Clinical activity and safety of sintilimab, bevacizumab, and TMZ in patients with recurrent glioblastoma.

PURPOSE: There are limited and no standard therapies for recurrent glioblastoma. We herein report the antitumour activity and safety of sintilimab, bevacizumab and temozolomide (TMZ) in recurrent glioblastoma. METHODS: We retrospectively analysed eight patients with recurrent glioblastoma treated with sintilimab (200 mg) every three weeks + bevacizumab (10 mg/kg) every three weeks + TMZ (200 mg/m²orally) (5 days orally every 28 days for a total of four weeks). The primary objective was investigator-assessed median progression-free survival(mPFS). Secondary objectives were to assess the 6-month PFS, objective response rate (ORR) and duration of response (DOR) accroding to RANO criteria. RESULTS: The mPFS time for 8 patients was 3.340 months (95% CI: 2.217-4.463), The longest PFS was close to 9 months. Five patients were assessed to have achieved partial response (PR), with an overall remission rate of 62.5%, Four patients experienced a change in tumour volume at the best response time of greater than 60% shrinkage from baseline, and one patient remained progression free upon review, with a DOR of more than 6.57 months. The 6-month PFS was 25% (95% CI: 5.0-55.0%). Three patients had a treatment-related adverse events, though no grade 4 or 5 adverse events occurred. CONCLUSION: In this small retrospective study, the combination regimen of sintilimab, bevacizumab and TMZ showed promising antitumour activity in treatment of recurrent glioblastoma, with a good objective remission rate.

Exogenous iron caused osteocyte apoptosis, increased RANKL production, and stimulated bone resorption through oxidative stress in a murine model.

Iron overload is a risk factor for osteoporosis due to its oxidative toxicity. Previous studies have demonstrated that an excessive amount of iron increases osteocyte apoptosis and receptor activator of nuclear factor κ-B ligand (RANKL) production, which stimulates osteoclast differentiation in vitro. However, the effects of exogenous iron supplementation-induced iron overload on osteocytes in vivo and its role in iron overload-induced bone loss are unknown. This work aimed to develop an iron overloaded murine model of C57BL/6 mice by intraperitoneal administration of iron dextran for two months. The iron levels in various organs, bone, and serum, as well as the microstructure and strength of bone, apoptosis of osteocytes, oxidative stress in bone tissue, and bone formation and resorption, were assessed. The results showed that 2 months of exogenous iron supplementation significantly increased iron levels in the liver, spleen, kidney, bone tissue, and serum. Iron overload negatively affected bone microstructure and strength. Osteocyte apoptosis and empty lacunae rate were elevated by exogenous iron. Iron overload upregulated RANKL expression but had no significant impact on osteoprotegerin (OPG) and sclerostin levels. Static and dynamic histologic analyses and serum biochemical assay showed that iron overload increased bone resorption without significantly affecting bone formation. Exogenous iron promoted oxidative stress in osteocytes in vivo and in vitro. Additional supplementation of iron chelator (deferoxamine) or N-acetyl-l-cysteine (NAC) partially alleviated bone loss, osteocyte apoptosis, osteoclast formation, and oxidative stress due to iron overload. These findings, in line with prior in vitro studies, suggest that exogenous iron supplementation induces osteoclastogenesis and osteoporosis by promoting osteocyte apoptosis and RANKL production via oxidative stress.

Cancer screening in hospitalized ischemic stroke patients: a multicenter study focused on multiparametric analysis to improve management of occult cancers.

Background/aims: The reciprocal promotion of cancer and stroke occurs due to changes in shared risk factors, such as metabolic pathways and molecular targets, creating a "vicious cycle." Cancer plays a direct or indirect role in the pathogenesis of ischemic stroke (IS), along with the reactive medical approach used in the treatment and clinical management of IS patients, resulting in clinical challenges associated with occult cancer in these patients. The lack of reliable and simple tools hinders the effectiveness of the predictive, preventive, and personalized medicine (PPPM/3PM) approach. Therefore, we conducted a multicenter study that focused on multiparametric analysis to facilitate early diagnosis of occult cancer and personalized treatment for stroke associated with cancer. Methods: Admission routine clinical examination indicators of IS patients were retrospectively collated from the electronic medical records. The training dataset comprised 136 IS patients with concurrent cancer, matched at a 1:1 ratio with a control group. The risk of occult cancer in IS patients was assessed through logistic regression and five alternative machine-learning models. Subsequently, select the model with the highest predictive efficacy to create a nomogram, which is a quantitative tool for predicting diagnosis in clinical practice. Internal validation employed a ten-fold cross-validation, while external validation involved 239 IS patients from six centers. Validation encompassed receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and comparison with models from prior research. Results: The ultimate prediction model was based on logistic regression and incorporated the following variables: regions of ischemic lesions, multiple vascular territories, hypertension, D-dimer, fibrinogen (FIB), and hemoglobin (Hb). The area under the ROC curve (AUC) for the nomogram was 0.871 in the training dataset and 0.834 in the external test dataset. Both calibration curves and DCA underscored the nomogram's strong performance. Conclusions: The nomogram enables early occult cancer diagnosis in hospitalized IS patients and helps to accurately identify the cause of IS, while the promotion of IS stratification makes personalized treatment feasible. The online nomogram based on routine clinical examination indicators of IS patients offered a cost-effective platform for secondary care in the framework of PPPM. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-024-00354-8.

2D-3D cascade network for glioma segmentation in multisequence MRI images using multiscale information.

