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pmid:32267939

Differences in gene-expression profiles in breast cancer between African and European-ancestry women.

Jie Ping · Xingyi Guo · Fei Ye · Jirong Long · Loren Lipworth · Qiuyin Cai · William Blot · Xiao-Ou Shu · Wei Zheng

Carcinogenesis · 2020 doi:10.1093/carcin/bgaa035

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Experiment

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Data

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Analysis

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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1.2
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pmid:32267939
kind
science-record
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content_hash
sha256:c26d7e04faf739a6a20bc0b477624de55ee39dc614c565ccebbe09b674e624db
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created_at
2026-11-01T15:40:59Z
updated_at
2026-11-01T21:23:05Z
generator object · 2 fields
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paper object · 10 fields
state
complete
title
Differences in gene-expression profiles in breast cancer between African and European-ancestry women.
doi
10.1093/carcin/bgaa035
pmid
32267939
authors array · 9 items
[0]
Jie Ping
[1]
Xingyi Guo
[2]
Fei Ye
[3]
Jirong Long
[4]
Loren Lipworth
[5]
Qiuyin Cai
[6]
William Blot
[7]
Xiao-Ou Shu
[8]
Wei Zheng
journal
Carcinogenesis
year
2020
abstract
African American (AA) women have an excess breast cancer mortality than European American (EA) women. To investigate the contribution of tumor biology to this survival health disparity, we compared gene expression profiles in breast tumors using RNA sequencing data derived from 260 AA and 155 EA women who were prospectively enrolled in the Southern Community Cohort Study (SCCS) and developed breast cancer during follow-up. We identified 59 genes (54 protein-coding genes and 5 long intergenic non-coding RNAs) that were expressed differently between EA and AA at a stringent false discovery rate (FDR) < 0.01. A gene signature was derived with these 59 genes and externally validated using the publicly available Cancer Genome Atlas (TCGA) data from180 AA and 838 EA breast cancer patients. Applying C-statistics, we found that this 59-gene signature has a high discriminative ability in distinguishing AA and EA breast cancer patients in the TCGA dataset (C-index = 0.81). These findings may provide new insight into tumor biological differences and the causes of the survival disparity between AA and EA breast cancer patients.
claims array · 2 items
[0] object · 6 fields
id
claim-method
statement
Allowing for retention of correlated genes, we used elastic net penalized Cox regression to identify a subset of the race-differentiated genes that were prognostic of breast cancer survival, adjusting for clinical variables, including age at diagnosis, stage, race, ER, PR, and HER2.
kind
methodological
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null
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source:pmid:32267939
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sections[9] "Survival analyses" paragraph 2
quote
Allowing for retention of correlated genes, we used elastic net penalized Cox regression to identify a subset of the race-differentiated genes that were prognostic of breast cancer survival, adjusting for clinical variables, including age at diagnosis, stage, race, ER, PR, and HER2.
state
complete
[1] object · 6 fields
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claim-data-access
statement
Breast cancer data from TCGA, which are publicly available from the NCI GDC data portal (https://portal.gdc.cancer.gov/), was used in this study as an independent validation set. We obtained the most updated clinical information from the TCGA Pan-Cancer Clinical Data Resource (18). HTSeq-FPKM data for TCGA breast cancer samples were downloaded as gene expression profiles and for further analysis, by using R package TCGAbiolinks (12,19).
kind
methodological
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null
evidence array · 1 item
[0] object · 3 fields
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source:pmid:32267939
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sections[6] "TCGA data" paragraph 2
quote
Breast cancer data from TCGA, which are publicly available from the NCI GDC data portal (https://portal.gdc.cancer.gov/), was used in this study as an independent validation set. We obtained the most updated clinical information from the TCGA Pan-Cancer Clinical Data Resource (18). HTSeq-FPKM data for TCGA breast cancer samples were downloaded as gene expression profiles and for further analysis, by using R package TCGAbiolinks (12,19).
