Tumor-infiltrating lymphocytes are related to positive clinical prognoses in numerous cancer types. Programmed death ligand 1 (PD-L1), a mediator of the PD-1 receptor, plays an inhibitory role in cancer immune responses. PD-L1 upregulation can impede infiltrating T-cell functions in lung adenocarcinoma (LUAD), a lung cancer subtype. However, associations between the expression of PD-L1 and infiltration of B cells (a major immunoregulatory cell) remain unknown. Therefore, we investigated the role of infiltrating B cells in LUAD progression and its correlation with PD-L1 expression. The Cancer Genome Atlas (TCGA) LUAD data set was used to explore associations among B-cell infiltration, PD-L1 expression, clinical outcome, and gene landscape. Gene set enrichment analysis was used to explore putative signaling pathways and candidate genes. The drug enrichment analysis was used to identify candidate genes and the related drugs. We found that high B-cell infiltration was correlated with better prognoses; however, PD-L1 may interfere with the survival advantage in patients with high B-cell infiltration. The gene landscape was characterized comprehensively, with distinct PD-L1 levels in cell populations with high B-cell infiltration. We obtained five upregulated signaling pathways from the gene landscape: apoptosis, tumor necrosis factor (TNF)-α signaling via nuclear factor (NF)-κB, apical surface, interferon-α response, and KRAS signaling. Moreover, four candidate genes and their related target drugs were also identified, namely interleukin-2β receptor (IL2RB), IL-2γ receptor (IL2RG), Toll-like receptor 8 (TLR8), and TNF. These findings suggest that tumor-infiltrating B cells could act as a clinical factor in anti-PD-L1 immunotherapy for LUAD.

An insufficient oxygen supply within the intratumoral environment, also known as hypoxia, induces glioblastoma multiforme (GBM) invasion, stemness, and temozolomide (TMZ) drug resistance. Long noncoding (lnc)RNAs have been reported to be involved in hypoxia and GBM progression. However, their roles in hypoxic GBM malignancy are still unclear. We investigated the mechanisms of hypoxia-mediated lncRNAs in regulating GBM processes. Using The Cancer Genome Atlas (TCGA) and data mining, hypoxia-correlated lncRNAs were identified. A hypoxia-upregulated lncRNA, MIR210HG, locating in nuclear regions, predicted poor prognoses of patients and modulated hypoxia-promoted glioma stemness, TMZ resistance, and invasion.Depletion of hypoxic MIR210HG suppressed GBM and patient-derived cell growth and increased TMZ sensitivity in vitro and vivo. Using RNA sequencing and gene set enrichment analysis (GSEA), MIR210HG-upregulated genes significantly belonged to the targets of octamer transcription factor 1 (OCT1) transcription factor. The direct interaction between OCT1 and MIR210HG was also validated. Two well-established worse prognostic factors of GBM, insulin-like growth factor-binding protein 2 (IGFBP2) and fibroblast growth factor receptor 1 (FGFR1), were identified as downstream targets of OCT1 through MIR210HG mediation in hypoxia. Consequently, the lncRNA MIR210HG is upregulated by hypoxia and interacts with OCT1 for modulating hypoxic GBM, leading to poor prognoses. These findings might provide a better understanding in functions of hypoxia/MIR210HG signaling for regulating GBM malignancy.

