CircATP13A1 (hsa_circ_0000919) promotes cell proliferation and metastasis and inhibits cell apoptosis in pancreatic ductal adenocarcinoma via the miR-186/miR-326/HMGA2 axis: implications for novel therapeutic targets.

Pancreatic ductal adenocarcinoma (PDAC) is a notoriously aggressive malignancy with a survival rate of merely 9%. The prognosis in patients with PDAC is relatively poor, particularly in patients with advanced distant metastases. However, the mechanisms of PDAC progression remain elusive. Circular RNAs (circRNAs) have been implicated in the development of various malignancies, including PDAC. Therefore, this study aimed to investigate how a novel circRNA, circATP13A1, regulates PDAC progression. We used the GEO database to determine circATP13A1 expression levels in cancer and adjacent cells and employed the limma package of R software to identify differentially expressed circRNAs. We detected the expression of circATP13A1, miR-186, and miR-326 using qRT-PCR and investigated the effect of circATP13A1 on cell proliferation, migration, invasion, and apoptosis in vitro using the Cell Counting Kit-8 (CCK-8), the transwell migration assay, and the flow cytometry assay. We then performed RNA pull-down assay, RNA immunoprecipitation (RIP), and Western blot to verify the interaction between circATP13A1, miR-186, miR-326, and HMGA2. Moreover, we used a naked mice model to determine how circATP13A1 affects tumor growth and progression in vivo. Loss and gain of function analyses revealed that circATP13A1 upregulation promotes cell proliferation, migration, invasion and tumor growth both in vitro and in vivo, which results in PDAC progression and poor prognosis in patients. CircATP13A1 knockdown significantly impaired cell proliferation and migration of PDAC cell lines. Additionally, circATP13A1 knockdown significantly increased the expression of miR-186 and miR-326, while reducing the expression of HMGA2 (P < 0.05), indicating that miR-186 and miR-326 are downstream targets of circATP13A1. Rescue experiments support the interactions between circATP13A1, miR-186, miR-326, and HMGA2. In conclusion, we demonstrated that circATP13A1 sponges the miR-186/miR-326/HMGA2/axis, acting as an oncogene to promote PDAC development.

The Role of Extracellular Vesicles in Colorectal Cancer.

Extracellular vesicles (EVs) are a class of spherical vesicles that are produced by active secretion of cells and encapsulated by phospholipid bilayers. In recent years, numerous studies have shown that EVs play pivotal roles in the regulation of intercellular communication between colorectal cancer (CRC) cells and target cells, and can regulate the proliferation, metastasis, and infiltration of tumor cells by regulating the microenvironment of tumor cells. EVs carry specific molecular substances in source CRC cells and are expected to serve as new molecular markers for the detection of cancers. This review highlights the current state of research and progress of potentially incorporating EVs in the diagnosis and treatment of CRC.

Investigation of trends in gut microbiome associated with colorectal cancer using machine learning.

Background: The rapid growth of publications on the gut microbiome and colorectal cancer (CRC) makes it feasible for text mining and bibliometric analysis. Methods: Publications were retrieved from the Web of Science. Bioinformatics analysis was performed, and a machine learning-based Latent Dirichlet Allocation (LDA) model was used to identify the subfield research topics. Results: A total of 5,696 publications related to the gut microbiome and CRC were retrieved from the Web of Science Core Collection from 2000 to 2022. China and the USA were the most productive countries. The top 25 references, institutions, and authors with the strongest citation bursts were identified. Abstracts from all 5,696 publications were extracted for a text mining analysis that identified the top 50 topics in this field with increasing interest. The colitis animal model, expression of cytokines, microbiome sequencing and 16s, microbiome composition and dysbiosis, and cell growth inhibition were increasingly noticed during the last two years. The 50 most intensively investigated topics were identified and further categorized into four clusters, including "microbiome sequencing and tumor," "microbiome compositions, interactions, and treatment," "microbiome molecular features and mechanisms," and "microbiome and metabolism." Conclusion: This bibliometric analysis explores the historical research tendencies in the gut microbiome and CRC and identifies specific topics of increasing interest. The developmental trajectory, along with the noticeable research topics characterized by this analysis, will contribute to the future direction of research in CRC and its clinical translation.

