The Nasopharyngeal carcinoma (NPC) is a common malignant tumor and precise gross tumor volume (GTV) delineation is crucial for effective NPC radiotherapy. Deep learning techniques have enabled automated GTV segmentation, nevertheless, model performance often degrades due to domain shifts in multi-center data scenarios. Recent source-free active domain adaptation methods have achieved promising results; however, these are still limited by several issues: (i) dependency on the source data features, (ii) inappropriate selection of biased and redundant samples, and (iii) catastrophic forgetting. In the current investigation, we propose a novel continual source-free active domain adaptation (CSFADA) framework for GTV segmentation of NPC. Inspired by self-supervised and cross-correlation learning, we introduce a domain reference and invariants selection strategy to address the first two challenges mentioned above. To this end, the strategy first acquire target domain knowledge in a self-supervised learning manner. It then computes a domain-distance and a domain-invariance score for each sample, thereby selecting informative samples. To address the third challenge mentioned above, we develop a dual-stage recurrent distillation strategy based on the clinical practice. Specifically, the stage I employs self-supervised learning approaches to learn generalizable representations and preserve source domain knowledge. The stage II decouples classical knowledge distillation to avoid optimization conflicts and thus better preserve source domain information. We conduct extensive experiments on datasets from three centers for GTV segmentation of NPC. The experimental results demonstrate the superiority of our proposed methods. Our code is publicly available at https://github.com/YZC-99/CSFADA.git.

Lung cancer is characterized by high morbidity and mortality due to the lack of practical early diagnostic and prognostic tools. The present study uses machine learning algorithms to construct a clinical predictive model for non-small cell lung cancer (NSCLC) patients. Laboratory indices of the NSCLC patients at their initial visit were collected for quality control and exploratory analysis. By comparing the levels of the above indices between the survival and death groups, the statistically significant indices were selected for subsequent machine learning modeling. Ten machine learning algorithms were then employed to develop the predictive models with survival and recurrence as outcomes, respectively. Moreover, regression models were constructed using the random survival forest algorithm by incorporating the survival time dimension. Finally, critical variables in the optimal model were screened based on the interpretable algorithms to build a decision tree to facilitate clinical application. 682 patients were enrolled according to the inclusion and exclusion criteria. The preliminary comparison results revealed that except for fast blood glucose, CD3+T cell proportion, NK cell proportion, and CA72-4, there were significant statistical differences in other tumor markers, inflammation, metabolism, and immune-related indices between the survival and death groups (p < 0.01). Subsequently, indices with statistical differences were incorporated into machine learning modeling and evaluation. The results showed that among the ten prognostic models constructed using survival status as the outcome, the neural network model obtained the best predictive performance, with accuracy, sensitivity, specificity, AUC, and precision values of 0.993, 0.987, 1.000, 0.994, and 1.000, respectively. The corresponding SHAP16 algorithm revealed that the top five variables in terms of importance were interleukin6 (IL-6), soluble interleukin2 receptor (sIL-2R), cholesterol, CEA, and Cy211, respectively. The random survival forest model also confirmed the critical role of CEA, sIL-2R, and IL-6 in predicting the prognosis of NSCLC patients. A decision tree model with seven cut-off points based on the above three indices was eventually built for clinical application. The neural network model exhibited ideal predictive performance in the survival status of NSCLC patients, and the decision tree model constructed based on selected important variables was conducive to rapid bedside prognosis assessment and decision-making. There is a lack of highly sensitive, specific, and organ-specific biomarkers to predict the prognosis of lung cancer patients. Compared with traditional predictive models, the models constructed by machine learning methods have incredibly high predictive accuracy, sensitivity, and specificity. Both classification and regression algorithms confirmed the significant predictive value of IL-6, sIL-2R, and CEA on the prognosis of lung cancer patients. A decision tree prognostic model including IL-6, sIL-2R, and CEA with explicit cutoff values was further provided for rapid prognostic assessment and clinical decision-making.

