Oestrogen-regulated protein SLC39A6: a biomarker of good prognosis in luminal breast cancer

Althobiti, Maryam; Elsharawy, Khloud A.; Joseph, Chitra; Aleskandarany, Mohammed A.; Toss, Michael S.; Green, Andrew; Rakha, Emad A.

doi:10.1007/s10549-021-06336-y

Cited by 7 publications

(6 citation statements)

References 51 publications

(73 reference statements)

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“…Finally, several authors have studied the relationship among some survival markers discovered in this research and breast cancer. In particular, AGR3 ( Garczyk et al , 2015 ), CA12 ( Li et al , 2019 ), CCDC170 (C6orf97; Yamamoto-Ibusuki et al , 2015 ), NDPKC (NME3; Wu et al , 2020 ), PEPT2 (SLC15A2; El Ansari et al , 2018 ), SUSD3 ( Zhao et al , 2016 ) and ZIP6 (SLC39A6; Althobiti et al , 2021 ) have been linked to breast cancer in different studies and several of these genes have also been reported to interact or be associated with ER expression and function. Furthermore, as can be seen from the included references, several of these genes have been correlated with patient survival and prognosis in breast cancer studies.…”

Section: Resultsmentioning

confidence: 99%

Identification of a gene expression signature associated with breast cancer survival and risk that improves clinical genomic platforms

Bueno-Fortes

Berral-González

Sánchez‐Santos

et al. 2023

Bioinformatics Advances

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Motivation Modern genomic technologies allow us to perform genome-wide analysis to find gene markers associated with the risk and survival in cancer patients. Accurate risk prediction and patient stratification based on robust gene signatures is a key path forward in personalized treatment and precision medicine. Several authors have proposed the identification of gene signatures to assign risk in patients with breast cancer (BRCA), and some of these signatures have been implemented within commercial platforms in the clinic, such as Oncotype and Prosigna. However, these platforms are black boxes in which the influence of selected genes as survival markers is unclear and where the risk scores provided can not be clearly related to the standard clinico-pathological tumor markers obtained by immunohistochemistry (IHC), which guide clinical and therapeutic decisions in breast cancer. Results Here we present a framework to discover a robust list of gene expression markers associated with survival that can be biologically interpreted in terms of the 3 main biomolecular factors (IHC clinical markers: ER, PR and HER2) that define clinical outcome in BRCA. To test and ensure the reproducibility of the results, we compiled and analyse two independent datasets with a large number of tumor samples (1,024 and 879) that include full genome-wide expression profiles and survival data. Using these two cohorts, we obtained a robust subset of gene survival markers that correlate well with the major IHC clinical markers used in breast cancer. The geneset of survival markers that we identify (which includes 34 genes) significantly improves the risk prediction provided by the genesets included in the commercial platforms: Oncotype (16 genes) and Prosigna (50 genes, i.e. PAM50). Furthermore, some of the genes identified have recently been proposed in the literature as new prognostic markers and may deserve more attention in current clinical trials to improve breast cancer risk prediction. Availability All data integrated and analyzed in this research will be available on GitHub, including the R scripts and protocols used for the analyses. Supplementary information Supplementary material is available at Bioinformatics Advances online.

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Section: Resultsmentioning

confidence: 99%

Identification of a gene expression signature associated with breast cancer survival and risk that improves clinical genomic platforms

Bueno-Fortes

Berral-González

Sánchez‐Santos

et al. 2023

Bioinformatics Advances

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“…However, no multivariate analysis was performed. A study by Althobiti et al [ 22 ] assessed LIV1 mRNA expression and copy-number alterations using the METABRIC cohort ( n = 1980) as well as immunohistochemistry in a large ( n = 670) and annotated series of early-stage (I–III) operable BC. High LIV1 mRNA was associated with ER-positivity, low grade, good Nottingham prognostic index (NPI), older age, and luminal A subtype.…”

Section: Discussionmentioning

confidence: 99%

“…In BC, a preclinical study showed the promoter effect of LIV1 on epithelio–mesenchymal transition [ 19 ]. A few studies are available regarding the assessment of its mRNA and/or protein expression in clinical samples and analysis of correlations with clinicopathological variables [ 20 , 21 , 22 , 23 ]. Overall, they highlight the potential favorable prognostic value of LIV1 expression in early-stage BC, but none of them presented analyses per molecular subtype, nor explored the predictive value for response to chemotherapy or vulnerability/actionability to current or future systemic therapies of BC.…”