A LASSO-based model to predict central lymph node metastasis in preoperative patients with cN0 papillary thyroid cancer.

Introduction: Central lymph node metastasis (CLNM) is common in papillary thyroid carcinoma (PTC). Prophylactic central lymph node dissection (PCLND) in clinically negative central compartment lymph node (cN0) PTC patients is still controversial. How to predict CLNM before the operation is very important for surgical decision making. Methods: In this article, we retrospectively enrolled 243 cN0 PTC patients and gathered data including clinical characteristics, ultrasound (US) characteristics, pathological results of fine-needle aspiration (FNA), thyroid function, eight gene mutations, and immunoenzymatic results. Least absolute shrinkage and selection operator (LASSO) analysis was used for data dimensionality reduction and feature analysis. Results: According to the results, the important predictors of CLNM were identified. Multivariable logistic regression analysis was used to establish a new nomogram prediction model. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) curve were used to evaluate the performance of the new prediction model. Discussion: The new nomogram prediction model was a reasonable and reliable model for predicting CLNM in cN0 PTC patients, but further validation is warranted.

Intraductal oncocytic papillary neoplasm arising in Peutz-Jeghers Syndrome bile duct: a unique case report.

BACKGROUND: Peutz-Jeghers syndrome (PJS) is a rare, autosomal dominant disorder caused by germline mutations of STK11/LKB1, with an increased risk of tumors at multiple sites. Intraductal oncocytic papillary neoplasm (IOPN) is a unique subtype of intraductal papillary neoplasm of the bile duct (IPNB) defined by a premalignant neoplasm with intraductal papillary or villous growth of biliary-type epithelium. IOPN has a distinct mutation profile compared with both IPNB and intraductal papillary mucinous neoplasm (IPMN). CASE PRESENTATION: We herein describe the case of a 44-year-old woman who presented as polyps in the intestinal lumen of sigmoid colon and a 3.1 × 2.1 cm mass in the left lobe of liver. Gross feature revealed a cystic papillary mass and the neoplasm had a clear boundary with the surrounding liver tissue. Histology revealed complex papillary structures, a small amount of fine fibrovascular cores and immunohistochemistry showed extensive positive for MUC5AC, MUC6, CD117. Therefore, histological and immunohistochemical examination of the liver tumor suggested the diagnosis of IOPN. Next-generation sequencing (NGS) revealed other than STK11 germline mutation, the tumor also harbors GNAS somatic mutation at codon 478 and EGFR amplification. CONCLUSION: To our knowledge, this is the first report of IOPN arising in PJS. This case enlarges the spectrum of PJS related tumors and genetic rearrangements in IOPN.

Pathological Nodal Staging Score for Gastric Signet Ring Cell Carcinoma: A Clinical Tool of Adequate Nodal Staging.

Background: Gastric signet ring cell carcinoma (GSRCC) is a subset of gastric cancer with distinct histological and inconsistent prognosis outcome. Currently, the association between the adequate regional lymph node and proper nodal staging in GSRCC is rarely noticed. Materials and methods: Clinical data of GSRCC were retrieved from the Surveillance, Epidemiology, and End Results database. Beta-binomial distribution model was employed for the estimation of the probability of missing nodal disease, followed by the development of a nodal staging score (NSS). Results: A total of 561 GSRCC patients were included in this study, with 193 in lymph node-negative and 368 in lymph node-positive diagnoses. As the number of examined lymph nodes increased, the probability of missing nodal disease decreased rapidly, with T stage-specific curves. The probability of missing nodal disease in T4 was lower than that in T1. NSS calculation indicated that T1 stage patients commonly had NSS > 0.8. However, with the NSS of T2−T4 to reach 0.8, the number of examined lymph node was required to be larger than 12 in T2, 17 in T3 and 27 in T4. NSS ≥ 0.75 (quantile 75%) subgroup in T2−T4 subgroups tended to have better outcome; however, without significant prognostic value. Conclusions: NSS is served as a reliable and feasible tool in adequate nodal staging of GSRCC with statistical basis and provides further evidence for clinical decision making.

