Cancer Informatics最新文献

{"title":"Pan-Cancer Survival Classification With Clinicopathological and Targeted Gene Expression Features.","authors":"Daniel Zhao,&nbsp;Daniel Y Kim,&nbsp;Peter Chen,&nbsp;Patrick Yu,&nbsp;Sophia Ho,&nbsp;Stephanie W Cheng,&nbsp;Cindy Zhao,&nbsp;Jimmy A Guo,&nbsp;Yun R Li","doi":"10.1177/11769351211035137","DOIUrl":"https://doi.org/10.1177/11769351211035137","url":null,"abstract":"<p><p>Prognostication for patients with cancer is important for clinical planning and management, but remains challenging given the large number of factors that can influence outcomes. As such, there is a need to identify features that can robustly predict patient outcomes. We evaluated 8608 patient tumor samples across 16 cancer types from The Cancer Genome Atlas and generated distinct survival classifiers for each using clinical and histopathological data accessible to standard oncology workflows. For cancers that had poor model performance, we deployed a random-forest-embedded sequential forward selection approach that began with an initial subset of the 15 most predictive clinicopathological features before sequentially appending the next most informative gene as an additional feature. With classifiers derived from clinical and histopathological features alone, we observed cancer-type-dependent model performance and an area under the receiver operating curve (AUROC) range of 0.65 to 0.91 across all 16 cancer types for 1- and 3-year survival prediction, with some classifiers consistently outperforming those for others. As such, for cancers that had poor model performance, we posited that the addition of more complex biomolecular features could enhance our ability to prognose patients where clinicopathological features were insufficient. With the inclusion of gene expression data, model performance for 3 select cancers (glioblastoma, stomach/gastric adenocarcinoma, ovarian serous carcinoma) markedly increased from initial AUROC scores of 0.66, 0.69, and 0.67 to 0.76, 0.77, and 0.77, respectively. As a whole, this study provides a thorough examination of the relative contributions of clinical, pathological, and gene expression data in predicting overall survival and reveals cancer types for which clinical features are already strong predictors and those where additional biomolecular information is needed.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"20 ","pages":"11769351211035137"},"PeriodicalIF":2.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/11769351211035137","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39299441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Establishing and Evaluating Cancer Surveillance System in KwaZulu-Natal, South Africa.","authors":"Noluthando P Mbeje,&nbsp;Themba G Ginindza,&nbsp;Nkosana Jafta","doi":"10.1177/11769351211029967","DOIUrl":"https://doi.org/10.1177/11769351211029967","url":null,"abstract":"<p><strong>Background: </strong>The increasing cancer burden remains a public health challenge. Quality and accurate population data is important to improve cancer control, screening, and treatment programmes for the sub-Saharan Africa region.</p><p><strong>Aim: </strong>The aim of this study was to establish hospital-based cancer surveillance system, thereby reporting the burden that cancer diagnosis and treatment place on 3 hospitals - an approach of health systems strengthening.</p><p><strong>Methods: </strong>A hospital-based cancer surveillance was established in 3 public health facilities that provide oncology services in KwaZulu-Natal. An active method was used for finding cancer cases. The cancer surveillance database was evaluated according to the criteria recommended for cancer registries. Analyses of data included descriptive and crude incidence rates.</p><p><strong>Results: </strong>A total of 2307 newly diagnosed cancer cases were reported in 2018, with a majority from Inkosi Albert Luthuli Central hospital (65.3%), followed by Greys hospital (30.8%) and then Addington hospital (3.94%). Most of the cancer cases were from the 2 major urban areas of the province (eThekwini and uMgungundlovu district). The most commonly diagnosed cancers from all combined 3 facilities for both sexes were breast, cervix, colorectal, Kaposi Sarcoma, and lung. Approximately half of the cancer cases had no staging, and 12.8% of the cases were diagnosed at stage 4. The mostly prescribed treatments for the patients were radiotherapy and chemotherapy.