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A novel strategy for combination of clofarabine and pictilisib is synergistic in gastric cancer

ABSTRACT: Highlights • Drug sensitivity testing identified novel drugs like clofarabine effective in treating gastric cancer.• mRNA sequencing can be used to identify agents with synergistic activity to a reference compound.• Pictilisib sensitizes gastric cancer to clofarabine treatment through AKT inhibition.• The combination of clofarabine and pictilisib inhibits tumor growth in cell lines and PDX models. Gastric cancer (GC) is frequently characterized by resistance to standard chemotherapeutic regimens and poor clinical outcomes. We aimed to identify a novel therapeutic approach using drug sensitivity testing (DST) and our computational SynerySeq pipeline. DST of GC cell lines was performed with a library of 215 Federal Drug Administration (FDA) approved compounds and identified clofarabine as a potential therapeutic agent. RNA-sequencing (RNAseq) of clofarabine treated GC cells was analyzed according to our SynergySeq pipeline and identified pictilisib as a potential synergistic agent. Clonogenic survival and Annexin V assays demonstrated increased cell death with clofarabine and pictilisib combination treatment (P<0.01). The combination induced double strand breaks (DSB) as indicated by phosphorylated H2A histone family member X (γH2AX) immunofluorescence and western blot analysis (P<0.01). Pictilisib treatment inhibited the protein kinase B (AKT) cell survival pathway and promoted a pro-apoptotic phenotype as evidenced by quantitative real time polymerase chain reaction (qRT-PCR) analysis of the B-cell lymphoma 2 (BCL2) protein family members (P<0.01). Patient derived xenograft (PDX) data confirmed that the combination is more effective in abrogating tumor growth with prolonged survival than single-agent treatment (P<0.01). The novel combination of clofarabine and pictilisib in GC promotes DNA damage and inhibits key cell survival pathways to induce cell death beyond single-agent treatment.

SUBMITTER: Khalafi S

PROVIDER: S-EPMC8571525 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundGastric cancer (GC) is one of the most common cancer worldwide. It is essential to identify non-invasive diagnostic and prognostic biomarkers of GC. The aim of the present study was to screen candidate biomarkers associated with the pathogenesis and prognosis of GC by a novel strategy.MethodsThe expression level of gene higher in cancer than in adjacent non-cancer tissue was defined as "positive", and the top 5% genes with "positive rate" were filtered out as candidate diagnostic biomarkers in three Gene Expression Omnibus (GEO) datasets. Further, a prognostic risk model was constructed by multivariate Cox regression analysis in GEO dataset and validated in The Cancer Genome Atlas (TCGA). The expression level of candidate biomarkers was determined in serum and serum-derived exosomes of GC patients. Moreover, the effect of biomarkers in exosomes on migration of GC cells was analyzed by transwell assay.ResultsTen candidate biomarkers (AGT, SERPINH1, WNT2, LIPG, PLAU, COL1A1, MMP7, MXRA5, CXCL1 and COL11A1) were identified with efficient diagnostic value in GC. A prognostic gene signature consisted of AGT, SERPINH1 and MMP7 was constructed and showed a good performance in predicting overall survivals in TCGA. Consistently, serum levels of the three biomarkers also showed high sensitivity and specificity in distinguishing GC patients from controls. In addition, the expression level of the three biomarkers were associated with malignant degree and decreased after surgery in GC patients. Moreover, the expression level of AGT and MMP7 in exosomes correlated positively with serum level. The exosomes derived from serum of GC patients can promote migration of SGC-7901 cells. After neutralized the expression level of three proteins in exosomes with antibodies, the migration of GC cells was obviously suppressed.ConclusionsOur findings provided a novel strategy to identify diagnostic biomarkers based on public datasets, and suggested that the three-gene signature was a candidate diagnostic and prognostic biomarker for patients with GC.

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A novel strategy for combination of clofarabine and pictilisib is synergistic in gastric cancer

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