Landscape of Artificial Intelligence in Breast Cancer (2000-2021): A Bibliometric Analysis.

BACKGROUND: Breast cancer remains one of the leading malignancies in women with distinct clinical heterogeneity and intense multidisciplinary cooperation. Remarkable progresses have been made in artificial intelligence (AI). A bibliometric analysis was taken to characterize the current picture of development of AI in breast cancer. MATERIALS AND METHODS: Search process was performed in the Web of Science Core Collection database with analysis and visualization performed by R software, VOSviewer, CiteSpace and Gephi. Latent Dirichlet Allocation (LDA), a machine learning based algorithm, was used for analysis of topic terms. RESULTS: A total of 511 publications in the field of AI in breast cancer were retrieved between 2000 to 2021. A total of 103 publications were from USA with 2482 citations, making USA the leading country in the field of AI in breast cancer, followed by China. Mem Sloan Kettering Canc Ctr, Radboud Univ Nijmegen, Peking Univ, Sichuan Univ, ScreenPoint Med BV, Lund Univ, Duke Univ, Univ Chicago, Harvard Med Sch and Univ Texas MD Anderson Canc Ctr were the leading institutions in the field of AI in breast cancer. AI, breast cancer and classification, mammography were the leading keywords. LDA topic modeling identified top fifty topics relating the AI in breast cancer. A total of five primary clusters were found within the network of fifty topics, including radiology feature, lymph node diagnosis and model, pathological tissue and image, dataset classification and machine learning, gene expression and survival. CONCLUSIONS: This research depicted AI studies in breast cancer and presented insightful topic terms with future perspective.

Identification of Key Genes and Pathways Involved in Circulating Tumor Cells in Colorectal Cancer.

BACKGROUND: Characterization of the features associated with circulating tumor cells (CTCs) is one of major interests for predicting clinical outcome of colorectal cancer (CRC) patients. However, the molecular features of CTCs remain largely unclear. METHODS: For identification of key genes and pathways, GSE31023, contained CTCs from six metastatic CRC patients and three controls, was retrieved for differentially expressed gene (DEG) analysis. Protein-protein interaction networks of DEGs were constructed. Hub genes from the network were prognostic analyzed, as well as the association with tumor-infiltrating immune cells. RESULTS: 1353 DEGs were identified between the CTC and control groups, with 403 genes upregulated and 950 downregulated. 32 pathways were significantly enriched in KEGG, with ribosome pathway as top. The top 10 hub genes were included, including eukaryotic translation elongation factor 2 (EEF2), ribosomal protein S2 (RPS2), ribosomal protein S5 (RPS5), ribosomal protein L3 (RPL3), ribosomal protein S3 (RPS3), ribosomal protein S14 (RPS14), ribosomal protein SA (RPSA), eukaryotic translation elongation factor 1 alpha 1 (EEF1A1), ribosomal protein S15a (RPS15A), and ribosomal protein L4 (RPL4). The correlation between CD4+ T cells and RPS14 (correlation = -0.5) was the highest in colon cancer while CD8+ T and RPS2 (correlation = -0.53) was the highest in rectal cancer. CONCLUSION: This study identified potential role of ribosome pathway in CTC, providing further insightful therapeutic targets and biomarkers for CRC.

The role of AI technology in prediction, diagnosis and treatment of colorectal cancer.

