In the last few decades, RNA-based drugs have emerged as a promising candidate to specifically target and modulate disease-relevant genes to cure genetic defects. The key to applying RNA therapy in clinical trials is developing safe and effective delivery systems. Exosomes have been exploited as a promising vehicle for drug delivery due to their nanoscale size, high stability, high biocompatibility, and low immunogenicity. We reviewed and summarized the progress in the strategy and application of exosome-mediated RNA therapy. The challenges of exosomes as a carrier for RNA drug delivery are also elucidated in this article. RNA molecules can be loaded into exosomes and then delivered to targeted cells or tissues via various biochemical or physical approaches. So far, exosome-mediated RNA therapy has shown potential in the treatment of cancer, central nervous system disorders, COVID-19, and other diseases. To further exploit the potential of exosomes for RNA delivery, more efforts should be made to overcome both technological and logistic problems. The last several decades have witnessed remarkable progress in RNA-based therapeutics for preventing and treating multiple diseases, such as immune diseases, cancers, and infectious diseases ,2,3. To Extracellular vesicles (EVs) are lipid bilayer vesicles that are naturally released from different cells . EVs canExosomes are small ~30–150 nm) lipid bilayer-coated extracellular vesicles (EVs), which are released into the microenvironment after the fusion of multivesicular bodies (MVBs) with the plasma membranes . Exosome0 nm lipiExosomes have increasingly become an efficient and promising carrier for drug delivery. Compared to lipid nanoparticles (LNP) and other traditional synthesis delivery systems, exosomes have their special advantages. (1) Exosomes have relatively low cytotoxicity and immunogenicity, for they are natural vehicles for cargos like proteins, nucleic acids and lipids, and they have better biocompatibility due to membrane proteins such as tetraspanin and fibronectin ,21. (2) Several studies have reported that exosomes originate from multiple cell lines, and body fluids contain various RNA molecules ,32, suchAlthough several reviews have summarized the applications of exosomes as a promising carrier for RNA therapeutics ,40,41, fThe generation of exosomes starts from the endosomal system, where early endosomes grow into mature endosomes or MVBs, and concomitantly the endosomal membrane invaginates to produce intraluminal vesicles (ILVs) in the lumens of organelles .First, the invagination of the plasma membrane leads to bud formation, during which process fluid, extracellular contents, and cell-surface proteins are incorporated. The budding process gives rise to the de novo formation of early endosomes, or the fusion of the preexisting early endosomes with constituents from the endoplasmic reticulum (ER) and trans-Golgi network (TGN). Early endosomes grow into late endosomes and further form the multivesicular bodies (MVBs) rich with intraluminal vesicles (ILVs) by invagination of the endosomal limiting membrane. In this process, various proteins are sorted into the inward budding endosomal membrane and some of the cytosolic contents are encased within the ILVs. MVBs will then choose between two cell fates. Most of the MVBs are transported to the plasma membrane through the cytoskeletal network, where they release the ILVs (future exosomes) into the extracellular environment upon exocytosis, post fusion with the plasma membrane. Otherwise, MVBs undergo degradation by fusion with lysosomes or autophagosomes ,14,43,44Several mechanisms of the biogenesis have been studied, among which the endosomal sorting complex required for transport (ESCRT)-dependent pathway is most well-known. ESCRT-0 assembles cargos and the ESCRT-I–ESCRT-II complex mediates membrane budding and cargo internalization. Subsequently, ESCRT-III is responsible for the scission of the membrane neck .Once released, exosomes may be taken up by recipient cells in various ways, including endocytosis, receptor-mediated interactions, and membrane fusion ,47,48. AIt is the parent cells, environmental stimulation, and physiological conditions that determine the composition and yield of exosomes. Exosomes can contain a variety of proteins, such as membrane proteins, nuclear proteins, and extracellular matrix proteins. Also, cytosolic metabolites and nucleic acids such as mRNA, noncoding RNA, and DNA can be found in exosomes ,52.Emerging studies of the exosomal components have displayed the existence of proteins, nucleic acids, lipids, and other components, where lipids are thought to be the main component. There is a glycan canopy attached to the surface proteins and outer leaflet lipids on the outermost surface of exosomes . BeneathTraditionally, there are several ways of direct cell-cell communication, such as gap junctions, cell surface protein interaction, or communication with distant cells with the help of secreted factors. Also, chemical and electrical signals participate in intercellular communication ,60,61. E+T cells and CD8+T cells can secrete exosomes that can target dendritic cells (DCs), leading to T cell silence in an antigen-specific way [+T cells [Exosomes play a significant role in immunoregulation, such as immune activation, antigen presentation, immune tolerance, and immune suppression. For example, CD4ific way . Exosomeific way . Regulat+T cells . Numerou+T cells . On the +T cells . TherefoAlmost all normal cells can generate exosomes, such as dendritic cells, human umbilical vein endothelial cells (HUVECs), T cells, B cells, macrophages, mesenchymal stem cells (MSCs), and natural killer (NK) cells . ExosomeUltracentrifugation is now considered the gold standard technique for exosome extraction and isolation. Ultracentrifugation mainly isolates the desired components based on the size and density differences of exosomes in solution, so it is generally used for the isolation of large-dose sample components with marked differences in sedimentation coefficient . Though Size-exclusion chromatography is one of the most common techniques for exosomal isolation that isolates components depending on size. Larger molecules cannot pass porous gel filtration polymer, which acts as the stationary phase, while the smaller molecules remain in the gel pores and are eventually enriched in the mobile phase. Size-exclusion chromatography is a rapid, easy, and cost-efficient method, and does not influence the biological properties of exosomes, but may lack specialty and purity ,72.Microfluidics-based methods use microfluidic devices to separate exosomes based on physical characteristics such as size and density, or chemical properties such as combining exosome surface antigens. The immune-microfluidic technique, which is similar to the immunoaffinity technique, is most commonly used. Exosomes are isolated by the specific binding to antibodies which are attached to the microfluidic devices as exosome markers. This method makes the separation of exosomes fast and efficient, with high purity. However, the devices needed are complex and expensive ,74.In immunoaffinity methods, exosomes are obtained by specifically combining antibodies or magnetic particles. Antibodies are commonly used to recognize specific exosome surface markers, such as the tetraspanins: CD9, CD63, and CD81 ,76. ImmuIn the polymer precipitation method, polyethylene glycol (PEG) is generally utilized as a medium to gather exosomes by reducing the solubility of exosomes during centrifugation. This method is time-efficient and can deal with large doses of samples. However, this method has the disadvantage of relatively low purity and recovery rate ,78.The isolation methods described above are the most commonly used in research, while there are currently more and more novel ways to separate exosomes. In some research, different isolation techniques are combined for a better isolation effect than that of a single technique. For example, combing UC with SEC makes it possible to deal with large amounts of samples as well as increasing the purity of products, which draws on each other’s advantages .Nevertheless, the characterization and quantification of exosomes are still challenges, for exosomes are below the detection range of many current techniques.To characterize exosomes precisely, size, shape, surface charge, density, and porosity are important properties in the analysis of exosomes. Currently, there are a variety of methods to characterize exosomes, including nanoparticle tracking analysis (NTA) , dynamicIt has been proven that exosome RNA can mediate cell-cell communication. Initial research showed the presence of approximately 121 miRNAs that were found in exosomes, some of which were expressed at a higher level than that in donor cells . TherefoThe most straightforward way to load drugs into exosomes is incubation. In this way, drugs are incubated with exosomes or the donor cells at a specific temperature and then diffuse into exosomes by a concentration gradient. Incubation has been widely used to load hydrophobic cargoes like curcumin and paclitaxel, since the plasma membrane of exosomes are hydrophobic and lipid-enriched ,87. HoweTransfection is the most common method for loading RNA into exosomes. To generate RNA-loaded exosomes, specifically encoded plasmids are transduced into the exosome-generating cells. In this way, the desired RNA can be sorted into exosomes in donor cells through natural mechanisms ,91. AlthPhysical methods such as electroporation ,104, sonIn addition to the classical methods mentioned above, there are several other potential ways to load RNAs into exosomes. For example, the Exo-Fect™ Exosome Transfection Kit that was recently developed by System Biosciences Co. for exosome delivery enables the insertion of RNAs, DNAs (including plasmids), and small molecules into isolated exosomes . Also, cThe aforementioned techniques for RNA loading, along with their principles, benefits, and drawbacks are summarized in Most studies regarding exosome biodistribution indicated that natural exosomes spread in the extracellular fluid through free diffusion and are taken up by recipient cells through different mechanisms. To deliver specific cargos to target cells or tissues, multiple exosomal engineering techniques and corresponding delivery strategies have been developed , which aExosomes are generated by multiple types of cells and carry donor-cell-specific ligands, lipids, and adhesion molecules. Vectors that can trigger the production of ligands on exosomal surfaces or fusion proteins associated with ligands have been developed. To date, the ligand-receptor-binding-based targeting strategy has been the most commonly used, and is a highly specific method for delivering exosomes that specifically bind to receptors on the cells of interest. In order to introduce the desired ligands on the exosomal surface, there are currently two common approaches: (i) ligand modification through transfection and (ii) direct chemical assembling of ligands.Vectors that produce specific ligands on the exosomal surface or fusion proteins associated with ligands have been developed ,112. TheIn addition to cancer therapy, the demand for targeted drug delivery to normal cells is increasing due to the increase in nervous system disorders and other diseases, particularly those protected by physiological barriers such as the blood-brain barrier (BBB). Alvarez-Erviti et al. engineered dendritic cells to express Lamp2b that fused to the neuron-specific rabies viral glycoprotein (RVG) peptide through transfection . ExosomeAlthough transfection is effective for presenting genetically engineered proteins