Prognostic factors in surgically treated tongue squamous cell carcinoma in stage T1-2N0-1M0: A retrospective analysis.

PURPOSE: The study aimed to retrospectively identify the prognostic factors of surgically treated primary tongue squamous cell carcinoma (TSCC) cases and assess the benefits of surgical neck lymph node dissection (LND) in early-stage cancer. METHODS: Patients with primary TSCC with pT1-2N0-1M0 stage without distant metastasis who were treated with surgery during 2014-2016 at Xiangya Hospital, Central South University were included. Univariate and multivariate Cox models were constructed to explore prognostic factors of overall survival (OS), disease-free survival (DFS), and local recurrence-free survival (LRFS). Sub-group analysis was used to assess the effect of adjuvant therapy and the prognostic value of LND for the early-stage patients. RESULTS: In total, 440 patients met the inclusion criteria. During the follow-up period, the 5-year OS, DFS, were 84.4% and 70.0%, respectively. Univariate analysis showed that TNM stage, lymphovascular invasion (LVI), and/or perineural invasion (PNI), pathological differentiation, etc. were significant predictors of OS and DFS. Multivariate analysis showed that TNM stage and the degree of pathological differentiation were independent prognostic factors for all outcomes. Besides, the number of cervical LND could independently predict both DFS and LRFS while LVI/PNI were associated with DFS. And high-quality neck LND (≥30) significantly improved DFS and LRFS for patients of pT1cN0M0 or stage I as compared to those without LND. CONCLUSIONS: TNM stage and pathological differentiation were crucial prognostic factors for postoperative patients with TSCC. Notably, high-quality cervical LND was beneficial for the improvement of DFS and LRFS for patients of pT1cN0M0 or stage I.

Refining the 8th edition TNM classification for EBV related nasopharyngeal carcinoma.

The AJCC/UICC TNM classification describes anatomic extent of tumor progression and guides treatment decisions. Our comprehensive analysis of 8,834 newly diagnosed patients with non-metastatic Epstein-Barr virus related nasopharyngeal carcinoma (NPC) from six Chinese centers indicates certain limitations in the current staging system. The 8th edition of the AJCC/UICC TNM classification inadequately differentiates patient outcomes, particularly between T2 and T3 categories and within the N classification. We propose reclassifying cases of T3 NPC with early skull-base invasion as T2, and elevating N1-N2 cases with grade 3 image-identified extranodal extension (ENE) to N3. Additionally, we suggest combining T2N0 with T1N0 into a single stage IA. For de novo metastatic (M1) NPC, we propose subdivisions of M1a, defined by 1-3 metastatic lesions without liver involvement, and M1b, characterized by >3 metastatic lesions or liver involvement. This proposal better reflects responses of NPC patients to the up-to-date treatments and their evolving risk profiles.

CT-based dosiomics and radiomics model predicts radiation-induced lymphopenia in nasopharyngeal carcinoma patients.

Purpose: This study aims to develop and validate a model predictive for the incidence of grade 4 radiation-induced lymphopenia (G4RIL), based on dosiomics features and radiomics features from the planning CT of nasopharyngeal carcinoma (NPC) treated by radiation therapy. Methods: The dataset of 125 NPC patients treated with radiotherapy from August 2018 to March 2019 was randomly divided into two sets-an 85-sample training set and a 40-sample test set. Dosiomics features and radiomics features of the CT image within the skull bone and cervical vertebrae were extracted. A feature selection process of multiple steps was employed to identify the features that most accurately forecast the data and eliminate superfluous or insignificant ones. A support vector machine learning classifier with correction for imbalanced data was trained on the patient dataset for prediction of RIL (positive classifier for G4RIL, negative otherwise). The model's predictive capability was gauged by gauging its sensitivity (the likelihood of a positive test being administered to patients with G4RIL) and specificity in the test set. The area beneath the ROC curve (AUC) was utilized to explore the association of characteristics with the occurrence of G4RIL. Results: Three clinical features, three dosiomics features, and three radiomics features exhibited significant correlations with G4RIL. Those features were then used for model construction. The combination model, based on nine robust features, yielded the most impressive results with an ACC value of 0.88 in the test set, while the dosiomics model, with three dosiomics features, had an ACC value of 0.82, the radiomics model, with three radiomics features, had an ACC value of 0.82, and the clinical model, with its initial features, had an ACC value of 0.6 for prediction performance. Conclusion: The findings show that radiomics and dosiomics features are correlated with the G4RIL of NPC patients. The model incorporating radiomics features and dosiomics features from planning CT can predict the incidence of G4RIL in NPC patients.