Artificial intelligence (AI) is a fascinating new technology that incorporates machine learning and neural networks to improve existing technology or create new ones. Potential applications of AI are introduced to aid in the fight against colorectal cancer (CRC). This includes how AI will affect the epidemiology of colorectal cancer and the new methods of mass information gathering like GeoAI, digital epidemiology and real-time information collection. Meanwhile, this review also examines existing tools for diagnosing disease like CT/MRI, endoscopes, genetics, and pathological assessments also benefitted greatly from implementation of deep learning. Finally, how treatment and treatment approaches to CRC can be enhanced when applying AI is under discussion. The power of AI regarding the therapeutic recommendation in colorectal cancer demonstrates much promise in clinical and translational field of oncology, which means better and personalized treatments for those in need.

Bibliometric Evaluation of Publications (2000-2020) on the Prognosis of Gastric Cancer.

Background: Gastric cancer remains a global malignancy. The role of bibliometric analysis is increasingly valued. It is feasible and necessary to perform a bibliometric analysis to regurgitate studies in the prognosis of gastric cancer. Materials and methods: Web of Science was selected for the dataset resource. Articles published between 2000 and 2020 within the database of Web of Science Core Collection were included with predefined search terms. CiteSpace version 5.7.R1 and R software program version 4.0.3 were used for bibliometric analysis with parameters extrapolated from included studies. Results: A total of 1721 articles were included from 2000 to 2020 with remarkably increasing trends. China (n=1183), Japan (n=218), and South Korea (n=119) showed the most publications. SUN YAT SEN University, FUDAN University, and NANJING MED University were the top institutions with most publications. Keywords with strongest citation bursts between 2000 and 2020 were characterized. Particularly, "statistics", "resistance", "mortality", "lncrna", "diagnosis", "outcome", "migration", "promote," and "regulatory t cell" were the latest rising keywords since 2017, indicating possible study trends ahead. Several articles showed strongest citation bursts, including Jemal A. CA-CANCER J CLIN, Van Cutsem E. LANCET, and Japanese Gastric Cancer Association GASTRIC CANCER. Conclusion: This bibliometric analysis provides a thought-provoking, insightful result concerning the trajectory of research development in prognosis of gastric cancer with a future perspective.

Detection and Clinical Value of Circulating Tumor Cells as an Assisted Prognostic Marker in Colorectal Cancer Patients.

BACKGROUND: Circulating tumor cells (CTCs) are cells that have been shed into the vasculature from a primary tumor and circulate in the bloodstream. It has been suggested that detecting CTCs could help the clinician to detect early metastasis or recurrence more effectively. This trial sets out to assess the detection and clinical value of CTCs as an assisted prognostic marker in patients with colon cancer and rectal cancer. METHODS: A prospective cohort of patients with colorectal cancer (CRC) was enrolled from July 2015 to February 2018 in Shanghai Minimally Invasive Surgery Center, Shanghai, China. In this study, 149 patients with CRC were enrolled and underwent surgical treatment. There were 79 cases of colon cancer and 70 cases of rectal cancer, including 93 males and 56 females. To investigate the correlativity and clinical value of CTCs, the patients were statistically analyzed in different subgroups: colon cancer group vs rectal cancer group, and left hemicolon cancer group vs right hemicolon cancer group. RESULTS: The results of analysis comparing CTC counts and clinical pathological features in colon and rectal cancer indicated that with increased tumor stage, the number of CTCs also increased, with significant statistical differences. CTC counts in patients with colon and rectal cancer showed positive correlations with TNM staging (P=0.001, 0.013, respectively), T staging (P=0.021, 0.001), N staging (P=0.014, 0.035) and M staging (P=0.018, 0.203). Detection of serum biomarkers in CTC-positive and CTC-negative groups indicated a significantly increasing expression in the CTC-positive group. To confirm the correlations between CTCs and histoembryological differences, analysis was conducted with the patients in two subgroups: left hemicolon cancer group and right hemicolon cancer group. The results showed that the positive rate of CTCs increased in both groups with the increase in tumor stage. The survival analysis indicated that there was a steep gradient in survival in the follow-up period, particularly in the CTC-positive group (P=0.000). Risk assessment curves showed that the change escalated more rapidly in the CTC-positive group. Furthermore, with the increase in T stage, changes in the survival curve and risk curve escalated more rapidly in the CTC-positive group. CONCLUSION: It was confirmed that in the left hemicolon cancer group, a much higher coincidence rate could be found on CTC-positive rate and clinicopathological features, than in the right hemicolon cancer group. The sensitivity of CTCs may be related to the histoembryological location of the tumor, lymphatic metastasis and the depth of infiltration. Monitoring CTCs may have value in evaluating clinical staging and estimating clinical prognosis.