</p><p><strong>Conclusions: </strong>Based on our hospital-based surveillance, cancer burden is high in the 3 facilities. Strengthening cancer screening and diagnostic policies and procedures that will allow expansion of accurate cancer surveillance system is essential in KwaZulu-Natal and South Africa as a whole.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"20 ","pages":"11769351211029967"},"PeriodicalIF":2.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/d2/c4/10.1177_11769351211029967.PMC8283221.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39281380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bioinformatics Study of Sea Cucumber Peptides as Antibreast Cancer Through Inhibiting the Activity of Overexpressed Protein (EGFR, PI3K, AKT1, and CDK4).","authors":"Teresa Liliana Wargasetia,&nbsp;Hana Ratnawati,&nbsp;Nashi Widodo,&nbsp;Muhammad Hermawan Widyananda","doi":"10.1177/11769351211031864","DOIUrl":"https://doi.org/10.1177/11769351211031864","url":null,"abstract":"<p><p>Breast cancer is the most common type of cancer in women globally. The overexpressed proteins, including EGFR, PI3K, AKT1, and CDK4, have a role in the growth of breast cancer cells. The 3D peptide structure of sea cucumber <i>Cucumaria frondosa</i> was modeled and then docked with EGFR, PI3K, AKT1, and CDK4 proteins using AutoDock Vina software. The docking result, which has the best binding affinity value, is continued with molecular dynamics simulation. The docking results showed that all peptides bind to the active sites of the four proteins. WPPNYQW and YDWRF peptides bind to proteins with lower binding affinity values than positive controls. The four proteins were in a stable state when complexed with the WPPNYQW peptide, which was seen from the RMSD and RMSF value. PI3K-YDWRF and AKT1-YDWRF complexes are stable, characterized by high RMSD values and increased volatility in several amino acids. WPPNYQW peptide has high potential as an antibreast cancer agent because it binds to the active sites of the four proteins with low binding affinity values and stable interactions. Meanwhile, the YDWRF peptide interacts with the four proteins with low binding affinity values, but the interaction is only stable on PI3K and AKT1 proteins.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"20 ","pages":"11769351211031864"},"PeriodicalIF":2.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/35/9c/10.1177_11769351211031864.PMC8283226.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39281381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial Distribution of Cancer Cases Seen in Three Major Public Hospitals in KwaZulu-Natal, South Africa.","authors":"Mpho Ktn Motlana,&nbsp;Themba G Ginindza,&nbsp;Aweke A Mitku,&nbsp;Nkosana Jafta","doi":"10.1177/11769351211028194","DOIUrl":"https://doi.org/10.1177/11769351211028194","url":null,"abstract":"<p><strong>Background: </strong>Noncommunicable diseases (NCDs) like cancer are posing a challenge in the health system especially in low- and middle-income countries (LMICs). In South Africa, cancer is under-reported due to the lack of a comprehensive cancer surveillance system. The limited knowledge on the extent of cancer burden has led to inaccurate allocation of public health resources. The aim of this study was to describe cancer incidence and spatial distribution of cancer cases seen at 3 main public oncology facilities in KwaZulu-Natal.</p><p><strong>Methods: </strong>In this retrospective study, cases of cancer observed from year 2015 to 2017 were extracted from medical records. The crude incidence rate was estimated for the total cancer cases and for different type of cancer reported over that period. Age-standardised incidence rates (ASR) per 100 000 was calculated per year using age groups and sex according to the district population data of KwaZulu-Natal. The comparisons of cancer diagnosed incidences were made between 11 districts using the ASR. Choropleth spatial maps and Moran's Index were used to assess the ASR cancer spatial distribution along with geographical patterns among the districts. One sample chi-square test was used to assess the significant increase/decrease over time.