Accumulating evidence indicates gut microbiota contributes to aging-related disorders. However, the exact mechanism underlying gut dysbiosis-related pathophysiological changes during aging remains largely unclear. In the current study, we first performed gut microbiota remodeling on old mice by fecal microbiota transplantation (FMT) from young mice, and then characterized the bacteria signature that was specifically altered by FMT. Our results revealed that FMT significantly improved natural aging-related systemic disorders, particularly exerted hepatoprotective effects, and improved glucose sensitivity, hepatosplenomegaly, inflammaging, antioxidative capacity and intestinal barrier. Moreover, FMT particularly increased the abundance of fecal A.muciniphila, which was almost nondetectable in old mice. Interestingly, A.muciniphila supplementation also exerted similar benefits with FMT on old mice. Notably, targeted metabolomics on short chain fatty acids (SCFAs) revealed that only acetic acid was consistently reversed by FMT. Then, acetic acid intervention exerted beneficial actions on both Caenorhabditis elegans and natural aging mice. In conclusion, our current study demonstrated that gut microbiota remodeling improved natural aging-related disorders through A.muciniphila and its derived acetic acid, suggesting that interventions with potent stimulative capacity on A. muciniphila growth and production of acetic acid was alternative and effective way to maintain healthy aging. Data availability statement: The data of RNAseq and 16 S rRNA gene sequencing can be accessed in NCBI with the accession number PRJNA848996 and PRJNA849355.

Circulating tumor cells (CTCs) are cells that detach from the primary tumor and enter the bloodstream, playing a crucial role in the metastasis of lung cancer. Unfortunately, there is currently a lack of drugs specifically designed to target CTCs and prevent tumor metastasis. In this study, we present evidence that polyphyllin VII, a potent anticancer compound, effectively inhibits the metastasis of lung cancer by inducing a process called anoikis in CTCs. We observed that polyphyllin VII had significant cytotoxicity and inhibited colony formation, migration, and invasion in both our newly established cell line CTC-TJH-01 and a commercial lung cancer cell line H1975. Furthermore, we found that polyphyllin VII induced anoikis and downregulated the TrkB and EGFR-MEK/ERK signaling pathways. Moreover, activation of TrkB protein did not reverse the inhibitory effect of polyphyllin VII on CTCs, while upregulation of EGFR protein effectively reversed it. Furthermore, our immunodeficient mouse models recapitulated that polyphyllin VII inhibited lung metastasis, which was associated with downregulation of the EGFR protein, and reduced the number of CTCs disseminated into the lungs by inducing anoikis. Together, these results suggest that polyphyllin VII may be a promising compound for the treatment of lung cancer metastasis by targeting CTCs.

Liver cancer is one of the highest causes of cancer-related deaths worldwide, and China accounts for more than half of the new cases and deaths. It’s highly malignant and progresses rapidly.

BACKGROUND Lung adenocarcinoma (LUAD) is the most common type of lung cancer, which poses a serious threat to human life and health. -(-)Guaiol, an effective ingredient of many medicinal herbs, has been shown to have a high potential for tumor interference and suppression. However, knowledge of pharmacological mechanisms is still lacking adequate identification or interpretation. MATERIAL AND METHODS The genes of LUAD patients collected from TCGA were analyzed using limma and WGCNA. In addition, targets of (-)-Guaiol treating LUAD were selected through a prediction network. Venn analysis was then used to visualize the overlapping genes, which were further condensed using the PPI network. GO and KEGG analyses were performed sequentially, and the essential targets were evaluated and validated using molecular docking. In addition, cell-based verification, including the CCK-8 assay, cell death assessment, apoptosis analysis, and western blot, was performed to determine the mechanism of action of (-)-Guaiol. RESULTS The genes included 959 differentially-expressed genes, 6075 highly-correlated genes, and 480 drug-target genes. Through multivariate analysis, 23 hub genes were identified and functional enrichment analyses revealed that the PI3K/Akt signaling pathway was the most significant. Experiment results showed that -(-)Guaiol can inhibit LUAD cell growth and induce apoptosis. Additional evidence suggested that the PI3K/Akt signaling pathway established an inseparable role in the antitumor processes of -(-)Guaiol, which is consistent with network pharmacology results. CONCLUSIONS Our results show that the effect of (-)-Guaiol in LUAD treatment involves the PI3K/Akt signaling pathway, providing a useful reference and medicinal value in the treatment of LUAD.