Development and validation of a Surveillance, Epidemiology, and End Results (SEER)-based prognostic nomogram for predicting survival in elderly patients with gastric cancer after surgery.

BACKGROUND: Elderly gastric cancer (ELGC) remains one of the intensively investigated topics during the last decades. To establish a comprehensive nomogram for effective clinical practice and assessment is of significance. This study is designed to develop a prognostic nomogram for ELGC both in overall survival (OS) and cancer-specific survival (CSS). METHODS: The recruited cases were from the Surveillance, Epidemiology, and End Results (SEER) database and input for the construction of nomogram. RESULTS: A total of 4,414 individuals were recruited for this study, of which 2,208 were randomly in training group and 2,206 were in validation group. In univariate analysis of OS, significant variables (P<0.05) included age, marital status, grade, American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) stage, bone/brain/liver/lung metastasis and tumor size. In univariate analysis of CSS, significant variables (P<0.05) included age, grade, AJCC TNM stage, bone/brain/liver/lung metastasis and tumor size. In multivariate analysis of OS, sex, age, race, grade, TNM stage, lung metastasis and tumor size were considered as the significant variables and subjected to the establishment of nomogram. In multivariable analysis of CSS, age, grade, TNM, tumor size were considered as the significant variables and input to the establishment of nomogram. Sex, age, race, grade, TNM stage, lung metastasis and tumor size were included for the establishment of nomogram in OS while age, grade, TNM, tumor size were included to the establishment of nomogram in CSS. C-index, decision curve analysis (DCA) and the area under the curve (AUC) showed distinct value of newly established nomogram models. Both OS and CSS nomograms showed higher statistic power over the AJCC stage. CONCLUSIONS: This study established and validated novel nomogram models of OS and CSS for ELGC based on population dataset.

Artificial intelligence in gastric cancer: a translational narrative review.

Increasing clinical contributions and novel techniques have been made by artificial intelligence (AI) during the last decade. The role of AI is increasingly recognized in cancer research and clinical application. Cancers like gastric cancer, or stomach cancer, are ideal testing grounds to see if early undertakings of applying AI to medicine can yield valuable results. There are numerous concepts derived from AI, including machine learning (ML) and deep learning (DL). ML is defined as the ability to learn data features without being explicitly programmed. It arises at the intersection of data science and computer science and aims at the efficiency of computing algorithms. In cancer research, ML has been increasingly used in predictive prognostic models. DL is defined as a subset of ML targeting multilayer computation processes. DL is less dependent on the understanding of data features than ML. Therefore, the algorithms of DL are much more difficult to interpret than ML, even potentially impossible. This review discussed the role of AI in the diagnostic, therapeutic and prognostic advances of gastric cancer. Models like convolutional neural networks (CNNs) or artificial neural networks (ANNs) achieved significant praise in their application. There is much more to be fully covered across the clinical administration of gastric cancer. Despite growing efforts, adapting AI to improving diagnoses for gastric cancer is a worthwhile venture. The information yield can revolutionize how we approach gastric cancer problems. Though integration might be slow and labored, it can be given the ability to enhance diagnosing through visual modalities and augment treatment strategies. It can grow to become an invaluable tool for physicians. AI not only benefits diagnostic and therapeutic outcomes, but also reshapes perspectives over future medical trajectory.