</p><p><strong>Results: </strong>The study lost numerous cases due to incompleteness. A total of 4909 new cases were diagnosed with cancer during 2015 to 2017, 62% of which were female. Both uMgungundlovu and eThekwini districts had the highest ASR among district municipalities of KwaZulu-Natal for both male and female (83.6 per 100 000 per men year for men, 158.2 per 100 000 women per year, and 60.1 per 100 000 men per year and 96.9 per 100 000 women per year, respectively). Random distribution of reported cancer cases in KwaZulu-Natal was observed with a high concentration being in and around 2 metropolitan districts. Spatial variation showed a significant difference from year to year between the districts with the random spatial distribution. Overall, there was a significant decline of cancer incidences observed from 2015 to 2017 (<i>P</i> < .05) in the province.</p><p><strong>Conclusion: </strong>The overall cancer incidence in the study shows that female cancers (breast and cervical) are still on the rise and still need to be given priority as they were most prevalent in KwaZulu-Natal. Spatial analysis (choropleth maps) was used to show a pattern of higher concentration of cancer incidence in the north-western parts of the province.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"20 ","pages":"11769351211028194"},"PeriodicalIF":2.0,"publicationDate":"2021-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/11769351211028194","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39202758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Re-Evaluate Fusion Genes in Prostate Cancer.","authors":"Ting Wei,&nbsp;Ji Lu,&nbsp;Tao Ma,&nbsp;Haojie Huang,&nbsp;Jean-Pierre Kocher,&nbsp;Liguo Wang","doi":"10.1177/11769351211027592","DOIUrl":"https://doi.org/10.1177/11769351211027592","url":null,"abstract":"<p><strong>Background: </strong>Thousands of gene fusions have been reported in prostate cancer, but their authenticity, incidence, and tumor specificity have not been thoroughly evaluated, nor have their genomic characteristics been carefully explored.</p><p><strong>Methods: </strong>We developed FusionVet to dedicatedly validate known fusion genes using RNA-seq alignments. Using FusionVet, we re-assessed 2727 gene fusions reported from 36 studies using the RNA-seq data generated by The Cancer Genome Atlas (TCGA). We also explored their genomic characteristics and interrogated the transcriptomic and DNA methylomic consequences of the E26 transformation-specific (ETS) fusions.</p><p><strong>Results: </strong>We found that nearly two-thirds of reported fusions are intra-chromosomal, and 80% of them were formed between 2 protein-coding genes. Although most (76%) genes were fused to only 1 partner, we observed many fusion hub genes that have multiple fusion partners, including ETS family genes, androgen receptor signaling pathway genes, tumor suppressor genes, and proto-oncogenes. More than 90% of the reported fusions cannot be validated by TCGA RNA-seq data. For those fusions that can be validated, 5% were detected from tumor and normal samples with similar frequencies, and only 4% (120 fusions) were tumor-specific. The occurrences of <i>ERG, ETV1</i>, and <i>ETV4</i> fusions were mutually exclusive, and their fusion statuses were tightly associated with overexpressions. Besides, we found <i>ERG</i> fusions were significantly co-occurred with <i>PTEN</i> deletion but mutually exclusive with common genomic alterations such as <i>SPOP</i> mutation and <i>FOXA1</i> mutation.</p><p><strong>Conclusions: </strong>Most of the reported fusion genes cannot be validated by TCGA samples. The ETS family and androgen response genes were significantly enriched in prostate cancer-specific fusion genes. Transcription activity was significantly repressed, and the DNA methylation was significantly increased in samples carrying <i>ERG</i> fusion.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"20 ","pages":"11769351211027592"},"PeriodicalIF":2.0,"publicationDate":"2021-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/11769351211027592","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39162136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational Methods for Structure-to-Function Analysis of Diet-Derived Catechins-Mediated Targeting of In Vitro Vasculogenic Mimicry.","authors":"Abicumaran Uthamacumaran,&nbsp;Narjara Gonzalez Suarez,&nbsp;Abdoulaye Baniré Diallo,&nbsp;Borhane Annabi","doi":"10.1177/11769351211009229","DOIUrl":"https://doi.org/10.1177/11769351211009229","url":null,"abstract":"<p><strong>Background: </strong>Vasculogenic mimicry (VM) is an adaptive biological phenomenon wherein cancer cells spontaneously self-organize into 3-dimensional (3D) branching network structures. This emergent behavior is considered central in promoting an invasive, metastatic, and therapy resistance molecular signature to cancer cells. The quantitative analysis of such complex phenotypic systems could require the use of computational approaches including machine learning algorithms originating from complexity science.