Gene expression profiling of breast cancer in Lebanese women

Makoukji, Joelle; Makhoul, Nadine J.; Khalil, Maya; El-Sitt, Sally; Aldin, Ehab Saad; Jabbour, Mark N.; Boulos, Fouad; Gadaleta, Emanuela; Sangaralingam, Ajanthah; Chelala, Claude; Boustany, Rose Mary; Tfayli, Arafat

doi:10.1038/srep36639

Cited by 39 publications

(32 citation statements)

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“…COL10A1 protein levels in plasma might be a potential diagnostic predictor for early breast cancer [9]. Although COL10A1 was reported to be highly expressed in tumors by high throughput sequencing, the specific role of COL10A1 in breast cancer was unknown [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Bioinformatics analysis of prognostic significance of COL10A1 in breast cancer

et al. 2020

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Correspondence: Kejin Wu (kejinwu@163.com) Background: Collagen type X alpha 1 (COL10A1) is overexpressed in diverse tumors and displays vital roles in tumorigenesis. However, the prognostic value of COL10A1 in breast cancer remains unclear. Methods: The expression of COL10A1 was analyzed by the Oncomine database and UAL-CAN cancer database. The relationship between COL10A1 expression level and clinical indicators including prognostic data in breast cancer were analyzed by the Kaplan-Meier Plotter, PrognoScan, and Breast Cancer Gene-Expression Miner (bc-GenExMiner) databases. Results: COL10A1 was up-regulated in different subtypes of breast cancer. Estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER-2) status and nodal status were positively correlated with COL10A1 expression. Conversely, age, the Scarff-Bloom-Richardson (SBR) grade, basal-like status, and triple-negative status were negatively related to COL10A1 level in breast cancer samples compared with normal tissues. Patients with increased COL10A1 expression level showed worse overall survival (OS), relapse-free survival (RFS), distant metastasis-free survival (DMFS) and disease-free survival (DFS). COL10A1 was positively correlated with metastatic relapse-free survival. GSEA analysis revealed that enrichment of TGF-β signaling pathway. 15-leucine-rich repeat containing membrane protein (LRRC15) is a correlated gene of COL10A1. Conclusion: Bioinformatics analysis revealed that COL10A1 might be considered as a predictive biomarker for prognosis of breast cancer. Further experiments and clinical trials are essential to elucidate the value of COL10A1 in breast cancer treatment.

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Section: Introductionmentioning

confidence: 99%

Bioinformatics analysis of prognostic significance of COL10A1 in breast cancer

et al. 2020

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“…The disruption on (or resistance to) the action of leptin is a hallmark of obesity, which in turn is a strong risk factor for several diseases including diabetes, cardiovascular disease, and certain types of cancers [ 29 ]. Recently, two independent studies reported that LEP was among the most down-regulated genes in breast cancers of Lebanese [ 30 ] and Saudi Arabian cohorts [ 31 ].…”

Section: Resultsmentioning

confidence: 99%

An integrated meta-analysis approach to identifying medications with potential to alter breast cancer risk through connectivity mapping

et al. 2017

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BackgroundGene expression connectivity mapping has gained much popularity in recent years with a number of successful applications in biomedical research testifying its utility and promise. A major application of connectivity mapping is the identification of small molecule compounds capable of inhibiting a disease state. In this study, we are additionally interested in small molecule compounds that may enhance a disease state or increase the risk of developing that disease. Using breast cancer as a case study, we aim to develop and test a methodology for identifying commonly prescribed drugs that may have a suppressing or inducing effect on the target disease (breast cancer).ResultsWe obtained from public data repositories a collection of breast cancer gene expression datasets with over 7000 patients. An integrated meta-analysis approach to gene expression connectivity mapping was developed, which involved unified processing and normalization of raw gene expression data, systematic removal of batch effects, and multiple runs of balanced sampling for differential expression analysis. Differentially expressed genes stringently selected were used to construct multiple non-joint gene signatures representing the same biological state. Remarkably these non-joint gene signatures retrieved from connectivity mapping separate lists of candidate drugs with significant overlaps, providing high confidence in their predicted effects on breast cancers. Of particular note, among the top 26 compounds identified as inversely connected to the breast cancer gene signatures, 14 of them are known anti-cancer drugs.ConclusionsA few candidate drugs with potential to enhance breast cancer or increase the risk of the disease were also identified; further investigation on a large population is required to firmly establish their effects on breast cancer risks. This work thus provides a novel approach and an applicable example for identifying medications with potential to alter cancer risks through gene expression connectivity mapping.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1989-x) contains supplementary material, which is available to authorized users.