Comparative study of oncologic efficacy of cephalomedial to lateral dissection versus medial to lateral dissection in laparoscopic total mesorectal excision for rectal cancer: An RCT study.

BACKGROUND AND OBJECTIVES: We compared the 3-year overall survival between cephalomedial-to-lateral approach proctectomy (CEMP) and medial-to-lateral approach proctectomy (MAP) in patients undergoing laparoscopic total mesorectal excision for rectal cancer. The advantages of CEMP and the clinical value of No. 253 lymph nodes resection have not been objectively analyzed in literature. METHODS: This was a prospective, two-arm, multicenter, single-blinded, randomized trial. The primary endpoint was 3-year overall survival, and secondary endpoints included safety, feasibility, oncological radicality (including number of No. 253 lymph nodes harvested), short-term outcome, 3-year disease-free survival, rate of postoperative complications, mortality, and rate of recurrence. RESULTS: From May 2016 to July 2020, 506 patients were enrolled-256 in the CEMP group and 250 in the MAP group. Comparison of overall survival and disease-free survival showed that there was treatment benefit in the CEMP group (28.22 ± 12.12 vs. 27.44 ± 13.06, p = 0.485; 27.24 ± 12.01 vs. 26.42 ± 12.81; p = 0.457). More No. 253 lymph nodes were harvested in the CEMP group, and cases with positive No. 253 lymph nodes had worse prognosis in stage III. Surgical safety was equal for both approaches. CONCLUSIONS: Dissection of No. 253 lymph nodes may be important to improve clinical prognosis, but further studies with larger samples are needed to confirm this finding.

A greater lymph node yield is required during pathological examination in microsatellite instability-high gastric cancer.

BACKGROUND: The impact of microsatellite status on lymph node (LN) yield during lymphadenectomy and pathological examination has never been assessed in gastric cancer (GC). In this study, we aimed to appraise the association between microsatellite instability-high (MSI-H) and LN yield after curative gastrectomy. METHODS: We retrospectively analyzed 1757 patients with GC undergoing curative gastrectomy and divided them into two groups: MSI-H (n = 185(10.5%)) and microsatellite stability (MSS) (n = 1572(89.5%)), using a five-Bethesda-marker (NR-24, BAT-25, BAT-26, CAT-25, MONO-27) panel. The median LN count and the percentage of specimens with a minimum of 16 LNs (adequate LN ratio) were compared between the two groups. The log odds (LODDS) of positive LN count (PLNC) to negative LN count (NLNC) and the target LN examined threshold (TLNT(x%)) were calculated in both groups. RESULTS: Statistically significant differences were found in the median LN count between MSI-H and MSS groups for the complete cohort (30 vs. 28, p = 0.031), for patients undergoing distal gastrectomy (DG) (30 vs. 27, p = 0.002), for stage II patients undergoing DG (34 vs. 28, p = 0.005), and for LN-negative patients undergoing DG (28 vs. 24, p = 0.002). MSI-H was an independent factor for higher total LN count in patients undergoing DG (p = 0.011), but it was not statistically correlated to the adequate LN ratio. Statistically significant differences in PLNC, NLNC and LODDS were found between MSI-H GC and MSS GC (all p < 0.001). The TLNT(90%) for MSI-H and MSS groups were 31 and 25, respectively. TLNT(X%) of MSI-H GC was always higher than that of MSS GC regardless of the given value of X%. CONCLUSIONS: MSI-H was associated with higher LN yield in patients undergoing gastrectomy for GC. Although MSI-H did not affect the adequacy of LN harvest, we speculate that a greater lymph node yield is required during pathological examination in MSI-H GC.

Establishment of prognostic nomogram for elderly colorectal cancer patients: a SEER database analysis.