Integrative analyses reveal biological function and prognostic role of m7G methylation regulators in high-grade glioma.

Based on 29 m7G regulators, glioma patients were categorized into three groups using data from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets. Distinct characteristics were observed in immune cell infiltration, functional enrichment, and clinical prognosis for every glioma subtype. Analyzing the differentially expressed genes (DEGs) confirmed the distinction among the three m7G clusters. A predictive tool for overall survival (OS) in high-grade glioma patients was developed and confirmed, consisting of 13 m7G regulators forming a prognostic signature. Elevated m7G levels were found to be associated with increased tumor mutation burden and immune activation, indicating a tumor microenvironment characterized by inflammation and a lower overall survival rate. In contrast, reduced m7G scores were linked to a deficiency in immune infiltration, a low burden of mutations, and a non-inflamed phenotype, suggesting a more positive clinical outlook. Additionally, the m7G risk scores were found to impact chemotherapy sensitivity. The m7G predictive pattern shows potential as a marker for the overall survival of patients with high-grade glioma. By significantly improving our comprehension of the functional role of m7G regulators in the advancement of glioma and their impact on clinical results, this study offers valuable perspectives for precision therapy in the management of high-grade glioma.

CT-based radiomics for predicting radio-chemotherapy response and overall survival in nonsurgical esophageal carcinoma.

Background: To predict treatment response and 2 years overall survival (OS) of radio-chemotherapy in patients with esophageal cancer (EC) by radiomics based on the computed tomography (CT) images. Methods: This study retrospectively collected 171 nonsurgical EC patients treated with radio-chemotherapy from Jan 2010 to Jan 2019. 80 patients were randomly divided into training (n=64) and validation (n=16) cohorts to predict the radiochemotherapy response. The models predicting treatment response were established by Lasso and logistic regression. A total of 156 patients were allocated into the training cohort (n=110), validation cohort (n=23) and test set (n=23) to predict 2-year OS. The Lasso Cox model and Cox proportional hazards model established the models predicting 2-year OS. Results: To predict the radiochemotherapy response, WFK as a radiomics feature, and clinical stages and clinical M stages (cM) as clinical features were selected to construct the clinical-radiomics model, achieving 0.78 and 0.75 AUC (area under the curve) in the training and validation sets, respectively. Furthermore, radiomics features called WFI and WGI combined with clinical features (smoking index, pathological types, cM) were the optimal predictors to predict 2-year OS. The AUC values of the clinical-radiomics model were 0.71 and 0.70 in the training set and validation set, respectively. Conclusions: This study demonstrated that planning CT-based radiomics showed the predictability of the radiochemotherapy response and 2-year OS in nonsurgical esophageal carcinoma. The predictive results prior to treatment have the potential to assist physicians in choosing the optimal therapeutic strategy to prolong overall survival.

P53-response circRNA_0006420 aggravates lung cancer radiotherapy resistance by promoting formation of HUR/PTBP1 complex.

