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All Journal The New Ropanasuri Journal of Surgery Narra J
Septelia I. Wanandi
Department of Biochemistry and Molecular Biology, Faculty of Medicine, Universitas Indonesia, Jakarta
Biochemistry, Genetics & Molecular Biology Health Professions Immunology & microbiology Medicine & Pharmacology Public Health

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Journal : Narra J

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Dual sgRNA-directed knock out survivin gene expression using CRISPR/Cas9 technology for editing survivin gene in triple-negative breast cancer Syahrani, Resda A.; Wanandi, Septelia I.; Arumsari, Sekar; Nihayah, Silviatun; Watanabe, Yukihide; Mizuno, Seiya; Louisa, Melva; Wuyung, Puspita E.
Narra J Vol. 4 No. 3 (2024): December 2024
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narra.v4i3.1177

Abstract

Clustered regularly interspaced short palindromic repeats (CRISPR)-associated nuclease 9 (CRISPR/Cas9) offers a robust approach for genome manipulation, particularly in cancer therapy. Given its high expression in triple-negative breast cancer (TNBC), targeting survivin with CRISPR/Cas9 holds promise as a therapeutic strategy. The aim of this study was to design specific single guide ribonucleic acid (sgRNA) for CRISPR/Cas9 to permanently knock out the survivin gene, exploring its potential as a therapeutic approach in breast cancer while addressing potential off-target effects. Survivin gene knockout was conducted in the TNBC cell line BT549. Intron 1, exon 2, and intron 2 of the survivin gene were selected as sgRNA targets. These sgRNAs were designed in silico and then cloned into a CRISPR/Cas9 expression plasmid. The cleavage activity was assessed using an enhanced green fluorescent protein (EGFP) expression plasmid. The sgRNAs with higher cleavage activity were selected for the establishment of knockout cells. After transfecting the plasmid into the cells, the success of the survivin gene knockout was validated at the deoxyribonucleic acid (DNA) level using polymerase chain reaction (PCR) and sequencing analysis, and at the protein expression level using Western blotting. The study found that sgRNAs survin1A (targeting intron 1), survex2A (targeting intron 2), and survin2A (targeting intron 2) demonstrated higher cleavage activities compared to the other sgRNAs. However, using the single sgRNA, survex2A did not generate mutations in the survivin gene. At the protein level, survivin was still expressed, indicating that a single sgRNA was ineffective in knocking out the survivin gene. In contrast, the combination of sgRNA survin1A and sgRNA survin2A was more effective in generating mutations in the survivin gene, resulting in the deletion of the entire exon 2 and leading to a loss of survivin protein expression. In conclusion, our work provides specific sgRNAs and demonstrates the utilization of dual sgRNAs strategy in the CRISPR/Cas9 technology to knock out the survivin gene, showing potential in breast cancer therapy.
DNA methylation profiles for breast cancer subtype classifications: A translational study from microarray to methylation-specific PCR (MSP) Panigoro, Sonar S.; Paramita, Rafika I.; Wanandi, Septelia I.; Fadilah, Fadilah; Wibisana, I GNG.; Sutandyo, Noorwati
Narra J Vol. 5 No. 1 (2025): April 2025
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narra.v5i1.1364

Abstract

Breast cancer subtypes can be categorized based on their gene expression profiles using immunohistochemistry into Luminal A, Luminal B, human epidermal growth factor receptor 2-positive (HER2+), and triple-negative breast cancer (TNBC) subtypes. However, immunohistochemistry has certain limitations that can lead to misclassification. DNA methylation is an epigenetic modification, and changes in the promoter region can alter gene expression and the quantity of functional protein synthesized, disrupting gene function. The aim of this study was to identify DNA methylation biomarkers for subtype classification in breast cancer using microarray and methylation-specific polymerase chain reaction (MSP) methods. DNA samples were extracted, subjected to bisulfite conversion and then used for both the microarray and MSP methods. This study successfully identified differentially methylated CpGs (DMCs) as biomarker for each subtype classification of breast cancer: Luminal A (hypermethylation of ADAMTSL2 gene; cg14397888), Luminal B (hypomethylation of ADAMTSL2 gene; cg14397888), HER2+ (hypermethylation of PTPRN2 gene; cg25910261), and TNBC (hypomethylation of LCLAT1 gene; cg15652532). The DMC biomarker found for the HER2+ subtype, hypermethylation in the PTPRN2 gene (cg25910261), has the potential to be used by healthcare providers to identify HER2+ patients and provide the HER2-targeted therapy to improve the patient’s survival. In addition, our developed MSP method could produce an effective diagnostic tool for classifying the Luminal A and Luminal B subtypes, with accuracies of 75% and 76%, respectively.
Co-Authors Adang Bachtiar Agnes Kurniawan Andi A. Victor Ani R. Prijanti Asmarinah Asmarinah Bethy S. Hernowo Chatarina Umbul Wahyuni Dewi Muliaty Din Syafruddin Elvira Hinsch Fadilah Fadilah, Fadilah Febriana C. Iswanti Franciscus D. Suyatna Frans Ferdinal H. J. Freisleben Habibah Muhiddin HANS-JOACHIM FREISLEBEN Harahap, Alida R. Herbowo A. Soetomenggolo Ida Gunawan Irawan Yusuf Jörg Gromoll Jeanne A. Pawitan Kartolo, Wiwi A. Melva Louisa Mizuno, Seiya Mohamad Sadikin Muhammad I. Saleh Nihayah, Silviatun Noorwati Sutandyo Novi S. Hardiany Nukman H. Moeloek Nukman Moeloek Nurjati C. Siregar Paramita, Rafika I. Puji B.S. Asih Purnomo Soeharso Puspita E. Wuyung Raafqi Ranasasmita Radiana D. Antarianto Reni Paramita Rianto Setiabudy Rostika Flora Sari, Dewi H. Sarwono Waspadji SEKAR ARUMSARI, SEKAR Siregar, Nurjati Siufui Hendrawan Sonar S. Panigoro Sri S. Ningsih, Sri S. Sri S. Sudardjat Sri W. Dwintasari Sri W.A. Jusman Syahrani, Resda A. Syarifah Dewi Tjahjono D. Gondhowiardjo Vanny Narita Wahyuning Ramelan Watanabe, Yukihide Wawan Mulyawan Wibisana, I GNG. Yefta Moenadjat Yohanna Sorontou Yuni Ahda Yurika Sandra