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https://doi.org/10.1093/carcin/bgaa035
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10.1093/carcin/bgaa035
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europe_pmc_fulltext
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Clinicopathological characteristics of breast cancer patients according to race groups in the SCCS and TCGA
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pmcid
PMC7359770
section_index
11
section_title
Study samples
row_count
31
column_count
7
table object · 8 fields
label
Table 1.
caption
Clinicopathological characteristics of breast cancer patients according to race groups in the SCCS and TCGA
rows array · 31 items
[0] array · 3 items
[0]
Variable
[1]
SCCS (n = 415)
[2]
TCGA (n = 1018)
[1] array · 7 items
[0]
Race
[1]
AA
[2]
EA
[3]
P value
[4]
AA
[5]
EA
[6]
P value
[2] array · 7 items
[0]
No. of subjects (%)
[1]
260 (62.7)
[2]
155 (37.3)
[3]
[4]
180 (17.7)
[5]
838 (82.3)
[6]
[3] array · 7 items
[0]
Age at diagnosis, mean (SD)
[1]
58.5 (9.0)
[2]
60.6 (9.4)
[3]
0.029
[4]
56.3 (13.5)
[5]
59.2 (13.1)
[6]
0.007
[4] array · 7 items
[0]
PAM50 subtype, no. (%)
[1]
[2]
[3]
[4]
[5]
[6]
[5] array · 7 items
[0]
Luminal A
[1]
112 (43.1)
[2]
78 (50.3)
[3]
0.474
[4]
48 (26.7)
[5]
410 (48.9)
[6]
<0.001
[6] array · 7 items
[0]
Luminal B
[1]
36 (13.8)
[2]
24 (15.5)
[3]
[4]
34 (18.9)
[5]
180 (21.5)
[6]
[7] array · 7 items
[0]
Basal-like
[1]
67 (25.8)
[2]
32 (20.6)
[3]
[4]
67 (37.2)
[5]
120 (14.3)
[6]
[8] array · 7 items
[0]
HER2-enriched
[1]
29 (11.2)
[2]
12 (7.7)
[3]
[4]
22 (12.2)
[5]
75 (8.9)
[6]
[9] array · 7 items
[0]
Normal-like
[1]
16 (6.2)
[2]
9 (5.8)
[3]
[4]
9 (5.0)
[5]
53 (6.3)
[6]
[10] array · 7 items
[0]
TNBC, no. (%)
[1]
[2]
[3]
[4]
[5]
[6]
[11] array · 7 items
[0]
Yes
[1]
47 (18.1)
[2]
21 (13.5)
[3]
0.285
[4]
33 (18.3)
[5]
73 (8.7)
[6]
<0.001
[12] array · 7 items
[0]
Noa
[1]
213 (81.9)
[2]
134 (86.5)
[3]
[4]
147 (81.7)
[5]
765 (91.3)
[6]
[13] array · 7 items
[0]
ER, no. (%)
[1]
[2]
[3]
[4]
[5]
[6]
[14] array · 7 items
[0]
Negative
[1]
85 (33.3)
[2]
36 (24.8)
[3]
0.095
[4]
69 (39.2)
[5]
148 (18.6)
[6]
<0.001
[15] array · 7 items
[0]
Positive
[1]
170 (66.7)
[2]
109 (75.2)
[3]
[4]
107 (60.8)
[5]
648 (81.4)
[6]
[16] array · 7 items
[0]
Undeterminedb
[1]
5
[2]
10
[3]
[4]
4
[5]
42
[6]
[17] array · 7 items
[0]
PR, no. (%)
[1]
[2]
[3]
[4]
[5]
[6]
[18] array · 7 items
[0]
Negative
[1]
110 (43.7)
[2]
52 (36.1)
[3]
0.173
[4]
88 (50)
[5]
229 (28.9)
[6]
<0.001
[19] array · 7 items
[0]
Positive
[1]
142 (56.3)
[2]
92 (63.9)
[3]
[4]
88 (50)
[5]
564 (71.1)
[6]
[20] array · 7 items
[0]
Undeterminedb
[1]
8
[2]
11
[3]
[4]
4
[5]
45
[6]
[21] array · 7 items
[0]
HER2, no. (%)
[1]
[2]
[3]
[4]
[5]
[6]
[22] array · 7 items
[0]
Negative
[1]
165 (85.5)
[2]
97 (84.3)
[3]
0.914
[4]
74 (83.1)
[5]
450 (77.4)
[6]
0.378
[23] array · 7 items
[0]
Positive
[1]
28 (14.5)
[2]
18 (15.7)
[3]
[4]
16 (16.9)
[5]
131 (22.6)
[6]
[24] array · 7 items
[0]
Undeterminedb
[1]
67
[2]
40
[3]
[4]
91
[5]
257
[6]