on the exosomal surface, it also exhibits several limitations, such as being expensive and complicated, as well as the inability to carry molecules other than genetically encodable peptides and proteins. The other method for adding desired ligands to the exosomal surface is direct chemical assembling, which allows for applying different types of ligands on the exosomal membrane through hydrophobic insertion or conjugation ,120,121.The specific chemical features of different cells or tissues are considered a focus for developing novel exosomal targeted delivery. Compared with normal cells, cancer cells display a higher rate of glycolysis and thereby elevated lactate production, contributing to an acidic microenvironment ,126. ThiIn addition to the targeted delivery approaches that use either biological or physicochemical properties of certain cells or tissues, the delivery can also be achieved by utilizing external attractive forces like magnetism ,129,130.Taken together, various methodologies have been developed for exosome engineering to efficiently deliver cargos to the target. Moreover, a combination of exosomal modification techniques can be used to achieve highly specific and more efficient drug delivery.With the advantages of safety, high biocompatibility, high bioavailability, and the ability to penetrate the BBB, exosomes have become increasingly promising and potential carriers for RNA drug delivery.Exosomes can be found in almost all kinds of body fluids, such as the blood, serum, synovial fluids, saliva, urine, amniotic fluid, and breast milk . They caTo improve the effectiveness of cancer therapy, it is urgent to deliver drugs to tumor cells specifically and accurately. Several RNA cancer therapies are in various stages of development, including mRNA, tRNA, siRNA, and RNA interference (RNAi) therapies, which are mainly concentrated in the early preclinical and clinical stages. The key to promoting RNA cancer treatment is to establish an effective delivery system that can solve the problems of early degradation, toxicity, and non-target-specificity of RNA molecules. Compared with other nanoparticle drug-delivery systems, exosomes have higher bioavailability for tumor tissues, as well as lower cytotoxicity and immunogenicity for normal tissues . Also, tmRNA cancer drugs can treat cancers by encoding and expressing tumor-specific antigen (TSA), a tumor-associated antigen (TAA), and other cytokines. It has been proven that exosomes may be a potential delivery carrier to increase the stability and transfection efficiency of mRNA as well . Wang etmiRNAs are a type of ncRNA commonly found in the non-coding region, which do not encode proteins. miRNAs play a significant role in regulating gene expression, since they can target mRNAs and promote their degradation or facilitate translation inhibition. The level of different miRNAs can thus efficiently affect the occurrence and growth of tumors. For instance, miR-708 can restrain the proliferation, survival, and migration of lung cancer cells, which is partly attributed to the inhibition of PGE2 signaling. In contrast, overexpression of miR-411-5p/3p may accelerate the proliferation and migration of non-small-cell carcinoma cells and inhibit cell apoptosis ,140. ThesiRNAs are another kind of RNA with double strands. siRNAs are mainly involved in RNAi reactions and regulate gene expression by inducing gene silencing. It is known that the development of cancer is closely associated with the overexpression of anti-apoptotic proteins such as KRAS, BCL-2, PLK1, survivin protein, and cell growth factors . TherefoCircular RNAs (circRNA) are an important class of noncoding RNAs without a 5′ cap or 3′ poly (A) tail. Through back-splicing by RNA polymerase II, circRNAs are covalently closed RNA circles. circRNA has been proven to participate in various biological reactions, such as cell proliferation, apoptosis, and survival. Also, some disease-related circRNAs can bind specific proteins, regulate RNA editing and transcription, serve as specific microRNA sponges, or produce peptides through translation ,151. AccIn addition to RNAs mentioned before, lncRNA, short hairpin RNA (shRNA), aptamer, and other types of RNA have gradually been introduced and explored to treat cancer. Exosomes can also act as suitable and efficient carriers for these RNAs. For example, Xiong et al. discovered a cancer-specific aberrant transcription-induced chimeric RNA encoding A-Pas, a cancer-specific chimeric protein that can modulate the occurrence and EMT of tumors. They used exosomes isolated from chimeric RNA-transfected dendritic cells to construct antitumor vaccines to treat esophagus cancer, resulting in the suppression of cancer and prolonged survival time of mouse models with tumors . Huang eThe previously described applications of RNA-loaded exosomes in cancer therapy are listed in Vaccines for infectious diseases are currently one of the most developed fields of gene therapy. To date, most studies use mRNA as therapeutic molecules to construct RNA vaccines. mRNA vaccines are taken up by target cells and then translated into antigens to induce immune responses. The key to delivering mRNA is to construct an efficient and stable delivery system. So far, most mRNA vaccines for research, or clinical use, use lipid nanoparticles (LNP) and virus-like particles (VLP) as delivery vehicles ,157. HowAccumulating evidence has indicated that exosomes play an important role in cell-cell communication and regulation. Exosomes are involved in the pathogenesis of many infectious diseases. Pathogens can be transmitted through incorporation into exosomes produced by host cells, or by viruses, parasites, and bacteria . During The outbreak of COVID-19 catalyzed the rapid development of mRNA vaccines. With the approval for use in humans of the Pfizer–BioNTech vaccine BNT162b2 and the Moderna vaccine mRNA-1273, an increasing number of researchers have realized the potential of mRNA vaccines and devoted themselves to the development of new mRNA vaccines . HoweverAlthough there are various examples of using exosomes to deliver pathogens such as proteins in the treatment of infectious diseases, RNA-loaded exosomes have not been widely used. However, many studies have shown that the use of exosome-mediated RNA therapy for infectious diseases is feasible and promising, and further studies are needed to expand knowledge in this field.In addition to playing an important role in intercellular communication, exosomes can also maintain myelin sheath, mediate neuronal protection, eliminate waste, and promote nerve and tissue regeneration in the central nervous system . DeliverParkinson’s disease (PD) is a common neurodegenerative disease resulting from an imbalance between excitatory and inhibitory neurotransmitters in the substantia nigra of patients . It is kAlzheimer’s disease (AD) is a prevalent neurodegenerative disease among the elderly. Currently, the cause of AD remains unclear and it is commonly assumed that amyloid-beta (Aβ) plaques and neurofibrillary tangles (NFTs) are related to the pathophysiology of AD . Due to Huntington’s disease (HD) is a mostly inherited neurodegenerative disease. A mutation results in the expression of an abnormal mutant protein (mHtt), which may be chronically harmful to brain cells via various possible mechanisms . AccordiA common feature of these neurodegenerative diseases is the deposition of insoluble proteins. After the RNA-loaded exosomes are delivered to the CNS, they can regulate the expression of these key proteins through transcription, gene silencing, and gene knockout to achieve therapeutic effects. Besides neurodegenerative diseases, RNA-loaded exosomes can be applied to treat stroke. After a stroke, the BBB is disrupted. It has been proven that exosomes can contribute to reconstruction in the long term by regulating peripheral immune response, promoting angiogenesis, and enhancing axonal dendritic remodeling . As the Exosomes can be used both as diagnostic indicators and as a means of treatment for central nervous system diseases. Exosomes are currently considered promising vehicles for transporting therapeutic molecules like RNAs to previously inaccessible brain areas due to their ability to penetrate BBB.Exosome-mediated RNA therapy has shown potential in the treatment of liver diseases. For example, Herrera et al. discovered that exosomes with cellular RNA separated from human liver stem cells may promote the proliferation of liver cells . Zhao etExosomes can also serve as a promising carrier in the treatment of kidney diseases. It has been proven that miRNA can suppress the process of kidney fibrosis by regulating the level of collagen and extracellular matrix . Thus, tIn the field of the treatment of lung diseases, exosomes can be a potential carrier for RNA therapy. Exosomes have the potential to overcome difficulties in delivering therapeutic molecules to lung tissue. Zhang et al. derived exosomes from serum and loaded small RNA into them. The results showed that the delivery system could efficiently target lung macrophages, suggesting that therapeutic RNA-loaded exosomes could be an effective and promising tool to treat inflammatory lung responses .Exosomes have been demonstrated to play a crucial regulatory role in cell-cell communication due to their capacity to deliver functional cargo molecules to recipient cells through circulation, and reprogram physiological processes in these cells. Exosomes are therefore promising therapeutic carriers in cell-free strategies for a variety of diseases due to their immunomodulatory properties. There are several advantages of utilizing exosomes as cargo delivery vehicles compared with liposomes and nanoparticles, particularly their stability in circulation. Covered with a biofilm, exosomes are capable of avoiding degradation by macrophages, which provides prolonged circulation times ,185. HowThe first and paramount challenge is the large-scale production of exosomes with high quality and well characterization ,187. ExoTechniques are needed to artificially increase the contents of specific RNAs . NeverthThe third challenge is to evaluate the safety, immunogenicity, and biodistribution of therapeutic exosomes in clinical trials. Since exosomes carry a group of signaling molecules, the administration of exosomes may elicit immune responses in the host, contributing to the toxicity and rapid clearance of exosomes ,199. TheThe clinical translation of exosomes is an exciting but complicated process filled with numerous challenges. For the successful commercialization of exosome-based therapeutics, not only scientists but commercial manufacturers should put effort in relevant investigations to resolve both technological and logistic issues.Taken together, accumulating evidence has demonstrated the potential of exosomes in delivering RNA. Exosomes have low immunogenicity, high biocompatibility, and high delivery efficiency, providing new ideas for the delivery of therapeutic RNA molecules. There are many methods for loading RNA into exosomes, such as incubation, transfection, and physical methods. However, further studies are still needed to achieve satisfactory loading efficiency. To improve the delivery efficiency of exosomes, various exosomal surface engineering techniques have been developed. Though exosome-mediated RNA therapy is considered a promising approach for the treatment of many diseases, many challenges remain to be overcome, such as the large-scale production of exosomes, the insufficient efficiency of RNA loading, and the evaluation of therapeutic effects. Further studies are needed to solve these problems and realize the full potential of exosome-based RNA therapy.


