo HCC tumours, which progress into incurable, advanced-stage disease in most patients. Thus, early detection and prevention of HCC development is, in principle, the most impactful strategy to improve patient prognosis. However, a "one-size-fits-all" approach to HCC screening for early tumour detection, as recommended by clinical practice guidelines, is utilised in less than 20% of the target population, and the performance of screening modalities, including ultrasound and alpha-fetoprotein, is suboptimal. Furthermore, optimal screening strategies for emerging at-risk patient populations, such as those with chronic hepatitis C after viral cure, or those with non-cirrhotic, non-alcoholic fatty liver disease remain controversial. New HCC biomarkers and imaging modalities may improve the sensitivity and specificity of HCC detection. Clinical and molecular HCC risk scores will enable precise HCC risk prediction followed by tailoured HCC screening of individual patients, maximising cost-effectiveness and optimising allocation of limited medical resources. Several aetiology-specific and generic HCC chemoprevention strategies are evolving. Epidemiological and experimental studies have identified candidate chemoprevention targets and therapies, including statins, anti-diabetic drugs, and selective molecular targeted agents, although their clinical testing has been limited by the lengthy process of cancer development that requires long-term, costly studies. Individual HCC risk prediction is expected to overcome the challenge by enabling personalised chemoprevention, targeting high-risk patients for precision HCC prevention and substantially improving the dismal prognosis of HCC.

Project description:In January 2015, President Barack Obama unveiled the "Precision Medicine Initiative," a nationwide research effort to help bring an effective, preventive, and therapeutic approach to medicine. The purpose of the initiative is to bring a precise understanding of the genetic and environmental determinants of disease into clinical settings across the United States.1 The announcement was coupled with $216 million provided in the President's proposed budget for a million-person national research cohort including public and private partnerships with academic medical centers, researchers, foundations, privacy experts, medical ethicists, and medical product innovators. The Initiative promises to expand the use of precision medicine in cancer research and modernize regulatory approval processes for genome sequencing technologies. In response, Congress passed the 21st Century Cures Act in December 2016, authorizing a total of $1.5 billion over 10 years for the program.2 Although the Precision Medicine Initiative heralds great promise for the future of disease treatment and eradication, its implementation and development must be carefully guided to ensure that the millions of federal dollars expended will be spent equitably. This commentary discusses two key threats to the Precision Medicine Initiative's ability to proceed in a manner consistent with the United States Constitutional requirement that the federal government shall not "deny to any person . . . the equal protection of the laws."3 In short, this commentary sounds two cautionary notes, in order to advance precision medicine equity. First, achieving precision medicine equity will require scientists and clinicians to fulfill their intellectual, moral, and indeed legal duty to work against abusive uses of precision medicine science to advance distorted views of racial group variation. Precision medicine scientists must decisively denounce and distinguish this Initiative from the pseudo-science of eugenics - the immoral and deadly pseudo-science that gave racist and nationalist ideologies what Troy Duster called a "halo of legitimacy" during the first half of the 20th century.4 Second, to combat the social threat to precision medicine, scientists must incorporate a comprehensive, ecological understanding of the fundamental social and environmental determinants of health outcomes in all research. Only then will the Precision Medicine Initiative live up to its potential to improve and indeed transform health care delivery for all patients, regardless of race, color, or national origin.

Dataset Information

Two predictive precision medicine tools for hepatocellular carcinoma.

Publications

Two predictive precision medicine tools for hepatocellular carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure