A Reconfigurable DNA Framework Nanotube-Assisted Antiangiogenic Therapy.

A major limitation of tumor antiangiogenic therapy is the pronounced off-target effect, which can lead to unavoidable injury in multiple organs. Ensuring sufficient delivery and controlled release of these antiangiogenic agents at tumor sites is crucial for realizing their clinical application. Here, we develop a smart DNA-based nanodrug, termed Endo-rDFN, by precisely assembling the antiangiogenic agent, endostar (Endo), into a reconfigurable DNA framework nanotube (rDFN) that could recognize tumor-overexpressed nucleolin to achieve the targeted delivery and controllable release of Endo. Endo-rDFN can not only effectively enhance the tumor-targeting capability of Endo and maintain its efficient accumulation in tumor tissues but also achieve on-demand release of Endo at tumor sites via the specific DNA aptamer for tumor-overexpressed nucleolin, named AS1411. We also found that Endo-rDFN exhibited significant inhibition of angiogenesis and tumor growth, while also providing effective protection against multiorgan injury (heart, liver, spleen, kidney, lung, etc.) to some extent, without compromising the function of these organs. Our study demonstrates that rDFN represents a promising vector for reducing antiangiogenic therapy-induced multiorgan injury, highlighting its potential for promoting the clinical application of antiangiogenic agents.

Prognostic value of circulating tumor DNA using target next-generation sequencing in extensive-stage small-cell lung cancer.

BACKGROUND: Chemotherapy remains the mainstay of treatment for small-cell lung cancer (SCLC). Liquid biopsies provide a convenient and non-invasive detection method for monitoring disease progression in patients with SCLC. METHODS: We performed next-generation sequencing of 159 plasma samples from 69 patients with extensive-stage (ES)-SCLC. Circulating tumor (ct)DNA levels were quantified in haploid genome equivalents per mL (hGE/mL). MuTect2 was used to detect single nucleotide variants and short insertions/deletions. The "enrichKEGG" function in the "clusterProfiler" R package was used to enrich the mutated genes that only appeared during disease progression. RESULTS: In our cohort, 66 of 69 (95.7%) plasma samples at the time of diagnosis had detectable somatic mutations; TP53 (89%) and RB1(56%) were the most frequent mutations, as well as copy number variations in some common SCLC-related genes such as RB1. Combination ctDNA and tissue testing improved the overall detection rate of actionable mutations from 19.4% to 26.9% compared with that of tissue detection alone. In addition, ctDNA levels changed dynamically during the course of treatment and were significantly associated with decreased progression-free survival. Notably, actionable mutations were detected at the time of diagnosis and during disease progression. CONCLUSIONS: Our study revealed a dynamic somatic mutation profile through continuous ctDNA detection and confirmed that ctDNA levels can reflect tumor burden and predict PFS in patients with extensive stage-SCLC. Furthermore, we demonstrated that plasma ctDNA assays can provide real-time information on somatic mutations for potential targeted therapies for SCLC.

Identifying CDC7 as a synergistic target of chemotherapy in resistant small-cell lung cancer via CRISPR/Cas9 screening.

There is currently a lack of efficacious treatments for patients with chemo-resistant small-cell lung cancer (SCLC), leading to poor prognoses. We examined a chemo-resistant SCLC cell line using genome-wide CRISPR/Cas9 screening and identified serine/threonine kinase cell division cycle 7 (CDC7) as a potential synergistic target. Silencing CDC7 in chemo-resistant SCLC cells decreased the IC50 and improved the efficacy of chemotherapy. Based on the highest single agent model, the CDC7 inhibitor XL413 had a synergistic effect with both cisplatin and etoposide in chemo-resistant SCLC cells, but had no such effect in chemo-sensitive SCLC cells; the combination of XL413 and chemotherapy significantly inhibited cell growth. Western blot and flow cytometry showed that the combined treatments increased apoptosis, whereas XL413 alone had little effect on apoptosis. An analysis of cell cycle and cyclin protein levels indicated that the combination of XL413 and chemotherapy-induced G1/S phase arrest and DNA damage in chemo-resistant SCLC cells. Xenografted tumor and histoculture drug response assays using patient-derived xenografts showed that XL413 improved the efficacy of chemotherapy in vivo and with SCLC tissues. These results suggest that XL413 exerts a synergistic effect with chemotherapy on chemo-resistant SCLC.

An accurate prediction of the origin for bone metastatic cancer using deep learning on digital pathological images.

BACKGROUND: Determining the origin of bone metastatic cancer (OBMC) is of great significance to clinical therapeutics. It is challenging for pathologists to determine the OBMC with limited clinical information and bone biopsy. METHODS: We designed a regional multiple-instance learning algorithm to predict the OBMC based on hematoxylin-eosin (H&E) staining slides alone. We collected 1041 cases from eight different hospitals and labeled 26,431 regions of interest to train the model. The performance of the model was assessed by ten-fold cross validation and external validation. Under the guidance of top3 predictions, we conducted an IHC test on 175 cases of unknown origins to compare the consistency of the results predicted by the model and indicated by the IHC markers. We also applied the model to identify whether there was tumor or not in a region, as well as distinguishing squamous cell carcinoma, adenocarcinoma, and neuroendocrine tumor. FINDINGS: In the within-cohort, our model achieved a top1-accuracy of 91.35% and a top3-accuracy of 97.75%. In the external cohort, our model displayed a good generalizability with a top3-accuracy of 97.44%. The top1 consistency between the results of the model and the immunohistochemistry markers was 83.90% and the top3 consistency was 94.33%. The model obtained an accuracy of 98.98% to identify whether there was tumor or not and an accuracy of 93.85% to differentiate three types of cancers. INTERPRETATION: Our model demonstrated good performance to predict the OBMC from routine histology and had great potential for assisting pathologists with determining the OBMC accurately. FUNDING: National Science Foundation of China (61875102 and 61975089), Natural Science Foundation of Guangdong province (2021A15-15012379 and 2022A1515 012550), Science and Technology Research Program of Shenzhen City (JCYJ20200109110606054 and WDZC20200821141349001), and Tsinghua University Spring Breeze Fund (2020Z99CFZ023).

Ligand-independent EphA2 contributes to chemoresistance in small-cell lung cancer by enhancing PRMT1-mediated SOX2 methylation.

Chemoresistance is the crux of clinical treatment failure of small-cell lung cancer (SCLC). Cancer stem cells play a critical role in therapeutic resistance of malignant tumors. Studies have shown that the role of erythropoietin-producing hepatocellular A2 (EphA2) in tumors is complex. This study aimed to test the hypothesis that ligand-independent activation of EphA2 modulates chemoresistance by enhancing stemness in SCLC. We verified that EphA2 was activated in chemoresistance sublines in a ligand-independent manner rather than a ligand-dependent manner. Ligand-independent EphA2 enhanced the expression of stemness-associated biomarkers (CD44, Myc, and SOX2), accelerated epithelial-mesenchymal transition (EMT) and reinforced self-renewal to drive the chemoresistance of SCLC, while the P817H mutant EphA2 neutralized intrinsic function. Co-immunoprecipitation (co-IP) and GST-pull down experiments were conducted to verify that EphA2 directly interacted with PRMT1. Moreover, EphA2 increased the expression and activity of PRMT1. Whereafter, PRMT1 interacted with and methylated SOX2 to induce stemness and chemoresistance in SCLC. Pharmacological inhibition of EphA2 showed a synergistic anti-tumor effect with chemotherapy in preclinical models, including patient-derived xenograft (PDX) models. These findings highlight, for the first time, that the EphA2/PRMT1/SOX2 pathway induces chemoresistance in SCLC by promoting stemness. EphA2 is a potential therapeutic target in SCLC treatment.

Identification of key genes and pathway related to chemoresistance of small cell lung cancer through an integrative bioinformatics analysis.

