Background: Breast cancer is one of the most common malignancies, and a threat to female health all over the world. However, the molecular mechanism of breast cancer has not been fully discovered yet.

Objective: It is crucial to identify breast cancer-related genes, which could provide new biomarker for breast cancer diagnosis as well as potential treatment targets.

Methods: Here we used the minimum redundancy-maximum relevance (mRMR) method to select significant genes, then mapped the transcripts of the genes on the Protein-Protein Interaction (PPI) network and traced the shortest path between each pair of two proteins.

Results: As a result, we identified 24 breast cancer-related genes whose betweenness were over 700. The GO enrichment analysis indicated that the transcription and oxygen level are very important in breast cancer. And the pathway analysis indicated that most of these 24 genes are enriched in prostate cancer, endocrine resistance, and pathways in cancer.

Conclusion: We hope these 24 genes might be useful for diagnosis, prognosis and treatment for breast cancer.

背景：乳腺癌是最常见的恶性肿瘤之一，对全世界的女性健康构成威胁。然而，尚未完全发现乳腺癌的分子机制。

目的：鉴定与乳腺癌相关的基因至关重要，它可以为乳腺癌的诊断和潜在的治疗靶标提供新的生物标记。

方法：在这里，我们使用最小冗余-最大相关性（mRMR）方法选择重要的基因，然后在蛋白质-蛋白质相互作用（PPI）网络上绘制基因的转录本，并追踪两个蛋白质之间的最短路径。

结果：结果，我们鉴定了24个之间相关性超过700的乳腺癌相关基因。GO富集分析表明，转录和氧水平在乳腺癌中非常重要。途径分析表明，这24个基因中的大多数都富含前列腺癌，内分泌抗药性和癌症途径。

结论：我们希望这24个基因可能对乳腺癌的诊断，预后和治疗有用。