Identifikasi Gen Kandidat yang Menghubungkan Stres Retikulum Endoplasma dan Ferroptosis akibat Induksi Lipopolisakarida pada Kanker Payudara: Pendekatan Bioinformatika

Aulia Wahyuni Ramadanti, Dr. apt. Soni Siswanto, M.Biomed.; apt. Sisca Ucche, M.Pharm.Sc., Ph.D.

2026 | Skripsi | FARMASI

Pendahuluan: Kanker payudara merupakan salah satu penyebab utama morbiditas dan mortalitas pada perempuan di seluruh dunia. Meskipun berbagai mekanisme molekuler yang mendasari perkembangan kanker payudara telah banyak dikaji, hubungan antara respons inflamasi akibat induksi lipopolisakarida (LPS), stres retikulum endoplasma (stres RE), dan ferroptosis dalam konteks kanker payudara, serta kaitannya dengan prognosis pasien, masih belum sepenuhnya dipahami. Oleh karena itu, penelitian ini bertujuan untuk mengidentifikasi gen-gen kunci yang terlibat pada ketiga kondisi tersebut dan mengevaluasi hubungannya dengan keberlangsungan hidup pasien kanker payudara melalui pendekatan bioinformatika.

Metode: Penelitian ini dilakukan secara in silico dengan menganalisis data ekspresi gen dari basis data publik menggunakan perangkat lunak R dengan koreksi false discovery rate (FDR). Gen yang menunjukkan perubahan ekspresi konsisten pada kondisi induksi lipopolisakarida, tunicamycin, dan erastin diidentifikasi sebagai differentially expressed genes (DEGs). Selanjutnya, evaluasi prognostik terhadap gen-gen tersebut dilakukan menggunakan platform cBioPortal dan GEPIA.

Hasil: Hasil analisis menunjukkan enam gen dengan perubahan ekspresi yang konsisten pada ketiga kondisi induksi, terdiri atas lima gen yang mengalami peningkatan ekspresi (XBP1, BIRC2, ARHGEF2, GADD45B, dan CLIC4) serta satu gen yang mengalami penurunan ekspresi (S100A4). Gen-gen tersebut menunjukkan adanya potensi keterkaitan molekuler antara respons inflamasi, stres RE, dan kondisi pro-ferroptotik. XBP1 dan S100A4 diketahui berkaitan dengan regulasi homeostasis redoks dan jalur terkait ferroptosis, sedangkan gen lainnya diduga berkontribusi dalam modulasi respons stres seluler. Analisis prognosis klinis berbasis dataset METABRIC dan GEPIA menunjukkan tidak adanya hubungan yang signifikan terhadap parameter overall survival (OS) maupun relapse-free survival (RFS) (p > 0,05). Meskipun demikian, beberapa gen seperti XBP1 dan ARHGEF2 menunjukkan nilai hazard ratio (HR) < 1>

Kesimpulan: Secara keseluruhan, hasil penelitian ini menunjukkan adanya kemungkinan hubungan molekuler antara respons inflamasi, stres RE, dan ferroptosis dalam konteks kanker payudara. Meskipun hubungan terhadap prognosis klinis belum menunjukkan perbedaan yang signifikan, temuan ini memberikan gambaran molekuler awal mengenai jaringan regulasi yang mendasari perkembangan kanker payudara dan berpotensi menjadi dasar untuk penelitian lanjutan berbasis validasi eksperimental.

Introduction: Breast cancer remains one of the leading causes of morbidity and mortality among women worldwide. Although various molecular mechanisms underlying breast cancer progression have been extensively studied, the relationship between lipopolysaccharide (LPS)-induced inflammatory responses, endoplasmic reticulum (ER) stress, and ferroptosis in the context of breast cancer, as well as their potential contribution to patient prognosis, remains unclear. Therefore, this study aimed to identify key genes involved in these three conditions and evaluate their association with the survival outcomes of breast cancer patients using a bioinformatic approach.

Methods: This in silico study analyzed gene expression datasets obtained from public databases using R software with false discovery rate (FDR) correction. Genes showing consistent change of expression patterns following LPS, tunicamycin, and erastin induction were identified as differentially expressed genes (DEGs). Prognostic evaluations of the identified genes were subsequently performed using the cBioPortal and GEPIA platforms.

Results: Six genes showed consistent expression changes across the three induction conditions, consisting of five upregulated genes (XBP1, BIRC2, ARHGEF2, GADD45B, and CLIC4) and one downregulated gene (S100A4). These genes may reflect potential molecular associations among inflammatory responses, ER stress, and pro-ferroptotic conditions. XBP1 and S100A4 were associated with redox homeostasis regulation and ferroptosis-related pathways, while the remaining genes may contribute to cellular stress response modulation. Prognostic analyses using the METABRIC and GEPIA datasets showed no significant association with overall survival (OS) or relapse-free survival (RFS) (p > 0.05). However, several genes, including XBP1 and ARHGEF2, demonstrated hazard ratio (HR) values below 1, suggesting a possible association with more favorable prognosis. These findings remain noteworthy considering the limitations of bioinformatic analyses, including database dependency and variability among patient datasets due to differences in treatment exposure.

Conclusion: The present findings suggest a potential molecular relationship among inflammatory responses, ER stress, and ferroptosis in breast cancer. Although no statistically significant association with prognostic outcomes was observed, this study provides preliminary molecular insights into the regulatory networks underlying breast cancer progression and may serve as a basis for future experimental validation.

Kata Kunci : Kanker Payudara, Kematian Sel, Bioinformatika, MCF-7