Background: Small cell lung cancer (SCLC), the most malignant of all the lung cancer subtypes, is characterized by drug resistance. This study sought to explore the key genes and pathways associated with the chemoresistance of SCLC. Methods: The drug sensitivity of chemosensitive and chemoresistance SCLC cell lines was measured by Cell Counting Kit-8 assays. The total RNA from chemosensitive cell line H69 and chemoresistance cell line H69AR cells was extracted and subjected to messenger RNA (mRNA) and long non-coding RNA (lncRNA) microarray analyses. The differentially expressed genes (DEGs) and the differentially expressed lncRNAs (DELs) were screened out with a threshold of a |log fold change | ≥1 and an adjusted P value <0.05. A protein-protein interaction network was constructed, and hub genes were screened out. A lncRNA-mRNA co-expression network was also constructed. Gene Ontology and Kyoto Encyclopedia of Genes, Genomes enrichment analyses and Cis-regulatory element analyses were conducted on the DEGs and the top 10 upregulated DEL-co-expressed DEGs. The expression of the key genes was further analyzed in the GSE149507 data set and validated in H69/H69AR and H446/H446DDP cells by quantitative polymerase chain reaction assays. Results: The microarray results showed that a total of 609 mRNAs and 394 lncRNAs were differentially expressed in the chemoresistant SCLC cells. The mammalian target of rapamycin (mTOR) signaling pathway was enriched among the DEGs, the top 10 upregulated DEL-co-expressed DEGs, and the NCRNA00173-co-expressed DEGs, which included IGF1, INS, WNT6, WNT11, WNT2B, and SESN2. IGF1, WNT2B, and SESN2 were downregulated, and WNT11 was upregulated in the SCLC tumor tissues in the GSE149507 data set. Further, IGF1, WNT6, WNT11, and WNT2B were lowlier expressed and SESN2 and NCRNA00173 were more highly expressed in the chemoresistant cells than sensitive cells. Conclusions: The top 10 upregulated DELs containing NCRNA00173 may be involved in the regulation of drug resistance in SCLC. These DELs may regulate the genes related to the mTOR signaling pathway. These genes may also be biomarkers and potential targets for the treatment of SCLC.

A machine learning model for grade 4 lymphopenia prediction during pelvic radiotherapy in patients with cervical cancer.

Background/purpose: Severe lymphopenia during pelvic radiotherapy (RT) predicts poor survival in patients with cervical cancer. However, the risk of severe lymphopenia has not been well predicted. We developed a machine learning model using clinical and dosimetric information to predict grade 4 (G4) lymphopenia during pelvic RT in patients with cervical cancer. Methods: This retrospective study included cervical cancer patients treated with definitive pelvic RT ± induction/concurrent chemotherapy. Clinical information and a set of dosimetric parameters of external beam radiotherapy plan were collected. G4 lymphopenia during RT, which was also referred to as G4 absolute lymphocyte count (ALC) nadir, was defined as ALC nadir <0.2 × 109 cells/L during RT according to Common Terminology Criteria for Adverse Events (CTCAE) v4.03. Elastic-net logistic regression models were constructed for the prediction of G4 lymphopenia during pelvic RT using a repeated cross-validation methodology. Results: A total of 130 patients were eligible, and 43 (33.1%) patients had G4 lymphopenia during RT. On multivariable analysis, G4 ALC nadir was associated with poor overall survival (OS) [hazard ratio (HR), 3.91; 95% confidence interval (CI), 1.34-11.38, p = 0.01]. Seven significant factors [Eastern Cooperative Oncology Group (ECOG) performance score, pre-RT hemoglobin, pre-RT lymphocytes, concurrent chemotherapy, gross tumor volume of regional lymphadenopathy (GTV_N volume), body volume, and maximum dose of planning target volume receiving at least 55 Gy (PTV_5500 Dmax)] were obtained by elastic-net logistic regression models and were included in the final prediction model for G4 ALC nadir. The model's predicting ability in test set was area under the curve (AUC) = 0.77 and accuracy = 0.76. A nomogram of the final predicting model was constructed. Conclusions: This study developed and validated a comprehensive model integrating clinical and dosimetric parameters by machine learning method, which performed well in predicting G4 lymphopenia during pelvic RT for cervical cancer and will facilitate physicians to identify patients at high risk of G4 lymphopenia who might benefit from modified treatment approaches.

HuR affects chemoresistance of small cell lung cancer by regulating FGFRL1 expression.

