AbstractThere are hundreds of genes typically overexpressed in breast cancer cells and it's often assumed that their overexpression contributes to cancer progression. However, the precise proportion of these overexpressed genes contributing to tumorigenicity remains unclear. To address this gap, we undertook a comprehensive screening of a diverse set of seventy-two genes overexpressed in breast cancer.

摘要乳腺癌细胞中通常有数百种基因过表达，人们通常认为它们的过表达有助于癌症的进展。然而，这些过度表达的基因对致瘤性的确切比例仍不清楚。为了解决这个差距，我们对乳腺癌中过表达的72个基因进行了全面筛选。

This systematic screening evaluated their potential for inducing malignant transformation and, concurrently, assessed their impact on breast cancer cell proliferation and viability. Select genes including ALDH3B1, CEACAM5, IL8, PYGO2, and WWTR1, exhibited pronounced activity in promoting tumor formation and establishing gene dependencies critical for tumorigenicity.

该系统筛选评估了它们诱导恶性转化的潜力，同时评估了它们对乳腺癌细胞增殖和活力的影响。包括ALDH3B1，CEACAM5，IL8，PYGO2和WWTR1在内的选择基因在促进肿瘤形成和建立对致瘤性至关重要的基因依赖性方面表现出明显的活性。

Subsequent investigations revealed that CEACAM5 overexpression triggered the activation of signaling pathways involving β-catenin, Cdk4, and mTOR. Additionally, it conferred a growth advantage independent of exogenous insulin in defined medium and facilitated spheroid expansion by inducing multiple layers of epithelial cells while preserving a hollow lumen.

随后的研究表明，CEACAM5过表达触发了涉及β-连环蛋白，Cdk4和mTOR的信号通路的激活。此外，它在确定的培养基中赋予了独立于外源胰岛素的生长优势，并通过诱导多层上皮细胞同时保留中空腔来促进球体扩张。

Furthermore, the silencing of CEACAM5 expression synergized with tamoxifen-induced growth inhibition in breast cancer cells. These findings underscore the potential of screening overexpressed genes for both oncogenic drivers and tumor dependencies to expand the repertoire of therapeutic targets for breast cancer treatment..

此外，CEACAM5表达的沉默与他莫昔芬诱导的乳腺癌细胞生长抑制协同作用。这些发现强调了筛选致癌驱动因素和肿瘤依赖性过表达基因的潜力，以扩大乳腺癌治疗靶点的范围。。

IntroductionGenome-wide estimates of the number of genes overexpressed in specific cancer types range in the low hundreds to high hundreds1,2. Depending upon their expression pattern in cancers, these genes can be useful biomarkers for detection, prognosis, or prediction of treatment response. However, determining whether they promote tumorigenicity or evaluating their utility as potential therapeutic targets requires functional analysis.

引言在特定癌症类型中过表达的基因数量的全基因组估计范围从低几百到高一百1,2。根据它们在癌症中的表达模式，这些基因可能是检测，预后或预测治疗反应的有用生物标志物。然而，确定它们是否促进致瘤性或评估其作为潜在治疗靶标的效用需要功能分析。

Overexpressed genes may be growth-inhibitory, particularly if their overexpression results from a dysregulated negative feedback loop. For example, the HPV oncoprotein E7 binds and induces proteolytic degradation of the Rb protein, which relieves the tumor suppressor gene p16Ink4a from negative feedback control, leading to its upregulation3,4.

过表达的基因可能具有生长抑制作用，特别是如果它们的过表达是由失调的负反馈环引起的。例如，HPV癌蛋白E7结合并诱导Rb蛋白的蛋白水解降解，从而减轻肿瘤抑制基因p16Ink4a的负反馈控制，导致其上调3,4。

Likewise, BRAF-V600E mutant melanomas and KRAS-mutant lung adenocarcinomas both overexpress several inhibitors of the mitogen-activated kinase pathway5,6. In these cases, the primary genetic alteration blocks the negative feedback exerted by the overexpressed inhibitory genes.Single-gene, small-scale functional analysis of overexpressed genes has led to the generation of hundreds of proposed tumor-promoting genes7.

同样，BRAF-V600E突变型黑色素瘤和KRAS突变型肺腺癌都过表达丝裂原活化激酶途径的几种抑制剂5,6。在这些情况下，主要的遗传改变会阻止过表达的抑制基因产生的负反馈。对过表达基因的单基因小规模功能分析导致了数百个拟议的肿瘤促进基因的产生7。

At present, it is difficult to evaluate many of these studies since they often use unique experimental conditions to determine oncogenicity. More systematic approaches that survey the induced oncogenic phenotypes of multiple candidate genes have the advantage of providing several internal comparisons.

目前，很难评估许多这些研究，因为它们经常使用独特的实验条件来确定致癌性。调查多个候选基因的诱导致癌表型的更系统的方法具有提供几个内部比较的优势。

Using cDNA-based or open-reading-frame (ORF) overexpression, systematic screening has identified oncogenic roles for PVRL4 in breast cancer and proliferation of T-cells by LTBR8,9. In addition to these systematic screens for genes capable of promoting the tumorigenicity or proliferation, .

