The combination therapy of oncolytic virotherapy.

Introduction: Compared to other cancer immunotherapies, oncolytic viruses possess several advantages, including high killing efficiency, excellent targeting capabilities, minimal adverse reactions, and multiple pathways for tumor destruction. However, the efficacy of oncolytic viruses as a monotherapy often falls short of expectations. Consequently, combining oncolytic viruses with traditional treatments to achieve synergistic effects has emerged as a promising direction for the development of oncolytic virus therapies. Methods: This article provides a comprehensive review of the current progress in preclinical and clinical trials exploring the combination therapies involving oncolytic viruses. Results: Specifically, we discuss the combination of oncolytic viruses with immune checkpoint inhibitors, chemotherapy, targeted therapy, and cellular therapy. Discussion: The aim of this review is to offer valuable insights and references for the further advancement of these combination strategies in clinical applications. Further research is necessary to refine the design of combination therapies and explore novel strategies to maximize the therapeutic benefits offered by oncolytic viruses.

LINC00173 silence and estrone supply suppress ER+ breast cancer by estrogen receptor α degradation and LITAF activation.

Persistent activation of estrogen receptor alpha (ERα)-mediated estrogen signaling plays a pivotal role in driving the progression of estrogen receptor positive (ER+) breast cancer (BC). In the current study, LINC00173, a long non-coding RNA, was found to bind both ERα and lipopolysaccharide (LPS)-induced tumor necrosis factor alpha (TNFα) factor (LITAF), then cooperatively to inhibit ERα protein degradation by impeding the nuclear export of ERα. Concurrently, LITAF was found to attenuate TNFα transcription after binding to LINC00173, and this attenuating transcriptional effect was quite significant under lipopolysaccharide stimulation. Distinct functional disparities between estrogen subtypes emerge, with estradiol synergistically promoting ER+ BC cell growth with LINC00173, while estrone (E1) facilitated LITAF-transcriptional activation. In terms of therapeutic significance, silencing LINC00173 alongside moderate addition of E1 heightened TNFα and induced apoptosis, effectively inhibiting ER+ BC progression.

Analyzing the characteristics of respiratory microbiota after the placement of an airway stent for malignant central airway obstruction.

Malignant central airway stenosis is treated with airway stent placement, but post-placement microbial characteristics remain unclear. We studied microbial features in 60 patients post-stent placement, focusing on changes during granulation tissue proliferation. Samples were collected before stent (N = 29), after stent on day 3 (N = 20), and after granulation tissue formation (AS-GTF, N = 43). Metagenomic sequencing showed significant respiratory tract microbiota changes with granulation tissue. The microbiota composition, dominated by Actinobacteria, Firmicutes, and Proteobacteria, was similar among the groups. At the species level, the AS-GTF group exhibited significant differences, with Peptostreptococcus stomatis and Achromobacter xylosoxidans enriched. Analysis based on tracheoesophageal fistula presence identified Tannerella forsythia and Stenotrophomonas maltophilia as the main differential species, enriched in the fistula subgroup. Viral and fungal detection showed Human gammaherpesvirus 4 and Candida albicans as the main species, respectively. These findings highlight microbiota changes after stent placement, potentially associated with granulation tissue proliferation, informing stent placement therapy and anti-infective treatment optimization. IMPORTANCE: Malignant central airway stenosis is a life-threatening condition that can be effectively treated with airway stent placement. However, despite its clinical importance, the microbial characteristics of the respiratory tract following stent insertion remain poorly understood. This study addresses this gap by investigating the microbial features in patients with malignant central airway stenosis after stent placement, with a specific focus on microbial changes during granulation tissue proliferation. The findings reveal significant alterations in the diversity and structure of the respiratory tract microbiota following the placement of malignant central airway stents. Notably, certain bacterial species, including Peptostreptococcus stomatis and Achromobacter xylosoxidans, exhibit distinct patterns in the after-stent granulation tissue formation group. Additionally, the presence of tracheoesophageal fistula further influences the microbial composition. These insights provide valuable references for optimizing stent placement therapy and enhancing clinical anti-infective strategies.

IL-6 regulates epithelial ovarian cancer EMT, invasion, and metastasis by modulating Let-7c and miR-200c through the STAT3/HIF-1α pathway.