Human antigen R (HuR), an RNA-binding protein, has been demonstrated to serve an oncogenic role in various types of cancer. Fibroblast growth factor receptor-like 1 (FGFRL1) has been shown to regulate small cell lung cancer (SCLC) chemoresistance. In the present study, the role of HuR in chemoresistance of SCLC, as well as its possible molecular mechanism involving FGFRL1, was explored by reverse transcription-quantitative PCR, western blotting, Cell Counting Kit-8 assay, flow cytometry and RNA immunoprecipitation. The results revealed that HuR expression levels were markedly upregulated in drug-resistant SCLC cell lines (H69AR and H446DDP) compared with in the parental cell lines (H69 and H446). Knockdown of HuR in drug-resistant SCLC cells enhanced drug sensitivity, cell apoptosis and cell cycle arrest. Furthermore, molecular mechanism studies indicated that HuR could bind and regulate FGFRL1 expression levels to increase FGFRL1 mRNA stability. Taken together, the present study suggested that HuR may mediate chemoresistance of SCLC by regulating FGFRL1 expression. HuR may represent a prognostic predictor and a potential target for overcoming chemoresistance in SCLC.

Single-Cell RNA-Sequencing Atlas Reveals the Tumor Microenvironment of Metastatic High-Grade Serous Ovarian Carcinoma.

Ovarian cancer is the most common and lethal gynecological tumor in women worldwide. High-grade serous ovarian carcinoma (HGSOC) is one of the histological subtypes of epithelial ovarian cancer, accounting for 70%. It often occurs at later stages associated with a more fatal prognosis than endometrioid carcinomas (EC), another subtype of epithelial ovarian cancer. However, the molecular mechanism and biology underlying the metastatic HGSOC (HG_M) immunophenotype remain poorly elusive. Here, we performed single-cell RNA sequencing analyses of primary HGSOC (HG_P) samples, metastatic HGSOC (HG_M) samples, and endometrioid carcinomas (EC) samples. We found that ERBB2 and HOXB-AS3 genes were more amplified in metastasis tumors than in primary tumors. Notably, high-grade serous ovarian cancer metastases are accompanied by dysregulation of multiple pathways. Malignant cells with features of epithelial-mesenchymal transition (EMT) affiliated with poor overall survival were identified. In addition, cancer-associated fibroblasts with EMT-program were enriched in HG_M, participating in angiogenesis and immune regulation, such as IL6/STAT3 pathway activity. Compared with ECs, HGSOCs exhibited higher T cell infiltration. PRDM1 regulators may be involved in T cell exhaustion in ovarian cancer. The CX3CR1_macro subpopulation may play a role in promoting tumor progression in ovarian cancer with high expression of BAG3, IL1B, and VEGFA. The new targets we discovered in this study will be useful in the future, providing guidance on the treatment of ovarian cancer.

Relationship between ATOH1 and tumor microenvironment in colon adenocarcinoma patients with different microsatellite instability status.

BACKGROUND: Colon adenocarcinoma (COAD) is one of the major varieties of malignant tumors threatening human health today. Immune checkpoint inhibitors (ICIs) have recently begun to emerge as an effective option for the treatment of COAD patients, but not all patients can benefit from ICI treatment. Previous studies have suggested that ICIs boast significant clinical effects on patients with microsatellite instability-high (MSI-H), while conversely patients with microsatellite-stable/microsatellite instability-low (MSS/MSI-L) have shown limited response. METHODS: We used ATAC-seq, RNA-seq, and mutation data from The Cancer Genome Atlas Colon adenocarcinoma (TCGA-COAD) cohort to perform multi-omics differential analysis on COAD samples with different MSI statuses, then further screened genes by additionally combining these results with survival analysis. We analyzed the effects of the screened genes on the tumor microenvironment and immunogenicity of COAD patients, and subsequently determined their influence on the efficacy of ICIs in COAD patients using a series of predictive indexes. RESULTS: Twelve genes were screened in the TCGA-COAD cohort, and after the combined survival analysis, we identified ATOH1 as having significant effects. ATOH1 is characterized by high chromatin accessibility, high expression, and high mutation in COAD patients in the MSI-H group. COAD patients with high ATOH1 expression are associated with a better prognosis, unique immune microenvironment, and higher efficacy in ICI treatment. Enrichment analysis showed that COAD patients with high ATOH1 expression displayed significant upregulation in their humoral immunity and other related pathways. CONCLUSIONS: We speculate that ATOH1 may influence the efficacy of ICIs therapy in patients with COAD by affecting the immune microenvironment and immunogenicity of the tumor.