Background: The baculoviral IAP repeat containing 5 (BIRC5) related to epithelial-mesenchymal transition (EMT) plays a crucial role in the pathogenesis of hepatocellular carcinoma (HCC). However, it remains unclear whether BIRC5-related genes can be used as prognostic markers of HCC. Methods: Kaplan-Meier (K-M) survival curve was used to assess the Overall Survival (OS) of high- and low-expression group divided by the median of BIRC5 expression. The differentially expressed genes (DEGs) between the two groups were screened using the limma package, and performed the functional enrichment analysis by the clusterProfiler package. WGCNA was used to analyze the relationship of the module and the clinical traits. The risk signature was constructed by univariate and multivariate Cox regression analyses and the enrichment analysis of genes in the risk signature was performed by the Intelligent pathway analysis (IPA). The immunophenoscore (IPS) and the tumor immune dysfunction and exclusion (TIDE) were used to estimate the clinical significance of the risk groups. Results: BIRC5 was high-expressed in HCC samples and associated with a poor prognosis (p-value < 0.0001). WGCNA screened 180 module genes which were overlapped with the 241 DEGs, ultimately getting 33 candidate genes. After the Cox regression analyses, CENPA, CDCA8, EZH2, KIF20A, KPNA2, CCNB1, KIF18B and MCM4 were preserved and used to construct risk signature, followed by calculating the risk score. The patients in high-risk groups stratified by median of the risk score were associated with a poor prognosis. The risk score had high accuracy [the area under the curve (AUC) >0.72] and was closely associated with clinicopathological characteristics of HCC patients. IPA suggested that the 8 genes were enriched in Cancer and Immunological disease related pathways. IPS and TIDE score indicated that the genes in low-risk group could cause an immune response, and patients in the low-risk group may be more sensitive to the immune checkpoint blockade (ICB) therapy. Conclusion: The risk score constructed by the 8 genes could not only predict the clinical outcome but also distinguish the cohort of ICB therapy in HCC, which exerted a vital value in treatment and prognosis of HCC.

Background Lung cancer is one of the most common causes of cancer-related deaths worldwide, metabolic disorders are also a problem that puzzles mankind. SREBP is overexpressed in non-small-cell lung cancer (NSCLC) and is also a key regulator of lipid synthesis. However, the mechanisms by which SREBP regulates the proliferation, migration and invasion in NSCLC remain unclear. Materials and Methods CCK-8, colony formation assay, soft agar assay, scratch wound healing assay and transwell assays were performed to detect proliferation, and invasion in NSCLC cells, respectively. In addition, Western blotting assay, qPCR and immunofluorescence were applied to detect the expressions of SREBP1, SREBP2, ki-67, PCNA, Bax, bcl-2, E-cadherin, N-cadherin, Vimentin, PI3K, p-PI3k, AKT, p-AKT, mTOR, p-mTOR in NSCLC cells. Results In this study, downregulation of SREBP significantly inhibited the proliferation, migration and invasion of A549 and H1299 cells. Moreover, the method of piecewise inhibition was adopted to prove that SREBP is a downstream molecule of the PI3K/Akt/mTOR signaling pathway. Conclusion Our study indicated that downregulation of SREBP inhibited the growth in NSCLC cells via PI3K/AKT/mTOR signaling pathway. Thus, we suggested SREBP may serve as a potential target for the treatment of patients with NSCLC.

The timely introduction and rapid development of precision medicine have provided strong theoretical support and technical support for tumor research. The treatment methods have been developed from single to multiple; the research technology has been transformed from macro to micro; the treatment drugs have been updated from systemic chemotherapy to targeted therapy and immunotherapy, and cancer has changed from a highly lethal disease to a "chronic disease". Based on the current international cancer research hotspots and treatment frontiers, this paper takes stock from five aspects, namely, treatment methods, detection technology, new drug research and development, information data and traditional Chinese medicine, with a view to "from the point to the surface", "from the outside to the inside", and "the combination of Chinese and western", so as to explore the overall picture of cancer treatment and research.

