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Improving personalized prediction of cancer prognoses with clonal evolution models

https://doi.org/10.1101/761510
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Outgoing claims: the papers this work cites, builds on, or argues with.

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Estrogen receptor (ER) and progesterone receptor (PgR), by ligand-binding assay compared with ER, PgR and pS2, by immuno-histochemistry in predicting response to tamoxifen in metastatic breast cancer: A Southwest Oncology Group study
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Aneuploidy, TP53 mutation, and amplification of MYC correlate with increased intratumor heterogeneity and poor prognosis of breast cancer patients
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Allele-Specific Quantification of Structural Variations in Cancer Genomes
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Tumour evolution inferred by single-cell sequencing
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Clonal evolution in cancer
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Comprehensive genomic characterization of squamous cell lung cancers
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Comprehensive molecular portraits of human breast tumours
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Mutational heterogeneity in cancer and the search for new cancer-associated genes
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Comprehensive molecular profiling of lung adenocarcinoma
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Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples
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The Cancer Genome Atlas Pan-Cancer analysis project
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Identification of neutral tumor evolution across cancer types
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IntOGen-mutations identifies cancer drivers across tumor types
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Integrative inference of subclonal tumour evolution from single-cell and bulk sequencing data
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Pan-cancer analysis of whole genomes
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Copy number signatures and mutational processes in ovarian carcinoma
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Empirical evaluation of variant calling accuracy using ultra-deep whole-genome sequencing data
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Assessing intratumor heterogeneity and tracking longitudinal and spatial clonal evolutionary history by next-generation sequencing
inferredcites →https://doi.org/10.1073/pnas.79.14.4381openalex-snapshot
Immunological method for mapping genes on Drosophila polytene chromosomes.
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The Putative Tumor Suppressor LRP1B, a Novel Member of the Low Density Lipoprotein (LDL) Receptor Family, Exhibits Both Overlapping and Distinct Properties with the LDL Receptor-related Protein
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Hierarchical Grouping to Optimize an Objective Function
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Toward Recovering Allele-specific Cancer Genome Graphs
inferredcites →https://doi.org/10.1089/cmb.2019.0302openalex-snapshot
Tumor Copy Number Deconvolution Integrating Bulk and Single-Cell Sequencing Data
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Phylogenetic analysis of multiprobe fluorescence in situ hybridization data from tumor cell populations
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Inferring models of multiscale copy number evolution for single-tumor phylogenetics
inferredcites →https://doi.org/10.1093/bioinformatics/btw242openalex-snapshot
WeSME: uncovering mutual exclusivity of cancer drivers and beyond
inferredcites →https://doi.org/10.1093/bioinformatics/bty270openalex-snapshot
Deconvolution and phylogeny inference of structural variations in tumor genomic samples
inferredcites →https://doi.org/10.1093/database/bar026openalex-snapshot
International Cancer Genome Consortium Data Portal--a one-stop shop for cancer genomics data
inferredcites →https://doi.org/10.1093/nar/gky1015openalex-snapshot
COSMIC: the Catalogue Of Somatic Mutations In Cancer
inferredcites →https://doi.org/10.1101/161638openalex-snapshot
Large-Scale Uniform Analysis of Cancer Whole Genomes in Multiple Computing Environments
inferredcites →https://doi.org/10.1101/162784openalex-snapshot
Pan-cancer analysis of whole genomes
inferredcites →https://doi.org/10.1101/187609openalex-snapshot
Selective and mechanistic sources of recurrent rearrangements across the cancer genome
inferredcites →https://doi.org/10.1101/322859openalex-snapshot
The Repertoire of Mutational Signatures in Human Cancer
inferredcites →https://doi.org/10.1101/gr.174789.114openalex-snapshot
Exonuclease mutations in DNA polymerase epsilon reveal replication strand specific mutation patterns and human origins of replication
inferredcites →https://doi.org/10.1109/tpami.2005.159openalex-snapshot
Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy
inferredcites →https://doi.org/10.1126/science.1088759openalex-snapshot
Breast and Ovarian Cancer Risks Due to Inherited Mutations in BRCA1 and BRCA2
inferredcites →https://doi.org/10.1126/science.959840openalex-snapshot
The Clonal Evolution of Tumor Cell Populations
inferredcites →https://doi.org/10.1136/jcp.2005.029991openalex-snapshot
The value of cytokeratin immunohistochemistry in the evaluation of axillary sentinel lymph nodes in patients with lobular breast carcinoma
inferredcites →https://doi.org/10.1142/9789811215636_0008openalex-snapshot
From genome to phenome: Predicting multiple cancer phenotypes based on somatic genomic alterations via the genomic impact transformer
inferredcites →https://doi.org/10.1142/s021972000700259xopenalex-snapshot
RECONSTRUCTING TUMOR PHYLOGENIES FROM HETEROGENEOUS SINGLE-CELL DATA
inferredcites →https://doi.org/10.1145/3214306openalex-snapshot
Machine Learning for Survival Analysis
inferredcites →https://doi.org/10.1158/2159-8290.cd-15-0344openalex-snapshot
APOBEC Enzymes: Mutagenic Fuel for Cancer Evolution and Heterogeneity
inferredcites →https://doi.org/10.1172/jci40724openalex-snapshot
Cellular and genetic diversity in the progression of in situ human breast carcinomas to an invasive phenotype
inferredcites →https://doi.org/10.1186/gb-2011-12-4-r41openalex-snapshot
GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers
inferredcites →https://doi.org/10.1186/gb-2011-12-s1-p3openalex-snapshot
COSMIC: the catalogue of somatic mutations in cancer
inferredcites →https://doi.org/10.1186/s12874-018-0482-1openalex-snapshot
DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network
inferredcites →https://doi.org/10.1186/s13059-016-1029-6openalex-snapshot
MuSE: accounting for tumor heterogeneity using a sample-specific error model improves sensitivity and specificity in mutation calling from sequencing data
inferredcites →https://doi.org/10.1214/16-sts602openalex-snapshot
Logistic Regression: From Art to Science
inferredcites →https://doi.org/10.1371/journal.pcbi.1003740openalex-snapshot
Algorithms to Model Single Gene, Single Chromosome, and Whole Genome Copy Number Changes Jointly in Tumor Phylogenetics
inferredcites →https://doi.org/10.18632/oncotarget.23729openalex-snapshot
Competing risks and cancer-specific mortality: why it matters
inferredcites →https://doi.org/10.21037/jtd.2017.05.30openalex-snapshot
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inferredcites →https://doi.org/10.2147/dddt.s78537openalex-snapshot
Clinicopathological significance and potential drug targeting of CDH1 in lung cancer: a meta-analysis and literature review
inferredcites →https://doi.org/10.3322/caac.21388openalex-snapshot
The Eighth Edition AJCC Cancer Staging Manual: Continuing to build a bridge from a population‐based to a more “personalized” approach to cancer staging
inferredcites →https://doi.org/10.48550/arxiv.1608.02158openalex-snapshot
Deep Survival Analysis
inferredcites →https://doi.org/10.48550/arxiv.1708.04649openalex-snapshot
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Application of Immunohistochemistry in Breast Pathology: A Review and Update

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s00521-023-08212-wopenalex-snapshot
Tumor growth prediction and classification based on the KNN algorithm and discrete-time Markov chains (DTMC)
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Precision cancer classification using liquid biopsy and advanced machine learning techniques
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Neural Network Deconvolution Method for Resolving Pathway-Level Progression of Tumor Clonal Expression Programs With Application to Breast Cancer Brain Metastases
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