BACKGROUND: p53 wild-type lung cancer cells can develop radiation resistance. Circular RNA (circRNA) consists of a family of transcripts with exclusive structures. circRNA is critical in tumorigenesis and is a potential biomarker or therapeutic target. It is uncertain how circRNA expression and functions are regulated post-radiation in p53 wild-type cancer cells. METHODS: A549 or H1299 cells were divided into p53-wt and p53-KO groups by CRISPR/Cas9; both groups were subjected to 4 Gy ionizing radiation (IR: p53-wt-IR and p53-KO-IR). RNA-seq, CCK8, cell cycle, and other functional and mechanism experiments were performed in vivo. p53 gene knockout mice were generated to test the cell results in vitro. RESULTS: circRNAs were found in differential groups. circRNA_0006420 (IRSense) was upregulated in p53-wt cells but had the same expression level as p53-KO cells after radiation, indicating that p53 silencing prevents its upregulation after IR. In the presence of p53, upregulated IRSense post-radiation induces G2/M arrest by regulating DNA damage repair (DDR) pathway-related proteins. Meanwhile, upregulated IRSense post-radiation aggravates the radiation-induced epithelial-mesenchymal transition (EMT). Interestingly, in the presence of p53, it promotes IRSense/HUR/PTBP1 complex formation resulting in the promotion of the radiation-induced EMT. Moreover, c-Jun regulates the upregulation of p53 transcription after radiation treatment. For these lung cancer cells with p53, upregulated IRSense aggravates lung cancer cell proliferation and increases radiation resistance by interacting with HUR (ElAV-like protein 1) and PTBP1 (polypyrimidine tract-binding protein 1) in the nucleus. CONCLUSIONS: Lung cancer cells retaining p53 may upregulate circRNA_0006420 (IRSense) expression post radiation to form an IRSense/HUR/PTBP1 complex leading to radiotherapy resistance. This study furthers our understanding of the roles of circRNA in regulating the effect of radiotherapy and provides novel therapeutic avenues for effective clinical lung cancer therapies.

Prognostic analysis and nomogram construction for older patients with IDH-wild-type glioblastoma.

As many countries face an ageing population, the number of older patients with glioblastoma (GB) is increasing. Thus, there is an urgent need for prognostic models to aid in treatment decision-making and life planning. A total of 98 patients with isocitrate dehydrogenase (IDH)-wild-type GB aged ≥65 years were analysed from January 2012 to January 2020. Independent prognostic factors were identified by prognostic analysis. Using the independent prognostic factors for overall survival (OS), a nomogram was constructed by R software to predict the prognosis of older patients with IDH-wild-type GB. The concordance index (C-index) and receiver operating characteristic (ROC) curve were used to assess model discrimination, and the calibration curve was used to assess model calibration. Prognostic analysis showed that the extent of resection (EOR), adjusted Charlson comorbidity index (ACCI), O6-methylguanine-DNA methyltransferase (MGMT) methylation status, postoperative radiotherapy, and postoperative temozolomide (TMZ) chemotherapy were independent prognostic factors for OS. MGMT methylation status and subventricular zone (SVZ) involvement were independent prognostic factors for progression-free survival (PFS). A nomogram was constructed based on EOR, ACCI, MGMT methylation status, postoperative radiotherapy and postoperative TMZ chemotherapy to predict the 6-month, 12-month and 18-month OS of older patients with IDH-wild-type GB. The C-index of the nomogram was 0.72, and the ROC curves showed that the areas under the curve (AUCs) at 6, 12 and 18 months were 0.874, 0.739 and 0.779, respectively. The calibration plots showed that the nomogram was in good agreement with the actual observations in predicting the OS of older patients with IDH-wild-type GB. Older patients with IDH-wild-type GB can benefit from gross total resection (GTR), postoperative radiotherapy and postoperative TMZ chemotherapy. A high ACCI score and MGMT nonmethylation are poor prognostic factors. We constructed a nomogram including the ACCI to facilitate clinical decision-making and follow-up interval selection.

Cascaded Nanozyme with In Situ Enhanced Photothermal Capacity for Tumor-Specific and Self-Replenishing Cancer Therapy.

Reactive oxygen species (ROS)-involved tumor therapeutic strategy, chemodynamic therapy (CDT), has attracted extensive research interest in the scientific community. However, the therapeutic effect of CDT is insufficient and unsustainable owing to the limited endogenous H2 O2 level in the tumor microenvironment. Here, peroxidase (POD)-like RuTe2 nanozyme with the immobilization of glucose oxidase (GOx) and allochroic 3,3',5,5'-tetramethylbenzidine (TMB) molecule have been synthesized to construct RuTe2 -GOx-TMB nanoreactors (RGT NRs) as cascade reaction systems for tumor-specific and self-replenishing cancer therapy. GOx in sequential nanocatalysts can effectively deplete glucose in tumor cells. Meanwhile, a sustainable supply of H2 O2 for subsequent Fenton-like reactions catalyzed by RuTe2 nanozyme is achieved in response to the mild acidic tumor microenvironment. Through this cascade reaction, highly toxic hydroxyl radicals (·OH) are produced, which can further oxidize TMB to trigger tumor-specific "turn-on" photothermal therapy (PTT). In addition, PTT and massive ROS can stimulate the tumor immune microenvironment and activate the systematic anti-tumor immune responses, exerting a notable effect on hindering tumor recurrence and metastasis. This study paves a promising paradigm for synergistic starvation therapy, PTT, and CDT cancer therapy with high efficiency.