1Department of Oncology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200071, People’s Republic of China; 2Department of Pathology, Caner Hospital Affiliated Zhengzhou University, Henan, Zhengzhou 450008, People’s Republic of China; 3Department of Oncology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, People’s Republic of China; 4Institute for Thoracic Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai 200030, People’s Republic of China

Objective To develop a protein-protein interaction network of rectal cancer, which is based on genetic genes as well as to predict biological pathways underlying the molecular complexes in the network. In order to analyze and summarize genetic markers related to diagnosis and prognosis of rectal cancer.Methods the genes expression profile was downloaded from OMIM (Online Mendelian Inheritance in Man) database ; the protein-protein interaction network of rectal cancer was established by Cytoscape; the molecular complexes in the network were detected by Clusterviz plugin and the pathways enrichment of molecular complexes were performed by DAVID online and Bingo (The Biological Networks Gene Ontology tool).Results and Discussion A total of 127 rectal cancer genes were identified to differentially express in OMIM Database. The protein-protein interaction network of rectal cancer was contained 966 nodes (proteins), 3377 edges (interactive relationships) and 7 molecular complexes (score>7.0). Regulatory effects of genes and proteins were focused on cell cycle, transcription regulation and cellular protein metabolic process . Genes of DDK1, sparcl1, wisp2, cux1, pabpc1, ptk2 and htral were significant nodes in PPI network . The discovery of featured genes which were probably related to rectal cancer, has a great significance on studying mechanism, distinguishing normal and cancer tissues, and exploring new treatments for rectal cancer.

Circulating tumor cells (CTCs) shed from tumor sites and represent the molecular characteristics of the tumor. Besides genetic and transcriptional characterization, it is important to profile a panel of proteins with single-cell precision for resolving CTCs' phenotype, organ-of-origin, and drug targets. We describe a new technology that enables profiling multiple protein markers of extraordinarily rare tumor cells at the single-cell level. This technology integrates a microchip consisting of 15000 60 pL-sized microwells and a novel beads-on-barcode antibody microarray (BOBarray). The BOBarray allows for multiplexed protein detection by assigning two independent identifiers (bead size and fluorescent color) of the beads to each protein. Four bead sizes (1.75, 3, 4.5, and 6 μm) and three colors (blue, green, and yellow) are utilized to encode up to 12 different proteins. The miniaturized BOBarray can fit an array of 60 pL-sized microwells that isolate single cells for cell lysis and the subsequent detection of protein markers. An enclosed 60 pL-sized microchamber defines a high concentration of proteins released from lysed single cells, leading to single-cell resolution of protein detection. The protein markers assayed in this study include organ-specific markers and drug targets that help to characterize the organ-of-origin and drug targets of isolated rare tumor cells from blood samples. This new approach enables handling a very small number of cells and achieves single-cell, multiplexed protein detection without loss of rare but clinically important tumor cells.

Genetic and transcriptional profiling, as well as surface marker identification of single circulating tumor cells (CTCs) have been demonstrated. However, quantitatively profiling of functional proteins at single CTC resolution has not yet been achieved, owing to the limited purity of the isolated CTC populations and a lack of single-cell proteomic approaches to handle and analyze rare CTCs. Here, we develop an integrated microfluidic system specifically designed for streamlining isolation, purification and single-cell secretomic profiling of CTCs from whole blood. Key to this platform is the use of photocleavable ssDNA-encoded antibody conjugates to enable a highly purified CTC population with <75 'contaminated' blood cells. An enhanced poly-L-lysine barcode pattern is created on the single-cell barcode chip for efficient capture rare CTC cells in microchambers for subsequent secreted protein profiling. This system was extensively evaluated and optimized with EpCAM-positive HCT116 cells seeded into whole blood. Patient blood samples were employed to assess the utility of the system for isolation, purification and single-cell secretion profiling of CTCs. The CTCs present in patient blood samples exhibit highly heterogeneous secretion profile of IL-8 and VEGF. The numbers of secreting CTCs are found not in accordance with CTC enumeration based on immunostaining in the parallel experiments.

Objective:To observe the curative effect of Zhushui Decoction in the treatment of malignant ascites.Methods:With randomized and controlled method,the patients with malignant ascites(n=78) were divided into treatment group and control group.The control group only received basic treatment,while treatment group received basic treatment and Zhushui Decoction.The efficacy,quality of life and side effects were evaluated after 2 weeks.Results:The total effective rate of treatment group was 45% and it was statistically different compared with control group(P0.05).The quality of life score was improved in treatment group than that in control group(P0.05).Zhushui Decoction didn't have significant toxicity.Conclusion:Zhushui Decoction had good curative effect on malignant ascites,and it is worthy of clinical application.