Interleukin-6 (IL-6) and hypoxia-inducible factor-1α (HIF-1α) play important roles in epithelial-mesenchymal transformation (EMT) and tumor development. Previous studies have demonstrated that IL-6 promotes EMT, invasion, and metastasis in epithelial ovarian cancer (EOC) cells by activating the STAT3/HIF-1α pathway. MicroRNA (miRNA) is non-coding small RNAs that also play an important role in tumor development. Notably, Let-7 and miR-200 families are prominently altered in EOC. However, whether IL-6 regulates the expression of Let-7 and miR-200 families through the STAT3/HIF-1α signaling to induce EMT in EOC remains poorly understood. In this study, we conducted in vitro and in vivo investigations using two EOC cell lines, SKOV3, and OVCAR3 cells. Our findings demonstrate that IL-6 down-regulates the mRNA levels of Let-7c and miR-200c while up-regulating their target genes HMGA2 and ZEB1 through the STAT3/HIF-1α signaling in EOC cells and in vivo. Additionally, to explore the regulatory role of HIF-1α on miRNAs, both exogenous HIF blockers YC-1 and endogenous high expression or inhibition of HIF-1α can be utilized. Both approaches can confirm that the downstream molecule HIF-1α inhibits the expression and function of Let-7c and miR-200c. Further mechanistic research revealed that the overexpression of Let-7c or miR-200c can reverse the malignant evolution of EOC cells induced by IL-6, including EMT, invasion, and metastasis. Consequently, our results suggest that IL-6 regulates the expression of Let-7c and miR-200c through the STAT3/HIF-1α pathway, thereby promoting EMT, invasion, and metastasis in EOC cells.

mTOR promotes an inflammatory response through the HIF1 signaling pathway in ulcerative colitis.

The imbalance between T helper cell 17 （Th17）and regulatory T cells (Treg) cells leading to inflammation has an important role in the pathogenesis of ulcerative colitis (UC). Mammalian target of rapamycin (mTOR) can regulate the differentiation of T cells, but the specific pathway leading mTOR to regulate Th17/Treg cells in UC remains unclear. Our aim with this study was to investigate the effects of mTOR overexpression and silencing on the hypoxia inducible factor-1α (HIF-1α) - Th17/Treg signaling pathway. To mimic a human study, we established a colon cancer epithelial cell line (HT-29) co-culture system with human CD4+ T cells, and we treated the cells with TNF-α. We observed the effects of mTOR on the HIF-Th17/Treg signaling pathway to determine whether mTOR is involved in the regulatory mechanism. Under the stimulation of TNF-α, the levels of HIF-1α in CD4+T cells were increased in the HT-29 co-culture with CD4+ T cells, promoting glycolysis, increasing the Th17 proportion, decreasing the Treg proportion, increasing the pro-inflammatory factors levels, and decreasing the anti-inflammatory factors levels. Moreover, after mTOR silencing, the HIF-1α level and cell glycolysis levels decreased, Th17 cell differentiation decreased, the pro-inflammatory factor levels decreased, and the anti-inflammatory factor levels increased. In contrast, mTOR overexpression lead to the opposite results.mTOR promotes inflammation by regulating the HIF signaling pathway during UC, and silencing mTOR may alleviate inflammation. An mTOR inhibitor is a potential therapeutic target for UC treatment.

Phenotypic, genomic, and transcriptomic heterogeneity in a pancreatic cancer cell line.

OBJECTIVES: To evaluate the suitability of the MIA PaCa-2 cell line for studying pancreatic cancer intratumor heterogeneity, we aim to further characterize the nature of MIA PaCa-2 cells' phenotypic, genomic, and transcriptomic heterogeneity. METHODS: MIA PaCa-2 single-cell clones were established through flow cytometry. For the phenotypic study, we quantified the cellular morphology, proliferation rate, migration potential, and drug sensitivity of the clones. The chromosome copy number and transcriptomic profiles were quantified using SNPa and RNA-seq, respectively. RESULTS: Four MIA PaCa-2 clones showed distinctive phenotypes, with differences in cellular morphology, proliferation rate, migration potential, and drug sensitivity. We also observed a degree of genomic variations between these clones in form of chromosome copy number alterations and single nucleotide variations, suggesting the genomic heterogeneity of the population, and the intrinsic genomic instability of MIA PaCa-2 cells. Lastly, transcriptomic analysis of the clones also revealed gene expression profile differences between the clones, including the uniquely regulated ITGAV, which dictates the morphology of MIA PaCa-2 clones. CONCLUSIONS: MIA PaCa-2 is comprised of cells with distinctive phenotypes, heterogeneous genomes, and differential transcriptomic profiles, suggesting its suitability as a model to study the underlying mechanisms behind pancreatic cancer heterogeneity.

Self-Assembled DNA Machine and Selective Complexation Recognition Enable Rapid Homogeneous Portable Quantification of Lung Cancer CTCs.

