Objective To screen immune-related long non-coding RNAs(LncRNAs)in the TCGA database pancreatic cancer dataset and construct a prognostic risk assessment model with immune-related LncRNAs to explore prognosis-related potential molecular mechanisms.Methods RNA-seq data of 171 pancreatic cancer samples and corresponding clinical information were obtained by The Cancer Genome Atlas(TCGA)database,and two classical immune-related gene datasets(GO0006955/IMMUNE RESPONSE and GO0002376/IMMUNE SYSTERM PROCESS)and gene annotation information were used to identify immune-related LncRNAs.The immune-related LncRNAs associated with pancreatic cancer prognosis were used for univariate and multivariate Cox analyses to establish a model for the assessment of pancreatic cancer prognostic risk based on immune-associated LncRNAs.This risk model was used for survival analysis,clinical correlation analysis,immune cell infiltration analysis,pathway enrichment analysis,and prognostic column line plot modeling.Results We screened 119 immune-related LncRNAs in pancreatic cancer,and five immune-related LncRNAs(AC064836.3,LINC00941,ZNF236-DT,TMEM161B-AS1 and AC068580.2)were identified for the development of pancreatic cancer prognostic risk assessment model.According to the prognostic risk assessment model,pancreatic cancer patients were divided into low-risk group(n=86)and high-risk group(n=85).Compared with the low-risk group,the high-risk group showed a significant negative enrichment trend for immune-related signaling pathways,the 5-year overall survival of pancreatic cancer patients was significantly increased in the low-risk group compared with the high-risk group.The expression of low-risk immune-related LncRNAs(AC064836.3,ZNF236-DT and TMEM161B-AS1)gradually decreased with increasing clinical stage of pancreatic cancer patients.Patient age(P=0.031,risk ratio and 95％CI:1.025/1.002-1.048)and prognostic risk score(P＜0.001,risk ratio and 95％ confidence interval 1.801/1.465-2.215)could be used as independent prognostic risk factors for overall survival in pancreatic cancer.In addition,the prognostic risk assessment model had better predictive efficiency(area under the curve=0.695)compared with the disease predictive ability of common clinical characteristics.Steroid biosynthesis,pentose phosphate pathway,intercellular linkage,cytoskeletal rearrangement and other pathways related to energy metabolism and invasive migration of pancreatic cancer cells were significantly activated in the high-risk group.Meanwhile,pancreatic cancer patients in the high-risk group had lower levels of naive B cells,plasma cells and neutrophils with anti-tumor activity,but their macrophage infiltration levels were significantly higher than those in the low-risk group.Conclusion The prognostic risk assessment model constructed based on five immune-related LncRNAs can effectively predict the survival status,clinical characteristics,molecular pathways,and immune cell infiltration differences of pancreatic cancer patients.Meanwhile,relying on this model,the prognosis of pancreatic cancer patients can be prospectively predicted,which enhances the usefulness of this risk prediction model.

