B7-H3 expression is associated with high PD-L1 expression in clear cell renal cell carcinoma and predicts poor prognosis

CD276 enhances sunitinib resistance in clear cell renal cell carcinoma by promoting DNA damage repair and activation of FAK-MAPK signaling pathway

OBJECTIVE

This study aimed to explore the effect of CD276 expression on the sunitinib sensitivity of clear cell renal cell carcinoma (ccRCC) cell and animal models and the potential mechanisms involved.

METHODS

CD276 expression levels of ccRCC and normal samples were analyzed via online databases and real-time quantitative PCR (RT-qPCR). CD276 was knocked down in ccRCC cell models (sunitinib-resistant 786-O/R cells and sunitinib-sensitive 786-O cells) using shRNA transfection, and the cells were exposed to a sunitinib (2 µM) environment. Cells proliferation was then analyzed using MTT assay and colony formation experiment. Alkaline comet assay, immunofluorescent staining, and western blot experiments were conducted to assess the DNA damage repair ability of the cells. Western blot was also used to observe the activation of FAK-MAPK pathway within the cells. Finally, a nude mouse xenograft model was established and the nude mice were orally administered sunitinib (40 mg/kg/d) to evaluate the in vivo effects of CD276 knockdown on the therapeutic efficacy of sunitinib against ccRCC.

RESULTS

CD276 was significantly upregulated in both ccRCC clinical tissue samples and cell models. In vitro experiments showed that knocking down CD276 reduced the survival rate, IC50 value, and colony-forming ability of ccRCC cells. Knocking down CD276 increased the comet tail moment (TM) values and γH2AX foci number, and reduced BRCA1 and RAD51 protein levels. Knocking down CD276 also decreased the levels of p-FAK, p-MEK, and p-ERK proteins.

CONCLUSION

Knocking down CD276 effectively improved the sensitivity of ccRCC cell and animal models to sunitinib treatment.

Survival and clinicopathological significance of B7-H3 in bladder cancer: a systematic review and meta-analysis

BACKGROUND

B7-H3 has been implicated in clinical pathological features and prognosis across various cancer types, suggesting its potential as a cancer biomarker. Nevertheless, consensus remains elusive regarding its clinical-pathological and prognostic significance in bladder cancer. To address this gap, we conducted a systematic review and meta-analysis.

METHODS

We systematically searched PubMed, Embase, Web of Science, Cochrane, and CNKI databases from their inception up to October 6, 2022. We evaluated the literature's quality using the Newcastle-Ottawa Scale. We performed meta-analysis using Review Manager 5.3 and STATA 12.0, synthesizing data and calculating odds ratios (ORs) or hazard ratios (HRs) with corresponding 95% confidence intervals (CIs).

RESULTS

After applying eligibility criteria and conducting assessments, we included data from 8 studies, encompassing 1622 bladder cancer patients. Bladder tumor tissues exhibited significantly elevated B7-H3 protein expression compared to normal bladder tissues. Elevated B7-H3 expression was notably associated with patient age, tumor infiltration, and recurrence in bladder cancer. However, no significant correlations were observed with other clinical characteristics. Our pooled HR analysis indicated no significant association between B7-H3 expression and overall survival in bladder cancer patients.

CONCLUSION

Our meta-analysis unveils the complex role of B7-H3 in bladder cancer progression. It appears to be directly involved in tumor infiltration and recurrence but cannot definitively serve as a prognostic biomarker for bladder cancer. To validate these findings, further well-designed studies, encompassing larger sample sizes and diverse racial backgrounds, are warranted.

PROSPERO REGISTRATION

No. CRD42022364688.

Establishment of a pathomic-based machine learning model to predict CD276 (B7-H3) expression in colon cancer

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.

New Emerging Targets in Cancer Immunotherapy: The Role of B7-H3

Immune checkpoints (ICs) are molecules implicated in the fine-tuning of immune response via co-inhibitory or co-stimulatory signals, and serve to secure minimized host damage. Targeting ICs with various therapeutic modalities, including checkpoint inhibitors/monoclonal antibodies (mAbs), antibody-drug conjugates (ADCs), and CAR-T cells has produced remarkable results, especially in immunogenic tumors, setting a paradigm shift in cancer therapeutics through the incorporation of these IC-targeted treatments. However, the large proportion of subjects who experience primary or secondary resistance to available IC-targeted options necessitates further advancements that render immunotherapy beneficial for a larger patient pool with longer duration of response. B7-H3 (B7 Homolog 3 Protein, CD276) is a member of the B7 family of IC proteins that exerts pleiotropic immunomodulatory effects both in physiologic and pathologic contexts. Mounting evidence has demonstrated an aberrant expression of B7-H3 in various solid malignancies, including tumors less sensitive to current immunotherapeutic options, and has associated its expression with advanced disease, worse patient survival and impaired response to IC-based regimens. Anti-B7-H3 agents, including novel mAbs, bispecific antibodies, ADCs, CAR-T cells, and radioimmunotherapy agents, have exhibited encouraging antitumor activity in preclinical models and have recently entered clinical testing for several cancer types. In the present review, we concisely present the functional implications of B7-H3 and discuss the latest evidence regarding its prognostic significance and therapeutic potential in solid malignancies, with emphasis on anti-B7-H3 modalities that are currently evaluated in clinical trial settings. Better understanding of B7-H3 intricate interactions in the tumor microenvironment will expand the oncological utility of anti-B7-H3 agents and further shape their role in cancer therapeutics.