FAM91A1 is a potential prognostic factor in breast cancer

doi:10.3877/cma.j.issn.1674-0807.2024.05.004

Abstract

Abstract:

Objective

To investigate the potential of FAM91A1 as an independent prognostic factor in breast cancer and explore the mechanism.

Methods

The expression of FAM91A1 in various breast cancer subtypes were obtained from the “TCGA” module of the UALCAN database， and the expression profiles and clinical data of 1101 breast cancer patients were downloaded from the TCGA database. The patients were divided into low expression group （n＝550） and high expression group （n＝551） according to the median value of FAM91A1 expression （37.653）. Using R 4.4.1 software， survival analysis was conducted to compare the OS between breast cancer patients with high and low FAM91A1 expression， and Cox regression analysis was used to find the influencing factors of OS in breast cancer patients. The correlation between FAM91A1 and immune checkpoints was analyzed， and Spearman method was used to analyze the correlation between FAM91A1 and tumor mutation burden. The STRING website and GEPIA2 database were used to construct FAM91A1-related gene dataset. The GO and KEGG enrichment analysis were used to find the FAM91A1 function and related pathways. FAM91A1-related ceRNA network was constructed using the MiRTarbase database and validated with the StarBase database.

Results

There was a statistically significant difference in FAM91A1 mRNA expression between normal control， luminal， HER-2-positive， and triple negative breast cancer patients in the TCGA database （P ＜0.001）.The results of the survival analysis indicated no significant difference in OS between FAM91A1 high expression group and low expression group （HR ＝1.36，95%CI：0.91-2.05，P ＝0.133）. Cox regression analysis revealed that age （HR ＝1.453，95%CI：1.128-1.875，P ＝0.004）， clinical grade （HR ＝1.773， 95%CI：1.125-2.794， P ＝0.014）， M stage （HR ＝2.155， 95% CI：1.365-3.403， P＜0.001）， and FAM91A1 expression （HR ＝1.297， 95%CI：1.031-1.631， P ＝0.026）were independent factor affecting OS in1101 breast cancer patients. The expression of immune checkpoints （LGLEC15， LAG3， PDCD1， HAVCR2，CD274， PDCD1LG2） was significantly different between FAM91A1 expression group and low expression group（all P ＜0.001）. The expression of FAM91A1 was positively correlated with tumor mutation burden （P ＜0.001）. The Gene Ontology （GO） functional enrichment analysis revealed that gene datasets related to FAM91A1 were predominantly enriched in the following metabolic processes （small molecule and lipid metabolism）， cellular components （external encapsulated structures， cellular unit cell edges） and molecular functions （enzyme activator activity， GTPase activator activity， and metallopeptidase activity）. In the KEGG pathway enrichment analysis， the genes related to FAM91A1 were predominantly enriched in the ABC transporter protein pathway，fatty acid metabolism pathway，etc. By the online database，one miRNA （hsa-mir-15a-5p） and seven lncRNAs （LINC01128， ERI3-IT1， FGD5-AS1， LINC02035， TUG1， XIST， ARMCX5-GPRASP2） were identified within the FAM91A1-associated ceRNA network.

Conclusions

FAM91A1 may serve as an independent prognostic factor in breast cancer， exhibiting a strong correlation with immune infiltration， ABC transporter protein pathway and fatty acid metabolism.

Key words: Breast neoplasms, Bioinformatics, Prognosis, FAM91A1

Rui Wang, Jun Deng, Tingxin Shi, Zhizhao Zhang, Chengfang Wang, Yi Zhang, Xiaowei Qi. FAM91A1 is a potential prognostic factor in breast cancer[J]. Chinese Journal of Breast Disease(Electronic Edition), 2024, 18(05): 274-280.

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URL: https://zhrxbzz.cma-cmc.com.cn/EN/10.3877/cma.j.issn.1674-0807.2024.05.004