Metastasis is a major cause of death in lung cancer patients. Therefore, a deeper understanding of the metastatic mechanisms is important for developing better management strategies for lung cancer patients. This study evaluated the patterns of extrathoracic metastases in lung cancer. We retrieved data for 25,103 lung cancer patients from an institutional database and then evaluated the impacts of clinicopathologic factors on metastasis patterns. We found that 36.5% of patients had extrathoracic metastasis. Younger patients had a significantly higher extrathoracic metastasis rate in most histologic subtypes. Metastases to the bone (58.3%), central nervous system (CNS) (44.3%), liver (26.6%) and adrenal gland (18.3%) accounted for 85.5% of all extrathoracic metastases. Patients with nonmucinous adenocarcinoma had significantly higher bone metastasis rate. Patients with small cell carcinoma and large cell neuroendocrine carcinoma (LCNEC) had significantly higher liver metastasis rates. Further, patients with LCNEC also had a significantly lower bone metastasis rate, and patients with squamous cell carcinoma had a significantly lower CNS metastasis rate. Patients with multiple cancers had similar patterns of metastasis compared to patients with only lung cancer. In conclusion, different histologic subtypes of lung cancer have different metastatic patterns. Our study might help clinicians decide on follow-up strategies. Metastasis is the major cause of death in patients with lung cancer , and 40–In the field of metastasis research, an important but unsolved question is what makes tumor cells prefer specific organs to metastasize . The conLung cancer has several histologic subtypes. Each subtype has a distinct morphology, clinical presentation and gene mutation profile . TherefoTherefore, we performed a large, retrospective, single-institution cohort study evaluating the impact of histologic subtypes and other clinical factors on the metastatic pattern of lung cancer.Data from 26,589 patients diagnosed with primary lung malignancy between 1994 and 2014 were retrieved from the Samsung Medical Center Cancer Registry. Retrieved data included age at diagnosis, sex, International Classification of Diseases for Oncology, 3rd Edition (ICD-O-3) histology codes, histological diagnosis, history of other malignancy, presence of metastasis, sites of distant metastasis, presence of recurrence, and sites of recurrence. Only cases with pathologically confirmed diagnoses were included. A total of 1470 patients with uncertain histological diagnosis or a diagnosis of carcinoid, lymphoid malignancy or sarcoma were excluded. In addition, 16 patients younger than 20 years were also excluded. Finally, 25,103 patients were included. The sites of metastasis or recurrence were reviewed and reclassified for each organ. Recurrences in distant organs were considered as metastases in this study. Lung-to-lung metastasis was excluded from analysis because it is very difficult to differentiate between lung-to-lung metastatic lesions and second primary lesions.U-test. Categorical variables were compared using the Pearson chi-square test or Fisher’s exact test, as appropriate.The normality of continuous variables was evaluated using the Kolmogorov–Smirnov test. Continuous variables without normal distribution are described as the median and interquartile range and were compared using the Mann–Whitney Statistical analyses were performed using OriginPro version 2021  and SPSS Version 17.0 .A total of 25,103 cases were included in this study. We categorized these cases according to their histologic diagnoses as follows: 12,878 adenocarcinomas (ADCs), 6655 squamous cell carcinomas (SCCs), 126 adenosquamous carcinomas (ASCs), 785 salivary gland-type carcinomas (SGCs), 225 sarcomatoid carcinomas (SCs), 1713 non-small cell lung cancers, not otherwise specified , 2373 small cell lung cancers (SCLCs) and 350 large cell neuroendocrine carcinomas (LCNECs). Of the 12,878 ADC cases, 12,455 were categorized as non-mucinous adenocarcinomas (N-MACs) and 421 were categorized as mucinous adenocarcinomas (MACs). The 225 SC cases included 220 pleomorphic carcinomas and 5 carcinosarcomas. Patient characteristics according to histologic diagnoses are summarized in Among the 25,103 cases, 9153 (36.5%) had at least one extrathoracic metastasis. NSCLC, NOS had the highest extrathoracic metastasis rate (52.1%), followed by SCLC (51.7%), LCNEC (46.6%), N-MAC (40.9%), SC (40.0%), ASC (35.7%), SCC (21.7%) and SGC (18.1%). MAC had the lowest extrathoracic metastasis rate (13.8%).p = 0.174 and p = 0.592, respectively). In the SGC group, patients with metastasis and patients without metastasis were similar in age (p = 0.908). In addition, female patients showed a significantly higher rate of metastasis than male patients in the major histologic groups, including the N-MAC (p = 0.048), SCC (p < 0.001), NSCLC, NOS (p < 0.001), and SCLC (p = 0.034) groups. In the other groups, sex was not significantly associated with metastasis , followed by the central nervous system (CNS) , liver  and adrenal gland . Regardless of the histologic subtype, most metastases were found in these four organs; metastases to these organs accounted for 85.5%  of all metastases. Distributions of metastases according to histologic type are illustrated in p = 0.064). N-MAC had a significantly higher rate of bone metastasis than other histologic subtypes  (p < 0.001). MAC  and ASC  also had higher rates of bone metastasis than other histologic subtypes, but they were not statistically significant . SCLC  and LCNEC  showed significantly higher rates of liver metastasis than other histologic subtypes (both p < 0.001). In contrast, LCNEC  had a significantly lower rate of bone metastasis than other histologic subtypes (p < 0.001). SCC  and SC  had significantly lower rates of CNS metastasis than other histologic subtypes .Next, we compared rates of metastasis to the adrenal gland, bone, liver and CNS to see whether there were significant differences in the metastatic pattern according to histologic type . SC had We calculated odds ratios to determine whether metastasis to a given organ could influence metastasis to another specific organ. In the entire cohort, most organs’ metastases were negatively correlated with metastasis to other organs . HoweverLast, we compared the metastatic pattern between patients with only lung cancer and patients with lung cancer and another cancer. Among 25,103 patients, 2370 (9.4%) had another carcinoma, including 373 with gastric cancer, 268 with colorectal cancer, 221 with thyroid cancer, 132 with liver cancer, 104 with prostate cancer, 90 with breast cancer, and 1183 with other carcinomas. Although the number of patients was insufficient for statistical analysis, we observed metastatic patterns in patients with multiple cancers similar to those in patients with only lung cancer .Metastasis is a complex and dynamic process mediated by numerous factors . TherefoThe NSCLC, NOS group showed the highest metastasis rate (52.1%), which was higher even than that of the SCLC group (51.7%). This result is consistent with those of several previous studies, which suggested that the diagnosis of NSCLC, NOS is a poor prognostic factor on its own ,20. HoweAmong the remaining histologic groups, the SCLC group (51.7%) and the LCNEC group (46.6%) had higher metastasis rates than the N-MAC group (40.9%). The SCC group 21.7%) had a significantly lower metastasis rate than the other major histologic subtype groups. These findings are consistent with those of several previous studies ,13. Addi.7% had aInterestingly, younger patients had a higher metastasis rate than older patients in all histologic groups except the SGC group. Several previous studies also reported higher metastasis rates in younger patients with lung cancer ,13,17,23Additionally, female patients had significantly higher metastasis rates than male patients in the major histologic groups, including in the N-MAC, SCC, NSCLC, NOS and SCLC groups. To our knowledge, no previous study has reported a higher metastasis rate in female lung cancer patients. Riihimäki et al. reported that female patients had a significantly higher rate of CNS metastasis ; howeverThe bone, CNS, liver and adrenal gland were common sites of distant metastasis in all histologic groups. These four sites accounted for 85.5%  of all metastases. However, lung cancer subtypes also showed significant differences with regard to metastasis to those four organs. N-MAC had a significantly higher bone metastasis rate than other subtypes, whereas SCLC and LCNEC had significantly higher liver metastasis rates. LCNEC had a significantly lower bone metastasis rate than other subtypes, and SCC and SC had significantly lower CNS metastasis rates. A high bone metastasis rate of N-MAC ,18, highWang et al. reported that bone metastasis tends to co-occur with liver or distant lymph node (DL) metastasis, and liver metastasis tends to co-occur with DL metastasis . We wereTo examine whether another carcinoma could influence the metastatic pattern of lung cancer, we compared metastatic patterns between patients with only lung cancer and patients with lung and other cancers. If metastatic organotropism is only mediated by intracellular factors, there would be no interaction between different carcinomas. However, Hoshino et al. previously reported that tumor-derived exosomes taken up by organ-specific cells prepare the pre-metastatic niche . AccordiIn conclusion, all histologic types of lung cancer showed a strong predilection of metastasis to the bone, CNS, liver and adrenal gland. However, there were significant differences in preference among these four organs based on the histologic subtype.


In 2022, population over the age of 65 is currently about 3.8 million  as an “aged society” in Taiwan. According to the report about the frailty of the elderly increases with age, especially 75 - 79 years old, are the most obvious functional decline . This trend that also happened in 2005, the interim report of the 3rd national health promotion measures showed an increased prevalence of diabetes mellitus and obesity in Japan. In response to this, Dr. Satake and Dr. Arai (2020) develop the questionnaire for Medical Checkup of Old-Old (QMCOO) suited measure frailty to people aged ≧75 years better and composed of 15 questions regarding the following 10 domains: health condition, mental health, eating behavior, oral function, body weight loss, physical function and falls, cognition function, smoking, social participation and social support implemented in April 2020. This study authorized by Dr. Satake et, al in August 2022, aims to translate the QMCOO in Chinese version and through expert discussions to confirm that there are no difference between the original version in Japanese/English, and the apply query specification for QMCOO in Taiwan. This study recruited 300 older adults in Taichung city to answer all the questions in QMCOO and analysis the diagnostic frailty distributed status compared to the data measure in the Kihon Checklist in the same time. This finding the cutoff scores 2/3 for the QMCOO might be effective in diagnosing frailty in Taiwan.


