Author Correction: Complete biosynthesis of cannabinoids and their unnatural analogues in yeast.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Complete biosynthesis of cannabinoids and their unnatural analogues in yeast.

Cannabis sativa L. has been cultivated and used around the globe for its medicinal properties for millennia1. Some cannabinoids, the hallmark constituents of Cannabis, and their analogues have been investigated extensively for their potential medical applications2. Certain cannabinoid formulations have been approved as prescription drugs in several countries for the treatment of a range of human ailments3. However, the study and medicinal use of cannabinoids has been hampered by the legal scheduling of Cannabis, the low in planta abundances of nearly all of the dozens of known cannabinoids4, and their structural complexity, which limits bulk chemical synthesis. Here we report the complete biosynthesis of the major cannabinoids cannabigerolic acid, Δ9-tetrahydrocannabinolic acid, cannabidiolic acid, Δ9-tetrahydrocannabivarinic acid and cannabidivarinic acid in Saccharomyces cerevisiae, from the simple sugar galactose. To accomplish this, we engineered the native mevalonate pathway to provide a high flux of geranyl pyrophosphate and introduced a heterologous, multi-organism-derived hexanoyl-CoA biosynthetic pathway5. We also introduced the Cannabis genes that encode the enzymes involved in the biosynthesis of olivetolic acid6, as well as the gene for a previously undiscovered enzyme with geranylpyrophosphate:olivetolate geranyltransferase activity and the genes for corresponding cannabinoid synthases7,8. Furthermore, we established a biosynthetic approach that harnessed the promiscuity of several pathway genes to produce cannabinoid analogues. Feeding different fatty acids to our engineered strains yielded cannabinoid analogues with modifications in the part of the molecule that is known to alter receptor binding affinity and potency9. We also demonstrated that our biological system could be complemented by simple synthetic chemistry to further expand the accessible chemical space. Our work presents a platform for the production of natural and unnatural cannabinoids that will allow for more rigorous study of these compounds and could be used in the development of treatments for a variety of human health problems.

FAP positive cancer-associated fibroblasts promote tumor progression and radioresistance in esophageal squamous cell carcinoma by transferring exosomal lncRNA AFAP1-AS1.

Cancer-associated fibroblasts (CAFs) are abundant and heterogeneous stromal cells in the tumor microenvironment, which play important roles in regulating tumor progression and therapy resistance by transferring exosomes to cancer cells. However, how CAFs modulate esophageal squamous cell carcinoma (ESCC) progression and radioresistance remains incompletely understood. The expression of fibroblast activation protein (FAP) in CAFs was evaluated by immunohistochemistry in 174 ESCC patients who underwent surgery and 78 pretreatment biopsy specimens of ESCC patients who underwent definitive chemoradiotherapy. We sorted CAFs according to FAP expression, and the conditioned medium (CM) was collected to culture ESCC cells. The expression levels of several lncRNAs that were considered to regulate ESCC progression and/or radioresistance were measured in exosomes derived from FAP+ CAFs and FAP- CAFs. Subsequently, cell counting kit-8, 5-ethynyl-2'-deoxyuridine, transwell, colony formation, and xenograft assays were performed to investigate the functional differences between FAP+ CAFs and FAP- CAFs. Finally, a series of in vitro and in vivo assays were used to evaluate the effect of AFAP1-AS1 on radiosensitivity of ESCC cells. FAP expression in stromal CAFs was positively correlated with nerve invasion, vascular invasion, depth of invasion, lymph node metastasis, lack of clinical complete response and poor survival. Culture of ESCC cells with CM/FAP+ CAFs significantly increased cancer proliferation, migration, invasion and radioresistance, compared with culture with CM/FAP- CAFs. Importantly, FAP+ CAFs exert their roles by directly transferring the functional lncRNA AFAP1-AS1 to ESCC cells via exosomes. Functional studies showed that AFAP1-AS1 promoted radioresistance by enhancing DNA damage repair in ESCC cells. Clinically, high levels of plasma AFAP1-AS1 correlated with poor responses to dCRT in ESCC patients. Our findings demonstrated that FAP+ CAFs promoted radioresistance in ESCC cells through transferring exosomal lncRNA AFAP1-AS1; and may be a potential therapeutic target for ESCC treatment.