FDX1 serves as a prognostic biomarker and promotes glioma progression by regulating the immune response.

The present study investigates the prognostic value of the FDX1 gene and its association with immune infiltration in gliomas. Gene expression profiles and corresponding clinical parameters of glioma patients were obtained from the Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. In vitro experiments were also performed to validate its impact on malignant phenotypes of glioma cells. Kaplan-Meier analysis demonstrated that high FDX1 expression was associated with poor prognosis in glioma. Function and pathway enrichment for FDX1 predominantly demonstrated immunomodulatory function. In addition, the high-FDX1 expression group had higher Estimation of Stromal and Immune cells in malignant tumor tissues using Expression data, stromal, and immune scores (p<0.001). On evaluation of immunotherapy response, TIDE and dysfunction scores were higher in the low-FDX1 group, while the exclusion score demonstrated an opposite trend. In vitro tests showed that FDX1 silencing-induced inhibition of cell invasion and migration inactivated the nucleotide oligomerization domain (NOD)-like receptor signaling pathway by regulating PD-L1 expression. Notably, NOD1 expression was reversed in FDX1-knockdown cells after treatment with NOD1 agonists. In conclusion, FDX1 may play an important role in the diagnosis and treatment of gliomas. Regulating its expression may therefore help improve immunotherapy for these tumors.

Pan-cancer analysis identifies the correlations of Thymosin Beta 10 with predicting prognosis and immunotherapy response.

Introduction: The biological function and prognosis roles of thymosin ß(TMSB) 10 are still unclear in pan-cancer. Methods: We retrieved The Cancer Genome Atlas and Genotype-tissue expression datasets to obtain the difference of TMSB10 expression between pan-cancer and normal tissues, and analyzed the biological function and prognosis role of TMSB10 in pan-cancer by using cBioPortal Webtool. Results: The expression of TMSB10 in tumor tissues was significantly higher than normal tissues, and showed the potential ability to predict the prognosis of patients in Pan-cancer. It was found that TMSB10 was significantly correlated with tumor microenvironment, immune cell infiltration and immune regulatory factor expression. TMSB10 is involved in the regulation of cellular signal transduction pathways in a variety of tumors, thereby mediating the occurrence of tumor cell invasion and metastasis. Finally, TMSB10 can not only effectively predict the anti-PD-L1 treatment response of cancer patients, but also be used as an important indicator to evaluate the sensitivity of chemotherapy. In vitro, low expression of TMSB10 inhibited clonogenic formation ability, invasion, and migration in glioma cells. Furthermore, TMSB10 may involve glioma immune regulation progression by promoting PD-L1 expression levels via activating STAT3 signaling pathway. Conclusions: Our results show that TMSB10 is abnormally expressed in tumor tissues, which may be related to the infiltration of immune cells in the tumor microenvironment. Clinically, TMSB10 is not only an effective prognostic factor for predicting the clinical treatment outcome of cancer patients, but also a promising biomarker for predicting the effect of tumor immune checkpoint inhibitors (ICIs) and chemotherapy in some cancers.

Prognosis Forecast of Re-Irradiation for Recurrent Nasopharyngeal Carcinoma Based on Deep Learning Multi-Modal Information Fusion.