Self-empowerment from abiotic matter to biological behavior does not just occur at the beginning of biological evolution; it is also essential for all levels of socially interacting RNAs, cells and viruses.Our understanding of the key players in evolution and of the development of all organisms in all domains of life has been aided by current knowledge about RNA stem-loop groups, their proposed interaction motifs in an early RNA world and their regulative roles in all steps and substeps of nearly all cellular processes, such as replication, transcription, translation, repair, immunity and epigenetic marking. Cooperative evolution was enabled by promiscuous interactions between single-stranded regions in the loops of naturally forming stem-loop structures in RNAs. It was also shown that cooperative RNA stem-loops outcompete selfish ones and provide foundational self-constructive groups (ribosome, editosome, spliceosome, The evolutionary split of RNA sequences into repetitive and non-repetitive nucleotide syntax had far-reaching consequences for the evolution of protein-coding complexity and regulation .Various highly coordinated processes are outlined by different RNA networks, such as RNA editing (editosome) and alternative splicing (spliceosome). Both the editosome and the spliceosome represent RNA stem-loop groups that assembled through ligation procedures during their long evolutionary history . This hi•DNA replication with important functions of centromeres and telomeres in genome maintenance•RNA guidance of chromosome structure•Regulation of transcriptional and post-transcriptional modifications by spliceosomes and editosomes according to the requirements of the context•Regulatory pathways and coordination in all steps of the translation into proteins•Epigenetic marking and short-term and long-term memory formation and its (re)modification•DNA repair organization and coordination in all detailed steps and substeps•Immunity organization and coordination in all steps and substeps by genome plasticity, V (ariable) D (iversity) J (oining) plasticity in adaptive immune response•Genetic identity of organisms which initiates motifs of self-interaction or non-self-interaction•Genetic content composition of host organisms by genetic parasites (viruses and defectives such as transposons and retroposons)•Intron/exon genome fragmentation as a benefit in immune functions (CRISPR/Cas) as well as in genome modularity and complexity.RNA stem-loop groups represent an unmanageable quantity of sophisticated regulatory networks . These g•pseudoknots, kissing loops, A-minor motifs, A-platforms, kink-turns, S-turns, tetraloops and their receptors, and a variety of non-canonical base-pairs and base-triples•ribosomal frameshift as a natural technique to process alternative translation of an mRNA sequence by changing the open-reading frame•bypassing translation•competing endogenous RNAs.The active roles played by RNA stem-loop groups ensure all life processes currently known and start with the transcription process out of the relatively stable DNA storage medium. After transcription, an abundance of RNA stem-loop variants are available and interact in well-coordinated actions. The folding loop remains as a single-stranded RNA sequence. Various motifs have been identified, yet all of them share a common function: they stabilize RNA tertiary formation. Such motifs include:All these highly coordinated and interconnected motifs of RNA stem-loop groups may alter the meaning of the information stored in the DNA according to the environmental and/or circumstantial requirements of an organism, which means that the information is context dependent. This is documented by the essential roles of riboswitches also .Group identity and membership of single RNA stem-loops in ensembles of formerly integrated groups seem to be useful in (re)building new RNA stem-loop groups. We must not forget the essential roles that RNA minorities such as former degraded RNAs play in small RNA stem-loop groups, or even single stem-loops ready to be reused in (re)building current functional RNA groups.The genetic code of DNA may represent the result of the effective escape strategy of RNA-networks: out of a competitive RNA world and into a new sequence space to better conserve successfully selected genetic identities. The reverse transciptases and related RNA networks produce complementary strands of RNA to DNA, which means it’s the crucial escape technique. As RNA polymerases they copy a single stranded RNA sequence into a single stranded DNA sequence. The reverse transcriptase is very old and a key driver of genomic plasticity and seems to stem from early RNA world replicons . In thisThis means DNA can also be investigated as fixed (memorized) evolutionary results arising from RNA stem-loop group competition and cooperation. In this perspective, DNA-based information represents a natural code, and RNA stem-loop groups represent the code editors. This makes sense because if DNA is really a natural code, we must not forget that no natural code codes itself, just as no natural language speaks itself . In all •may identify the key players that edit (modify and determine) the genetic codes of host genomes as consortia of RNA agents and virus-like genetic parasites that drive evolutionary novelty;•investigates RNA group behavioral motifs and their role in regulating replication, gene expression, recombination, immune functions and generation of new nucleotide sequences;•explains the emergence of new sequence space not as a result of selection arising from error-replication events, but as a result of competent generation of nucleotide sequences and genome editing;•focuses on social behavior of RNA agents with their emerging properties, such as communicative interactions represented by cooperation and competition .In contrast to mathematical modelling, socially interacting RNA stem-loop groups may help us better understand group membership and interactional motifs to establish relevant genetic identities . RNA socThe natural code and its users and their communicative interactions can be investigated as social phenomena which cannot be fully understood by mathematical modelling (see chapter 3) and physical/chemical investigations alone, as these focus on statistical mechanics which differ from biotic behavior .i.e. RNA stem-loop groups interact and self reproduce. They were convinced that the whole object of investigation principally can be fully described in terms of physics, which means, can be computed and depicted in mathematical equations . Not the superficial DNA sequence syntax determines the meaning (function) but pragmatic context of real life in which organisms are involved. This is a crucial difference in explaining genetic information. In the explanatory models of the 20th century, the superficial DNA syntax was thought to represent the final information not its pragmatic use with its varying context dependent meanings. In contrast to 20th century narratives which tried to identify meaning out of superficial sign sequence syntax, we now know that it is the context in which sign sequences are used that determines the meaning, not the syntax. This was completely ignored by linguist Chomsky and chemist Eigen  that govern the following: the combination of signs (syntax), the coherence between sign and content (semantics) and, most importantly, the use of signs according to a specific context (pragmatics). Rule-following in communicative interactions is essentially a social event, because a single agent cannot follow a rule only once, as proved by Ludwig Wittgenstein . The useCells, tissues, organs and organisms communicate at four key levels that are essential for all cell-based life forms see Witzan,2019.e.g. dialects in bacteria or even in bee languages, and generate really new sign sequences with really new content  being key evolutionary drivers of genetic variations . We now century .Cellular organisms primarily try to survive by producing individual and social pathways embedded in situational contexts. This affects bodily impressions, actions and reactions which are relevant for epigenetic markings. At this stage, we have to realize that the transgenerational inheritance of epigenetically memorized and learned capabilities, in particular, does not fit the mutation/selection narrative of the modern synthesis, which is insufficiently complex to integrate that .Last but not least, we have to identify how ancient RNA-world networks came into the cellular domains. Where do all these RNA regulators in cells come from? How did RNA get that crucial role for cell-based life ? In thisAfter nearly a hundred years of cell biology, it is usual to think about life on this planet as cellular life forms that colonized nearly all ecological niches. All definitions of life have focused on cellular life. We know three domains of cellular life which assemble all kinds of cell-based life, from simple archaea to the most complex brain organs in humans. What appears to be still unusual is thinking about life as a virosphere dominating the whole planet, in so far as viruses outnumber cellular life forms tenfold . In 1 miThe early quasispecies, RNA viruses and related genetic parasites can be considered as key drivers of evolutionary processes in the evolution of all domains of life. Viruses have colonized all cellular organisms since the beginning of life . In mostMeanwhile, we know many examples in which viruses and related genetic parasites are key drivers for the evolution of new features in organisms . Well-knLynn Margulis showed convincingly that the eukaryotic cell is not the result of a series of selected replication errors but a social compound of former free-living prokaryotes . A furthA helpful model to understand the persistent lifestyle of viruses and related genetic parasites in cellular organisms is the “addiction module”. This presents an empirically based explanatory model which may be intrinsic to all regulations/counter-regulations in cellular organisms. Currently we can identify such addiction modules in toxin/antitoxin, restriction/modification and several insertion/deletion modules. They derived from infectious viral clouds and competing viral clouds that, together with the host immune system, reach an equilibrium status which is missing in the members of the species which did not experience these infection waves and their remnants. These addiction modules change the genetic identity of the host organism. Members of the same species that integrated such addiction modules into their genetic identity are protected against the toxin, whereas members without this integration are exposed to the toxin .Together with the RNA remnants of former genetic parasites (defectives), such as long non-coding RNAs and the abundance of short non-coding RNAs or microRNAs and their dominant roles in gene regulation of all cellular processes such as replication, transcription, translation, repair, immunity, epigenetics and additionally the several substeps, we must acknowledge that, without RNA stem-loop group interactions, life as we know it on our planet would not function in detail and as a whole  based on the 21st century denotes a paradigmatic change in explaining and understanding life  being key drivers of genetic/genomic novelty is insufficiently complex to integrate RNA productivity. This is shown by our current knowledge about the pre-cellular emergence of the RNA world, the dominant role of persistent viruses, their relatives and defectives, such as mobile genetic elements, and their descendants, such as the abundance of non-coding RNAs and their role in gene regulation, generation of variants and genetic novelty, together with knowledge of the variety of epigenetic programming and the transgenerational inheritance of acquired characteristics.RNA