https://zhrxbzz.cma-cmc.com.cn/EN/Y2024/V18/I05/274

Figures/Tables 8

References 22

［1］	Bray F，Laversanne M， Sung H， et al. Global cancer statistics 2022：GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries［J］. CA Cancer J Clin， 2024， 74（3）：229-263.
［2］	Lei S， Zheng R， Zhang S， et al. Global patterns of breast cancer incidence and mortality： a population-based cancer registry data analysis from 2000 to 2020［J］. Cancer Commun （Lond）， 2021，41（11）： 1183-1194.
［3］	Jeyabalan J， Aqil F， Munagala R， et al. Chemopreventive and therapeutic activity of dietary blueberry against estrogen-mediated breast cancer［J］. J Agric Food Chem， 2014， 62（18）： 3963-3971.
［4］	Wang J， Xu B， Yuan P， et al. HER2 as a predictive factor for successful neoadjuvant anthracycline chemotherapy of locally advanced and early breast cancer［J］. Int J Biol Markers，2014，29（3）：e187-192.
［5］	Pathmanathan N， Balleine RL. Ki67 and proliferation in breast cancer［J］. J Clin Pathol， 2013， 66（6）： 512-516.
［6］	Nass N， Walter S， Jechorek D， et al. High neuronatin （NNAT）expression is associated with poor outcome in breast cancer ［J］.Virchows Arch， 2017， 471（1）： 23-30.
［7］	Ryu S， McDonnell K， Choi H， et al. Suppression of miRNA-708 by polycomb group promotes metastases by calcium-induced cell migration［J］. Cancer Celll， 2013， 23（1）： 63-76.
［8］	Spiering D， Hodgson L. Dynamics of the Rho-family small GTPases in actin regulation and motility［J］.Cell Adh Migr，2011，5（2）：170-180.
［9］	Lv X， Wang Y，Song Y，et al. Association between ALDH1＋/CD133＋stem-like cells and tumor angiogenesis in invasive ductal breast carcinoma［J］. Oncol Lett， 2016， 11（3）： 1750-1756.
［10］	Fromme JC， Munson M. Capturing endosomal vesicles at the Golgi［J］.Nat Cell Biol， 2017， 19（12）： 1384-1386.
［11］	Barr FA，Short B.Golgins in the structure and dynamics of the Golgi apparatus［J］.Curr Opin Cell Biol，2003，15（4）：405-413.
［12］	Miao J， Yang Z，Guo W，et al. Integrative analysis of the proteome and transcriptome in gastric cancer identified LRP1B as a potential biomarker［J］. Biomark Med， 2022， 16（15）： 1101-1111.
［13］	Abuobeid R， Sánchez-Marco J， Felices MJ， et al. Squalene through its post-squalene metabolites is a modulator of hepatic transcriptome in rabbits［J］. Int J Mol Sci， 2022， 23（8）： 4172.
［14］	Chandrashekar DS， Bashel B， Balasubramanya SAH， et al. UALCAN：a portal for facilitating tumor subgroup gene expression and survival analyses［J］. Neoplasia， 2017， 19（8）： 649-658.
［15］	Chandrashekar DS， Karthikeyan SK， Korla PK， et al. UALCAN： An update to the integrated cancer data analysis platform［J］.Neoplasia，2022， 25： 18-27.
［16］	Russell B， Melanie AK， Esko AK， et al. Landscape of microsatellite instability across 39 cancer types［J］. JCO Precis Oncol， 2017， 2017：PO.17.00073.
［17］	Kim B， Bae H， Lee H， et al. Proton beams inhibit proliferation of breast cancer cells by altering DNA methylation Status［J］. J Cancer，2016， 7（3）： 344-352.
［18］	Lord EM， Penney DP， Sutherland RM， et al. Morphological and functional characteristics of cells infiltrating and destroying tumor multicellular spheroids in vivo［J］. Virchows Arch B Cell Pathol Incl Mol Pathol， 1979， 31（2）： 103-116.
［19］	Bu X， Yao Y， Li X. Immune checkpoint blockade in breast cancer therapy［J］. Adv Exp Med Biol， 2017， 1026： 383-402.
［20］	Wang X， Teng F， Kong L， et al. PD-L1 expression in human cancers and its association with clinical outcomes［J］. Onco Targets Ther，2016， 9： 5023-5039.
［21］	Lynch D， Murphy A. The emerging role of immunotherapy in colorectal cancer［J］.Ann Transl Med，2016，4（16）：305.
［22］	Salmena L， Poliseno L，Tay Y，et al. A ceRNA hypothesis：the rosetta stone of a hidden RNA language？［J］. Cell，2011，146（3）：353-358.

临床因素	单因素分析			多因素分析
临床因素	HR	95％置信区间	P值	HR	95％置信区间	P值
年龄（＞60岁比≤60岁）	1.493	1.166～1.911	0.001	1.453	1.128～1.873	0.004
临床分级（Ⅲ-Ⅳ比Ⅰ-Ⅱ）	1.966	1.534～2.521	＜0.001	1.773	1.125～2.794	0.014
T分期（T_3-4比T_1-2）	1.529	1.159～2.018	0.003	0.956	0.665～1.374	0.808
N分期（N_2-3比N_0-1）	1.841	1.389～2.439	＜0.001	1.048	0.693～1.584	0.824
M分期（M₁比M₀）	3.741	2.488～5.624	＜0.001	2.155	1.365～3.403	＜0.001
FAM91A1（高表达比低表达）	1.361	1.067～1.736	0.013	1.297	1.031～1.631	0.026

临床因素	单因素分析			多因素分析
临床因素	HR	95％置信区间	P值	HR	95％置信区间	P值
年龄（＞60岁比≤60岁）	1.493	1.166～1.911	0.001	1.453	1.128～1.873	0.004
临床分级（Ⅲ-Ⅳ比Ⅰ-Ⅱ）	1.966	1.534～2.521	＜0.001	1.773	1.125～2.794	0.014
T分期（T_3-4比T_1-2）	1.529	1.159～2.018	0.003	0.956	0.665～1.374	0.808
N分期（N_2-3比N_0-1）	1.841	1.389～2.439	＜0.001	1.048	0.693～1.584	0.824
M分期（M₁比M₀）	3.741	2.488～5.624	＜0.001	2.155	1.365～3.403	＜0.001
FAM91A1（高表达比低表达）	1.361	1.067～1.736	0.013	1.297	1.031～1.631	0.026

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