In this study, we systematically investigated the interactions between Cu2+ and various biomolecules, including double-stranded DNA, Y-shaped DNA nanospheres, the double strand of the hybridization chain reaction (HCR), the network structure of cross-linked HCR (cHCR), and small molecules (PPi and His), using Cu2+ as an illustrative example. Our research demonstrated that the coordination between Cu2+ and these biomolecules not only is suitable for modulating luminescent material signals through complexation reactions with Cu2+ but also enhances signal intensities in materials based on chemical reactions by increasing spatial site resistance and local concentration. Building upon these findings, we harnessed the potential for signal amplification in self-assembled DNA nanospheres and the selective complexation modulation of calcein in conjunction with the aptamer targeting mucin 1 as a recognition probe. We applied this approach to the analysis of circulating tumor cells, with the lung cancer cell line A549 serving as a representative model. Our assay, utilizing both a fluorometer and a handheld detector, achieved impressive detection limits of ag/ml and single-cell levels for mucin 1 and A549 cells, and this approach was successfully validated using 46 clinical samples, yielding 100% specificity and 86.5% sensitivity. Consequently, our strategy has paved the way for more portable and precise disease diagnosis.

Elevated mRNA level indicates FSIP1 promotes EMT and gastric cancer progression by regulating fibroblasts in tumor microenvironment.

Fiber sheath interaction protein 1 (FSIP1) plays a crucial role in cancer development and occurrence, but its influence on gastric cancer is still unclear. In this study, differential mRNA analysis was performed by TCGA database for the Limma analysis algorithm, and the gene ontology, the Kyoto Encyclopedia of Genes and Genomes, and the gene set enrichment analysis (GSEA) were used for bioinformatics functional enrichment analysis. A gastric cancer cell model with FSIP1 mRNA knockdown was constructed by RNA interference. Cell counting kit-8 and transwell migration/invasion assay were performed to verify the cell function, and western blotting was employed to confirm the expression of target genes. The GSEA analysis revealed that FSIP1 was associated with epithelial-mesenchymal transition (EMT). The high expression group also had a significant positive correlation with the markers of fibroblast in tumor microenvironment (TME). Western blotting showed that FSIP1 was generally upregulated in gastric cancer cell lines. FSIP1 mRNA knockdown cell lines inhibited gastric cells proliferation, migration, and metastasis in vitro, and the protein levels of EMT-related markers N-cadherin and vimentin were reduced. Our work proved that FSIP1 promoted EMT by regulating fibroblasts in the TME, thereby promoting the carcinogenic activity of cancer cells in proliferation, invasion, and migration. FSIP1 may take a role of the occurrence and could be a potential therapeutic target and offer a new insight into the underlying mechanism of gastric cancer.

Enhanced localized therapeutic precision: A face-to-face folate-targeted Cu2+-mediated nanotherapy with thermosensitive sustained-release system.

Safe and effective Cu2+ supplementation in local lesion is crucial for minimizing toxicity of DSF-based chemotherapy. Targeted delivery of Cu2+ appears more promising. Intraperitoneal chemotherapy for peritoneal carcinoma (PC) establishes "face-to-face" contact between targeted nanocarriers and tumor tissue. Herein, this study developed a biodegradable, injectable thermosensitive hydrogel that coencapsulating DSF submicroemulsion (DSF-SE) and folate-modified liposome loading glycyrrhizic acid-Cu (FCDL). FCDL acted as 'beneficial horse' to target the tumor-localized folate receptor, thus liberating Cu2+ in tumor nidus. The prepared FCDL and DSF-SE were found with uniform sizes (160.2 nm, 175.4 nm), low surface charge (-25.77 mV, -16.40 mV) and high encapsulation efficiency (97.93 %, 90.08 %). In vitro drug release profile of FCDL, DSF-SE and FCDL＆DSF-SE@G followed a sustained release pattern. And the release behavior of Cu2+ from FCDL was pH-related, i.e., Cu2+ was released faster under acidic condition. When FCDL and DSF-SE were loaded into an PLGA-PEG-PLGA-based hydrogel system, FCDL＆DSF-SE@G was formed to ensure separated delivery of Cu2+ and DSF in space but synchronized release over time. The rheology experiment showed a satisfactory gelling temperature of 32.7 °C. In vitro cytotoxicity study demonstrated that FCDL＆DSF-SE@G significantly lowered the IC50 of free Cu2+/DSF, Cu2+/DSF hydrogel and non-targeted analogue by almost 70 %, 65 % and 32 %, respectively. Accordingly, in tumor-bearing mice, FCDL＆DSF-SE@G augmented the tumor inhibition rates for the same formulations by 352 %, 145 % and 44 %, respectively. The main mechanism was attributed to higher uptake of FCDL and DSF-SE, resulting in increased Cu(DDTC)2 formation, ROS production and cell apoptosis. In conclusion, this targeted nanotherapy approach with dual-nanocarriers loaded hydrogel system, with its focus on face-to-face contact between nanocarriers and tumor tissues in the peritoneal cavity, holds significant promise for intraperitoneal chemotherapy in PC.

AnnoSpat annotates cell types and quantifies cellular arrangements from spatial proteomics.