networks, viruses and their defectives constantly produce new genetic variants and generate new sequences which are exposed to selective forces. This constant production is an innovative process, not an error in pre-existing DNA sequences, and therefore should be denoted more precisely as high productivity being the essential driver of random variations. What was described by Manfred Eigen as self-organization of matter, we can now modify and call the self-empowerment of life, because the competencies and behavioral motifs of RNA stem-loop groups empower all organisms which host such groups to evolve, develop, adapt and perform all the regulatory processes necessary for all known life processes. As this high productivity is not part of the modern synthesis of evolution, it is time to develop an integrative theory of evolution which has better explanatory power to integrate the abundance of empirical data on RNA biology, virology and biocommunication of cells produced in recent decades. This author is in complete agreement and enthusiastic about the change of the narrative of life to a more vital , non-mechanistic and non-only syntactic one. Nietzsche made the first advances in this line for biology taking man as if he were just another biological being where he soon encountered difficulties in thinking in only Darwinian terms. “Self-empowerment” was exactly the metaphysical alternative set by Nietzsche to confront Spinoza’s “self-preservation”, the concept that Nietzsche discovered to be the strong metaphysical support to Darwin's natural selection. Malthus' theory was rejected by Nietzsche because its simple to explain the whole life. I agree the “self-empowerment” concept can be proposed as a hypothesis for scientific research. And it can be formulated in scientific terms, which can be proposed to change M. Eigen's narrative of “self-organization of matter”, which has self-preservation in its focus. By accepting life as a dynamic of power relations, self-destruction is one of the possibilities. We - men - seem to be moving rapidly in this direction. The hypothesis is that what matters is no longer the individual who enters the struggle of life but winning in the struggle, for which individuals must sacrifice part of their own aspects. This agrees with the authors: from individual replicons, they will become "quasispeices" then “consortia of quasispeices", covalently-fixed consortia (tRNA), rRNA. Nietzsche, first observed that the struggle of life explained as a competition  ignores the immense amount of co-operation in the struggle (simultaneous co-operation and competition) because this struggle is not to preserve one’s life, but rather in the main to achieve power:«My idea is that every specific body strives to become master over all space and to extend its force (its will to power) and to thrust back all that resists its extension. But it continually encounters similar efforts on the part of other bodies and ends by coming to an arrangement (‘union’) with those of them that are sufficiently related to it: thus they conspire together for power. And the process goes on»Darwin forgot the spirit (that is English!); ….. It will be noted that by "spirit" I mean care, patience, cunning, simulation, great self-control, and everything that is mimicry .” “ Communication is at the center for reaching agreements and social relations -“mimicry” is a communication element- and yes, at the center of self-empowering. Communication rules will change accordingly, the ‘organism’ interprets according to its biological interest in surviving and advancing itself. For this reason, Nietzsche’s perspectivism is not entirely relativist, but pragmatic. “There are no facts, only interpretations” /// “In fact, interpretation is itself a means of becoming master of something. : 3543–3547. Memory in Viral Quasispecies. Page 9: “Such memory/learning skills can be found in organisms ranging from viruses…”  Add citation of Esteban Domingo. Page 12: Table 1. “dead”. Probably better “inert”?Is the review written in accessible language?YesAre all factual statements correct and adequately supported by citations?YesAre the conclusions drawn appropriate in the context of the current research literature?YesIs the topic of the review discussed comprehensively in the context of the current literature?YesReviewer Expertise:Biochemistry and Molecular Biology.I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Yes, Communication on all levels of sign-mediated interactions within and between RNA networks, viruses and cellular organisms together with epigenetic markings that ensure memory and learning empower biotic agents to survive beyond the outdated concept of mutations (error replications) and selection.  If better learned skills and competencies are relevant for survival, then it is clear that the old narrative is insufficiently complex to integrate that. An integrative theory of evolution has to outline this in future. Villarreal and Witzany define a novel and thought-provoking concept in Biocommunications: Self-empowerment as the key feature during evolution and the core of biotic communication. They establish RNA stem-loop groups as essential molecules involved in the initial step between abiotic matter and life. These RNA stem-loops are the main characters of evolution, creating communicative interactions with themselves and other molecules by competition and cooperativity, building molecular consortia, and allowing the emergence of viruses, cells, and organisms. Life complexity is sustained by complex RNA networks, viruses, and molecular editing, constantly changing and adapting to each context, allowing biocommunication at all levels. As experts in Biocommunications, the authors argue for a more complex understanding of the role of RNA productivity, viruses, and epigenetics in shaping genetic variation and driving evolutionary change. The manuscript is thorough, and the authors show a deep and updated knowledge of RNA, Virology, and Evolution, besides providing a compelling and innovative perspective. From my point of view, the article is clear, but the authors assume all readers will have a wide knowledge of Biocommunications, and some ideas are based on concepts not sufficiently described in the text. I understand the difficulties of including all this information, but an introduction to the essential concepts may be helpful for a more fluent reading. Some examples are RNA syntax; “The Shooting of the Hunters”; “Umwelt”; Teleonomic key technique; Proponents; Turing, and von Neumann machines ideas; and “hypercycles”. Additionally, there is a concept that might be interesting to include in the paper regarding Biocommunication and context: Riboswitches. These are molecules found in all life realms that show conformational changes in response to a specific ligand, like a secondary metabolite, modulating transcription and translation. Overall, I consider this study of significant interest to the general readership of F1000Research journal.Figure 1 provides ample information, but I have found some difficulties trying to understand it. Perhaps more details in the legend will improve its interpretation. Likewise, more details about the flow of arrows should be explained to clarify their meaning.I suggest changing the wording of RNAses to RNases. This is a common misuse, but the proper term is RNase.The text states that RNase H emerged from the RNA world and is introduced before the proteins’ emergence. It can be misunderstood as an RNA molecule, but this RNase is formed exclusively by protein.The tri-peptide concept can be ambiguous and unclear for the reader. It would also be helpful to provide some additional explanation.This section is especially engaging and covers a logical evolution in the interconnections between RNA activities and how they became more complex. However, everything is explained as if RNA was the only starter, whereas that occurs in collaboration with other types of molecules which appear during evolution, such as proteins, essential to make more complex relationships with RNA. Maybe the authors mean ribosome and RNase activities in RNA molecules, which evolve later in protein molecules.Section 2.1:There is a typo, "startet" instead of started.Please, consider a period after the reference .Section 2.4:Section 2.5: there is an absence of a period or comma after the references .The evolution of living systems with quasispecies dynamics and proteins depends on an unequivocal “code-system” and a relational protein system which evolves via “hypercycles”.I have found this section a little hard to understand, and I would appreciate some help from the authors to make it clearer. Especially the sentence: There is a typo, "irreversibe" instead of irreversible (include the “l”).Section 3:Section 4: Please, consider a period after .Section 5.1: I miss the presence of two periods in this section, after , and . Finally, I would like to give a list of suggestions to improve the clarity and impact of the manuscript:Is the review written in accessible language?YesAre all factual statements correct and adequately supported by citations?YesAre the conclusions drawn appropriate in the context of the current research literature?YesIs the topic of the review discussed comprehensively in the context of the current literature?YesReviewer Expertise:Structural Biology, RNA Structure, Virology, Hepatitis C Virus, RNA-protein Interactions, Translation Regulation, Fragile X syndrome.I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. according the suggestions in the 2nd paragraph of this review: Important issues, but this would need another chapter to integrate all suggestions. further suggestion to Figure 1: will be integrated to RNase H: corrected to section 2.1: looks rather clear to section 2.4: corrected to section 2.5: corrected to section 3, 4 and 5.1: corrected This article introduces the concept of "self-empowerment" of life, the key message of which is that life forms and their evolution cannot be explained if viewed as purely syntax (coding DNA/RNA) driven automatons (Turing or von Neumann machines). Instead, the specific context (pragmatics) of the syntax, which is governed primarily through RNA agents that communicate via stem-loop structures, is the more important aspect of life. RNAs regulate various life processes including epigenetics (and inheritance thereof), which represents an essential layer of context for the coding genes, which is subject to evolutionary selection and more important for evolutionary processes when compared to random mutations of coding genes. The article is well-written and conveys the message in a comprehensive yet concise manner. Overall the article is already in a very good shape. However, the authors may consider the following suggestions and comments:, there is evidence that selfish or parasitic replicators (RNAs) do take over a population, leading to the collapse of the population, unless there is compartmentalization. Once compartmentalization is introduced, not only are the parasites prevented from eradicating the population, they are also actively contributing to the evolution of complexity. I suggest including this information and some relevant references by answering the question whether the models in which "cooperative RNA stem-loops outcompete selfish ones" also require compartmentalization. Page 3, around "An unexpected finding is that cooperative RNA stem-loops outcompete selfish ones". Looking at experiments and computational data published, for example, by Ichihashi Page 4, bottom: Assuming that viruses and cells have common ancestors, that cells evolved from viruses or vice versa, or at least there is constant lateral gene exchange between virosphere and cellular life, do the authors have any explanation as to why there is not a single virus expressing a ribosome? Has the ribosome become