TNBCtype statistics

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Protocols

TNBCtype specifications

Information


Unique identifier OMICS_19773
Name TNBCtype
Alternative name Triple-Negative Breast Cancer type
Interface Web user interface
Restrictions to use None
Input data Gene expression values.
Input format CSV
Computer skills Basic
Stability Stable
Maintained Yes

Maintainers


  • person_outline Jennifer Pietenpol
  • person_outline Xi Chen

Additional information


http://cbc.mc.vanderbilt.edu/tnbc/help.php

Publication for Triple-Negative Breast Cancer type

TNBCtype citations

 (14)
library_books

How shall we treat early triple negative breast cancer (TNBC): from the current standard to upcoming immuno molecular strategies

2018
PMCID: 5950702
PMID: 29765774
DOI: 10.1136/esmoopen-2018-000357

[…] e majority of TNBC subtypes other than MSL and LAR were classified as BLBC. Recently, Lehmann et al revised their previous subclassification to a more concise system consisting of only four subtypes (TNBCtype-4): BL1, BL2, M and LAR. A noticeable remark from this study was that the IM phenotype was not an isolated molecular subtype, but can exist within all molecular subtypes to varying degrees. B […]

call_split

Differential prioritization of therapies to subtypes of triple negative breast cancer using a systems medicine method

2017
Oncotarget
PMCID: 5696233
PMID: 29190967
DOI: 10.18632/oncotarget.21669
call_split See protocol

[…] -derived TNBC gene expression (RNAseq) data for primary tumors were obtained from The Cancer Genome Atlas (TCGA) [] via extraction from the UCSC Cancer Genome Browser []. For each patient sample, the TNBCtype webtool [] was used to classify that sample into the subtype according to Lehmann et al []. Differential gene expression analysis (DGEA) was performed in R [] where one TNBC patient subtype g […]

library_books

Reverse phase protein array identification of triple negative breast cancer subtypes and comparison with mRNA molecular subtypes

2017
Oncotarget
PMCID: 5642571
PMID: 29050296
DOI: 10.18632/oncotarget.19719

[…] the most correlation was seen in only the BL1/2 subtypes, and we couldn’t identify the 6 molecular subtypes using functional proteomics analysis.Lehmann et al refined TNBC molecular subtypes from 6 (TNBCtype) into 4 (TNBCtype-4) tumor-specific subtypes (BL1, BL2, M, and LAR) because they found significant evidence that the IM and MSL TNBC subtypes represent tumors with substantial numbers of infi […]

call_split

Efficacy and Molecular Mechanisms of Differentiated Response to the Aurora and Angiogenic Kinase Inhibitor ENMD 2076 in Preclinical Models of p53 Mutated Triple Negative Breast Cancer

2017
PMCID: 5430301
PMID: 28555173
DOI: 10.3389/fonc.2017.00094
call_split See protocol

[…] To predict the TNBC subtypes of the PDX models, we used the TNBCtype web tool (http://cbc.mc.vanderbilt.edu/tnbc) (). RNA-seq data for these models were uploaded to the TNBCtype web tool. Based on the gene expression profiles, the TNBCtype was assigned to the […]

library_books

Single cell RNA seq enables comprehensive tumour and immune cell profiling in primary breast cancer

2017
Nat Commun
PMCID: 5424158
PMID: 28474673
DOI: 10.1038/ncomms15081

[…] l correlations; comparisons with immunofluorescence staining results; comparisons of immune marker expression; and application of self-normalizing tools such as Gene Set Variation Analysis (GSVA) and TNBCtype. […]

library_books

Comparison of triple negative breast cancer molecular subtyping using RNA from matched fresh frozen versus formalin fixed paraffin embedded tissue

2017
BMC Cancer
PMCID: 5379658
PMID: 28376728
DOI: 10.1186/s12885-017-3237-1

[…] e extended to FFPE samples profiled by RNA-seq, we performed subtyping on gene expression data derived from RNA prepared from 21 matched FF and FFPE pairs and sequenced on a HiSeq or MiSeq. Using the TNBCtype algorithm on samples sequenced on the HiSeq, we obtained subtype calls for 10 FF and 9 FFPE samples (with 9 sample pairs having calls for both FF and FFPE).The concordance rate was 67% (6 of […]

Citations

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TNBCtype institution(s)
Department of Biostatistics, Vanderbilt University, Nashville, TN, USA; Center for Quantitative Sciences, Vanderbilt University, Nashville, TN, USA; Department of Biochemistry, Vanderbilt University, Nashville, TN, USA; Vanderbilt Institute of Chemical Biology, Vanderbilt University, Nashville, TN, USA; Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, TN, USA
TNBCtype funding source(s)
Supported by NIH grants CA068485; CA95131 (Specialized Program of Research Excellence in Breast Cancer); CA148375; CA105436; CA070856; CA009385; American Cancer Society Grant #PF-10-226-01-TBG; and Komen Foundation grant SAC110030.2.0

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