[25] array · 7 items
[0]
AJCC stage, no. (%)
[1]
[2]
[3]
[4]
[5]
[6]
[26] array · 7 items
[0]
Stage I
[1]
74 (36.1)
[2]
65 (51.2)
[3]
0.02
[4]
32 (18.2)
[5]
145 (17.7)
[6]
0.614
[27] array · 7 items
[0]
Stage II
[1]
83 (40.5)
[2]
46 (36.2)
[3]
[4]
106 (60.2)
[5]
465 (56.6)
[6]
[28] array · 7 items
[0]
Stage III
[1]
38 (18.5)
[2]
14 (11.0)
[3]
[4]
34 (19.3)
[5]
196 (23.9)
[6]
[29] array · 7 items
[0]
Stage IV
[1]
10 (4.9)
[2]
2 (1.6)
[3]
[4]
4 (2.3)
[5]
15 (1.8)
[6]
[30] array · 7 items
[0]
Stage X or unknown
[1]
55
[2]
28
[3]
[4]
4
[5]
19
[6]
row_count
31
column_count
7
numeric_cells
109
header_rows
2
locator
section[11]/table-wrap[1]#T1
[2] object · 16 fields
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note
The set of 59 genes found to be significantly differential expressed in the SCCS at FDR-adjusted P value < 0.01
structure object · 5 fields
pmcid
PMC7359770
section_index
12
section_title
Race-differentiated gene signature in breast cancer tumor tissues
row_count
60
column_count
5
table object · 8 fields
label
Table 2.
caption
The set of 59 genes found to be significantly differential expressed in the SCCS at FDR-adjusted P value < 0.01
rows array · 60 items
[0] array · 5 items
[0]
ENSEMBL ID
[1]
Gene symbol
[2]
P value (SCCS)
[3]
FDR (SCCS)
[4]
P value (TCGA)
[1] array · 5 items
[0]
ENSG00000255374
[1]
TAS2R43
[2]
<0.001
[3]
<0.001
[4]
<0.001
[2] array · 5 items
[0]
ENSG00000130950
[1]
NUTM2F
[2]
<0.001
[3]
<0.001
[4]
<0.001
[3] array · 5 items
[0]
ENSG00000241945
[1]
PWP2
[2]
<0.001
[3]
<0.001
[4]
<0.001
[4] array · 5 items
[0]
ENSG00000259604
[1]
Lnc-ALDH1A3-1
[2]
<0.001
[3]
0.005
[4]
<0.001
[5] array · 5 items
[0]
ENSG00000160221
[1]
GATD3A
[2]
<0.001
[3]
<0.001
[4]
<0.001
[6] array · 5 items
[0]
ENSG00000176681
[1]
LRRC37A
[2]
<0.001
[3]
<0.001
[4]
<0.001
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[0]
ENSG00000142178
[1]
SIK1
[2]
<0.001
[3]
0.001
[4]
<0.001
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[0]
ENSG00000134184
[1]
GSTM1
[2]
<0.001
[3]
<0.001
[4]
<0.001
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[0]
ENSG00000261701
[1]
HPR
[2]
<0.001
[3]
0.008
[4]
<0.001
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[0]
ENSG00000158488
[1]
CD1E
[2]
<0.001
[3]
<0.001
[4]
<0.001
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[0]
ENSG00000196436
[1]
NPIPB15
[2]
<0.001
[3]
<0.001
[4]
<0.001
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[0]
ENSG00000173678
[1]
SPDYE2B
[2]
<0.001
[3]
<0.001
[4]
<0.001
[13] array · 5 items
[0]
ENSG00000224635
[1]
AL391095.1
[2]
<0.001
[3]
<0.001
[4]
<0.001
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[0]
ENSG00000106113
[1]
CRHR2
[2]
<0.001
[3]
0.004
[4]
<0.001
[15] array · 5 items
[0]
ENSG00000105499
[1]
PLA2G4C
[2]
<0.001
[3]
<0.001
[4]
<0.001
[16] array · 5 items
[0]
ENSG00000204147
[1]
ASAH2B
[2]
<0.001
[3]
0.002
[4]
<0.001
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[0]
ENSG00000197822
[1]
OCLN
[2]
<0.001
[3]
0.008
[4]
<0.001
[18] array · 5 items