Objective To observe the effects of capsule for invigorating qi and blood in the treatment of non-small cell lung cancer patients undergoing chemotherapy.Methods Non-small cell lung cancer patients were randomly divided into treatment group and control group.Both groups were treated by two cycles of gemcitabine plus cisplatin chemotherapy,which is using gemcitabine 1000 mg/m2 plus cisplatin 75 mg/m2 by intravenous once for the first day,repeated once every three weeks.Three weeks was a cycle.In the week before chemotherapy,treatment group was us ing capsule for invigorating qi and blood by oral,three capsules each time,three times a day,for eight weeks.Results Kamofsky score in treatment group increased more than control group,the difference between the two groups was sig nificant(P 0.05).Effective rate in the treatment group and control group were 42.9% and 34.3% respectively,but there was no significant difference(P 0.05).Compared with control group,the incidence of hemoglobin reducing in treatment group was significantly decreased(P 0.05).Conclusion The efficacy of capsule for invigorating qi and blood with GP regimen was similar to simple GP regimen in treatment of lung cancer,but the former can significantly improve quality of life of the patients,prevent bone marrow suppression,and increase hemoglobin levels.

Objective:To study the research progress of traditional Chinese medicine with high intensity focused ultrasound in treating pancreatic cancer.Methods:The mechanism of action and clinical application of high intensity focused ultrasound combined with Chinese medicine treatment of pancreatic cancer were summerized and concluded through consulting relevant literature.Results:Because of traditional Chinese medicine combined with high intensity focused ultrasound via skin put heat energy into the body through the local heating technology,and the combination of heat therapy and Chinese medicine,using Chinese medicine heat-clearing and detoxifying and blood-activating and stasis-dissolving as the guide,and the methods of internal or external application can reduce thermal damage,Improve the living quality.Conclusion:traditional Chinese medicine combined with high intensity focused ultrasound has low adverse reaction,and the curative effect is clear,which Has become a new treatment mode of comprehensive treatment of pancreatic cancer.

<正>原发性支气管肺癌(简称肺癌)为最常见的恶性肿瘤之一,而中晚期原发性非小细胞肺癌(NSCLC)在治疗上十分困难,预后差,生存期短,目前国内外尚无较好的治疗方法。随着中医对肺癌的认识的深入,临床疗效不断提高,中医药疗法已成为治疗中晚期NSCLC的主要方法之一。中医药在缓解症状、改善生存质量、增加机体抵抗力、延长生存期、提高机体免疫力、稳定病灶及中医药对放化疗等的减毒增效方面取得了肯定疗效,并在抗复发转移方面具有潜在优势。本

This paper discusses the research ideas to construct the middle-range theory of TCM based on famous doctor's clinical experience from the view of methodology.It analyzes the main achievements and issues exists in inheritance of famous doctor's experience and put forward some strategies based on famous doctor's clinical experience to carry out the construction of the middle-range theory in TCM.Including enhancement of self-consciousness,qualitative research methods introduced in the data collection phase,qualitative research methods to explore the systematic and programmed theoretical construction methods.

《黄帝内经》,我国历史悠久、博大精深的传统医学理论,在指导临床医学肺癌治疗中做出了突出贡献.内经理论对于指导肺癌预防、诊断及治疗各阶段均有着极为重要的指导作用.内经指导肺癌的治疗,既补机体之虚,又祛残存之邪.此外,内经“治未病”学术思想对于肺癌的临床治疗、预防复发转移方面均有十分重要的指导意义,即:肺癌未发病前预防其发病,肺癌已发早期诊治,综合治疗预防其复发转移.

This paper aims at the predominance of positivism,detachment of TCM theories from clinical practice,separation of experiences of doctors' from patients',and with the tendency to dis-humanization,over-simplification as well as linearization to discuss the possibility of transition between methodology and research paradigm.This paper proposed that research on TCM doctors' experiences,thought process and patients' experiences should be applied narrative method,which was characterized by qualitative research,by means of the introduction and analysis of the narrative inquiry.This has the positive significance on explaining the practical experience of TCM,enriching the connotation of TCM theory,and exploring the humanist values of TCM.It holds that narrative inquiry is beneficial to expand the theoretical thought and research method of TCM experience as well as to preserve historical materials on the exploration of TCM experience.