Radiation therapy is the primary treatment for recurrent nasopharyngeal carcinoma. However, it may induce necrosis of the nasopharynx, leading to severe complications such as bleeding and headache. Therefore, forecasting necrosis of the nasopharynx and initiating timely clinical intervention has important implications for reducing complications caused by re-irradiation. This research informs clinical decision-making by making predictions on re-irradiation of recurrent nasopharyngeal carcinoma using deep learning multi-modal information fusion between multi-sequence nuclear magnetic resonance imaging and plan dose. Specifically, we assume that the hidden variables of model data can be divided into two categories: task-consistency and task-inconsistency. The task-consistency variables are characteristic variables contributing to target tasks, while the task-inconsistency variables are not apparently helpful. These modal characteristics are adaptively fused when the relevant tasks are expressed through the construction of supervised classification loss and self-supervised reconstruction loss. The cooperation of supervised classification loss and self-supervised reconstruction loss simultaneously reserves the information of characteristic space and controls potential interference simultaneously. Finally, multi-modal fusion effectively fuses information through an adaptive linking module. We evaluated this method on a multi-center dataset. and found the prediction based on multi-modal features fusion outperformed predictions based on single-modal, partial modal fusion or traditional machine learning methods.

Integrative Analysis of the Predictive Value of Perilipin Family on Clinical Significance, Prognosis and Immunotherapy of Glioma.

Gliomas are common tumors of the central nervous system. The PLINs family is widely involved in the regulation of lipid metabolism and has been associated with the development and invasive metastasis of various malignancies. However, the biological role of the PLINs family in gliomas is still unclear. TIMER and UALCAN were used to assess PLINs mRNA expression in gliomas. "Survminer" and "Survival" were used to evaluate the connection between PLINs expression and glioma patients' survival. cBioPortal was applied to assess PLINs' genetic alterations in glioblastoma multiforme (GBM) and low-grade glioma (LGG). The correlation of PLINs expression with tumor immune cells was analyzed by TIMER. The expressions of PLIN1, PLIN4, and PLIN5 were decreased in GBM compared to normal tissues. However, PLIN2 and PLIN3 were significantly increased in GBM. Prognostic analysis showed that LGG patients with high PLIN1 expression had better overall survival (OS), and high expression of PLIN2/3/4/5 was associated with unfavorable OS. We further determined that the expression of PLINs members in gliomas was strongly related to tumor immune cells and immune checkpoint-associated genes. PLINS may be potential biomarkers for regulating the tumor microenvironment and predicting the efficacy of immunotherapy. In addition, we determined that PLIN1 may affect glioma patients' therapeutic sensitivity to temozolomide. Our results demonstrated the biological significance and clinical values of PLINs in gliomas and provide a basis for future in-depth exploration of the specific mechanisms of each member of PLINs in gliomas.

Contribution of whole slide imaging-based deep learning in the assessment of intraoperative and postoperative sections in neuropathology.

The pathological diagnosis of intracranial germinoma (IG), oligodendroglioma, and low-grade astrocytoma on intraoperative frozen section (IFS) and hematoxylin-eosin (HE)-staining section directly determines patients' treatment options, but it is a difficult task for pathologists. We aimed to investigate whether whole-slide imaging (WSI)-based deep learning can contribute new precision to the diagnosis of IG, oligodendroglioma, and low-grade astrocytoma. Two types of WSIs (500 IFSs and 832 HE-staining sections) were collected from 379 patients at multiple medical centers. Patients at Center 1 were split into the training, testing, and internal validation sets (3:1:1), while the other centers were the external validation sets. First, we subdivided WSIs into small tiles and selected tissue tiles using a tissue tile selection model. Then a tile-level classification model was established, and the majority voting method was used to determine the final diagnoses. Color jitter was applied to the tiles so that the deep learning (DL) models could adapt to the variations in the staining. Last, we investigated the effectiveness of model assistance. The internal validation accuracies of the IFS and HE models were 93.9% and 95.3%, respectively. The external validation accuracies of the IFS and HE models were 82.0% and 76.9%, respectively. Furthermore, the IFS and HE models can predict Ki-67 positive cell areas with R2 of 0.81 and 0.86, respectively. With model assistance, the IFS and HE diagnosis accuracy of pathologists improved from 54.6%-69.7% and 53.5%-83.7% to 87.9%-93.9% and 86.0%-90.7%, respectively. Both the IFS model and the HE model can differentiate the three tumors, predict the expression of Ki-67, and improve the diagnostic accuracy of pathologists. The use of our model can assist clinicians in providing patients with optimal and timely treatment options.

