Dataset Information

Molecular Pathways: Targeting B7-H3 (CD276) for Human Cancer Immunotherapy.

ABSTRACT: B7-H3 (CD276) is an important immune checkpoint member of the B7 and CD28 families. Induced on antigen-presenting cells, B7-H3 plays an important role in the inhibition of T-cell function. Importantly, B7-H3 is highly overexpressed on a wide range of human solid cancers and often correlates with both negative prognosis and poor clinical outcome in patients. Challenges remain to identify the receptor(s) of B7-H3 and thus better elucidate the role of the B7-H3 pathway in immune responses and tumor evasion. With a preferential expression on tumor cells, B7-H3 is an attractive target for cancer immunotherapy. Based on the clinical success of inhibitory immune checkpoint blockade (CTLA-4, PD-1, and PD-L1), mAbs against B7-H3 appear to be a promising therapeutic strategy worthy of development. An unconventional mAb against B7-H3 with antibody-dependent cell-mediated cytotoxicity is currently being evaluated in a phase I clinical trial and has shown encouraging preliminary results. Additional therapeutic approaches in targeting B7-H3, such as blocking mAbs, bispecific mAbs, chimeric antigen receptor T cells, small-molecule inhibitors, and combination therapies, should be evaluated, as these technologies have already shown positive results in various cancer settings. A better understanding of the B7-H3 pathway in humans will surely help to further optimize associated cancer immunotherapies. Clin Cancer Res; 22(14); 3425-31. ©2016 AACR.

SUBMITTER: Picarda E

PROVIDER: S-EPMC4947428 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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Molecular Pathways: Targeting B7-H3 (CD276) for Human Cancer Immunotherapy.

Picarda Elodie E Ohaegbulam Kim C KC Zang Xingxing X

Clinical cancer research : an official journal of the American Association for Cancer Research 20160520 14

B7-H3 (CD276) is an important immune checkpoint member of the B7 and CD28 families. Induced on antigen-presenting cells, B7-H3 plays an important role in the inhibition of T-cell function. Importantly, B7-H3 is highly overexpressed on a wide range of human solid cancers and often correlates with both negative prognosis and poor clinical outcome in patients. Challenges remain to identify the receptor(s) of B7-H3 and thus better elucidate the role of the B7-H3 pathway in immune responses and tumor ...[more]

PMID: 27208063

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Project description:CD276 is a promising prognostic indicator and an attractive therapeutic target in various malignancies. However, current methods for CD276 detection are time-consuming and expensive, limiting extensive studies and applications of CD276. We aimed to develop a pathomic model for CD276 prediction from H&E-stained pathological images, and explore the underlying mechanism of the pathomic features by associating the pathomic model with transcription profiles. A dataset of colon adenocarcinoma (COAD) patients was retrieved from the Cancer Genome Atlas (TCGA) database. The dataset was divided into the training and validation sets according to the ratio of 8:2 by a stratified sampling method. Using the gradient boosting machine (GBM) algorithm, we established a pathomic model to predict CD276 expression in COAD. Univariate and multivariate Cox regression analyses were conducted to assess the predictive performance of the pathomic model for overall survival in COAD. Gene Set Enrichment Analysis (GESA) was performed to explore the underlying biological mechanisms of the pathomic model. The pathomic model formed by three pathomic features for CD276 prediction showed an area under the curve (AUC) of 0.833 (95%CI: 0.784-0.882) in the training set and 0.758 (95%CI: 0.637-0.878) in the validation set, respectively. The calibration curves and Hosmer-Lemeshow goodness of fit test showed that the prediction probability of high/low expression of CD276 was in favorable agreement with the real situation in both the training and validation sets (P=0.176 and 0.255, respectively). The DCA curves suggested that the pathomic model acquired high clinical benefit. All the subjects were categorized into high pathomic score (PS) (PS-H) and low PS (PS-L) groups according to the cutoff value of PS. Univariate and multivariate Cox regression analysis indicated that PS was a risk factor for overall survival in COAD. Furthermore, through GESA analysis, we found several immune and inflammatory-related pathways and genes were associated with the pathomic model. We constructed a pathomics-based machine learning model for CD276 prediction directly from H&E-stained images in COAD. Through integrated analysis of the pathomic model and transcriptomics, the interpretability of the pathomic model provide a theoretical basis for further hypothesis and experimental research.

Dataset Information

Molecular Pathways: Targeting B7-H3 (CD276) for Human Cancer Immunotherapy.

Publications

Molecular Pathways: Targeting B7-H3 (CD276) for Human Cancer Immunotherapy.

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