ITC-6102RO, a novel B7-H3 antibody-drug conjugate, exhibits potent therapeutic effects against B7-H3 expressing solid tumors

Abstract Background The B7-H3 protein, encoded by the CD276 gene, is a member of the B7 family of proteins and a transmembrane glycoprotein. It is highly expressed in various solid tumors, such as lung and breast cancer, and has been associated with limited expression in normal tissues and poor clinical outcomes across different malignancies. Additionally, B7-H3 plays a crucial role in anticancer immune responses. Antibody-drug conjugates (ADCs) are a promising therapeutic modality, utilizing antibodies targeting tumor antigens to selectively and effectively deliver potent cytotoxic agents to tumors. Methods In this study, we demonstrate the potential of a novel B7-H3-targeting ADC, ITC-6102RO, for B7-H3-targeted therapy. ITC-6102RO was developed and conjugated with dHBD, a soluble derivative of pyrrolobenzodiazepine (PBD), using Ortho Hydroxy-Protected Aryl Sulfate (OHPAS) linkers with high biostability. We assessed the cytotoxicity and internalization of ITC-6102RO in B7-H3 overexpressing cell lines in vitro and evaluated its anticancer efficacy and mode of action in B7-H3 overexpressing cell-derived and patient-derived xenograft models in vivo. Results ITC-6102RO inhibited cell viability in B7-H3-positive lung and breast cancer cell lines, inducing cell cycle arrest in the S phase, DNA damage, and apoptosis in vitro. The binding activity and selectivity of ITC-6102RO with B7-H3 were comparable to those of the unconjugated anti-B7-H3 antibody. Furthermore, ITC-6102RO proved effective in B7-H3-positive JIMT-1 subcutaneously xenografted mice and exhibited a potent antitumor effect on B7-H3-positive lung cancer patient-derived xenograft (PDX) models. The mode of action, including S phase arrest and DNA damage induced by dHBD, was confirmed in JIMT-1 tumor tissues. Conclusions Our preclinical data indicate that ITC-6102RO is a promising therapeutic agent for B7-H3-targeted therapy. Moreover, we anticipate that OHPAS linkers will serve as a valuable platform for developing novel ADCs targeting a wide range of targets

Development of a Prediction Rule for Estimating Postoperative Pulmonary Complications

<div><p>Patient- and procedure-related factors associated with postoperative pulmonary complications (PPCs) have changed over the last decade. Therefore, we sought to identify independent risk factors of PPCs and to develop a clinically applicable scoring system. We retrospectively analyzed clinical data from 2,059 patients who received preoperative evaluations from respiratory physicians between June 2011 and October 2012. A new scoring system for estimating PPCs was developed using beta coefficients of the final multiple regression models. Of the 2,059 patients studied, 140 (6.8%) had PPCs. A multiple logistic regression model revealed seven independent risk factors (with scores in parentheses): age ≥70 years (2 points), current smoker (1 point), the presence of airflow limitation (1 point), American Society of Anesthesiologists class ≥2 (1 point), serum albumin <4 g/dL (1 point), emergency surgery (2 points), and non-laparoscopic abdominal/cardiac/aortic aneurysm repair surgery (4 points). The area under the curve was 0.79 (95% CI, 0.75–0.83) with the newly developed model. The new risk stratification including laparoscopic surgery has a good discriminative ability for estimating PPCs in our study cohort. Further research is needed to validate this new prediction rule.</p></div

Recruitment flow chart.

<p>Recruitment flow chart.</p

Prevalence of postoperative pulmonary complications according to each type of surgery.

<p>*included upper abdominal, lower abdominal, and laparoscopic abdominal surgery.</p><p>PPC, postoperative pulmonary complications.</p><p>Cases are duplicated.</p><p>Prevalence of postoperative pulmonary complications according to each type of surgery.</p

Results of logistic regression model to predict postoperative pulmonary complications (PPC) and assigned points based on regression coefficient to develop the PPC scoring index.

<p>A multivariable analysis using a logistic regression model was conducted with backward step-wise selection with p<0.05 for inclusion of variables and p>0.10 for removal of variables from all variables used for Univariable analysis and only significant variables in a multivariable analysis were indicated in the table.</p><p>PPC, postoperative pulmonary complications; OR, odds ratio; CI, confidence interval; CHF, congestive heart failure; ASA, American Society of Anesthesiologists.</p><p>Hosmer-Lemeshow test, χ² = 7.653, p = 0.468.</p><p>Results of logistic regression model to predict postoperative pulmonary complications (PPC) and assigned points based on regression coefficient to develop the PPC scoring index.</p

Baseline characteristics (n = 2,059).

<p>*included 49 endocrine, 35 eye and plastic, and 29 breast surgery.</p><p>SD, standard deviation; CHF, congestive heart failure; ASA, American Society of Anesthesiologists.</p><p>Baseline characteristics (n = 2,059).</p

Additional file 1 of ITC-6102RO, a novel B7-H3 antibody-drug conjugate, exhibits potent therapeutic effects against B7-H3 expressing solid tumors

Supplementary Material