使用基于cDNA或开放阅读框（ORF）的过表达，系统筛选已经确定了PVRL4在乳腺癌中的致癌作用以及LTBR8,9对T细胞的增殖。除了这些能够促进致瘤性或增殖的基因的系统筛选之外。

Data availability

数据可用性

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

本研究中使用和/或分析的数据集可根据合理要求从通讯作者处获得。

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Download referencesAcknowledgementsThe authors thank members of the Powers and Hemann labs for discussions. The authors also thank the staff in the Biostatistics & Data Science Shared Resources of the Stony Brook Cancer Center.FundingThis research was supported by the NIH under Award Numbers R01CA217206 and U01CA168409, a Peter Rowley Breast Cancer Research Award from the New York State Department of Health, the Stony Brook Cancer Center, the Babylon Breast Cancer Coalition, the Carol M.

下载参考文献致谢作者感谢Powers和Hemann实验室的成员进行讨论。作者还感谢石溪癌症中心生物统计学和数据科学共享资源的工作人员。资助这项研究得到了美国国立卫生研究院的支持，奖项编号为R01CA217206和U01CA168409，这是纽约州卫生部、石溪癌症中心、巴比伦乳腺癌联盟、卡罗尔·M·彼得·罗利乳腺癌研究奖。

Baldwin Breast Cancer Research Fund, and the Walk-for-Beauty Foundation Award. The Functional Proteomics RPPA Core facility is supported by MD Anderson Cancer Center Support Grant # 5 P30 CA016672-40. All studies utilizing mice were approved by and in accordance with Stony Brook University Institutional Animal Care and Use Committee and in accordance with ARRIVE guidelines (https://arriveguidelines.org).

鲍德温乳腺癌研究基金会和步行美容基金会奖。功能蛋白质组学RPPA核心设施由MD安德森癌症中心支持拨款#5 P30 CA016672-40支持。所有利用小鼠的研究都得到了石溪大学机构动物护理和使用委员会的批准，并符合ARRIVE指南(https://arriveguidelines.org)。

We acknowledge the Stony Brook Cancer Center Biostatistics & Bioinformatics Shared Resource for expert assistance with bioinformatic analysis. All data and generated materials (plasmids) are available upon request.Author informationAuthor notesKenneth L. Scott is deceased.Authors and AffiliationsDepartment of Pathology, Stony Brook Cancer Center, Stony Brook, NY, 11794, USAAdaobi Mofunanya, Frank Celeste, Xiaoyu Zhao, Jinyu Li & Scott PowersKoch Institute for Integrative Cancer Research and Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, 02139, USAEleanor R.

我们感谢石溪癌症中心生物统计学和生物信息学共享资源，为生物信息学分析提供专家帮助。可根据要求提供所有数据和生成的材料（质粒）。作者信息作者notesKenneth L.Scott去世。作者和附属机构纽约州石溪市石溪癌症中心病理学系，11794，USAAdaobi MOFUNAYA，Frank Celeste，赵晓宇，李金宇和斯科特·PowersKoch综合癌症研究所和麻省理工学院生物学系，剑桥，马萨诸塞州，02139，USAELENOR R。

Cameron, Christian J. Braun & Michael T. HemannGraduate Program in Genetics, Stony Brook University, Stony Brook, NY, 11794, USAFrank Celeste & Scott PowersGraduate Program in Molecular and Cellular Biology, Stony Brook University, Stony Brook, NY, 11794, USAXiaoyu Zhao & Scott PowersDepa.

Cameron，Christian J.Braun和Michael T.Hemann遗传学研究生课程，纽约州石溪大学，11794年，USAFrank Celeste和Scott PowersGraduate分子和细胞生物学研究生课程，纽约州石溪大学，11794年，USAXiaoyu Zhao和Scott PowersDepa。

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PubMed Google ScholarContributionsA.M. performed the majority of experiments and analyzed data. E.C., C.B., and M.H. designed and constructed the shRNA library. F.C. and X.Z. performed experiments. J.L. analyzed data. S.P. conceived of the study, performed experiments, analyzed data, and wrote the manuscript.

PubMed谷歌学术贡献。M、 进行了大部分实验并分析了数据。E、 C.，C.B。和M.H.设计并构建了shRNA文库。F、 C.和X.Z.进行了实验。J、 L.分析数据。S、 P.构思了这项研究，进行了实验，分析了数据并撰写了手稿。

All authors reviewed the manuscript. All authors have consented to publication.Corresponding authorCorrespondence to.

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Reprints and permissionsAbout this articleCite this articleMofunanya, A., Cameron, E.R., Braun, C.J. et al. Simultaneous screening of overexpressed genes in breast cancer for oncogenic drivers and tumor dependencies.

转载和许可本文引用本文Mofunanya，A.，Cameron，E.R.，Braun，C.J。等人同时筛选乳腺癌中过表达基因的致癌驱动因素和肿瘤依赖性。

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