SCOPe: improvements to the structural classification of proteins - extended database to facilitate variant interpretation and machine learning.

The Structural Classification of Proteins-extended (SCOPe, https://scop.berkeley.edu) knowledgebase aims to provide an accurate, detailed, and comprehensive description of the structural and evolutionary relationships amongst the majority of proteins of known structure, along with resources for analyzing the protein structures and their sequences. Structures from the PDB are divided into domains and classified using a combination of manual curation and highly precise automated methods. In the current release of SCOPe, 2.08, we have developed search and display tools for analysis of genetic variants we mapped to structures classified in SCOPe. In order to improve the utility of SCOPe to automated methods such as deep learning classifiers that rely on multiple alignment of sequences of homologous proteins, we have introduced new machine-parseable annotations that indicate aberrant structures as well as domains that are distinguished by a smaller repeat unit. We also classified structures from 74 of the largest Pfam families not previously classified in SCOPe, and we improved our algorithm to remove N- and C-terminal cloning, expression and purification sequences from SCOPe domains. SCOPe 2.08-stable classifies 106 976 PDB entries (about 60% of PDB entries).

Conjugation of TLR7 Agonist Combined with Demethylation Treatment Improves Whole-Cell Tumor Vaccine Potency in Acute Myeloid Leukemia.

Background: Acute myeloid leukemia (AML) is a malignant hematological disease with high refractory rate. Immune escape of AML cells is one of the underlying mechanisms mediating the relapse of the cancers. Various immunotherapies based on the 'patients' immune response to tumor cells have been developed to targeting the immune escape of AML cells, which lead to the minimal residual disease (MRD) after treatment. But the efficacy of those treatments or the combination of treatments remains unsatisfactory. Methods: A Toll-like receptor (TLR)-7 agonist SZU-106 was chemically synthesized. SZU-106 was conjugated to Decitabine (DAC), a demethylation agent, treated AML cells to construct tumor vaccine. The potency of the newly constructed AML cell vaccine, SZU-106-DAC-AML was tested in vitro and in vivo for the expression of tumor antigens and the activation level of immune responses. Results: Compared to the well characterized TLR7 agonist R848, SZU-106 has a comparable potency to activate TLR7 signaling pathway. SZU-106-DAC-AML, constructed by conjugating SZU-106 to DAC treated tumor cells, exhibited increased expression of tumor antigens, and enhanced the activation of DC cells and T cells in vitro and in vivo. The result of xenograft tumor model showed that SZU-106-DAC-AML tumor vaccine greatly inhibited tumor growth and prolonged animal survival. Conclusions: Conjugation of TLR7 agonist combined with up-regulation of tumor antigen expression improved the effectiveness of whole-cell tumor vaccine in AML.

Exosomes Mediated Transfer of Circ_UBE2D2 Enhances the Resistance of Breast Cancer to Tamoxifen by Binding to MiR-200a-3p.

BACKGROUND Circular RNA UBE2D2 (circ_UBE2D2) has been found to be involved in the progression of breast cancer. Exosomes are critical mediators of intercellular communication, however, the function of exosomal circ_UBE2D2 in breast cancer remains vague. MATERIAL AND METHODS Cell viability was measured by Cell Counting Kit-8 assay. Western blot was used to detect the levels of estrogen receptor alpha (ERalpha), E-cadherin, vimentin, CD9, and CD63. Migrated and invaded cells were examined using Transwell assay. Circ_UBE2D2 and microRNA (miR)-200a-3p levels were detected using quantitative real-time polymerase chain reaction. Exosomes were isolated by ultracentrifugation method. The interaction between circ_UBE2D2 and miR-200a-3p was confirmed by dual-luciferase reporter assay and RNA immunoprecipitation assay. Murine xenograft model was established to conduct in vivo experiments. RESULTS We found that circ_UBE2D2 was upregulated in breast cancer tamoxifen-resistant tissues and cell lines, and circ_UBE2D2 deletion mitigated tamoxifen resistance in breast cancer cells. Circ_UBE2D2 was also significantly loaded in exosomes isolated from resistant cells and could be transferred to parental cells. MiR-200a-3p was a target of circ_UBE2D2, and we demonstrated that exosomes mediated transfer of circ_UBE2D2 interacted with miR-200a-3p to enhance tamoxifen resistance of breast cancer cells by regulating cell viability, metastasis, and the level of ERalpha in vivo and in vitro. CONCLUSIONS Exosomes mediated transfer of circ_UBE2D2 reinforced tamoxifen resistance in breast cancer by binding to miR-200a-3p, providing new insights into the boost of the effectiveness of tamoxifen on breast cancer patients.

Xigua Video as a Source of Information on Breast Cancer: Content Analysis.

BACKGROUND: Seeking health information on the internet is a popular trend. Xigua Video, a short video platform in China, ranks among the most accessed websites in the country and hosts an increasing number of videos with medical information. However, the nature of these videos is frequently unscientific, misleading, or even harmful. OBJECTIVE: Little is known about Xigua Video as a source of information on breast cancer. Thus, the study aimed to investigate the contents, quality, and reliability of breast cancer-related content on Xigua Video. METHODS: On February 4, 2020, a Xigua Video search was performed using the keyword "breast cancer." Videos were categorized by 2 doctors based on whether the video content provided useful or misleading information. Furthermore, the reliability and quality of the videos were assessed using the 5-point DISCERN tool and 5-point global quality score criteria. RESULTS: Out of the 170 videos selected for the study, 64 (37.6%) were classified as useful, whereas 106 (62.4%) provided misleading information. A total of 41.8% videos (71/170) were generated by individuals compared to 19.4% videos (33/170) contributed by health care professionals. The topics mainly covered etiology, anatomy, symptoms, preventions, treatments, and prognosis. The top topic was "treatments" (119/170, 70%). The reliability scores and global quality scores of the videos in the useful information group were high (P<.001). No differences were observed between the 2 groups in terms of video length, duration in months, and comments. The number of total views was higher for the misleading information group (819,478.5 vs 647,940) but did not reach a level of statistical significance (P=.112). The uploading sources of the videos were mainly health care professionals, health information websites, medical advertisements, and individuals. Statistical differences were found between the uploading source groups in terms of reliability scores and global quality scores (P<.001). In terms of total views, video length, duration, and comments, no statistical differences were indicated among the said groups. However, a statistical difference was noted between the useful and misleading information video groups with respect to the uploading sources (P<.001). CONCLUSIONS: A large number of Xigua videos pertaining to breast cancer contain misleading information. There is a need for accurate health information to be provided on Xigua Video and other social media; health care professionals should address this challenge.

VIPdb, a genetic Variant Impact Predictor Database.

Genome sequencing identifies vast number of genetic variants. Predicting these variants' molecular and clinical effects is one of the preeminent challenges in human genetics. Accurate prediction of the impact of genetic variants improves our understanding of how genetic information is conveyed to molecular and cellular functions, and is an essential step towards precision medicine. Over one hundred tools/resources have been developed specifically for this purpose. We summarize these tools as well as their characteristics, in the genetic Variant Impact Predictor Database (VIPdb). This database will help researchers and clinicians explore appropriate tools, and inform the development of improved methods. VIPdb can be browsed and downloaded at https://genomeinterpretation.org/vipdb.

Assessing computational predictions of the phenotypic effect of cystathionine-beta-synthase variants.

Accurate prediction of the impact of genomic variation on phenotype is a major goal of computational biology and an important contributor to personalized medicine. Computational predictions can lead to a better understanding of the mechanisms underlying genetic diseases, including cancer, but their adoption requires thorough and unbiased assessment. Cystathionine-beta-synthase (CBS) is an enzyme that catalyzes the first step of the transsulfuration pathway, from homocysteine to cystathionine, and in which variations are associated with human hyperhomocysteinemia and homocystinuria. We have created a computational challenge under the CAGI framework to evaluate how well different methods can predict the phenotypic effect(s) of CBS single amino acid substitutions using a blinded experimental data set. CAGI participants were asked to predict yeast growth based on the identity of the mutations. The performance of the methods was evaluated using several metrics. The CBS challenge highlighted the difficulty of predicting the phenotype of an ex vivo system in a model organism when classification models were trained on human disease data. We also discuss the variations in difficulty of prediction for known benign and deleterious variants, as well as identify methodological and experimental constraints with lessons to be learned for future challenges.