Bioinformatic Analysis of Prognostic Value of SNTG2 with Immune Implications in Lung Adenocarcinoma.

Background: Lung cancer is the most morbid and fatal cancer in the world, and nearly 85% of lung cancer is non-small cell lung cancer (NSCLC). Besides traditional chemotherapies, molecular targeted therapies and immunotherapies are increasing rapidly, but the treatment is still unsatisfactory. The study is to identify a new diagnostic and prognostic biomarker. Methods: Data including mRNA expression and clinical information of lung adenocarcinoma (LUAD) patients were downloaded from The Cancer Genome Atlas (TCGA) database. Receiver operating characteristic (ROC) curve was constructed to assess the diagnostic value of syntrophin-γ2 (SNTG2) expression and Kaplan-Meier (KM) survival curves were used to compare the survival disparities. The protein-protein interaction (PPI) network was analysed by Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and the connections between SNTG2 and immune cell infiltration were found with Tumor Immunoassay Resource (TIMER). Genetic mutation in SNTG2 and its association with overall survival (OS) were evaluated by cBioPortal. The relationship between SNTG2 and methylation and its association with overall survival were evaluated by MethSurv. Chi square and Mann-Whitney tests were used for statistical analyses. Xiantao Academic Online Website was used for online analysis. Results: Our results revealed that SNTG2 mRNA expression was lower in LUAD tissues than in both adjacent and non-adjacent normal tissues and low SNTG2 mRNA expression was verified to be correlated with histological grade, clinical stage, first therapy outcome and poor overall survival of LUAD. Next, ROC curve revealed diagnostic and prognostic value of SNTG2 for LUAD patients. Moreover, SNTG2 presented correlation with immune cell infiltration and immune checkpoints. Then, we revealed CC chemokine ligand 14 (CCL14), a co-expression gene with SNTG2, which has consistent influence with SNTG2. Furthermore, hypomethylation was found to be associated with high SNTG2 expression. Conclusion: We revealed a potential diagnostic and prognostic indicator in LUAD and analyzed its influence on immunotherapy.

Genomic and immunological profiles of small-cell lung cancer between East Asians and Caucasian.

The characterization of immunological and genomic differences in small-cell lung cancer (SCLC) between East Asian (EA) and Caucasian patients can reveal important clinical therapies for EA patients with SCLC. By sequencing and analyzing a molecular and immunological dataset of 98-SCLC patients of EA ancestry, immunogenicity, including DNA damage repair alterations and tumor mutation burden (TMB), was found to be significantly higher in the EA cohort than in the Caucasian cohort. The epithelial-mesenchymal transition (EMT) was the signaling signature with the predominant frequency of mutations across all patients in the EA cohort. Analysis of tumor-infiltrated immune cells revealed that resting lymphocytes were significantly enriched in the EA cohort. Compound-targeting analysis showed that topoisomerase inhibitors might be capable of targeting TP53 and RB1 comutations in EA SCLC patients. EA SCLC patients who harbored COL6A6 mutations had poor survival, while Caucasian SCLC patients with OTOF, ANKRD30B, and TECPR2 mutations were identified to have a shorter survival.

CCL5 as a Prognostic Marker for Survival and an Indicator for Immune Checkpoint Therapies in Small Cell Lung Cancer.

The standard treatment for small cell lung cancer (SCLC) has not changed in decades. Recently, important advances have been made in immunotherapy. However, analysis of these trials suggests that only a small proportion of patients benefit from immune checkpoint blockade (ICB). Identifying these patients is a clinical challenge. In this study, we applied the ESTIMATE calculation to calculate immune scores in 159 cases of SCLC from two published cohorts. COX regression analysis was used to analyze the differentially expressed genes (DEGs) with high and low immune score. We found that CCL5 expression was positively correlated with survival in SCLC patients. In addition, we verified the effect of CCL5 on survival and response to treatment in another cohort that received immunotherapy. Meanwhile, Gene set enrichment analysis (GSEA) showed that genes with high expression of CCL5 were mainly enriched in immune-related activities. The result of Tumor Immune Dysfunction and Exclusion (TIDE) demonstrated that CCL5 was a potential biomarker to predict response to ICB for SCLC, which is correspondent with the result in verified cohort. These results suggest that CCL5 may be the reason for TME to maintain its immune dominance, making it a favorable factor for ICB. Therefore, CCL5 levels may help to outline the prognosis of patients with SCLC.