too complex (optimized) in present-day cells, requiring dozens of accessory proteins? I am asking also in light of the finding that some of the NCLDVs were found to have genetic information (incomplete) of the translational machinery.. RTs had existed probably long before the emergence of retroviruses. Page 6, "The reverse transcriptase (…) seems to stem from a retroviral origin." In my understanding, retroviruses as we know them have relatively recently emerged evolutionarily. We know that a ribozyme-reverse transcriptase can evolve Page 7, "Empirical data contradict this model of explanation." – I suggest softening this to "There is no empirical data to explain this model." (or similar) unless there is actual contradicting data, in which case it should be briefly mentioned/explained. Page 7, around the paragraph starting with "Eigen’s adaptation…" Very interesting. Just a thought that came to my mind is that, for example, humans and mice share virtually the same set of genes , yet the phenotype of both species differs substantially. The phenotypic differences are mostly the result of pragmatic context rather than amino acid sequence, i.e., syntax. Technical: There are some full stops missing throughout the manuscript, especially after citations.Is the review written in accessible language?YesAre all factual statements correct and adequately supported by citations?YesAre the conclusions drawn appropriate in the context of the current research literature?YesIs the topic of the review discussed comprehensively in the context of the current literature?YesReviewer Expertise:Mobile genetic elements, (evolutionary) virology, vaccines, immunologyI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. ad page 3: Yes, we will include these arguments ad page 4: The issue of the ribosome and virus is indeed fundamental and interesting.  Although some viruses do enclose host ribosomes in virions and as noted NCLDV can encode many translational components, to date no virus appears to encode the ribosome itself.  Yet the ribosome itself clearly appears to be a collective of ligated stem-loop RNAs originally derived from various sources (in a virus-like process).  This implies that once the ribosome emerged, it became the fundamental host for all subsequent viruses as well as a fundamental entity for cells themselves.  Thus the clear and lasting virus-host dynamic emerged from the collective and transmissible RNA world and created a host that could acquire meaningful virus-derived code. ad page 6: Yes, important note! As Reverse Transcriptase based early RNA world Replicons predated the DNA world and the cellular world, and retroviruses emerged propably in a later stage of evolution there is no doubt, that retroviruses decended from these early reverse transcriptase sharing RNA replicons. We will note that  ad page 7: Empirical Evidence of the non-existence of von Neumann and Turing machines as well as theoretical considerations contradict this model of explanation. Nature of living organisms cannot be properly accommodated within such a theoretical framework. This is because the language that codes machine programs is not compatible with that of the genetic code. Languages controlling Turing and von Neumann machines are formal algorithms, in which syntax determines meaning independently of context. Gene expression depends on environmental context, however, so cannot be similarly treated as a formal language. ad Page 7, around the paragraph starting with "Eigen’s adaptation…": Yes, as most presentations at the meeting in Salzburg 2022 (How Evolution Learnt to Learn) demonstrated the phenotypic differences depend on epigenetic markings, which indeed are the result of pragmatic context of different lifeworlds (of e.g. humans and mice) ad Technical: Will be corrected This is very important and interesting manuscript illuminating diverse roles of RNA networks in evolution and development of organisms in all domains of life. Cooperative evolution of viruses, cells and organisms is under-appreciated but it allows understanding a the most complex issues related emergence and evolution of life. This RNA sociology places life in a correct context and explains many mysteries left behind from the outdated 29th century concepts based primarily on statistical mathematics. Life is not based on mechanistic machines or automatons but is based on truly living organism which actively experience and interpret their ever-changing and very complex abiotic and biotic environment. All organisms are based on cells which communicate, learn and memorize their experiences. I have only three small comments: 1) Authors could briefly discuss the still confusing issue if viruses are living or non-living agents. Also, why viruses act as living agents only if they invade living cells and seems to be inert (non-living) outside of cells.. 2) For the alternative endosymbiotic origin of the eukaryotic nucleus see Baluška F, Lyons S (2021). 3) Roles of viral infections in the evolution of cells were discussed earlier. Baluška F (2009)Is the review written in accessible language?YesAre all factual statements correct and adequately supported by citations?YesAre the conclusions drawn appropriate in the context of the current research literature?YesIs the topic of the review discussed comprehensively in the context of the current literature?YesReviewer Expertise:Cell Biology, Plant Sensory Biology, EvolutionI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. ad 1: As viruses seem to predate cellular life and together with RNA networks invented cellular life and additionally outnumber cellular life 10 times and infect cells multiple throughout their lifes it would extend energy costs to still carry on cell-independent replication apparatus, which could have led to an evolutionary arms race between cell-dependent and cell-independent replicating viruses. Viruses invented the cellular life-sphere that guarantees their replication. The cellular biosphere on this planet is the dominant lifesphere of viruses. This is the benefit for current viral life styles. We have outlined this definition problem of viruses being alive or not in chapter 6 of: Villarreal LP, Witzany G. Social Networking of Quasi-Species Consortia drive Virolution via Persistence. AIMS Microbiol. 2021 Apr 30;7(2):138-162. ad 2+3: We will insert suggested references


In addition, we discover several point mutations using a generalized linear model, and motifs of interest, which also match transcription factor-binding motifs.Alu elements are one of the most successful groups of RNA retrotransposons and make up 11% of the human genome with over 1 million individual loci. They are linked to genetic defects, increases in sequence diversity, and influence transcriptional activity. Still, their RNA metabolism is poorly understood yet. It is even unclear whether Alu elements are mostly transcribed by RNA Polymerase II or III. We have conducted a transcription shutoff experiment by α-amanitin and metabolic RNA labeling by 4-thiouridine combined with RNA fragmentation (TT-seq) and RNA-seq to shed further light on the origin and life cycle of Alu transcripts. We find that Alu RNAs are more stable than previously thought and seem to originate in part from RNA Polymerase II activity, as previous reports suggest. Their expression however seems to be independent of the transcriptional activity of adjacent genes. Furthermore, we have developed a novel statistical test for detecting the expression of quantitative trait loci in Alu elements that relies on the de Bruijn graph representation of all Alu sequences. It controls for both statistical significance and biological relevance using a tuned  Alu elements are around 300-bp-long RNA retrotransposons  in primates, which lastly fused to form the Alu elements .Methods, Alu RNA used interchangeably with Alu transcripts). This is of particular interest regarding past experiments that utilized Pol-II inhibition, as it is common practice to rely on SINEs as a non-Pol-II-dependent negative control group in such cases.Despite the presence of a Pol-III promoter in their sequence, Alu elements are expected to be transcribed not only by Pol-III but also by RNA polymerase II (Pol-II) . Biological replicates were cultured independently.Human K562 erythroleukemia cells were obtained from DSMZ . K562 cells were cultured in accordance with the DSMZ Cell Culture standards in RPMI 1640 medium (Thermo Fisher Scientific) containing 10% heat inactivated fetal bovine serum (Thermo Fisher Scientific), 1% penicillin–streptomycin, and 1× GlutaMAX supplement (Thermo Fisher Scientific) at 37°C in a humidified 5% COAmanita phalloides and a potent inhibitor of RNA Pol-II (−1), while RNA polymerase I (Pol-I) and mitochondrial RNA polymerases remain unaffected by α-amanitin. Treatment conditions were optimized for selective RNA Pol-II inhibition (see RT-qPCR and Western blotting). For α-amanitin (5 or 15 µg mL−1) treatments of K562 cells, cells were treated for a time course of 0–9 h at 37°C in a humidified 5% CO2 incubator. For TT-seq and RNA-seq, K562 cells were treated for 8 h at 37°C in a humidified 5% CO2 incubator with 5 µg mL−1 α-amanitin or solvent (water).α-Amanitin is a toxic substance from the mushroom −1 α-amanitin or solvent), g for 2 min. Total RNA was isolated with QIAzol (QIAGEN) according to manufacturer’s instructions except for the addition of 10 ng RNA spike-in mix (6 spike-ins selected from ERCC RNA spike-in mix) (−1), and dNTP mix  were mixed and incubated at 65°C for 5 min. Subsequently, Maxima H Minus Reverse Transcriptase (RT)  and 5× Maxima RT buffer (Thermo Fisher Scientific) were added (+RT reaction). For DNA contamination control, cDNA synthesis without RT (−RT reaction) was performed (RT was substituted with water). The (−/+) RT reactions were incubated in a PCR cycler at 25°C for 10 min, 50°C for 30 min, and 85°C for 5 min. Primers for quantitative PCR were designed by using the online primer design software Primer3 v.0.4.0 (E) for each target gene, slope of standard curve (S), and mean threshold cycle (Ct) (For each condition (5 or 15 µg mL v.0.4.0 . Brieflycle (Ct) .