High expression of long non-coding RNA AFAP1-AS1 predicts chemoradioresistance and poor prognosis in patients with esophageal squamous cell carcinoma treated with definitive chemoradiotherapy.

To evaluate the clinical significance of lncRNAs in the resistance to cisplatin-based chemoradiotherapy in esophageal squamous cell carcinoma (ESCC). We focused on lncRNAs which were frequently reported in ESCC or were involved in chemoradiotherapy resistance. LncRNA expressions were examined in paired cisplatin-resistant and parental ESCC cell lines. Dysregulated lncRNAs were further measured in 162 pretreatment biopsy specimens of ESCC who received definitive chemoradiotherapy (dCRT). Then the correlations between lncRNA expression and response to dCRT and prognosis were analyzed. Three lncRNAs (AFAP1-AS1, UCA1, HOTAIR) were found to be deregulated in cisplatin-resistant cells compared with their parent cells. AFAP1-AS1 was significantly up-regulated in tumor tissues compared with adjacent normal tissues (P = 0.006). Furthermore, overexpression of AFAP1-AS1 was closely associated with lymph node metastasis (P < 0.001), distant metastasis (P = 0.016), advanced clinical stage (P = 0.002), and response to dCRT (P < 0.001). Kaplan-Meier survival analysis revealed that high expression of AFAP1-AS1 was significantly associated with shorter progression free survival (PFS) (median, 15 months vs. 27 months, P < 0.001) and overall survival (OS) (median, 29 months vs. 42 months, P < 0.001). In the multivariate analysis, high expression of AFAP1-AS1 was found to be an independent risk factor to predict poor PFS (HR, 1.626; P = 0.027) and OS (HR, 1.888; P = 0.004). Thus, high expression of AFAP1-AS1 could serve as a potential biomarker to predict tumor response and survival. Determination of this lncRNA expression might be useful for selection ESCC patients for dCRT. © 2016 The Authors. Molecular Carcinogenesis published by Wiley Periodicals, Inc.

The Leu72Met polymorphism of the GHRL gene prevents the development of diabetic nephropathy in Chinese patients with type 2 diabetes mellitus.

The preproghrelin (GHRL) Leu72Met polymorphism (rs 696217) is associated with obesity, reduced glucose-induced insulin secretion in healthy or diabetic subjects, and reduced serum creatinine (Scr) levels in type 2 diabetes. We evaluated the association of the Leu72Met polymorphism with measures of insulin sensitivity in non-diabetic control individuals and type 2 diabetics, and whether this variation contributes to the development of diabetic nephropathy (DN) in type 2 diabetes. A case-control study was performed of 291 non-diabetic control subjects and 466 patients with type 2 diabetes, of whom 238 had DN with overt albuminuria (DN group; albuminuric excretion rate [AER] ≥ 300 mg/24 h) and 228 did not have DN, but had diabetes for more than 10 years (non-DN group). Genotyping was performed using a TaqMan PCR assay. The Leu/Leu, Leu/Met, and Met/Met genotype frequencies were significantly different between the non-DN and DN groups (p = 0.011). The frequency of the variant genotypes (Leu/Met, Met/Met) was significantly lower in the DN group than the non-DN group (23.5 vs. 36.0 %, p = 0.003). Met/Met non-diabetic control subjects had lower BMI and Scr levels and higher eGFR level than Leu/Leu or Leu/Met individuals (p < 0.05). Leu/Met and Met/Met type 2 diabetics had significantly lower AER and Scr levels and higher eGFR level than Leu/Leu type 2 diabetics (all p < 0.001). The GHRL Leu72Met polymorphism may help to maintain normal renal function and may protect against the development of DN by reducing albuminuria and improving renal function in Chinese patients with type 2 diabetes.

Reduction of acute radiation-induced brain injury in rats by anlotinib.

