Breast cancer gene expression datasets do not reflect the disease at the population level

Xie, Yanping; Lynn, Brittny C. Davis; Moir, Nicholas; Cameron, David; Figueroa, Jonine D.; Sims, Andrew H.

doi:10.1038/s41523-020-00180-x

Cited by 6 publications

(10 citation statements)

References 22 publications

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“…In addition, although datasets provide a valuable resource to test hypotheses for individual genes/signatures, there are variations in terms of size, patient characteristics and molecular composition of datasets and they do not necessarily reflect the studied cohort of BC patients. This is reported in the literature [45]. However, this indicates the need for more studies to test the value of these two proteins as prognostic markers in BC.…”

Section: Discussionmentioning

confidence: 88%

The impact of CBP expression in estrogen receptor-positive breast cancer

et al. 2021

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Background The development of new biomarkers with diagnostic, prognostic and therapeutic prominence will greatly enhance the management of breast cancer (BC). Several reports suggest the involvement of the histone acetyltransferases CREB-binding protein (CBP) and general control non-depressible 5 (GCN5) in tumor formation; however, their clinical significance in BC remains poorly understood. This study aims to investigate the value of CBP and GCN5 as markers and/or targets for BC prognosis and therapy. Expression of CBP, GCN5, estrogen receptor α (ERα), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) in BC was analyzed in cell lines by western blot and in patients’ tissues by immunohistochemistry. The gene amplification data were also analyzed for CBP and GCN5 using the publicly available data from BC patients. Results Elevated expression of CBP and GCN5 was detected in BC tissues from patients and cell lines more than normal ones. In particular, CBP was more expressed in luminal A and B subtypes. Using chemical and biological inhibitors for CBP, ERα and HER2 showed a strong association between CBP and the expression of ERα and HER2. Moreover, analysis of the CREBBP (for CBP) and KAT2A (for GCN5) genes in a larger number of patients in publicly available databases showed amplification of both genes in BC patients. Amplification of CREBBP gene was observed in luminal A, luminal B and triple-negative but not in HER2 overexpressing subtypes. Furthermore, patients with high CREBBP or KAT2A gene expression had better 5-year disease-free survival than the low gene expression group (p = 0.0018 and p < 0.00001, respectively). Conclusions We conclude that the persistent amplification and overexpression of CBP in ERα- and PR-positive BC highlights the significance of CBP as a new diagnostic marker and therapeutic target in hormone-positive BC.

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Section: Discussionmentioning

confidence: 88%

The impact of CBP expression in estrogen receptor-positive breast cancer

et al. 2021

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“…We set out to validate our results in the TCGA breast cancer cohort 52 . Albeit not population-based, and as previously reported, having a bias towards larger tumors with higher grade and stage 53 , this dataset represents a comparably large tumor collection with publicly available RNA-seq data. Generally, the SCAN-B results were confirmed in TCGA.…”

Section: Resultsmentioning

confidence: 99%

Clinical associations of ESR2 (estrogen receptor beta) expression across thousands of primary breast tumors

Dalal

Dahlgren

Gladchuk

et al. 2022

Sci Rep

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Estrogen receptor alpha (ERα, encoded by ESR1) is a well-characterized transcription factor expressed in more than 75% of breast tumors and is the key biomarker to direct endocrine therapies. On the other hand, much less is known about estrogen receptor beta (ERβ, encoded by ESR2) and its importance in cancer. Previous studies had some disagreement, however most reports suggested a more favorable prognosis for patients with high ESR2 expression. To add further clarity to ESR2 in breast cancer, we interrogated a large population-based cohort of primary breast tumors (n = 3207) from the SCAN-B study. RNA-seq shows ESR2 is expressed at low levels overall with a slight inverse correlation to ESR1 expression (Spearman R = −0.18, p = 2.2e−16), and highest ESR2 expression in the basal- and normal-like PAM50 subtypes. ESR2-high tumors had favorable overall survival (p = 0.006), particularly in subgroups receiving endocrine therapy (p = 0.03) and in triple-negative breast cancer (p = 0.01). These results were generally robust in multivariable analyses accounting for patient age, tumor size, node status, and grade. Gene modules consistent with immune response were associated to ESR2-high tumors. Taken together, our results indicate that ESR2 is generally expressed at low levels in breast cancer but associated with improved overall survival and may be related to immune response modulation.

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“…In fact, the PAM50 panel and intrinsic subtypes gene signature prototypes were obtained from bulk tissue data, and this can introduce a bias due to sampling procedures, as also discussed in [ 35 ]. Furthermore, one has to take into account that currently available large expression sets are poorly able to reflect BRCA at the population level [ 36 ]; thus, larger curated datasets will be required to refine predictions. In Supplementary Figure S2, the relative abundance of each SURFACER subtype into classic PAM50-assigned patients clusters is showed.…”

Section: Resultsmentioning

confidence: 99%

“…Most of the differences showed between TCGA and METABRIC cohorts KM curves may be in part dependent to the difference in both sample composition and the completeness of associated clinical data. In fact, it was previously observed that molecular subtypes composition between TCGA and METABRIC datasets is variable, and it does not adequately capture BRCA real subtype distribution at the population level [ 36 ].…”

Section: Resultsmentioning

confidence: 99%

Detection of subtype-specific breast cancer surface protein biomarkers via a novel transcriptomics approach

et al. 2021

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Background: Cell-surface proteins have been widely used as diagnostic and prognostic markers in cancer research, and as targets for the development of anti-cancer agents. So far, very few attempts have been made to characterize the surfaceome of breast cancer patients, particularly in relation with the current molecular breast cancer (BRCA) classification. In this view, we developed a new computational method to infer cell-surface protein activities from transcriptomics data, termed “SURFACER”. Methods: Gene expression data from GTEx were used to build a normal breast network model as input to infer differential cell-surface proteins activity in BRCA tissue samples retrieved from TCGA vs. normal samples. Data were stratified according to the PAM50 transcriptional subtypes (Luminal A, Luminal B, HER2, Basal), while unsupervised clustering techniques were applied to define BRCA subtypes according to cell-surface proteins activity. Results: Our approach led to the identification of 213 PAM50 subtypes-specific deregulated surface genes and the definition of 5 BRCA subtypes, whose prognostic value was assessed by survival analysis, identifying a cell-surface activity configuration at increased risk. The value of the SURFACER method in BRCA genotyping was tested by evaluating the performance of 11 different machine learning classification algorithms. Conclusions: BRCA patients can be stratified into 5 surface activity-specific groups having the potential to identify subtype-specific actionable targets to design tailored targeted therapies, or for diagnostic purposes. SURFACER-defined subtypes show also a prognostic value, identifying surface-activity profiles at higher risk.

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Breast cancer gene expression datasets do not reflect the disease at the population level

Cited by 6 publications

References 22 publications

The impact of CBP expression in estrogen receptor-positive breast cancer

The impact of CBP expression in estrogen receptor-positive breast cancer

Clinical associations of ESR2 (estrogen receptor beta) expression across thousands of primary breast tumors

Detection of subtype-specific breast cancer surface protein biomarkers via a novel transcriptomics approach

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