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posted on 2025-03-05, 07:20 authored by Megumi Kuronishi, Yoichi Ozawa, Takayuki Kimura, Shuyu Dan Li, Yu Kato <p>Relationship between MVD gene score and Tcell<sub>inf</sub>GEP in mouse syngeneic tumor models and human pan-cancer dataset. <b>A,</b> Relationship between MVD(IHC) and Tcell<sub>inf</sub>GEP of baseline tumors in 12 mouse syngeneic models. Data are shown as mean ± SD [<i>n</i> = 5 for MVD(IHC); <i>n</i> = 3 except for MC38 (<i>n</i> = 2) for Tcell<sub>inf</sub>GEP]. <b>B,</b> Proportion of samples in each subgroup defined by median values of the MVD gene score and Tcell<sub>inf</sub>GEP in all samples. <b>C,</b> MVD gene score and Tcell<sub>inf</sub>GEP within each major solid tumor type computed using gene expression data from TCGA pan-cancer dataset. Dotted lines represent the median value of each gene signature in all samples. BLCA, bladder urothelial carcinoma; BRCA, breast invasive carcinoma; CESC, cervical squamous cell carcinoma and endocervical adenocarcinoma; COADREAD, colon adenocarcinoma and rectal adenocarcinoma; ESCA, esophageal carcinoma; GBM, glioblastoma multiforme; HNSC, head and neck squamous cell carcinoma; KICH, kidney chromophobe; KIRP, kidney renal papillary cell carcinoma; LGG, brain lower-grade glioma; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; OV, ovarian serous cystadenocarcinoma; PAAD, pancreatic adenocarcinoma; PRAD, prostate adenocarcinoma; SARC, sarcoma; SKCM, skin cutaneous melanoma; STAD, stomach adenocarcinoma; THCA, thyroid carcinoma; UCEC, uterine corpus endometrial carcinoma.</p>
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ARTICLE ABSTRACT
Combination therapy with antiangiogenic drugs and immune checkpoint inhibitors has shown enhanced clinical activity and has been approved for the treatment of multiple tumor types. Despite extensive research, predictive biomarkers for combination therapy remain poorly understood. Microvessel density (MVD), a surrogate marker for aberrant angiogenesis measured by IHC, has been associated with response to monotherapy with antiangiogenic inhibitors. However, obtaining tumor tissue with a sufficient mass for IHC analysis is not always practical, and IHC-based MVD measurements are unavailable in large public datasets. In this study, we developed an MVD gene score based on RNA sequencing data that reflects MVD by using RNA sequencing and MVD measured by IHC in 12 mouse syngeneic tumor models. We explored the relationship between the MVD gene score and a gene signature, predicting the response to anti–PD-1 therapy in mouse and human tumor datasets. The MVD gene score correlated with the antitumor activity of lenvatinib, a multiple tyrosine kinase inhibitor mainly targeting VEGFRs and FGFRs, in mouse tumor models, and MVD measured by IHC in commercially available human formalin-fixed, paraffin-embedded tumor samples. Tumor types in The Cancer Genome Atlas were classified into four subgroups based on the MVD gene score and T cell–inflamed gene expression profile, which were correlated with clinical indications for treatment. In conclusion, the newly developed MVD gene score enables the estimation of MVD in large public datasets in which IHC data are unavailable and has potential clinical utility together with the T cell–inflamed gene expression profile to characterize tumors of patients for precision medicine.
A novel gene signature for MVD was developed. This MVD gene score enables the estimation of MVD, reflecting the sensitivity to antiangiogenic inhibitors, in transcriptomic datasets. We demonstrated the utility of the MVD gene score together with a T cell–inflamed gene signature for potential future use as a clinical biomarker.