OBJECTIVES: Radiation therapy in the treatment of brain tumors also leads to the occurrence of radiation brain injury (RBI). Anlotinib is a small-molecule inhibitor of multi-receptor tyrosine kinase with high selectivity for vascular endothelial growth factor receptor-2. In this study, we constructed a rat model of RBI and investigated the effect of anlotinib on RBI and its mechanism of action through drug intervention during the acute phase of RBI. METHODS: Six-week-old male (Sprague-Dawley) rats were used to construct an animal model of RBI to evaluate the protective effect of anlotinib on acute RBI by histopathological staining, brain edema determination, blood-brain barrier integrity evaluation and quick real time-polymerase chain reaction , ELISA detection of inflammation-related indexes, and western-blot detection of related gene protein expression. RESULTS: Anlotinib reduced the degree of edema in the hippocampal region of rats, improved the pathological morphology of neural cells and vascular endothelial cells, and decreased blood-brain barrier permeability. Anlotinib reduced glial fibrillary acidic protein protein expression in the hippocampal region of rat brain tissue and inhibited astrocyte activation. It inhibited the release of inflammatory factors (interleukin [IL]-6, IL-8 and vascular endothelial growth factor) and down-regulated the expression of janus kinase-2/signal transducer and activator of transcription-3 (JAK2/STAT3) signaling pathway-related proteins. CONCLUSION: This study found that anlotinib has a protective effect against RBI in rats and anlotinib may be a new candidate for the treatment of RBI.

Evaluating the Quality of Cancer-Related WeChat Public Accounts: Cross-Sectional Study.

BACKGROUND: WeChat (Tencent) is one of the most important information sources for Chinese people. Relevantly, various health-related data are constantly transmitted among WeChat users. WeChat public accounts (WPAs) for health are rapidly emerging. Health-related WeChat public accounts have a significant impact on public health. Because of the rise in web-based health-seeking behavior, the general public has grown accustomed to obtaining cancer information from WPAs. Although WPAs make it easy for people to obtain health information, the quality of the information is questionable. OBJECTIVE: This study aims to assess the quality and suitability of cancer-related WeChat public accounts (CWPAs). METHODS: The survey was conducted from February 1 to 28, 2023. Based on the WPA monthly list provided by Qingbo Big Data, 28 CWPAs in the WeChat communication index were selected as the survey sample. Quality assessment of the included CWPAs was performed using the HONcode instrument. Furthermore, suitability was measured by using the Suitability Assessment of Materials. A total of 2 researchers conducted the evaluations independently. RESULTS: Of the 28 CWPAs, 12 (43%) were academic and 16 (57%) were commercial. No statistical difference was found regarding the HONcode scores between the 2 groups (P=.96). The quality of the academic and commercial CWPAs evaluated using the HONcode instrument demonstrated mean scores of 5.58 (SD 2.02) and 5.63 (SD 2.16), respectively, corresponding to a moderate class. All CWPAs' compliance with the HONcode principles was unsatisfactory. A statistically significant difference between the 2 groups was observed in the Suitability Assessment of Materials scores (P=.04). The commercial WPAs reached an overall 55.1% (SD 5.5%) score versus the 50.2% (SD 6.4%) score reached by academic WPAs. The suitability of academic and commercial CWPAs was considered adequate. CONCLUSIONS: This study revealed that CWPAs are not sufficiently credible. WPA owners must endeavor to create reliable health websites using approved tools such as the HONcode criteria. However, it is necessary to educate the public about the evaluation tools of health websites to assess their credibility before using the provided content. In addition, improving readability will allow the public to read and understand the content.

A Foundation Model for Cell Segmentation.

Cells are a fundamental unit of biological organization, and identifying them in imaging data - cell segmentation - is a critical task for various cellular imaging experiments. While deep learning methods have led to substantial progress on this problem, most models in use are specialist models that work well for specific domains. Methods that have learned the general notion of "what is a cell" and can identify them across different domains of cellular imaging data have proven elusive. In this work, we present CellSAM, a foundation model for cell segmentation that generalizes across diverse cellular imaging data. CellSAM builds on top of the Segment Anything Model (SAM) by developing a prompt engineering approach for mask generation. We train an object detector, CellFinder, to automatically detect cells and prompt SAM to generate segmentations. We show that this approach allows a single model to achieve human-level performance for segmenting images of mammalian cells (in tissues and cell culture), yeast, and bacteria collected across various imaging modalities. We show that CellSAM has strong zero-shot performance and can be improved with a few examples via few-shot learning. We also show that CellSAM can unify bioimaging analysis workflows such as spatial transcriptomics and cell tracking. A deployed version of CellSAM is available at https://cellsam.deepcell.org/.

