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ONCOLOGY RESEARCH · 2024 · IF 2

Development of a cell adhesion-based prognostic model for multiple myeloma: Insights into chemotherapy response and potential reversal of adhesion effects

QIAN HU,MENGYAO WANG,JINJIN WANG,YALI TAO,TING NIU

Multiple myeloma (MM) is a hematologic malignancy notorious for its high relapse rate and development of drug resistance, in which cell adhesion-mediated drug resistance plays a critical role. This study integrated four RNA sequencing datasets (CoMMpass, {"type":"entrez-geo","attrs":{"text":"GSE136337","term_id":"136337"}} GSE136337 , {"type":"entrez-geo","attrs":{"text":"GSE9782","term_id":"9782"}} GSE9782 , and {"type":"entrez-geo","attrs":{"text":"GSE2658","term_id":"2658"}} GSE2658 ) and focused on analyzing 1706 adhesion-related genes. Rigorous univariate Cox regression analysis identified 18 key prognosis-related genes, including KIF14, TROAP, FLNA, MSN, LGALS1, PECAM1, and ALCAM, which demonstrated the strongest associations with poor overall survival (OS) in MM patients. To comprehensively evaluate the impact of cell adhesion on MM prognosis, an adhesion-related risk score (ARRS) model was constructed using Lasso Cox regression analysis. The ARRS model emerged as an independent prognostic factor for predicting OS. Furthermore, our findings revealed that a heightened cell adhesion effect correlated with tumor resistance to DNA-damaging drugs, protein kinase inhibitors, and drugs targeting the PI3K/Akt/mTOR signaling pathway. Nevertheless, we identified promising drug candidates, such as tirofiban, pirenzepine, erlotinib, and bosutinib, which exhibit potential in reversing this resistance. In vitro , experiments employing NCIH929, RPMI8226, and AMO1 cell lines confirmed that MM cell lines with high ARRS exhibited poor sensitivity to the aforementioned candidate drugs. By employing siRNA-mediated knockdown of the key ARRS model gene KIF14, we observed suppressed proliferation of NCIH929 cells, along with decreased adhesion to BMSCs and fibronectin. This study presents compelling evidence establishing cell adhesion as a significant prognostic factor in MM. Additionally, potential molecular mechanisms underlying adhesion-related resistance are proposed, along with viable strategies to overcome such resistance. These findings provide a solid scientific foundation for facilitating clinically stratified treatment of MM.

研究领域: 肿瘤学 · 血液学 · 分子生物学 · 药理学
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Scientific Reports · 2025 ·Vol. 15 ·期 1 ·1-18 · IF 3.9

The molecular subtype based on cell cycle-related gene signature predicts the prognosis and chemotherapy and immunotherapy response in gastric cancer

Su Rishun,Chen Jia,Dai Chen,Yin Songcheng,Chen Haoming,Sun Xuezeng,Fang Zhaoxin,Zhang Changhua,Chen Jingyao,Gu Liang

G2/M checkpoint and P53 pathway are essential in regulating the cell cycle and proliferation of cells, which is related to the progress of tumors. Here, we carried out an integrative analysis of the prognostic genes of these pathways in gastric cancer (GC) and thus developed a molecular subtype. We identified prognostic differential expression genes (PDEGs) of G2/M checkpoint and P53 pathways between normal and tumor tissue in TCGA-STAD and developed a molecular subtype based on PDEGs. Meanwhile, the clinical significance of the molecular subtype was further explored. In addition, a comprehensive model and nomogram based on PDEGs score were constructed and validated by GSE26901 and GSE13861. Gastric cancer cell lines and patients’ specimens were used to validate the expression of selected genes.19 PDEGs were identified from these pathways in TCGA-STAD. Ulteriorly, a PDEGs score model consisting of 4 genes (PVT1, F2R, INCENP, IRAK1) was generated to classify patients into high- and low- PDEGs score subgroups. Patients in low PDEGs score groups had a better prognosis and a higher tumor mutational burden and may be more sensitive to chemotherapy and immunotherapy. Notably, the combination of PDEGs score and clinical features showed a pleasing survival prediction ability. In the GSE13861 cohort, the PDEGs score and its derivative model were confirmed with significant predictive effects in overall survival. Furthermore, these genes were significantly upregulated in both GC cell lines and tumor tissues and F2R was the hub gene resulting in poor survival. This paper has provided a distinct insight for tumor classification predicting prognosis more accurately and having the potential to instruct the use of chemotherapy and immunotherapy for patients with GC.

CAS / MDL: 61825-94-3
研究领域: 癌症研究 · 分子生物学 · 生物信息学 · 基因组学 · 肿瘤学 · 计算生物学 · 医学遗传学
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