−1) treatments of K562 cells, cells were treated for 8 h at 37°C in a humidified 5% CO2 incubator. Water was used as a solvent. After 8 h of treatment, K562 cells were harvested at 3,000 × g for 2 min and washed twice in Dulbecco's phosphate-buffered saline (DPBS). Cells were lysed in radioimmunoprecipitation assay (RIPA) lysis buffer for 45 min on ice and centrifuged at 14,000 × g for 15 min at 4°C. Samples were quantified with the Bradford method. Fifteen micrograms of cell lysate was denatured in 4× Loading Dye (including 100 mM DTT) at 70°C for 10 min. PrecisionPlus Protein All Blue Standard  was used as marker. NuPAGE 4–12% Bis–Tris Protein Gels and MOPS buffer were used according to manufacturer’s instructions. Transfer of a single NuPAGE onto PVDF membrane was performed in transfer buffer at 30 V for 1 h in a XCell II Blot Module (semiwet transfer unit) according to manufacturer’s instructions. Membrane blocking was performed in 5% milk PBS-T on a rocking surface for at least 1 h. Primary antibody was added overnight. The following primary antibodies were used in this study: N-terminal POLR2A/hRPB1 antibody, clone F-12  and GAPDH antibody, clone C 71.1  as a loading control. HRP-coupled secondary antibody targeting mouse IgG  was used at a dilution of 1:3,000 and incubated on a rocking surface for 1 h. Enhanced chemiluminescenc (ECL) working solution of SuperSignal West Pico PLUS Chemiluminescent Substrate was prepared according to manufacturer’s instructions. Proteins were visualized by chemiluminescence detection on INTAS. POLR2A/hRPB1 (RNA Pol-II) degradation, which is α-amanitin dose dependent (For α-amanitin (5 or 15 µg mLSynthetic RNA spike-in controls are derived from selected RNAs of the ERCC RNA Spike-in Mix (Ambion) as described in −1 of α-amanitin or solvent (water) for 8 h. After 7 h 55 min, a 4-thiouridine (4sU) labeling pulse  was applied for 5 min using 500 µM . Similar results were obtained when spike-in RNAs were taken as reference as compared to mtRNAs  to analyze the genomic sequences of all annotated Alu elements on base level were created with the glmnet package for R  to illusk-mer length of 9 and including 100 bp of flanking regions up- and downstream of each Alu sequence. k = 9 was chosen so that the distribution of Alu sequences per node in the graph was smooth, neither running into the lower nor the upper range of possible values (k-mer connecting tips were kept by using the –keep-mercy (-y) argument, and the compacted de Bruijn graph was colored using the –colors (-c) argument.The de Bruijn graph of all Alu sequences, regardless of expression, was generated using bifrost v1.0.5 , with a e values . Low-covk = 9 is almost complete: It contains 131,070 nodes, i.e. k-mers and 1,048,544 in-edges, resulting in >7.99 edges per node (similarly >7.99 for out-edges). Note that the maximum in-degree and out-degree in the compacted graph is 8, not only 4, since each node can be traversed in forward and reverse complement direction , as well as the stability of Alu transcripts, which is expected to be low in comparison to regular mRNA (Methods), which relates to the degradation rate δ by As was found by lar mRNA . We usedP < 0.05 in all comparisons, Kolmogorov–Smirnov (KS) test or Wilcoxon test, both with Bonferroni multiple testing correction]. The split can be further verified by performing average linkage hierarchical clustering with the KS test statistic as a distance measure between Alu families. This separates the AluY subfamilies clearly from the older families, except for the aforementioned AluSq10 and AluYc3 (AluYc2)  .Methods). However, due to the overall paucity of Alu read counts, our MLE results are relative and do not represent explicit values (see Discussion). Our half-life estimates for Alu elements show a dispersion very similar to that of mRNAs . We quantified the degree of inhibition using mitochondrial RNAs as a negative control group, which are unaffected by α-amanitin (see Methods). Similar results were obtained when spike-in RNAs were taken as reference  of −0.70  significantly upregulated but 7,770 (42%) significantly downregulated transcripts for mRNAs and 47 (0.2%) significantly upregulated but 2,071 (11%) significantly downregulated transcripts for Alu elements.It is remarkable that some Alu elements show significant downregulation under α-amanitin treatment at all, which suggests that the affected Alu elements could be partly Pol-II transcripts.Introduction).Evolutionary changes in the Alu sequence could reveal informative clues on sequence features that influence the mechanism of Alu transcription and retrotransposition. Obvious, prominent features of potential impact are the Pol-III promoter split into A and B box and the SRP-binding motif used for attachment to the ribosome exit tunnel (see Methods). Due to the encoding of the sequence changes with respect to the Alu consensus sequence, this results in individual effect sizes (β parameters) for the 3 types of examined point mutations, base exchanges, deletions, and insertions, for each position in the Alu consensus sequence. The abundance of Alu sequences in the genome offers the unique opportunity to use an analysis strategy resembling a genome-wide association study. We used a GLM to link Alu sequence features to their transcript abundance , which resulted in 2 positions of interest, all in the vicinity of terminal loops 4 and 5  of the right arm, which is also the region containing the SRP 9/14-binding motif: UGU(NR) (Due to the large number of samples (i.e. Alu elements), we could also investigate interactions between paired bases in the secondary structure . Next, we filtered for k-mers with statistical significance and biological relevance. Each k-mer splits the group of all Alu sequences into those containing the k-mer and those that do not. At the same time, each Alu element can be either expressed (at least 1 read count) or not. This gives rise to a 2 × 2 contingency table, to which we apply a Fisher test and calculate the odds ratio . k-mers with both an OR of less than 0.5 or greater than 2 and a Bonferroni-corrected Fisher test P-value less than 0.05 were included in the downstream analysis, leaving us with 38 k-mers of interest. Finally, we performed another Fisher test comparing expressed and nonexpressed Alu elements in the group containing a specific k-mer of interest vs the group of Alu elements containing the k-1 Prefix and suffix of that k-mer. This resulted in merely 12 remaining k-mers of interest after applying the same stringency criteria , NFIX , and TFE3 . Also, all listed transcription factors are Pol-II specific . This exposes the cells to extreme levels of stress, as their protein metabolism is breaking down. This, in turn, may lead to the retention and accumulation of RNAs that are not related to shock response in the nucleus. As our DTA does not differentiate between nuclear and cytoplasmic RNA fractions, this could appear as apparent upregulation. Alternatively, protein translation inhibition, especially of proteins related to mRNA degradation (such as deadenylases or Xrn1), could be involved . We found that with a k either smaller or larger than 9, the high sequence similarity of Alu elements quickly leads to problems. With a k smaller than 9, many k-mers are possessed by all or almost all Alu elements, while with a k larger than 9, a high number of k-mers are unique to a few or even a single Alu sequence. In both unfavorable cases, a majority of k-mers are ruled out simply by the selection of k. This might appear as a limitation of our method, but in fact, it is an intrinsic limitation shared by all continuous-motif-based methods. Our method merely makes this problem noticeable and offers a solution through parameter tuning. We also see the potential for our approach to be applied to other data sets in the future.It is remarkable that our new method employing de Bruijn graph k-mers.Taken together, we present a compendium of results regarding the RNA metabolism of Alu elements. Our analyses affirm that older Alu families are more strongly expressed than younger Alu families, but the stability of Alu transcripts appears to be close to that of mRNA. Furthermore, we find evidence for Alu transcripts originating both from Pol-II and Pol-III activities, but no evidence for Alu transcripts being side products of Pol-II gene transcription. Finally, we have identified a list of sequence features that influence Alu transcription and are thus targets for further investigations and developed a novel method to test the statistical significance and biological relevance of de Bruijn graph https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE75792) for the data described in https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE185485) for the data relating to the inhibition of RNA Pol-II by α-amanitin. GSE75792 was used for all non-interventional analyses, while GSE185485 was used for the differential expression analysis.The sequencing data used in this publication have been deposited in NCBI’s Gene Expression Omnibus (G3 online.Supplemental material is available at jkac054_Supplement_S1Click here for additional data file.jkac054_Supplement_S2Click here for additional data file.jkac054_Supplement_S3Click here for additional data file.jkac054_Supplement_S4Click here for additional data file.jkac054_Supplement_S5Click here for additional data file.jkac054_Supplement_S6Click here for additional data file.jkac054_Supplement_S7Click here for additional data file.jkac054_Supplement_S8Click here for additional data file.jkac054_Supplement_S9Click here for additional data file.jkac054_Supplement_S10Click here for additional data file.jkac054_Supplement_S11Click here for additional data file.


In vitro transcribed, modified messenger RNAs (IVTmRNAs) have been used to vaccinate billions of individuals against the SARS-CoV-2 virus, and are currently being developed for many additional therapeutic applications. IVTmRNAs must be translated into proteins with therapeutic activity by the same cellular machinery that also translates native endogenous transcripts. However, different genesis pathways and routes of entry into target cells as well as the presence of modified nucleotides mean that the way in which IVTmRNAs engage with the translational machinery, and the efficiency with which they are being translated, differs from native mRNAs. This review summarises our current knowledge of commonalities and differences in translation between IVTmRNAs and cellular mRNAs, which is key for the development of future design strategies that can generate IVTmRNAs with improved activity in therapeutic applications. These early experiments demonstrated that the injection of pure, in vitro transcribed mRNA into mouse muscle resulted in the detectable production of the encoded protein , and better understanding of IVTmRNA-specific translation mechanisms is required to generate more efficient sequence design approaches. With these aims in mind, this review summarises the current literature and understanding of the mechanism of protein synthesis from IVTmRNAs and its relation to protein synthesis on natural transcripts.in vitro transcription template. All these UTR elements play key roles in recruiting ribosomes and translation factors to the RNA.All eukaryotic mRNAs, whether mature endogenous transcripts or IVTmRNAs, consist of a number of non-coding elements alongside the protein coding open reading frame ORF, . The nonWhilst such elements are common between IVTmRNAs and endogenous mRNAs, their effect on translation can differ between natural transcripts and IVTmRNAs due to their differing routes of entry into the cytoplasm and differing modes of engagement with the translational machinery . A partiNative mRNAs engage the translational machinery following nuclear transcription, processing and export to the cytoplasm. During this journey, transcripts do not exist as naked RNAs, instead, they associate with RNA binding proteins to form messenger Ribonucleoproteins (mRNPs). According to the current view in the field, mRNPs change composition as they progress through the different steps of a transcript’s life cycle, in a manner that involves coordinated handover events between the different protein complexes . An impoHallmarks of nuclear mRNPs following transcription, splicing and export include a dimeric nuclear cap-binding complex (CBC) on the mRNA cap structure. On spliced mRNAs, an additional hallmark is the presence of exon junction complexes (EJCs) which are deposited over exon:exon junctions during splicing and which signal the location of such sites to the translational machinery and the cellular mRNA surveillance pathways. The first or “pioneer” round of translation is thought to occur on mRNPs in this state . During via interactions with additional translation initiation factors. The active translational state can be interrupted by several eIF4E binding proteins which disrupt eIF4E:eIF4G contacts  tail are placed downstream of a T7 promoter sequence  tail . In currin vivo . DespiteOne of the fundamental differences between natural transcripts and IVTmRNAs is the fact that the latter do not pass through the natural mRNP states that precede engagement of the translational machinery. Any of the processes that have been identified as functionally dependent on the pioneer round of translation, including secretion and antigen presentation, may thus be less efficient for IVTmRNAs.The synergistic effect from the presence of both a cap structure and the poly(A) tail in IVTmRNAs  