Identification of Immune Infiltration and Prognostic Biomarkers in Small Cell Lung Cancer Based on Bioinformatic Methods from 3 Studies.

AIMS: This study aimed to investigate the correlation between gene expression and immune cell infiltration and the overall survival rate in tumor tissues, which may contribute to the therapy and prognosis of small cell lung cancer (SCLC) patients. BACKGROUND: SCLC is the most aggressive type of lung neoplasm. There is no proper marker for the treatment and prediction of prognosis in SCLC. OBJECTIVES: Three gene expression profiles of SCLC patients were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified between normal lung samples and SCLC lung samples. METHODS: Functional enrichment analysis of all DEGs was performed to explore the linkage among DEGs, the tumor immune microenvironment, and SCLC tumorigenesis. The common genes among the 3 groups in the Venn diagram and hub genes in protein-protein interaction (PPI) networks were considered potential key genes in SCLC patients. The TIMER (tumor immune estimation resource) database calculation and Kaplan-Meier survival curves were used to investigate the association between potential key genes and immune infiltrate prognosis of SCLC patients. RESULTS: A total of 750 (top 250 from each study) differentially expressed genes (DEGs) were identified. CLDN18 and BRIP1 were significantly related to immune infiltration in the tumor microenvironment. SHCBP1 and KIF23 were related mostly to prognosis in SCLC patients. CONCLUSION: The present study may provide some potential biomarkers for the therapy and prognosis of SCLC.

Role of cancer-associated fibroblasts in the progression, therapeutic resistance and targeted therapy of oesophageal squamous cell carcinoma.

Oesophageal squamous cell carcinoma (ESCC) is one of the most aggressive malignant tumours with high morbidity and mortality. Although surgery, radiotherapy and chemotherapy are common treatment options available for oesophageal cancer, the 5-year survival rate remains low after treatment. On the one hand, many oesophageal cancers are are discovered at an advanced stage and, on the other hand, treatment resistance is a major obstacle to treating locally advanced ESCC. Cancer-associated fibroblasts (CAFs), the main type of stromal cell in the tumour microenvironment, enhance tumour progression and treatment resistance and have emerged as a major focus of study on targeted therapy of oesophageal cancer.With the aim of providing potential, prospective targets for improving therapeutic efficacy, this review summarises the origin and activation of CAFs and their specific role in regulating tumour progression and treatment resistance in ESCC. We also emphasize the clinical potential and emerging trends of ESCC CAFs-targeted treatments.

Expression of Serpin Family E Member 1 (SERPINE1) Is Associated with Poor Prognosis of Gastric Adenocarcinoma.

BACKGROUND: The aberrant expression of serpin family E member 1 (SERPINE1) is associated with carcinogenesis. This study assessed the alteration of SERPINE1 expression for an association with gastric adenocarcinoma prognosis. METHODS: The Cancer Genome Atlas (TCGA) dataset was applied to investigate the impact of SERPINE1 expression on the survival of patients afflicted with gastric cancer. Subsequently, 136 samples from the Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University were subjected to qRT-PCR and Western blot to validate the expression level of SERPINE1 between tumor and adjacent normal tissues. The correlation between the expression of SERPINE1 with the clinicopathological features in TCGA patients was analyzed using Wilcoxon signed-rank and logistic regression tests. The potential molecular mechanism associated with SERPINE1 expression in gastric cancer were confirmed using gene set enrichment analysis (GSEA). RESULTS: The TCGA data showed that SERPINE1 was overexpressed in tumor tissues compared to normal mucosae and associated with the tumor T stage and pathological grade. SERPINE1 overexpression was associated with the poor overall survival (OS) of patients. The findings were confirmed with 136 patients, that is, SERPINE1 expression was associated with poor OS (hazard ratio (HR): 1.82; 95% confidence interval (CI): 0.84-1.83; p = 0.012)) as an independent predictor (HR: 2.11, 95% CI: 0.81-2.34; p = 0.009). The resulting data were further processed by GSEA showed that SERPINE1 overexpression was associated with the activation of EPITHELIAL_MESENCHYMAL_TRANSITION, TNFA_SIGNALING_VIA_NFKB, INFLAMMATORY_RESPONSE, ANGIOGENESIS, and HYPOXIA. CONCLUSIONS: SERPINE1 overexpression is associated with a poor gastric cancer prognosis.

