Background Immune checkpoint (IC) blockades (ICBs) significantly improve patients’ clinical outcomes with solid tumors. Because the objective response rate of single-agent ICB is limited, it is meaningful to explore the combination of ICs for immunotherapy. Methods RNA sequencing data of 95 newly diagnosed patients with esophageal squamous cell carcinoma (ESCC) from The Cancer Genome Atlas (TCGA) database were used to explore the prognostic significance of ICs. The results were validated by immunohistochemistry of 58 ESCC tissue samples from our clinical center. Results The results of both TCGA and validation data suggested that high expression of programmed cell death 1 ligand 1 (PD-L1), T-cell immunoglobulin and mucin-domain-containing-3 (TIM3), and T-cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domain (TIGIT) was associated with poor overall survival (OS) of patients with ESCC. Importantly, PD-L1/TIM3 or PD-L1/TIGIT was the optimal combination for predicting poor OS and short restricted mean survival time of patients with ESCC and was an independent prognostic factor. Moreover, a nomogram model constructed by PD-L1, TIM3, and TIGIT together with the primary tumor, regional lymph node, distant metastasis stage could provide a concise and precise prediction of 1-year and 2-year OS rates and median survival time. PD-L1/TIM3 or PD-L1/TIGIT had a positive correlation with CD8+ T cells. Notably, PD-1 and TIM3/TIGIT were primarily coexpressed on CD8+ tumor-infiltrating lymphocyte in patients with ESCC by multiplexed immunofluorescence. Conclusion High expression of ICs was associated with poor OS of patients with ESCC. PD-L1/TIM3 and PD-L1/TIGIT were the optimal combinations for predicting OS, which might be potential targets for future ICBs therapy of ESCC.

Little is known about the biological functions of neuron-specific enolase (NSE) as a specific biomarker for small-cell lung cancer (SCLC). Herein, we elucidate the effect and mechanism of NSE on SCLC stem cell-like characteristics. Upregulated NSE expression was observed in spheroid cells. The gain-of-function and loss-of-function approaches demonstrated that modulation of NSE positively regulated cell proliferation, drug resistance, spherical clone formation, tumor growth, and stem cell-like characteristics of SCLC cells. Mechanistic studies revealed that NSE might downregulate the expression of neuroblastoma suppressor of tumorigenicity 1 (NBL1) by interacting with NBL1, thereby attenuating the competitive inhibitory effect of NBL1 on BMP2 and enhancing the interaction between BMP2 and BMPR1A; this, in turn, may activate the BMP2/Smad/ID1 pathway and promote SCLC stem cell-like characteristics. Moreover, overexpression of NBL1or knockdown of BMP2 rescued the NSE-induced stem cell-like characteristics. In clinical specimens, NSE expression was positively associated with ALDH1A1 expression and negatively correlated with NBL1 expression. High NSE and ALDH1A1 expressions and low NBL1 expression were correlated with poor prognosis in patients with SCLC. In summary, our study demonstrated that NSE promoted stem cell-like characteristics of SCLC via NBL1 and the activation of the BMP2/Smad/ID1 pathway.

Our previous report has identified a lncRNA SATB2-AS1, which was significantly up-regulated in osteosarcoma tissue and promotes the proliferation of osteosarcoma cells in vitro. However, the mechanisms of SATB2-AS1 regulating the growth and metastasis of osteosarcoma cells in vivo and its role in the prognosis of osteosarcoma patients are still unclear. In this study, the transcriptome sequencing data of 87 patients with osteosarcoma from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database and 7 patients from our clinical center (GZFPH) was used to evaluate the importance of SATB2-AS1 and SATB2 on the prognosis. The effect of SATB2-AS1 on the growth and metastasis of osteosarcoma cells in vivo was verified by a mouse tumor model. The potential mechanisms of SATB2-AS1 regulating SATB2 were further explored by dual-luciferase reporter gene assay, RNA pull-down assay, and bioinformatics analysis. The results suggested that increased co-expression of SATB2-AS1 and SATB2 was significantly associated with poor overall survival (OS) and relapse-free survival (RFS), and was a biomarker for risk stratification in patients with osteosarcoma. Mechanistically, SATB2-AS1 promotes tumor growth and lung metastasis by regulating SATB2 in vivo. SATB2-AS1 directly binds to POU3F1 for mediating SATB2 expression in MNNG/HOS cells. In addition, SATB2-AS1 and SATB2 might be potential immunomodulators for negatively affecting immune cell infiltration by the IL-17 signaling pathway. In summary, SATB2-AS1 promoted tumor cell growth and lung metastasis by activating SATB2, thereby associated with poor prognosis in patients with osteosarcoma, which indicated that SATB2-AS1 and SATB2 might be novel biomarkers for risk stratification and promising therapeutic targets for osteosarcoma.

This study aimed to evaluate the diagnostic potential of a novel RFO model in differentiating GBM and SBM with multiparametric MR sequences collected from 244 (131 GBM and 113 SBM) patients. Three basic volume of interests (VOIs) were delineated on the conventional axial MR images (T₁WI, T₂WI, T₂_FLAIR, and CE_T₁WI), including volumetric non-enhanced tumor (nET), enhanced tumor (ET), and peritumoral edema (pTE). Using the RFO model, radiomics features extracted from different multiparametric MRI sequence(s) and VOI(s) were fused and the best sequence and VOI, or possible combinations, were determined. A multi-disciplinary team (MDT)-like fusion was performed to integrate predictions from the high-performing models for the final discrimination of GBM vs. SBM. Image features extracted from the volumetric ET (VOI_ET) had dominant predictive performances over features from other VOI combinations. Fusion of VOI_ET features from the T₁WI and T₂_FLAIR sequences via the RFO model achieved a discrimination accuracy of AUC = 0.925, accuracy = 0.855, sensitivity = 0.856, and specificity = 0.853, on the independent testing cohort 1, and AUC = 0.859, accuracy = 0.836, sensitivity = 0.708, and specificity = 0.919 on the independent testing cohort 2, which significantly outperformed three experienced radiologists (p = 0.03, 0.01, 0.02, and 0.01, and p = 0.02, 0.01, 0.45, and 0.02, respectively) and the MDT-decision result of three experienced experts (p = 0.03, 0.02, 0.03, and 0.02, and p = 0.03, 0.02, 0.44, and 0.03, respectively).

To assess the impact of the key non-synonymous amino acid substitutions in the RBD of the spike protein of SARS-CoV-2 variant B.1.617.1 (dominant variant identified in the current India outbreak) on the infectivity and neutralization activities of the immune sera, L452R and E484Q (L452R-E484Q variant), pseudotyped virus was constructed (with the D614G background). The impact on binding with the neutralizing antibodies was also assessed with an ELISA assay. Pseudotyped virus carrying a L452R-E484Q variant showed a comparable infectivity compared with D614G. However, there was a significant reduction in the neutralization activity of the immune sera from non-human primates vaccinated with a recombinant receptor binding domain (RBD) protein, convalescent patients, and healthy vaccinees vaccinated with an mRNA vaccine. In addition, there was a reduction in binding of L452R-E484Q-D614G protein to the antibodies of the immune sera from vaccinated non-human primates. These results highlight the interplay between infectivity and other biologic factors involved in the natural evolution of SARS-CoV-2. Reduced neutralization activities against the L452R-E484Q variant will have an impact on health authority planning and implications for the vaccination strategy/new vaccine development.