[0]
ENSG00000197728
[1]
RPS26
[2]
<0.001
[3]
<0.001
[4]
<0.001
[19] array · 5 items
[0]
ENSG00000168255
[1]
POLR2J3
[2]
<0.001
[3]
<0.001
[4]
<0.001
[20] array · 5 items
[0]
ENSG00000203666
[1]
EFCAB2
[2]
<0.001
[3]
0.003
[4]
<0.001
[21] array · 5 items
[0]
ENSG00000106686
[1]
SPATA6L
[2]
<0.001
[3]
<0.001
[4]
<0.001
[22] array · 5 items
[0]
ENSG00000152689
[1]
RASGRP3
[2]
<0.001
[3]
0.008
[4]
<0.001
[23] array · 5 items
[0]
ENSG00000178295
[1]
GEN1
[2]
<0.001
[3]
<0.001
[4]
<0.001
[24] array · 5 items
[0]
ENSG00000215908
[1]
CROCCP2
[2]
<0.001
[3]
<0.001
[4]
<0.001
[25] array · 5 items
[0]
ENSG00000154237
[1]
LRRK1
[2]
<0.001
[3]
0.001
[4]
<0.001
[26] array · 5 items
[0]
ENSG00000026950
[1]
BTN3A1
[2]
<0.001
[3]
0.007
[4]
<0.001
[27] array · 5 items
[0]
ENSG00000149292
[1]
TTC12
[2]
<0.001
[3]
0.004
[4]
<0.001
[28] array · 5 items
[0]
ENSG00000198060
[1]
MARCH5
[2]
<0.001
[3]
0.004
[4]
<0.001
[29] array · 5 items
[0]
ENSG00000154096
[1]
THY1
[2]
<0.001
[3]
<0.001
[4]
<0.001
[30] array · 5 items
[0]
ENSG00000111671
[1]
SPSB2
[2]
<0.001
[3]
0.008
[4]
<0.001
[31] array · 5 items
[0]
ENSG00000135723
[1]
FHOD1
[2]
<0.001
[3]
0.004
[4]
<0.001
[32] array · 5 items
[0]
ENSG00000150477
[1]
KIAA1328
[2]
<0.001
[3]
0.009
[4]
<0.001
[33] array · 5 items
[0]
ENSG00000231389
[1]
HLA-DPA1
[2]
<0.001
[3]
0.008
[4]
<0.001
[34] array · 5 items
[0]
ENSG00000131669
[1]
NINJ1
[2]
<0.001
[3]
0.009
[4]
<0.001
[35] array · 5 items
[0]
ENSG00000181481
[1]
RNF135
[2]
<0.001
[3]
0.009
[4]
<0.001
[36] array · 5 items
[0]
ENSG00000203747
[1]
FCGR3A
[2]
<0.001
[3]
0.002
[4]
<0.001
[37] array · 5 items
[0]
ENSG00000144026
[1]
ZNF514
[2]
<0.001
[3]
0.001
[4]
<0.001
[38] array · 5 items
[0]
ENSG00000186468
[1]
RPS23
[2]
<0.001
[3]
<0.001
[4]
<0.001
[39] array · 5 items
[0]
ENSG00000175745
[1]
NR2F1
[2]
<0.001
[3]
0.009
[4]
<0.001
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ENSG00000171503
[1]
ETFDH
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<0.001
[3]
0.002
[4]
<0.001
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ENSG00000068654
[1]
POLR1A
[2]
<0.001
[3]
<0.001
[4]
<0.001
[42] array · 5 items
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ENSG00000185684
[1]
EP400P1
[2]
<0.001
[3]
<0.001
[4]
<0.001
[43] array · 5 items
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ENSG00000279457
[1]
WASH9P
[2]
<0.001
[3]
0.004
[4]
<0.001
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[0]
ENSG00000280670
[1]
CCDC163
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<0.001
[3]
0.008
[4]
<0.001
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ENSG00000149089
[1]
APIP
[2]
<0.001
[3]
<0.001
[4]
<0.001
[46] array · 5 items
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ENSG00000273136
[1]
NBPF26
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<0.001
[3]
<0.001
[4]
<0.001
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ENSG00000140263
[1]
SORD
[2]