HDAC4 mediated LHPP deacetylation enhances its destabilization and promotes the proliferation and metastasis of nasopharyngeal carcinoma.

Studies have shown that acetylation modification plays an important role in tumor proliferation and metastasis. Phospholysine phosphohistidine inorganic pyrophosphate phosphatase (LHPP) is downregulated in certain tumors, as a tumor suppressor role. However, the regulation of LHPP expression and its function in nasopharyngeal carcinoma (NPC) remain unclear. In the present study, we found that LHPP was downregulated in NPC, and overexpression of LHPP inhibited the proliferation and invasion of NPC cells. Mechanistically, HDAC4 deacetylated LHPP at K6 and promoted the degradation of LHPP through TRIM21 mediated K48-linked ubiquitination. HDAC4 was confirmed to be highly expressed in NPC cells and promoted the proliferation and invasion of NPC cells through LHPP. Further research found that LHPP could inhibit the phosphorylation of tyrosine kinase TYK2, thereby inhibiting the activity of STAT1. In vivo, knockdown of HDAC4 or treatment with small molecule inhibitor Tasquinimod targeting HDAC4 could significantly inhibit the proliferation and metastasis of NPC by upregulating LHPP. In conclusion, our finding demonstrated that HDAC4/LHPP signal axis promotes the proliferation and metastasis of NPC through upregulating TYK2-STAT1 phosphorylation activation. This research will provide novel evidence and intervention targets for NPC metastasis.

E3 ligase MAEA-mediated ubiquitination and degradation of PHD3 promotes glioblastoma progression.

Glioblastoma (GBM) is the most common malignant glioma, with a high recurrence rate and a poor prognosis. However, the molecular mechanism behind the malignant progression of GBM is still unclear. In the present study, through the tandem mass tag (TMT)-based quantitative proteomic analysis of clinical primary and recurrent glioma samples, we identified that aberrant E3 ligase MAEA was expressed in recurrent samples. The results of bioinformatics analysis showed that the high expression of MAEA was related to the recurrence and poor prognosis of glioma and GBM. Functional studies showed that MAEA could promote proliferation, invasion, stemness and temozolomide (TMZ) resistance. Mechanistically, the data indicated that MAEA targeted prolyl hydroxylase domain 3 (PHD3) K159 to promote its K48-linked polyubiquitination and degradation, thus enhancing the stability of HIF-1α, thereby promoting the stemness and TMZ resistance of GBM cells through upregulating CD133. The in vivo experiments further confirmed that knocking down MAEA could inhibit the growth of GBM xenograft tumors. In summary, MAEA enhances the expression of HIF-1α/CD133 through the degradation of PHD3 and promotes the malignant progression of GBM.

Efficacy and safety of KL-A167 in previously treated recurrent or metastatic nasopharyngeal carcinoma: a multicenter, single-arm, phase 2 study.