BACKGROUND: This study aimed to establish nomogram models of overall survival (OS) and cancer-specific survival (CSS) in elderly colorectal cancer (ECRC) patients (Age ≥ 70). METHODS: The clinical variables of patients confirmed as ECRC between 2004 and 2016 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate analysis were performed, followed by the construction of nomograms in OS and CSS. RESULTS: A total of 44,761 cases were finally included in this study. Both C-index and calibration plots indicated noticeable performance of newly established nomograms. Moreover, nomograms also showed higher outcomes of decision curve analysis (DCA) and the area under the curve (AUC) compared to American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) stage and SEER stage. CONCLUSIONS: This study established nomograms of elderly colorectal cancer patients with distinct clinical values compared to AJCC TNM and SEER stages regarding both OS and CSS.

Identification of biomarkers associated with extracellular vesicles based on an integrative pan-cancer bioinformatics analysis.

Extracellular vesicle (EV) has received increasing attention over the last decade. However, biomarkers and mechanisms underlying remain largely limited. Three microarray profiles, GSE78718 (K562 leukemia cell line), GSE45301 (U87-MG glioblastoma cell line), and GSE9589 (SW480 colon cancer cell line), were analyzed for the overlapped differentially expressed genes (DEGs). SurvExpress was used for the prognostic analysis of hub genes signature. Predicted transcription factors networks were built by NetworkAnalysis. Characterization between hub genes and immune cells was analyzed by the tumor immune estimation resources (TIMER) and single-sample gene set enrichment analysis (ssGSEA). The most significantly enriched pathway was lysosome. Hub genes included lysosomal-associated membrane protein 1 (LAMP1), heat shock protein family A (Hsp70) member 5 (HSPA5), lysosomal-associated membrane protein 2 (LAMP2), integrin subunit alpha V (ITGAV), and transmembrane protein 30A (TMEM30A). Significant prognostic values of hub genes signature were identified in glioblastoma (P-value = 0.006), but not colon cancer. In colon cancer, ITGAV displayed remarkably high correlation with tumor immune infiltrating cells. In glioblastoma, the highest correlation was found between HSPA5 and dendritic cell. Moreover, distinct association of immune cells between cell and EV were identified via ssGSEA. This study identified biomarkers in EV with potential immunological insights and clinical values.

Association between liver targeted antiviral therapy in colorectal cancer and survival benefits: An appraisal.

In colorectal cancer (CRC), liver metastasis remains a major contributor to the cause of cancer-related death. Putative biomarkers, therapeutic efficacy, and drug insensitivity still pose clinical challenges for metastatic CRC patients. Interestingly, previous studies indicated that tumor cells in CRC did not metastasize to the injured liver, which included hepatitis or cirrhotic liver. The benefits of antiviral therapy on hepatocellular carcinoma have also been identified. This review discusses the role of antiviral therapy on the liver. Antiviral therapy may reduce potential liver metastasis associated with CRC in several mechanistic aspects.

Prognostic characterization of OAS1/OAS2/OAS3/OASL in breast cancer.

BACKGROUND: Prognostic biomarkers remain a focus in breast cancer during last decades. More reliable predictors to adequately characterize the prognosis of breast cancer are essential. The 2'-5'-oligoadenylate synthetases (OAS), composing of OAS1, OAS2, OAS3, and OAS-like (OASL), are interferon (IFN)-induced antiviral enzymes, with their prognostic roles remain to be characterized. METHODS: Prognostic values of OAS family members were assessed by multiple public available resources. RESULTS: High mRNA expression of OAS1 and OAS3 were correlated with worse prognosis for all breast cancer patients, whereas OAS2 was associated with favorable prognosis. The prognostic values of OAS family in different clinicopathologic subtypes were also characterized. In DNA methylation level, cg12560128 in OAS2, cg06800840 and cg26328872 in OASL showed significant prognostic values. The mRNA expression of OAS members signature in high/low risk overall survival groups was opposite to the high/low risk recurrence free survival groups. Neutrophil cell exhibited highest correlation with all OAS members in tumor immune infiltrating estimation. CONCLUSIONS: This study provided new insight into the prognostic roles of OAS in breast cancer with potential mechanistic values.