Sparc/osteonectin, cwcv, and kazal-like domains proteoglycan 1 (SPOCK1) has been reported to play an oncogenic role in certain cancer types; however, the role of SPOCK1 in the progression of clear cell renal cell carcinoma (ccRCC) remains elusive. Here, higher SPOCK1 transcript and protein levels were observed in ccRCC tissues compared to normal tissues and correlated with advanced clinical stages, larger tumor sizes, and lymph node and distal metastases. Knockdown and overexpression of SPOCK1 in ccRCC cells led to decreased and increased cell clonogenic and migratory/invasive abilities in vitro as well as lower and higher tumor growth and invasion in vivo, respectively. Mechanistically, the gene set enrichment analysis (GSEA) database was used to identify the gene set of epithelial-to-mesenchymal transition (EMT) pathways enriched in ccRCC samples with high SPOCK1 expression. Further mechanistic investigations revealed that SPOCK1 triggered the Snail/Slug–matrix metalloproteinase (MMP)-2 axis to promote EMT and cell motility. Clinical ccRCC samples revealed SPOCK1 to be an independent prognostic factor for overall survival (OS), and positive correlations of SPOCK1 with MMP-2 and mesenchymal-related gene expression levels were found. We observed that patients with SPOCK1high/MMP2high tumors had the shortest OS times compared to others. In conclusion, our findings reveal that SPOCK1 can serve as a useful biomarker for predicting ccRCC progression and prognosis, and as a promising target for treating ccRCC.

Background KH-type splicing regulatory protein (KHSRP, also called KSRP), a versatile RNA-binding protein, plays a critical role in various physiological and pathological conditions through modulating gene expressions at multiple levels. However, the role of KSRP in clear cell renal cell carcinoma (ccRCC) remains poorly understood. Methods KSRP expression was detected by a ccRCC tissue microarray and evaluated by an in silico analysis. Cell loss-of-function and gain-of-function, colony-formation, anoikis, and transwell assays, and an orthotopic bioluminescent xenograft model were conducted to determine the functional role of KRSP in ccRCC progression. Micro (mi)RNA and complementary (c)DNA microarrays were used to identify downstream targets of KSRP. Western blotting, quantitative real-time polymerase chain reaction, and promoter- and 3-untranslated region (3'UTR)-luciferase reporter assays were employed to validate the underlying mechanisms of KSRP which aggravate progression of ccRCC. Results Our results showed that dysregulated high levels of KSRP were correlated with advanced clinical stages, larger tumor sizes, recurrence, and poor prognoses of ccRCC. Neural precursor cell-expressed developmentally downregulated 4 like (NEDD4L) was identified as a novel target of KSRP, which can reverse the protumorigenic and prometastatic characteristics as well as epithelial-mesenchymal transition (EMT) promotion by KSRP in vitro and in vivo. Molecular studies revealed that KSRP can decrease NEDD4L messenger (m)RNA stability via inducing mir-629-5p upregulation and directly targeting the AU-rich elements (AREs) of the 3’UTR. Moreover, KSRP was shown to transcriptionally suppress NEDD4L via inducing the transcriptional repressor, Wilm's tumor 1 (WT1). In the clinic, ccRCC samples revealed a positive correlation between KSRP and mesenchymal-related genes, and patients expressing high KSRP and low NEDD4L had the worst prognoses. Conclusion The current findings unveil novel mechanisms of KSRP which promote malignant progression of ccRCC through transcriptional inhibition and post-transcriptional destabilization of NEDD4L transcripts. Targeting KSRP and its pathways may be a novel pharmaceutical intervention for ccRCC.

Policy optimization is a fundamental principle for designing reinforcement learning algorithms, and one example is the proximal policy optimization algorithm with a clipped surrogate objective (PPO-clip), which has been popularly used in deep reinforcement learning due to its simplicity and effectiveness. Despite its superior empirical performance, PPO-clip has not been justified via theoretical proof up to date. This paper proposes to rethink policy optimization and reinterpret the theory of PPO-clip based on hinge policy optimization (HPO), called to improve policy by hinge loss in this paper. Specifically, we first identify sufficient conditions of state-wise policy improvement and then rethink policy update as solving a large-margin classification problem with hinge loss. By leveraging various types of classifiers, the proposed design opens up a whole new family of policy-based algorithms, including the PPO-clip as a special case. Based on this construct, we prove that these algorithms asymptotically attain a globally optimal policy. To our knowledge, this is the first ever that can prove global convergence to an optimal policy for a variant of PPO-clip. We corroborate the performance of a variety of HPO algorithms through experiments and an ablation study.