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Allowing for retention of correlated genes, we used elastic net penalized Cox regression to identify a subset of the race-differentiated genes that were prognostic of breast cancer survival, adjusting for clinical variables, including age at diagnosis, stage, race, ER, PR, and HER2.
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Breast cancer data from TCGA, which are publicly available from the NCI GDC data portal (https://portal.gdc.cancer.gov/), was used in this study as an independent validation set. We obtained the most updated clinical information from the TCGA Pan-Cancer Clinical Data Resource (18). HTSeq-FPKM data for TCGA breast cancer samples were downloaded as gene expression profiles and for further analysis, by using R package TCGAbiolinks (12,19).
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e expression profiles in breast tumors using RNA sequencing data derived from 260 AA and 155 EA women wh
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Allowing for retention of correlated genes, we used elastic net penalized Cox regression to identify a subset of the race-differentiated genes that were prognostic of breast cancer survival, adjusting for clinical variables, including age at diagnosis, stage, race, ER, PR, and HER2.
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Complete file 
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32267939", "kind": "science-record", "revision": 6, "content_hash": "sha256:c26d7e04faf739a6a20bc0b477624de55ee39dc614c565ccebbe09b674e624db", "created_at": "2026-11-01T15:40:59Z", "updated_at": "2026-11-01T21:23:05Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Differences in gene-expression profiles in breast cancer between African and European-ancestry women.", "doi": "10.1093/carcin/bgaa035", "pmid": "32267939", "authors": ["Jie Ping", "Xingyi Guo", "Fei Ye", "Jirong Long", "Loren Lipworth", "Qiuyin Cai", "William Blot", "Xiao-Ou Shu", "Wei Zheng"], "journal": "Carcinogenesis", "year": 2020, "abstract": "African American (AA) women have an excess breast cancer mortality than European American (EA) women. To investigate the contribution of tumor biology to this survival health disparity, we compared gene expression profiles in breast tumors using RNA sequencing data derived from 260 AA and 155 EA women who were prospectively enrolled in the Southern Community Cohort Study (SCCS) and developed breast cancer during follow-up. We identified 59 genes (54 protein-coding genes and 5 long intergenic non-coding RNAs) that were expressed differently between EA and AA at a stringent false discovery rate (FDR) < 0.01. A gene signature was derived with these 59 genes and externally validated using the publicly available Cancer Genome Atlas (TCGA) data from180 AA and 838 EA breast cancer patients. Applying C-statistics, we found that this 59-gene signature has a high discriminative ability in distinguishing AA and EA breast cancer patients in the TCGA dataset (C-index = 0.81). 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