Section: Introductionmentioning

confidence: 99%

Prognostic and Predictive Value of LIV1 Expression in Early Breast Cancer and by Molecular Subtype

et al. 2023

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Background: LIV1 is a transmembrane protein that may become a new therapeutic target through the development of antibody–drug conjugates (ADCs). Few studies are available regarding the assessment of LIV1 expression in clinical breast cancer (BC) samples. Methods: We analyzed LIV1 mRNA expression in 8982 primary BC. We searched for correlations between LIV1 expression and clinicopathological data, including disease-free survival (DFS), overall survival (OS), pathological complete response to chemotherapy (pCR), and potential vulnerability and actionability to anti-cancer drugs used or under development in BC. Analyses were performed in the whole population and each molecular subtype separately. Results: LIV1 expression was associated with good-prognosis features and with longer DFS and OS in multivariate analysis. However, patients with high LIV1 expression displayed a lower pCR rate than patients with low expression after anthracycline-based neoadjuvant chemotherapy, including in multivariate analysis adjusted on grade and molecular subtypes. LIV1-high tumors were associated with higher probabilities of sensitivity to hormone therapy and CDK4/6 inhibitors and lower probabilities of sensitivity to immune-checkpoint inhibitors and PARP inhibitors. These observations were different according to the molecular subtypes when analyzed separately. Conclusions: These results may provide novel insights into the clinical development and use of LIV1-targeted ADCs by identifying prognostic and predictive value of LIV1 expression in each molecular subtype and associated vulnerability to other systemic therapies.

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“…SLC39A6 can also be used as an indicator for early diagnosis of esophageal cancer ( 49 ). However, in luminal breast cancer, the Oestrogen-regulated protein SLC39A6 acts as a benign prognostic indicator ( 50 ). One study reported that transmembrane protein 117 (TMEM117) was associated with endoplasmic reticulum stress-mediated mitochondrial-mediated cell death ( 51 ).…”

Section: Discussionmentioning

confidence: 99%

The role of cuproptosis-related gene in the classification and prognosis of melanoma

Liu

et al. 2022

Front. Immunol.

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BackgroundMelanoma, as one of the most aggressive and malignant cancers, ranks first in the lethality rate of skin cancers. Cuproptosis has been shown to paly a role in tumorigenesis, However, the role of cuproptosis in melanoma metastasis are not clear. Studying the correlation beteen the molecular subtypes of cuproptosis-related genes (CRGs) and metastasis of melanoma may provide some guidance for the prognosis of melanoma.MethodsWe collected 1085 melanoma samples in The Cancer Genome Atlas(TCGA) and Gene Expression Omnibus(GEO) databases, constructed CRGs molecular subtypes and gene subtypes according to clinical characteristics, and investigated the role of CRGs in melanoma metastasis. We randomly divide the samples into train set and validation set according to the ratio of 1:1. A prognostic model was constructed using data from the train set and then validated on the validation set. We performed tumor microenvironment analysis and drug sensitivity analyses for high and low risk groups based on the outcome of the prognostic model risk score. Finally, we established a metastatic model of melanoma.ResultsAccording to the expression levels of 12 cuproptosis-related genes, we obtained three subtypes of A1, B1, and C1. Among them, C1 subtype had the best survival outcome. Based on the differentially expressed genes shared by A1, B1, and C1 genotypes, we obtained the results of three gene subtypes of A2, B2, and C2. Among them, the B2 group had the best survival outcome. Then, we constructed a prognostic model consisting of 6 key variable genes, which could more accurately predict the 1-, 3-, and 5-year overall survival rates of melanoma patients. Besides, 98 drugs were screened out. Finally, we explored the role of cuproptosis-related genes in melanoma metastasis and established a metastasis model using seven key genes.ConclusionsIn conclusion, CRGs play a role in the metastasis and prognosis of melanoma, and also provide new insights into the underlying pathogenesis of melanoma.

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Oestrogen-regulated protein SLC39A6: a biomarker of good prognosis in luminal breast cancer

Cited by 7 publications

References 51 publications

Identification of a gene expression signature associated with breast cancer survival and risk that improves clinical genomic platforms

Identification of a gene expression signature associated with breast cancer survival and risk that improves clinical genomic platforms

Prognostic and Predictive Value of LIV1 Expression in Early Breast Cancer and by Molecular Subtype

The role of cuproptosis-related gene in the classification and prognosis of melanoma

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