AMLBreast cancerColon cancerGastric cancerLung cancerMyelomaOvarian cancerPancreatic cancer Breast cancerLiver cancerPan-cancer Breast cancerLiver cancerPan-cancer Breast cancer Custom Pan-cancer DNA Immunotherapy

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1. Select miRNA ID:

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2. Select dataset: Compare

METABRIC (n=1262)

TCGA (n=1078)

GSE40267 (n=181)

GSE19783 (n=101)

Survival options

Survival	OS (n=2515)
Split patients by	--none-- lower quartile lower tertile median upper tertile upper quartile
	Auto select best cutoff all percentile
	Trichotomization --none-- T1 vs T3 Q1 vs Q4

Follow up threshold:

all2 months4 months6 months12 months18 months24 months30 months36 months48 months60 months120 months180 months240 months

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Restrict analysis to subtypes...

ER status:	IHC:	allER positive (n=1524)ER negative (n=591)
	Gene chip:	allER positive (n=979)ER negative (n=283)
PGR status:	IHC:	allPGR positive (n=435)PGR negative (n=337)
HER2 status:	IHC:	allHER2 negative (n=683)HER2 positive (n=741)
	Gene chip:	allHER2 negative (n=1105)HER2 positive (n=157)

Molecular subtype:

all TNBC (n=300) luminal A(ER+HER2-KI67-) (n=546) luminal B (n=433) HER2+ER- (n=105)

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Grade:	all 1 (n=108) 2 (n=510) 3 (n=774)
Lymph node status:	all positive (n=954) negative (n=1024)

Restrict analysis to selected cohorts...

	systemically untreated patients:		include (n=199)exclude (n=1063)
	systemically treated patients:
ER-positive endocrine therapy:			any (n=1262)include all (n=779)exclude all (n=483)
chemotherapy:			anyinclude all (n=280)exclude all (n=982)
	do not use cohorts

Compare datasets

METABRIC: long follow-up (median: 94 months), average characteristics (78% ER positive, 12% HER2 positive), treatment data available for this dataset only!
TCGA: very short follow-up (median only 25 months), no grade.
GSE40267: almost exclusively ER negative patients (92%).
GSE19783: nodal status not available, 38% ER negative, high proportion of HER2 positive patients (18%).

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Please note: the generated p value does not include correction for multiple hypothesis testing by default.

Please kindly cite our latest paper to support further development: Győrffy B. Survival analysis across the entire transcriptome identifies biomarkers with the highest prognostic power in breast cancer, Computational and Structural Biotechnology Journal, 2021;19:4101-4109, https://doi.org/10.1016/j.csbj.2021.07.014