is similMultiple lines of evidence indicate that introduction of IVTmRNA-containing LNPs into cells is perceived as a stress that activates various translational control mechanisms. The interaction of nanoparticles with cells can be a cause of stress in itself , althougin vitro transcription process  such as toll-like receptors 7, 8, and 3 that sense single and double stranded RNA, thereby generating its own immune response . Moreover, response . Both arnded RNA . Althougnded RNA .in vitro transcribed RNA (The activation of both PKR and innate immune response pathways can be suppressed by introducing various modified nucleotides into the ibed RNA . Most cuibed RNA . Despiteibed RNA .Pseudouridine (Ψ) is the most common natural base modification in RNAs, including mRNAs . AlthougDespite the similar geometry of their base-pairing hydrogen bonds, experimental studies have shown that U and Ψ form base pairs with other bases with different affinities. In addition to stabilising the canonical base-pair with adenine, Ψ also stabilises wobble-base pairs with guanine and uridine, but not with cytidine . These eFollowing initial work with pseudouridine, it was found that methylation of its N1 atom  further It is difficult to compare the translational activity of uridine-, Ψ- and m1Ψ-containing IVTmRNAs directly because effects of the modifications on the transcript itself need to be disentangled from the PKR-dependent global regulation of translation. Using a massively parallel survey of 5′-UTRs, in vitro with bacterial ribosomes  was impaired, indicating that communication between the decoding centre and the PTC is less efficient on Ψ containing codons.The inhibitory effect of Ψ and m1Ψ in both UTRs and ORFs may be in part attributable to the effect of the modifications on the stability of secondary structure elements, although increased stability could also result in a prolonged lifetime and therefore prolonged expression of the target antigen. A direct inhibitory effect of Ψ on codon decoding was confirmed ibosomes . In thisin vivo, the overall time required to decode a codon is dependent on the number and type of non-cognate tRNAs that need to be rejected before a cognate tRNA is accepted (In decoding systems accepted . A partiaccepted . Near-coaccepted . Since Ψaccepted  and bothaccepted , Ψ incoraccepted , and a raccepted . TogetheThe effects resulting from intended uridine modifications may overlap with effects caused by inadvertent modifications that can occur in IVTmRNAs, notably those arising from the oxidation of nucleotides in RNA. Oxidatively damaged nucleotides in RNA can lead to amino acid misincorporation  and riboet al. observed that membrane association could relieve m1Ψ-dependent ribosome collisions in vitro (, potentially as a consequence of the altered translational dynamics of membrane associated ribosomes. In sum, whether ribosome collisions occur on modified or unmodified therapeutic mRNAs in vivo is unknown, although if collisions do occur they are likely to reduce the efficiency with which such transcripts are translated.One consequence of reduced ribosome speed can be ribosome collisions, which cells can perceive as signalling events that elicit a variety of cellular responses. Ribosome collisions can activate Gcn2, p38 and JNK kinases and reduce global translational activity in the affected cell . At the in vitro , potentiHow much protein an mRNA can produce can be limited either by the translation initiation rate or by the translation elongation rate, depending on the ratio of the two activities . While tDifferent studies have emphasized various design principles for nucleic acid-based vaccines. These include copying codon usage from highly expressed mammalian genes, which improves translational dynamics and also increases the GC content of the ORF ; more fiAlthough IVTmRNAs are translated by the cellular gene expression machinery, their genesis and route of entry into the cell are fundamentally different from native transcripts. In consequence the location of their first engagement with the translational machinery, their arrival as a non-protein bound, “naked” RNA molecule rather than a pre-formed mRNP, and the presence of modified nucleotides in high densities all have consequences for the efficiency with which IVTmRNAs are translated. Understanding these differences in better detail is required if protein synthesis rates of therapeutic mRNAs are to be improved.Although therapeutics currently in clinical use are clearly efficient enough to form effective vaccines, the expression levels required to stimulate immune responses are relatively low. The various modes for non-vaccine therapeutics that are currently being explored will require higher expression levels, and for such applications removing the translational limitations of current constructs is of key importance.


At the same time, the levels of serum tumor markers and cytokines and tumor markers and cytokines in intraoperative peritoneal lavage fluid were compared among the three groups. The results showed that the proportion of TNM stage III in peritoneal metastasis group and other metastasis group was 68.00% and 62.50%, respectively, and the proportion of tumor >5 cm was 64.00% and 59.38%, respectively, which was significantly higher than that in the control group. The 1-year survival rate of peritoneal metastasis group and other metastasis group was 44.00% and 40.63%, respectively, which was significantly lower than that of nonmetastasis group (P < 0.05).The serum levels of CEA, CA125, CA19-9, IL-6, IL-4, and IL-2 in peritoneal metastasis group and other metastasis group were higher than those in nonmetastasis group. The intraoperative peritoneal lavage fluid CEA, CA125, and IL-6 were 13.41 ± 3.72 ng/ml, 8.97 ± 1.33 U/ml, and 1.85 ± 0.44 pg/ml, respectively, which were higher than those in other metastasis groups and nonmetastasis groups (P < 0.05). There was no significant difference in the levels of CA19-9, IL-4, and IL-2 in peritoneal lavage fluid among peritoneal metastasis group, other metastasis groups, and nonmetastasis groups (P > 0.05); the areas under the ROC curve of intraoperative peritoneal lavage fluid CEA, CA125, and IL-6 in predicting peritoneal metastasis were 0.850, 0.902, and 0.806, respectively, P < 0.05. Thus, the conclusion is that peritoneal lavage fluid CEA, CA125, and IL-6 have certain application value in predicting and diagnosing peritoneal metastasis of gastric cancer, while the other indexes have no application value.The paper is written to investigate the levels and significance of tumor markers  and cytokines  in serum and peritoneal lavage fluid of patients with peritoneal metastasis of gastric cancer. For this research, 145 patients with gastric cancer treated in our hospital were divided into peritoneal metastasis group ( Patients with advanced gastric cancer are prone to liver, peritoneal cavity and other important organ metastasis, and about 14%~43% of patients with gastric cancer have peritoneal metastasis . PeritonRelevant studies  suggest 145 patients with gastric cancer treated in our hospital were included in the time range from January 2017 to January 2020. They met the following inclusion criteria: (1) confirmed by pathology; (2) radical gastrectomy in our hospital; (3) AJCC stage I~III; (4) no antitumor treatment before operation; and (5) informed consent of patients and their families. Meanwhile, they avoided the following exclusion criteria: (1) incomplete follow-up data; (2) tuberculosis, HIV, and other infections; and (3) accompanied by chronic obstructive pulmonary disease, coagulation dysfunction, and other serious diseases.n = 25), other metastasis group (n = 32), and nonmetastasis group (n = 88). There are 13 males and 12 females in peritoneal metastasis group, with an average age of 51.54 ± 8.22 years, ranging from 31 to 68 years; there are 20 males and 12 females in other metastasis groups, with an average age of 50.42 ± 9.15 years, ranging from 28 to 73 years old; there were 52 males and 36 females in the nonmetastasis group, with an average age of 51.22 ± 8.90 years, ranging from 30 to 74 years old. There was no significant difference in gender and age among the three groups (P > 0.05).According to the occurrence of metastasis, the patients were divided into three groups: peritoneal metastasis group . There was no significant difference in sex, age, tumor location, and pathological type between peritoneal metastasis group, other metastasis group, and nonmetastasis group (P > 0.05). It is as shown in The proportion of TNM stage III and the proportion of tumor size >5 cm in peritoneal metastasis group and other metastasis groups were significantly higher than those in nonmetastasis group (P < 0.05), as shown in The 1-year survival rate of peritoneal metastasis group and other metastasis group was 44.00% and 40.63%, respectively, which was significantly lower than that of nonmetastasis group (P < 0.05). There was no significant difference in serum levels of CEA, CA125, CA19-9, IL-6, IL-4, and IL-2 between peritoneal metastasis group and other metastasis groups (P > 0.05). It is as shown in The levels of serum CEA, CA125, CA19-9, IL-6, IL-4, and IL-2 in peritoneal metastasis group and other metastasis groups were higher than those in nonmetastasis group (P < 0.05); there was no significant difference in the intraoperative peritoneal lavage fluid CA19-9, IL-4, and IL-2 levels among peritoneal metastasis group, other metastasis groups, and nonmetastasis groups (P > 0.05). It is as shown in The intraoperative peritoneal lavage fluid CEA, CA125, and IL-6 in peritoneal metastasis group were higher than those in other metastasis groups and nonmetastasis groups (P < 0.05), as shown in The areas under the ROC curve of intraoperative peritoneal lavage fluid CEA, CA125, and IL-6 to predict peritoneal metastasis were 0.850, 0.902, and 0.806, respectively (Malignant tumor progression is the most common recurrence and metastasis, and peritoneal metastasis is one of the common biological behaviors in the recurrence and progression of gastric cancer. When it is diagnosed, it is mostly at the end of the disease , 6. GastCEA, CA125, and CA19-9 are important tumor markers. The changes of the above markers are commonly used in clinical work to detect the metastasis, recurrence, and curative effect evaluation of malignant tumors , 8. IL-2Traditional cytological examination of peritoneal lavage fluid is an important method for clinical detection of peritoneal free cancer cells. Relevant studies suggest that laparoscopic exploration and peritoneal lavage fluid cytology can find out whether there is peritoneal metastasis and the degree of peritoneal metastasis in gastric cancer patients with suspected peritoneal metastasis –13. The Further studies showed that the areas under the ROC curve of intraoperative peritoneal lavage fluid CEA, CA125, and IL-6 in predicting peritoneal metastasis were 0.850 and 0.902, respectively. It is suggested that peritoneal lavage fluid CEA, CA125, and IL-6 have certain application value in the prediction and diagnosis for peritoneal metastasis of gastric cancer. CEA is a carcinoembryonic antigen in embryo and fetus, which belongs to a protein complex rich in polysaccharides. Studies suggest that CEA is closely related to the prognosis of cancer. CA125 is a macromolecular carbohydrate protein complex, which does not rise significantly in mucinous epithelial carcinoma and granulosa cells but significantly increases in serous epithelial carcinoma and endometrioid carcinoma. It has become a commonly used tumor marker in clinic. Relevant literature  suggestsIn conclusion, CEA, CA125, and IL-6 in peritoneal lavage fluid have certain application value in the prediction and diagnosis of gastric cancer peritoneal metastasis, but other indexes have no application value.