Cancer Res Treat.  2021 Jan;53(1):9-24. 10.4143/crt.2020.434.

TM4SF4 and LRRK2 Are Potential Therapeutic Targets in Lung and Breast Cancers through Outlier Analysis

• Jung K
• Choi JS
• Koo BM
• Kim YJ
• Song JY
• Sung M
• Chang ES
• Noh KW
• An S
• Lee MS
• Song K
• Lee H
• Kim RN
• Shin YK
• Oh DY
• Choi YL

• KMID: 2510643
• DOI: http://doi.org/10.4143/crt.2020.434

Abstract

Purpose
To find biomarkers for disease, there have been constant attempts to investigate the genes that differ from those in the disease groups. However, the values that lie outside the overall pattern of a distribution, the outliers, are frequently excluded in traditional analytical methods as they are considered to be ‘some sort of problem.’ Such outliers may have a biologic role in the disease group. Thus, this study explored new biomarker using outlier analysis, and verified the suitability of therapeutic potential of two genes (TM4SF4 and LRRK2).
Materials and Methods
Modified Tukey’s fences outlier analysis was carried out to identify new biomarkers using the public gene expression datasets. And we verified the presence of the selected biomarkers in other clinical samples via customized gene expression panels and tissue microarrays. Moreover, a siRNA-based knockdown test was performed to evaluate the impact of the biomarkers on oncogenic phenotypes.
Results
TM4SF4 in lung cancer and LRRK2 in breast cancer were chosen as candidates among the genes derived from the analysis. TM4SF4 and LRRK2 were overexpressed in the small number of samples with lung cancer (4.20%) and breast cancer (2.42%), respectively. Knockdown of TM4SF4 and LRRK2 suppressed the growth of lung and breast cancer cell lines. The LRRK2 overexpressing cell lines were more sensitive to LRRK2-IN-1 than the LRRK2 under-expressing cell lines
Conclusion
Our modified outlier-based analysis method has proved to rescue biomarkers previously missed or unnoticed by traditional analysis showing TM4SF4 and LRRK2 are novel target candidates for lung and breast cancer, respectively.

Keyword

TM4SF4; LRRK2; Molecular targeted therapy

Figure

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  Fig. 1 The scheme of outlier analysis based on a modified Tukey’s Fences method. CCLE, Cancer Cell Line Encyclopedia; TCGA, The Cancer Genome Atlas.

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  Fig. 2 The causative mechanism of the overexpression of the outlier genes. Scatter plots of outlier kinase group-related DNA copy number and DNA methylation status in lung cancer (A, C) and breast cancer (B, D). Red and black circles indicate the outlier and others, respectively. Table shows the number of samples and percentage. These datasets are downloaded from The Cancer Genome Atlas. RSEM, RNA-seq by expectation maximization.

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  Fig. 3 Validation of TM4SF4 as an outlier gene. (A) Representative images for immunohistochemistry of TM4SF4-low (others) and TM4SF4-high (outlier) lung adenocarcinoma. (B–D) TM4SF4 expression is validated using quantitative reverse transcription–polymerase chain reaction, flow cytometry (fluorescence-activated cell sorting), and immunohistochemistry in lung adenocarcinoma cell lines.

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  Fig. 4 TM4SF4 knockdown in lung adenocarcinoma cell lines reduces cell growth. A549 and Calu-3 are treated with lenti-shTM4SF4. (A) Growth curve shows the effect of targeting TM4SF4 in A549 and Calu-3 cells. (B, C) TM4SF4 knockdown is confirmed by quantitative reverse transcription–polymerase chain reaction and fluorescence-activated cell sorting analysis. Values represent mean±standard deviation. *p < 0.05, **p < 0.01, ***p < 0.001.

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  Fig. 5 Validation of LRRK2 as an outlier gene. (A) Representative images for immunohistochemistry of LRRK2 expression. In total, 552 breast cancer samples are investigated. (B, C) LRRK2 expression is validated by quantitative real-time polymerase chain reaction and immunoblotting in breast cancer cell lines. The blots crop from different parts of the same gel. The values below the gels represent the LRRK2 protein signal intensities after normalization to glyceraldehyde 3-phosphate dehydrogenase (GAPDH) protein signal intensities.

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  Fig. 6 Inhibition of LRRK2 in LRRK2-overexpressing breast cancer cell lines reduces cell viability. (A) Suppression of LRRK2 expression leads to reduced cell growth in MDA-MB 231 and ZR-75-1 cells. (B, C) The efficiency of LRRK2 knockdown is evaluated by quantitative reverse transcription–polymerase chain reaction and western blotting. (D) Data quantification of panel (C). (E) Breast cancer cell lines overexpressing LRRK2 respond to LRRK2-IN-1 dose-dependently. (F) Immunoblot of LRRK2-IN-1-treated MDA-MB-231 and ZR-75-1 cells. The blots of individual cell lines crop from different part of the same gel, respectively. The ZR-75-1 cell lines data of LRRK2-IN-1 were captured by an ImageQuant LAS 4000 biomolecular imager. (G) Data quantification of panel (F). GAPDH, glyceraldehyde 3-phosphate dehydrogenase; NC, negative control siRNA. Values are presented as mean±standard deviation. *p < 0.05, **p < 0.01, ***p < 0.001.

Reference

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