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BackgroundThe present study aimed to identify indispensable genes associated with tumor cell viability according to the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR‐associated protein 9 (Cas9) datasets, which may support new therapeutic targets for patients with osteosarcoma.MethodsThe transcriptome patterns between tumor and normal tissues, which were obtained from the Therapeutically Applicable Research to Generate Effective Treatments dataset, were overlapped with the genomics associated with cell viability screened by CRISPR‐Cas9 technology. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses were employed to determine enrichment pathways related to lethal genes. Least absolute shrinkage and selection operator (LASSO) regression was employed to construct a risk model related to lethal genes for predicting clinical outcomes of osteosarcoma. Univariate and multivariate Cox regressions were conducted to assess the prognostic value of this feature. Weighted gene co‐expression network analysis was performed to identify modules associated with patients with high‐risk score.ResultsIn total, 34 lethal genes were identified in this investigation. These genes were enriched in the necroptosis pathway. The risk model based on LASSO regression algorithm distinguishes patients with high‐risk score from patients with low‐risk score. Compared with low‐risk patients, high‐risk patients showed a shorter overall survival rate in both the training and validation sets. The time‐dependent receiver operating characteristic curves of 1, 3 and 5 years displayed that the risk score has great prediction performance. The necroptosis pathway represents the main difference in biological behavior between the high‐risk group and the low‐risk group. Meanwhile, CDK6 and SMARCB1 may serve as important targets for detecting osteosarcoma progression.ConclusionsThe present study developed a predictive model that outperformed classical clinicopathological parameters for predicting the clinical outcomes of osteosarcoma patients and identified specific lethal genes, including CDK6 and SMARCB1, as well as the necroptosis pathway. These findings may serve as potential targets for future osteosarcoma treatments.

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Background To investigate the effect of TriBAFF-CAR-T cells on hematological tumor cells. Methods TriBAFF-CAR-T and CD19-CAR-T cells were co-cultured with BAFFR-bearing B-cell malignancies at different effector/target ratios to evaluate the anti-tumor effects. In vivo, TriBAFF-CAR-T and CD19-CAR-T cells were intravenously injected into Raji-luciferase xenograft mice. CD19 antigens losing lymphoblasts was simulated by Raji knocking out CD19 (CD19KO) to investigate the effect of TriBAFF-CAR-T cells on CD19KO Raji. Results Both TriBAFF-CAR-T and CD19-CAR-T cells significantly induced the lysis of Raji, BALL-1, and Jeko-1. Moreover, when CD19-CAR-T cells specifically caused the lysis of K562 with overexpressed CD19, the lethal effect of TriBAFF-CAR-T cells was also specific for BAFFR-bearing K562 with increasing levels of interleukin-2 and INF-γ. The TriBAFF-CAR-T have the same effect with CD19-CAR-T cells in treating Raji xenofraft mice. TriBAFF-CAR-T cells also have great effect in CD19KO Raji cells. Conclusions In this study, we successfully constructed novel TriBAFF-CAR-T cells to eliminate BAFFR-bearing and CD19 antigen loss in hematological tumor cells.

Background This study aims to estimate the amount of axillary lymph node (ALN) involvement in early-stage breast cancer utilizing a field of view (FOV) optimized and constrained undistorted single-shot (FOCUS) diffusion-weighted imaging (DWI) approach, as well as a whole-lesion histogram analysis. Methods This retrospective analysis involved 81 individuals with invasive breast cancer. The patients were divided into three groups: N0 (negative ALN metastasis), N1–2 (low metastatic burden with 1–2 ALNs), and N≥3 (heavy metastatic burden with ≥ 3 ALNs) based on their sentinel lymph node biopsy (SLNB) or axillary lymph node dissection (ALND). Histogram parameters of apparent diffusion coefficient (ADC) depending basically on FOCUS DWI were performed using 3D-Slicer software for whole lesions. The typical histogram characteristics for N0, N1–2, and N≥ 3 were compared to identify the significantly different parameters. To determine the diagnostic efficacy of significantly different factors, the area under their receiver operating characteristic (ROC) curves was examined. Results There were significant differences in the energy, maximum, 90 percentile, range, and lesion size among N0, N1–2, and N≥ 3 groups (P < 0.05). The energy differed significantly between N0 and N1–2 groups (P < 0.05), and some certain ADC histogram parameters and lesion sizes differed significantly between N0 and N≥3, or N1–2 and N≥3 groups. For ROC analysis, the energy yielded the best diagnostic performance in distinguishing N0 and N1–2 groups from N≥3 group with an AUC value of0.853. All parameters revealed excellent inter-observer agreement with inter-reader consistencies data ranging from0.919 to 0.982. Conclusion By employing FOCUS DWI method, the analysis of whole-lesion ADC histogram quantitatively provides a non-invasive way to evaluate the degree of ALN metastatic spread in early-stage breast cancer.