Early onset of severe lymphopenia during definitive radiotherapy correlates with mean body dose and predicts poor survival in cervical cancer.

BACKGROUND: Lymphopenia during definitive radiotherapy (RT) has been shown to reduce survival in patients with cervical cancer. However, there are few studies on the significance of onset time of lymphopenia during RT in patients with cervical cancer. OBJECTIVE: This study aimed to exam the prognostic significance of early onset of severe lymphopenia (EOSL) during definitive RT in patients with cervical cancer. METHODS: Newly diagnosed cervical cancer patients treated with definitive RT from January 2015 to December 2019 were eligible for this retrospective study. EOSL was defined as first onset of grade 3-4 lymphopenia ⩽ 3 weeks from the start of RT. Mean body dose (MBD) was the mean radiation dose absorbed by the body during the whole course of external beam RT (EBRT) and was directly obtained from the dose volume histogram (DVH) of the EBRT planning. Logistic regression analysis and restricted cubic spline (RCS) models were applied to assess relationships between clinicopathological factors and EOSL. Survival analysis was performed using Kaplan-Meier curves and log-rank test. A COX regression model was developed to predict overall survival (OS). RESULTS: A total of 104 patients were included and 59.6% had EOSL. MBD (P= 0.04), concurrent cisplatin (P= 0.011), and pre-RT absolute lymphocyte count (ALC) (P= 0.001) were associated with EOSL. A linear relationship (P for non-linearity = 0.803) between MBD and risk of EOSL was found. Patients with EOSL had decreased OS (2-yr 75.1% vs 91.1%, P= 0.021) and progression-free survival (PFS) (2-yr 71.2% vs 83.7%, P= 0.071). An OS prediction COX model was developed with C-index of 0.835 and AUC of 0.872. CONCLUSIONS: EOSL during definitive RT correlates with MBD and predicts poor survival in patients with cervical cancer.

Optimization of high-dose methotrexate prophylaxis for central nervous system relapse in diffuse large B-cell lymphoma: a multicenter analysis.

Central nervous system (CNS) relapse of diffuse large B-cell lymphoma (DLBCL) is a rare but devastating event. Intravenous high-dose methotrexate (HD-MTX) is recommended as CNS prophylaxis, but the optimal timing and dose has not been elucidated. Here, we report a multicenter analysis of prophylactic HD-MTX administration for DLBCL. Two hundred eighty-four patients receiving HD-MTX either concurrent with each induction chemotherapy cycle (n = 221) or at the end of induction therapy (EOI, n = 63) were included. Patients with CNS-IPI scoring 4-6, and/or testicular involvement, and/or double/triple hit lymphoma, were stratified into the high-risk group and the others into the moderate-risk group. Concurrent HD-MTX was associated with increased risk of grade 3/4 treatment-related toxicity (OR,1.49; P = 0.006) and subsequent chemotherapy delays (OR, 1.87; P = 0.003) in multivariate analysis. With a median follow-up of 36.0 months, no significant difference in CNS relapse rate was identified between the concurrent and EOI groups (3.2% vs 4.8%, P = 0.34), even in the high-risk group. Analysis on systemic MTX dose suggested that high-dose MTX (≥ 2 g/m2) was associated with better CNS relapse control only in the high-risk group, but not in the moderate-risk group. This study may elucidate the superiority of EOI HD-MTX to some extent. High MTX dose (≥ 2 g/m2) may not be necessary for the moderate-risk patients.

Comprehensive histological imaging of native microbiota in human glioma.

