Challenges translating breast cancer gene signatures into the clinic (Q45233639)

11 December 2017

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title

Challenges translating breast cancer gene signatures into the clinic (English)

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11 December 2017

4

Jorge S Reis-Filho

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11 December 2017

1

Britta Weigelt

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11 December 2017

3

Alan Ashworth

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11 December 2017

Lajos Pusztai

2

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PubMed ID

21878891

11 December 2017

language of work or name

English

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publication date

30 August 2011

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Nature Reviews Clinical Oncology

11 December 2017

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11 December 2017

9

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11 December 2017

1

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11 December 2017

58-64

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The molecular portraits of breast tumors are conserved across microarray platforms

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Effect of training-sample size and classification difficulty on the accuracy of genomic predictors

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Biological Processes Associated with Breast Cancer Clinical Outcome Depend on the Molecular Subtypes

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Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures

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Breast cancer molecular profiling with single sample predictors: a retrospective analysis

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Supervised risk predictor of breast cancer based on intrinsic subtypes

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Concordance of clinical and molecular breast cancer subtyping in the context of preoperative chemotherapy response

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The effect of the stromal component of breast tumours on prediction of clinical outcome using gene expression microarray analysis

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Molecular classification of breast cancer: limitations and potential

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Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification

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Microarray-based class discovery for molecular classification of breast cancer: analysis of interobserver agreement

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Calibration and discriminatory accuracy of prognosis calculation for breast cancer with the online Adjuvant! program: a hospital-based retrospective cohort study.

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Molecular profiling currently offers no more than tumour morphology and basic immunohistochemistry

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T-cell metagene predicts a favorable prognosis in estrogen receptor-negative and HER2-positive breast cancers.

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A robust classifier of high predictive value to identify good prognosis patients in ER-negative breast cancer

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Immunohistochemical demonstration of oestrogen and progesterone receptors: correlation of standards achieved on in house tumours with that achieved on external quality assessment material in over 150 laboratories from 26 countries

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Estrogen- and progesterone-receptor status in ECOG 2197: comparison of immunohistochemistry by local and central laboratories and quantitative reverse transcription polymerase chain reaction by central laboratory

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The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

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Evaluation of a 30-gene paclitaxel, fluorouracil, doxorubicin, and cyclophosphamide chemotherapy response predictor in a multicenter randomized trial in breast cancer.

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Genome remodelling in a basal-like breast cancer metastasis and xenograft

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Complex landscapes of somatic rearrangement in human breast cancer genomes

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Microarrays and breast cancer clinical studies: forgetting what we have not yet learnt

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Deflating the Genomic Bubble

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Genetic Interactions in Cancer Progression and Treatment

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Prognostic value of Ki67 expression after short-term presurgical endocrine therapy for primary breast cancer

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A marker of homologous recombination predicts pathologic complete response to neoadjuvant chemotherapy in primary breast cancer

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Using functional genetics to understand breast cancer biology

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Personalizing cancer treatment in the age of global genomic analyses: PALB2 gene mutations and the response to DNA damaging agents in pancreatic cancer

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12 December 2020

Estrogen receptor status in breast cancer is associated with remarkably distinct gene expression patterns

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The contribution of gene expression profiling to breast cancer classification, prognostication and prediction: a retrospective of the last decade

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Identifiers

DOI

1 reference

11 December 2017

1 reference

PubMed ID

21878891