MAGEA1 and hTERT Peptide Treatment Improves the Potency of The Dendritic Cell- Cytotoxic T Lymphocytes (DC-CTL) Immunotherapy in DAC Treated Acute Myeloid Leukemia.

Background: Acute myeloid leukemia (AML) is a type of heterogenous malignant hematological disorder. Recently developed immunotherapies such as chimeric antigen receptor T cell (CAR-T) do not demonstrated promising therapeutic results due to the off-target effect. The Dendritic cell-cytotoxic T lymphocyte adoptive immunotherapy (DC-CTL) is one of the recently developed immunotherapies. One of the reasons that DC-CTL does not work well in AML is the lack of antigens with high binding affinity, high antigen presentation potency, and the specificity to AML cells. Methods: DAC was used to treat AML cells to find overexpressed CTAs upon DAC treatment. The overexpression was confirmed at both mRNA and protein level by realtime PCR and western blotting. Peptides was designed by using the NetMHCpan database and EPIP based on the out-screened protein sequences. The peptides were then used to pulse DC-CTL coculture in vitro and tested the cytotoxicity of CTLs in vitro and their cancer inhibition potency in vivo. Results: Two cancer testis antigen (CTA) proteins, MAGEA1 and hTERT, was up-regulated in DAC treated AML cells. DC cells pulsed by the antigen peptides designed based on the sequence of these two proteins demonstrated increased potency to stimulate CTL cells in terms of cytokines secretion. These cytokines included IFN-γ, IL-6, and TNF-α. Moreover, enhanced in vitro cytotoxicity was found in CTL cells treated with peptide pulsed DC cells. AML progress was inhibited by CTA peptides pulsed DC-CTL in a mouse AML model. Conclusions: MAGEA1 and hTERT could possibly serve as specific tumor antigens upon DAC treatment, providing potential targets for the development of immunotherapies for AML in the future.

Correlation of hedgehog signal activation with chemoradiotherapy sensitivity and survival in esophageal squamous cell carcinomas.

OBJECTIVE: To investigate the significance of hedgehog signaling pathway in chemoradiotherapy sensitivity and its effect on the prognosis of esophageal squamous cell carcinoma. METHODS: In the present study, we used the method of immunohistochemistry to examine the expression status of two hedgehog components, PTCH1 and glioma-associated oncogene GLI-1, in 100 pre-treated biopsy specimens of esophageal squamous cell carcinoma patients treated with definitive chemoradiotherapy. RESULTS: We find that high levels of PTCH1 and GLI-1 were detected in 76.0 and 72.0% of esophageal squamous cell carcinoma, respectively. Significant associations of high PTCH1 and GLI-1 expression with large tumor size (both P = 0.01), locoregional progression (P= 0.001 and 0.003, respectively) and the lack of complete response to chemoradiotherapy (P= 0.008 and 0.01, respectively) were observed. Univariate analysis revealed that high PTCH1 and GLI-1 expression was associated with poor locoregional progression-free survival, distant progression-free survival and overall survival. Furthermore, esophageal squamous cell carcinoma patients with high PTCH1 and GLI-1 expression have the shorter survival time than the subgroups with negative and low PTCH1 and GLI-1 expression. In multivariate analysis, PTCH1 and GLI-1 expression status were both evaluated as independent prognostic factors for locoregional progression-free survival, distant progression-free survival and overall survival. CONCLUSIONS: These findings suggest an important role for the activation of hedgehog signaling in esophageal squamous cell carcinoma progression and that PTCH1 and GLI-1 expression may be significantly associated with esophageal squamous cell carcinoma resistance to chemoradiotherapy.