</p><p><strong>Procedures: </strong><i>In vitro</i> 3D VM was performed with SKOV3 and ES2 ovarian cancer cells cultured on Matrigel. Diet-derived catechins disruption of VM was monitored at 24 hours with pictures taken with an inverted microscope. Three computational algorithms for complex feature extraction relevant for 3D VM, including 2D wavelet analysis, fractal dimension, and percolation clustering scores were assessed coupled with machine learning classifiers.</p><p><strong>Results: </strong>These algorithms demonstrated the structure-to-function galloyl moiety impact on VM for each of the gallated catechin tested, and shown applicable in quantifying the drug-mediated structural changes in VM processes.</p><p><strong>Conclusions: </strong>Our study provides evidence of how appropriate 3D VM compression and feature extractors coupled with classification/regression methods could be efficient to study <i>in vitro</i> drug-induced perturbation of complex processes. Such approaches could be exploited in the development and characterization of drugs targeting VM.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"20 ","pages":"11769351211009229"},"PeriodicalIF":2.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/11769351211009229","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38954027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pan-Cancer Transcriptional Models Predicting Chemosensitivity in Human Tumors.","authors":"Jason D Wells, Jacqueline R Griffin, Todd W Miller","doi":"10.1177/11769351211002494","DOIUrl":"10.1177/11769351211002494","url":null,"abstract":"<p><strong>Motivation: </strong>Despite increasing understanding of the molecular characteristics of cancer, chemotherapy success rates remain low for many cancer types. Studies have attempted to identify patient and tumor characteristics that predict sensitivity or resistance to different types of conventional chemotherapies, yet a concise model that predicts chemosensitivity based on gene expression profiles across cancer types remains to be formulated. We attempted to generate pan-cancer models predictive of chemosensitivity and chemoresistance. Such models may increase the likelihood of identifying the type of chemotherapy most likely to be effective for a given patient based on the overall gene expression of their tumor.</p><p><strong>Results: </strong>Gene expression and drug sensitivity data from solid tumor cell lines were used to build predictive models for 11 individual chemotherapy drugs. Models were validated using datasets from solid tumors from patients. For all drug models, accuracy ranged from 0.81 to 0.93 when applied to all relevant cancer types in the testing dataset. When considering how well the models predicted chemosensitivity or chemoresistance within individual cancer types in the testing dataset, accuracy was as high as 0.98. Cell line-derived pan-cancer models were able to statistically significantly predict sensitivity in human tumors in some instances; for example, a pan-cancer model predicting sensitivity in patients with bladder cancer treated with cisplatin was able to significantly segregate sensitive and resistant patients based on recurrence-free survival times (<i>P</i> = .048) and in patients with pancreatic cancer treated with gemcitabine (<i>P</i> = .038). These models can predict chemosensitivity and chemoresistance across cancer types with clinically useful levels of accuracy.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"20 ","pages":"11769351211002494"},"PeriodicalIF":2.0,"publicationDate":"2021-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/11769351211002494","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25555274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Goldilocks Rounding: Achieving Balance Between Accuracy and Parsimony in the Reporting of Relative Effect Estimates.","authors":"Jimmy T Efird","doi":"10.1177/1176935120985132","DOIUrl":"https://doi.org/10.1177/1176935120985132","url":null,"abstract":"<p><p>Researchers often report a measure to several decimal places more than what is sensible or realistic. Rounding involves replacing a number with a value of lesser accuracy while minimizing the practical loss of validity. This practice is generally acceptable to simplify data presentation and to facilitate the communication