Mounting evidence suggests that distinct microbial communities reside in tumors and play important roles in tumor physiology. Recently, a previous study profiled the composition and localization of intratumoral bacteria using 16S ribosomal DNA (rDNA) sequencing and histological visualization methods across seven tumor types, including human glioblastoma. However, their results based on traditional histological examinations should be further validated considering potential sources of contamination originating from sample collection and processing. Here, we aim to propose a three-dimensional (3D) in situ intratumoral microbiota visualization and quantification protocol avoiding surface contamination and provide a comprehensive histological investigation on local bacteria within human glioma samples. We develop a 3D quantitative in situ intratumoral microbiota imaging strategy, combining tissue clearing, immunofluorescent labeling, optical sectioning microscopy, and image processing, to visualize bacterial lipopolysaccharide (LPS) within gliomas in a direct, contaminant-free, and unambiguous manner. Through an automated statistical algorithm, reliable signals can be distinguished for further analysis of their sizes, distribution, and fluorescence intensities. In tandem, we also combined 2D images obtained from thin-section histological methods, including immunohistochemistry and fluorescence in situ hybridization, to provide comprehensive histological imaging for local bacterial components within human glioma samples. We have, for the first time, achieved 3D quantitative imaging of bacterial LPS colonized in gliomas in a contamination-free manner within human glioma samples. We also built the multiple histological evidence chain demonstrating the irregular shapes and sparse distribution of bacterial components within human glioma samples, mostly localized near nuclear membranes or in the intercellular space. This study provides favorable evidence for the presence of microbiota in human gliomas and provides information on the feature and distribution of bacterial components. The results, along with the integrated 3D quantitative intratumoral microbiota imaging method, are promising to provide insightful information into the direct interactions between the microbial community and the host in the tumor microenvironment.

Hypoxic Characteristic Genes Predict Response to Immunotherapy for Urothelial Carcinoma.

Objective: Resistance to immune checkpoint inhibitors (ICIs) has been a massive obstacle to ICI treatment in metastatic urothelial carcinoma (MUC). Recently, increasing evidence indicates the clinical importance of the association between hypoxia and immune status in tumor patients. Therefore, it is necessary to investigate the relationship between hypoxia and prognosis in metastatic urothelial carcinoma. Methods: Transcriptomic and clinical data from 348 MUC patients who underwent ICI treatment from a large phase 2 trial (IMvigor210) were investigated in this study. The cohort was randomly divided into two datasets, a training set (n = 213) and a testing set (n = 135). Data of hypoxia-related genes were downloaded from the molecular signatures database (MSigDB), and screened by univariate and multivariate Cox regression analysis to construct a prognosis-predictive model. The robustness of the model was evaluated in two melanoma cohorts. Furthermore, an external validation cohort, the bladder cancer cohort, from the Cancer Genome Atlas (TCGA) database, was t used to explore the mechanism of gene mutation, immune cell infiltration, signaling pathway enrichment, and drug sensitivity. Results: We categorized patients as the high- or low- risk group using a four-gene hypoxia risk model which we constructed. It was found that patients with high-risk scores had significantly worse overall survival (OS) compared with those with low-risk scores. The prognostic model covers 0.71 of the area under the ROC curve in the training set and 0.59 in the testing set, which is better than the survival prediction of MUC patients using the clinical characteristics. Mutation analysis results showed that deletion mutations in RB1, TP53, TSC1 and KDM6A were correlated with hypoxic status. Immune cell infiltration analysis illustrated that the infiltration T cells, B cells, Treg cells, and macrophages was correlated with hypoxia. Functional enrichment analysis revealed that a hypoxic microenvironment activated inflammatory pathways, glucose metabolism pathways, and immune-related pathways. Conclusion: In this investigation, a four-gene hypoxia risk model was developed to evaluate the degree of hypoxia and prognosis of ICI treatment, which showed a promising clinical prediction value in MUC. Furthermore, the hypoxia risk model revealed a close relationship between hypoxia and the tumor immune microenvironment.

WITHDRAWN: lncRNA Linc00173 modulates glucose metabolism and multidrug chemoresistance in SCLC: Potential molecular panel for targeted therapy.

This article has been withdrawn at the request of the editor-in-chief. Following publication of this article, the editor-in-chief discovered evidence of image duplication in Figures 1I, 1J, 3F, S5B, and S6B. Given the duplication of several western blots representing several gene products, the editor-in-chief has lost faith in the findings presented in this article. The authors maintain that these image duplications were the result of errors in file management and do not affect the conclusions of the study. The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/our-business/policies/article-withdrawal.