Background: KL-A167 is a fully humanized monoclonal antibody targeting programmed cell death-ligand 1. This phase 2 study aimed to evaluate the efficacy and safety of KL-A167 in Chinese patients with previously treated recurrent or metastatic (R/M) nasopharyngeal carcinoma (NPC). Methods: This was a multicentre, single-arm, phase 2 study of KL-A167 in R/M NPC (KL167-2-05-CTP) (NCT03848286), conducted at 42 hospitals across the People's Republic of China. Eligible patients had histologically confirmed non-keratinising R/M NPC, and had failed at least two lines of chemotherapy. Patients received KL-A167 900mg intravenously once every 2 weeks until confirmed disease progression, intolerable toxicity, or withdrawal of informed consent. The primary endpoint was objective response rate (ORR) assessed by the independent review committee (IRC) according to RECIST v1.1. Findings: Between Feb 26th, 2019 and Jan 13th, 2021, 153 patients were treated. Totally, 132 patients entered full analysis set (FAS) and were evaluated for the efficacy. As of data cutoff date on Jul 13th, 2021, the median follow-up time was 21.7 months (95%CI 19.8-22.5). For FAS population, the IRC-assessed ORR was 26.5% (95%CI 19.2-34.9%), and disease control rate (DCR) was 56.8% (95%CI 47.9-65.4%). Median progression-free survival (PFS) was 2.8 months (95%CI 1.5-4.1) . Median duration of response was 12.4 months (95%CI 6.8-16.5), and median overall survival (OS) was 16.2 months (95%CI 13.4-21.3). When using the cutoff of 1000 copies/ml, 5000 copies/ml and 10,000 copies/ml for plasma EBV DNA titer, baseline low plasma EBV DNA was consistently related with better DCR, PFS and OS. Dynamic change of plasma EBV DNA was significantly associated with ORR and PFS. Among 153 patients, treatment related-adverse events (TRAEs) occurred in 73.2% of patients, and grade ≥3 TRAEs were in 15.0% of patients. No TRAE leading to death was reported. Conclusion: In this study, KL-A167 showed promising efficacy and an acceptable safety profile in patients with previously treated R/M NPC. Baseline plasma EBV DNA copy number might be a potentially useful prognostic biomarker for KL-A167 treatment, and post-treatment EBV DNA decrease might be correlated with better response to KL-A167. Funding: Sichuan Kelun-Biotech Biopharmaceutical Co., Ltd., China National Major Project for New Drug Innovation (2017ZX09304015).

Integrative analyses reveal prognostic and immunogenic characteristics of m7G methylation regulators in patients with glioma.

OBJECTIVES: The expression profiles, biological mechanisms, and clinical relevance of m7G regulators in glioma were studied in this research. METHODS: Based on the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets, glioma patients, can be categorized into three groups according to 29 m7G regulators, and different subtypes of glioma show different immune cell infiltration characteristics, function enrichment, and clinical prognosis. Three gene clusters were confirmed by utilizing the differentially expressed genes (DEGs) across the three m7G clusters. RESULTS: A prognostic signature based on 12 m7G regulators was established and validated, producing an effective tool for predicting overall survival (OS) in glioma patients. High m7G scores indicated elevated tumor mutation burden and activation of immunity, suggesting an inflamed tumor microenvironment phenotype with poor overall survival. Low m7G scores characterized by a lack of immune infiltration and low mutation burden indicated a non-inflamed phenotype with a favorable clinical prognosis. It was also found that the m7G risk scores can affect chemotherapy sensitivity and prognosis of patients who received immunotherapy. The hub gene EIF4E1B of m7G regulators can inhibit the in vitro progression of glioma cells by regulating PD-L1 expression through p53 signaling pathway-related inactivation. CONCLUSIONS: The m7G prognostic signature can be a biomarker of the overall survival of patients with glioma. An initial in-vitro experiment suggested the potential biological mechanisms of immune regulation, with m7G regulators affecting glioma progression by modulating immune responses. The present research provides a better understanding of how m7G regulators function in glioma progression as well as the impact on clinical outcomes, which can provide new insights that might be beneficial for precision therapy of glioma.

Retraction notice to "Tim-4 promotes the growth of colorectal cancer by activating angiogenesis and recruiting tumor-associated macrophages via the PI3K/AKT/mTOR signaling pathway" [Canc. Lett. 436 (2018) 119-128].

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Emerging role of inositol monophosphatase in cancer.

Inositol monophosphatase (IMPase) is an enzyme with two homologs-IMPA1 and IMPA2-that is responsible for dephosphorylating myo-inositol monophosphate to generate myo-inositol. IMPase has been extensively studied in neuropsychiatric diseases and is regarded as a susceptibility gene. Recently, emerging evidence has implied that IMPase is linked to cancer development and progression and correlates with patient survival outcomes. Interestingly, whether it acts as a tumor-promoter or tumor-suppressor is inconsistent among different research studies. In this review, we summarize the latest findings on IMPase in cancer, focusing on exploring the underlying mechanisms for its pro- and anticancer roles. In addition, we discuss the potential methods of IMPase regulation in cancer cells and the possible approaches for IMPase intervention in clinical practice.