and comparison of research results. Rounding also may reduce spurious accuracy when the extraneous digits are not justified by the exactness of the recording instrument or data collection procedure. However, substituting a more explicit or simpler representation for an original measure may not be practicable or acceptable if an adequate degree of accuracy is not retained. The error introduced by rounding exact numbers may result in misleading conclusions and the interpretation of study findings. For example, rounding the upper confidence interval for a relative effect estimate of 0.996 to 2 decimal places may obscure the statistical significance of the result. When presenting the findings of a study, authors need to be careful that they do not report numbers that contain too few significant digits. Equally important, they should avoid providing more significant figures than are warranted to convey the underlying meaning of the result.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"20 ","pages":"1176935120985132"},"PeriodicalIF":2.0,"publicationDate":"2021-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1176935120985132","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38827602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of Prognostic Genes and Pathways in Lung Adenocarcinoma Using a Bayesian Approach.","authors":"Yu Jiang, Yuan Huang, Yinhao Du, Yinjun Zhao, Jie Ren, Shuangge Ma, Cen Wu","doi":"10.1177/1176935116684825","DOIUrl":"10.1177/1176935116684825","url":null,"abstract":"<p><p>Lung cancer is the leading cause of cancer-associated mortality in the United States and the world. Adenocarcinoma, the most common subtype of lung cancer, is generally diagnosed at the late stage with poor prognosis. In the past, extensive effort has been devoted to elucidating lung cancer pathogenesis and pinpointing genes associated with survival outcomes. As the progression of lung cancer is a complex process that involves coordinated actions of functionally associated genes from cancer-related pathways, there is a growing interest in simultaneous identification of both prognostic pathways and important genes within those pathways. In this study, we analyse The Cancer Genome Atlas lung adenocarcinoma data using a Bayesian approach incorporating the pathway information as well as the interconnections among genes. The top 11 pathways have been found to play significant roles in lung adenocarcinoma prognosis, including pathways in mitogen-activated protein kinase signalling, cytokine-cytokine receptor interaction, and ubiquitin-mediated proteolysis. We have also located key gene signatures such as <i>RELB</i>, <i>MAP4K1</i>, and <i>UBE2C</i>. These results indicate that the Bayesian approach may facilitate discovery of important genes and pathways that are tightly associated with the survival of patients with lung adenocarcinoma.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"16 ","pages":"1176935116684825"},"PeriodicalIF":2.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1176935116684825","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38743896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"VarCon: An R Package for Retrieving Neighboring Nucleotides of an SNV.","authors":"Johannes Ptok,&nbsp;Stephan Theiss,&nbsp;Heiner Schaal","doi":"10.1177/1176935120976399","DOIUrl":"https://doi.org/10.1177/1176935120976399","url":null,"abstract":"<p><p>Reporting of a single nucleotide variant (SNV) follows the Sequence Variant Nomenclature (http://varnomen.hgvs.org/), using an unambiguous numbering scheme specific for coding and noncoding DNA. However, the corresponding sequence neighborhood of a given SNV, which is required to assess its impact on splicing regulation, is not easily accessible from this nomenclature. Providing fast and easy access to this neighborhood just from a given SNV reference, the novel tool VarCon combines information of the Ensembl human reference genome and the corresponding transcript table for accurate retrieval. VarCon also displays splice site scores (HBond and MaxEnt scores) and HEXplorer profiles of an SNV neighborhood, reflecting position-dependent splice enhancing and silencing properties.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"19 ","pages":"1176935120976399"},"PeriodicalIF":2.0,"publicationDate":"2020-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1176935120976399","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38689828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}