BACKGROUND AND OBJECTIVE: Glioma segmentation is an important procedure for the treatment plan and follow-up evaluation of patients with glioma. UNet-based networks are widely used in medical image segmentation tasks and have achieved state-of-the-art performance. However, context information along the third dimension is ignored in 2D convolutions, whereas difference between z-axis and in-plane resolutions is large in 3D convolutions. Moreover, an original UNet structure cannot capture fine details because of the reduced resolution of feature maps near bottleneck layers. METHODS: To address these issues, a novel 2D-3D cascade network with multiscale information module is proposed for the multiclass segmentation of gliomas in multisequence MRI images. First, a 2D network is applied to fully exploit potential intra-slice features. A variational autoencoder module is incorporated into 2D DenseUNet to regularize a shared encoder, extract useful information, and represent glioma heterogeneity. Second, we integrated 3D DenseUNet with the 2D network in cascade mode to extract useful inter-slice features and alleviate the influence of large difference between z-axis and in-plane resolutions. Moreover, a multiscale information module is used in the 2D and 3D networks to further capture the fine details of gliomas. Finally, the whole 2D-3D cascade network is trained in an end-to-end manner, where the intra-slice and inter-slice features are fused and optimized jointly to take full advantage of 3D image information. RESULTS: Our method is evaluated on publicly available and clinical datasets and achieves competitive performance in these two datasets. CONCLUSIONS: These results indicate that the proposed method may be a useful tool for glioma segmentation.

PITPNC1 fuels radioresistance of rectal cancer by inhibiting reactive oxygen species production.

BACKGROUND: Neoadjuvant radiotherapy is a commonly used method for the current standard-of-care for most patients with rectal cancer, when the effects of radioresistance are limited. The phosphatidylinositol transfer protein, cytoplasmic 1 (PITPNC1), a lipid-metabolism-related gene, has previously been proved to manifest pro-cancer effects in multiple types of cancer. However, whether PITPNC1 plays a role for developing radioresistance in rectal cancer patients is still unknown. Therefore, this study aims to investigate the role of PITPNC1 in rectal cancer radioresistance. METHODS: Patient-derived tissue were used to detect the difference in the expression level of PITPNC1 between radioresistant and radiosensitive patients. Bioinformatic analyses of high-throughput gene expression data were applied to uncover the correlations between PITPNC1 level and oxidative stress. Two rectal cancer cell lines, SW620, and HCT116, were selected in vitro to investigate the effect of PITPNC1 on radioresistance, reactive oxygen species (ROS) generation, apoptosis, and proliferation in rectal cancer. RESULTS: PITPNC1 is highly expressed in radioresistant patient-derived rectal cancer tissues compared to radiosensitive tissue; therefore, PITPNC1 inhibits the generation of ROS and improves the extent of radioresistance of rectal cancer cell lines and then inhibits apoptosis. Knocking down PITPNC1 facilitates the production of ROS while application of the ROS scavenger, N-acetyl-L-cysteine (NAC), could reverse this effect. CONCLUSIONS: PITPNC1 fuels radioresistance of rectal cancer via the inhibition of ROS generation.

Differentiation of Recurrence from Radiation Necrosis in Gliomas Based on the Radiomics of Combinational Features and Multimodality MRI Images.

PURPOSE: To classify radiation necrosis versus recurrence in glioma patients using a radiomics model based on combinational features and multimodality MRI images. METHODS: Fifty-one glioma patients who underwent radiation treatments after surgery were enrolled in this study. Sixteen patients revealed radiation necrosis while 35 patients showed tumor recurrence during the follow-up period. After treatment, all patients underwent T1-weighted, T1-weighted postcontrast, T2-weighted, and fluid-attenuated inversion recovery scans. A total of 41,284 handcrafted and 24,576 deep features were extracted for each patient. The 0.623 + bootstrap method and the area under the curve (denoted as 0.632 + bootstrap AUC) metric were used to select the features. The stepwise forward method was applied to construct 10 logistic regression models based on different combinations of image features. RESULTS: For handcrafted features on multimodality MRI, model 7 with seven features yielded the highest AUC of 0.9624, sensitivity of 0.8497, and specificity of 0.9083 in the validation set. These values were higher than the accuracy of using handcrafted features on single-modality MRI (paired t-test, p < 0.05, except sensitivity). For combined handcrafted and AlexNet features on multimodality MRI, model 6 with six features achieved the highest AUC of 0.9982, sensitivity of 0.9941, and specificity of 0.9755 in the validation set. These values were higher than the accuracy of using handcrafted features on multimodality MRI (paired t-test, p < 0.05). CONCLUSIONS: Handcrafted and deep features extracted from multimodality MRI images reflecting the heterogeneity of gliomas can provide useful information for glioma necrosis/recurrence classification.

Galangin inhibits human osteosarcoma cells growth by inducing transforming growth factor-ß1-dependent osteogenic differentiation.

Osteosarcoma is the most common primary malignancy of the musculoskeletal system, and is associated with excessive proliferation and poor differentiation of osteoblasts. Currently, despite the use of traditional chemotherapy and radiotherapy, no satisfactory and effective agent has been developed to treat the disease. Herein, we found that a flavonoid natural product, galangin, could significantly attenuate human osteosarcoma cells proliferation, without causing obvious cell apoptosis. Moreover, galangin enhanced the expression of osteoblast differentiation markers (collagen type I, alkaline phosphatase, osteocalcin and osteopontin) remarkably and elevated the alkaline phosphatase activity in human osteosarcoma cells. And galangin could also attenuated osteosarcoma growth in vivo. These bioactivities of galangin resulted from its selective activation of the transforming growth factor (TGF)-ß1/Smad2/3 signaling pathway, which was demonstrated by pathway blocking experiments. These findings suggested that galangin could be a promising agent to treat osteosarcoma. In addition, targeting TGF-ß1 to induce osteogenic differentiation might represent a novel therapeutic strategy to treat osteosarcoma with minimal side effects.