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“…However, it is largely unknown how collagen type VI α4, α5 and α6 are implicated in tumor development. COL6A6 has been reported to be down-regulated in breast cancer [27][28][29] . Significant down-regulation of COL6A5 has been proved in esophageal squamous cell carcinoma 30 and fibrous epulis 31 .…”

Section: Discussionmentioning

confidence: 99%

Collagen type VI α5 gene variations may predict the risk of lung cancer development in Chinese Han population

Duan

Liu

Sun

et al. 2020

Sci Rep

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the abundant expression of collagen type VI α5 (COL6A5) exists in lung tissue, and its role in lung cancer is still unknown. We performed a genetic association study with an attempt to detect the relationships between single nucleotide polymorphisms (Snps) in COL6A5 and lung cancer predisposition in chinese Han population. We finally selected six tag-SNPs to determine their genotypes among 510 lung cancer patients and 495 healthy controls with the MassARRAY platform. The associations of SNPs and lung cancer risk were estimated by logistic regression method with adjustment for confounding factors. two available databases were used for gene expression and prognosis analysis. COL6A5 rs13062453, rs1497305, and rs77123808 were significantly associated with the risk of lung cancer in the whole population or stratified subgroups (p < 0.05). Among them, COL6A5 rs13062453 and rs1497305 were also linked to the susceptibility of lung adenocarcinoma. Additionally, rs1497305 was found to be strongly related to the TNM staging under five genetic models (p < 0.05). Results from databases suggested the important role of COL6A5 in lung cancer development. COL6A5 polymorphisms rs13062453, rs1497305 and rs77123808 were associated with lung cancer risk in Chinese Han population. These findings first yield new insight of COL6A5 in lung cancer.The incidence and mortality rates of lung cancer rank first worldwide, with 2,093,876 (11.6% of total cancer patients) new cases and 1,761,007 (18.4% of total cancer deaths) deaths occurred globally in 2018 1 . Considering the sex-distribution difference, lung cancer is the leading cause of cancer incidence (1,368,524 new cases) and death (1,184,947 deaths) among males, accounting for approximately 14.4% new cases and 22.0% deaths respectively, and the third prevalent cancer (725,352 new cases, 8.4%) with second fatality rate (576,060 deaths, 13.8%) among females 1 . The morbidity and mortality of lung cancer is very high in China, even worse, continue rising in recent years 2 . Previous epidemiological studies have reported a dramatical increase of crude incidence of lung cancer among Chinese from 2000 to 2014, which reached 57.13 per 100,000 in 2014 (74.31 per 100,000 in males and 39.08 per 100,000 in females) 2,3 . In the same year, the estimated mortality rate of lung cancer deaths is 45.80 per 100,000 (61.10 per 100,000 in males and 29.71 per 100,000 in females) 3 . Multiple etiological analyses have found that external risk factors such as smoking, air pollution and occupational exposure contribute to the lung tumorigenesis 4-6 . Moreover, researchers have emphasized that genetic factors play critical roles in the development of lung cancer as well. Nowadays, accumulating evidence has elucidated that genetic polymorphisms are risk markers that can mediate individual susceptibility to lung cancer 7-11 . These findings also provide multiple promising indicators that pave the road for individual cancer risk assessment. Therefore, exploring these novel factors is a vital step which not only re...

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Gene expression profiling of breast cancer in Lebanese women

Cited by 39 publications

References 60 publications

Bioinformatics analysis of prognostic significance of COL10A1 in breast cancer

Bioinformatics analysis of prognostic significance of COL10A1 in breast cancer

An integrated meta-analysis approach to identifying medications with potential to alter breast cancer risk through connectivity mapping

Collagen type VI α5 gene variations may predict the risk of lung cancer development in Chinese Han population

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