Genes and functions from breast cancer signatures

Huang, Shujun; Murphy, Leigh; Xu, Wayne

doi:10.1186/s12885-018-4388-4

BMC Cancer

Table 1 Published signatures included in the analysis

From: Genes and functions from breast cancer signatures

Full name	Short name^a	gene #	Extract #	Cov %^b	Used for^c	Platform^d	Purpose^e
Full name	Short name^a	gene #	Extract #	Cov %^b	Used for^c	Platform^d	Prognosis	Predict	Subtyping
70-gene signature [1]	Mamma	70	66	100	ER+	Agilent Hu25K	yes	yes	no
21-gene signature [4]	RS	16	16	100	ER+	RT-PCR	yes	yes	no
97-gene genomic grade index [15]	GGI97	97	94	100	ER+	Affymetrix U133A	yes	yes	no
8-gene genomic grade index [27]	GGI8	4	4	100	ER+	qRT-PCR	yes	yes	no
EndoPredict assay [33]	Endo	8	8	100	ER+	qRT-PCR	yes	yes	no
Breast cancer index [21]	BCI	7	7	100	ER+	qRT-PCR	yes	yes	no
HOXB13:IL17 BR ratio [14]	HI	2	2	100	ER+	Agilent Arcturus 22 k	yes	yes	no
IHC4 Score [32]	IHC4	4	4	100	ER+	IHC	yes	yes	no
14-gene metastasis score [23]	MS14	14	14	100	ER+	RT-PCR	yes	no	no
8-gene score [29]	SMS	8	8	100	ER+	qRT-PCR	yes	no	no
PAM50 assay [3]	PAM50	50	50	100	BC	Agilent human 1Av2	yes	yes	yes
76-gene signature [10]	Wang	76	71	100	BC	Affymetrix U133A	yes	yes	no
64-gene expression signature [9]	Pawitan	64	48	75	BC	Affymetrix U133	yes	yes	no
32-gene p53 status signature [7]	p53	32	21	100	BC	Affymetrix U133 A or B	yes	yes	yes
Cell cycle pathway signature [20]	CCPS	26	26	100	BC	Affymetrix U95 Av2 or U133	yes	no	no
127-gene classifier [24]	Robust	127	127	100	BC	Affymetrix microarray	yes	no	no
26-gene stroma-derived prognostic predictor [19]	SDPP	26	26	100	BC	Agilent 44 k	yes	no	no
54-gene lung metastasis signature [8]	LM	54	54	100	BC	Affymetrix U133A	yes	no	no
186-invasivenessgene signature [17]	IGS	186	186	100	BC	Affymetrix U133 A or B	yes	no	no
92-gene predictor [2]	Chang	92	86	100	BC	Affymetrix U95 Av2	no	yes	no
85-gene signature [6]	Iwao	85	73	100	BC	ATAC-PCR	no	yes	no
512-gene signature [16]	Olaf	512	355	69	BC	Human Oligo set 2.1	no	yes	no
7-gene immune response module [18]	IR7	7	7	100	ER-	Agilent and Affymetrix microarray	yes	no	yes
T-cell metagene [26]	Tcell	50	50	100	ER-	Affymetrix U133A	yes	no	no
Multigene HRneg/Tneg signature [31]	Multigene	14	14	100	TNBC	Affymetrix U133A	yes	no	no
26-gene signature [35]	Novel1	26	20	100	TNBC	Affymetrix U133	yes	yes	no
264-gene signature [35]	Novel2	264	225	100	TNBC	Affymetrix U133	yes	no	no
B-cell:IL8 ratio [41]	Bcell	22	20	100	100 TNBC	Affymetrix U133A or U133 Plus 2.0	yes	no	no
MAGE-A [38]	MAGEA	2	2	100	TNBC	Affymetrix U133	yes	no	no
368-gene medullary breast cancer like signature [36]	MBC	368	368	100	TNBC	Affymetrix or Agilent aaray	yes	no	yes
158-gene HER2-derived prognostic predictor [30]	HDPP	158	158	100	HER2+	SWEGENE H_v2.1.1 55 K	yes	no	yes
GCNs of MET and HGF [39]	GCN	2	2	100	HER2+	Fluorescence in situ hybridisation (FISH)	no	yes	No
28-gene expression profile [28]	Vegran	28	27	100	HER2+	Affymetrix microarray	no	yes	no

^aThe short name for the full name used in this paper
^bFor some signatures with 100% coverage (all signature genes were found in data set), the extracted gene No (Extract# column) is less than the reported gene No (gene# column) because some genes are duplicated with different probe names within a signature
^cThe subtype the signatures are developed for: ER+, the signature is used for ER-positive breast cancer; ER-, the signature is used for ER-negative breast cancer; uc-BC, the signature is used for un-classified breast cancer with mixed subtypes; TNBC, the signature is used for TNBC or basal breast cancer; HER2+, the signature is used for HER2-positive breast cancer
^dThe experimental platform used for developing the signatures
^eThe clinical purpose of these signatures: prognosis, the signature can be used for prognosis; prediction, the signature can be used for predicting the response to treatment or drug; subtyping, the signature can be used for further subtyping breast cancers

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ISSN: 1471-2407

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