Objective To screen immune-related long non-coding RNAs(LncRNAs)in the TCGA database pancreatic cancer dataset and construct a prognostic risk assessment model with immune-related LncRNAs to explore prognosis-related potential molecular mechanisms.Methods RNA-seq data of 171 pancreatic cancer samples and corresponding clinical information were obtained by The Cancer Genome Atlas(TCGA)database,and two classical immune-related gene datasets(GO0006955/IMMUNE RESPONSE and GO0002376/IMMUNE SYSTERM PROCESS)and gene annotation information were used to identify immune-related LncRNAs.The immune-related LncRNAs associated with pancreatic cancer prognosis were used for univariate and multivariate Cox analyses to establish a model for the assessment of pancreatic cancer prognostic risk based on immune-associated LncRNAs.This risk model was used for survival analysis,clinical correlation analysis,immune cell infiltration analysis,pathway enrichment analysis,and prognostic column line plot modeling.Results We screened 119 immune-related LncRNAs in pancreatic cancer,and five immune-related LncRNAs(AC064836.3,LINC00941,ZNF236-DT,TMEM161B-AS1 and AC068580.2)were identified for the development of pancreatic cancer prognostic risk assessment model.According to the prognostic risk assessment model,pancreatic cancer patients were divided into low-risk group(n=86)and high-risk group(n=85).Compared with the low-risk group,the high-risk group showed a significant negative enrichment trend for immune-related signaling pathways,the 5-year overall survival of pancreatic cancer patients was significantly increased in the low-risk group compared with the high-risk group.The expression of low-risk immune-related LncRNAs(AC064836.3,ZNF236-DT and TMEM161B-AS1)gradually decreased with increasing clinical stage of pancreatic cancer patients.Patient age(P=0.031,risk ratio and 95％CI:1.025/1.002-1.048)and prognostic risk score(P＜0.001,risk ratio and 95％ confidence interval 1.801/1.465-2.215)could be used as independent prognostic risk factors for overall survival in pancreatic cancer.In addition,the prognostic risk assessment model had better predictive efficiency(area under the curve=0.695)compared with the disease predictive ability of common clinical characteristics.Steroid biosynthesis,pentose phosphate pathway,intercellular linkage,cytoskeletal rearrangement and other pathways related to energy metabolism and invasive migration of pancreatic cancer cells were significantly activated in the high-risk group.Meanwhile,pancreatic cancer patients in the high-risk group had lower levels of naive B cells,plasma cells and neutrophils with anti-tumor activity,but their macrophage infiltration levels were significantly higher than those in the low-risk group.Conclusion The prognostic risk assessment model constructed based on five immune-related LncRNAs can effectively predict the survival status,clinical characteristics,molecular pathways,and immune cell infiltration differences of pancreatic cancer patients.Meanwhile,relying on this model,the prognosis of pancreatic cancer patients can be prospectively predicted,which enhances the usefulness of this risk prediction model.

Objective To investigate the clinical efficacy of endoscopic surgery for extensive osteoradionecrosis (ORN) of skull base in patients with nasopharyngeal carcinoma (NPC) after radiotherapy.Methods Seventeen patients diagnosed as ORN of skull base after radiotherapy for NPC and underwent endoscopic surgery were retrospectively studied with their clinic data.Results Based on the CT and endoscopic examination,all patients had large skull base defects with bone defects averaged 7.02 cm2 (range,3.60-14.19 cm2).Excepting for curetting the sequestra,endoscopic surgery was also used to repair the wound or to protect the internal carotid artery with flap in 12 patients.No bone reconstructions were conducted in all patients with the bone defects of skull base.CT examinations were taken after endoscopic surgery when required.The postoperative follow-up ranged from 8 months to 6 years (average,14 months).Aside from 1 patient with delayed cerebrospinal fluid (CSF),others had no related complications.Conclusions The patients with extensive ORN can be treated with endoscopic surgery to curette the necrotic bone of skull base,and endoscopic reconstruction provides an alternative technique.It may not be necessary to reconstruct the bone defects at skull base,however,the exposed important structures of skull base,such as internal carotid artery,need to repair with soft tissue such as flap.

Objective: Identification of the genes specially expressed in tumor cell but not in normal cell is important for understanding the molecular mechanisms of carcinogencsis. This study will focus on identification of differentially expressed gene fragments in human stomach cancer. Methods: By using the new developing mRNA differential display (DD) technique, genes fragments differentially expressed in stomach cancer tissues from a patient and the adjacent normal tissues beyond the tumor mass were studied. Results: Two differentially displayed complementary DNA fragments from stomach cancer tissues, scgl and scg2 (stomach cancer-associated gene, scg), cofirmed by Northern Blot, were cloned and sequenced. The nucleotide length of scgl is 194 base pairs and that of scg2 is 343 base pairs. After searching against GenBank databases by BLASTN, neither scgl nor scg2 had significant homological gene sequences with the known genes. Conclusion: These results suggested scgl and scg2 might be complementary DNA fragments of novel genes expressed in stomach cancer tissues, but not in normal tissues and may play a role in the occurrence and development of stomach cancer. Further characterization of full-length of these two complementary DNA fragments will be continued.