Cellular composition and anatomical organization influence normal and aberrant organ functions. Emerging spatial single-cell proteomic assays such as Image Mass Cytometry (IMC) and Co-Detection by Indexing (CODEX) have facilitated the study of cellular composition and organization by enabling high-throughput measurement of cells and their localization directly in intact tissues. However, annotation of cell types and quantification of their relative localization in tissues remain challenging. To address these unmet needs for atlas-scale datasets like Human Pancreas Analysis Program (HPAP), we develop AnnoSpat (Annotator and Spatial Pattern Finder) that uses neural network and point process algorithms to automatically identify cell types and quantify cell-cell proximity relationships. Our study of data from IMC and CODEX shows the higher performance of AnnoSpat in rapid and accurate annotation of cell types compared to alternative approaches. Moreover, the application of AnnoSpat to type 1 diabetic, non-diabetic autoantibody-positive, and non-diabetic organ donor cohorts recapitulates known islet pathobiology and shows differential dynamics of pancreatic polypeptide (PP) cell abundance and CD8+ T cells infiltration in islets during type 1 diabetes progression.

Single-cell SERS imaging of dual cell membrane receptors expression influenced by extracellular matrix stiffness.

Membrane receptors perform a diverse range of cellular functions, accounting for more than half of all drug targets. The mechanical microenvironment regulates cell behaviors and phenotype. However, conventional analysis methods of membrane receptors often ignore the effects of the extracellular matrix stiffness, failing to reveal the heterogeneity of cell membrane receptors expression. Herein, we developed an in-situ surface-enhanced Raman scattering (SERS) imaging method to visualize single-cell membrane receptors on substrates with different stiffness. Two SERS substrates, Au@4-mercaptobenzonitrile@Ag@Sgc8c and Au@4-pethynylaniline@Ag@SYL3c, were employed to specifically target protein tyrosine kinase-7 (PTK7) and epithelial cell adhesion molecule (EpCAM), respectively. The polyacrylamide (PA) gels with tunable stiffness (2.5-25 kPa) were constructed to mimic extracellular matrix. The simultaneous SERS imaging of dual membrane receptors on single cancer cells on substrates with different stiffness was achieved. Our findings reveal decreased expression of PTK7 and EpCAM on cells cultured on stiffer substrates and higher migration ability of the cells. The results elucidate the heterogeneity of membrane receptors expression of cells cultured on the substrates with different stiffness. This single-cell analysis method offers an in-situ platform for investigating the impacts of extracellular matrix stiffness on the expression of membrane receptors, providing insights into the role of cell membrane receptors in cancer metastasis.

Synergistic effects of graphene microgrooves and electrical stimulation on M2 macrophage polarization.

Macrophages play a crucial role in host response and wound healing, with M2 polarization contributing to the reduction of foreign-body reactions induced by the implantation of biomaterials and promoting tissue regeneration. Electrical stimulation (ES) and micropatterned substrates have a significant impact on the macrophage polarization. However, there is currently a lack of well-established cell culture platforms for studying the synergistic effects of these two factors. In this study, we prepared a graphene free-standing substrate with 20 µm microgrooves using capillary forces induced by water evaporation. Subsequently, we established an ES cell culture platform for macrophage cultivation by integrating a self-designed multi-well chamber cell culture device. We observed that graphene microgrooves, in combination with ES, significantly reduce cell spreading area and circularity. Results from immunofluorescence, ELISA, and flow cytometry demonstrate that the synergistic effect of graphene microgrooves and ES effectively promotes macrophage M2 phenotypic polarization. Finally, RNA sequencing results reveal that the synergistic effects of ES and graphene microgrooves inhibit the macrophage actin polymerization and the downstream PI3K signaling pathway, thereby influencing the phenotypic transition. Our results demonstrate the potential of graphene-based microgrooves and ES to synergistically modulate macrophage polarization, offering promising applications in regenerative medicine.

Advances in the pharmacological effects and mechanisms of Nelumbo nucifera gaertn. Extract nuciferine.

ETHNOPHARMACOLOGIC RELEVANCE: The leaves of Nelumbo nucifera Gaertn. Are recorded in the earliest written documentation of traditional Chinese medicinal as "Ben Cao Gang Mu", a medicinal herb for blood clotting, dysentery and dizziness. Nuciferine, one of N. nucifera Gaertn. leaf extracts, has been shown to possess several pharmacological properties, including but not limited to ameliorating hyperlipidemia, stimulating insulin secretion, inducing vasodilation, reducing blood pressure, and demonstrating anti-arrhythmic properties. AIM OF THE STUDY: In light of the latest research findings on nuciferine, this article provides a comprehensive overview of its chemical properties, pharmacological activities, and the underlying regulatory mechanisms. It aims to serve as a dependable reference for further investigations into the pharmacological effects and mechanisms of nuciferine. MATERIALS AND METHODS: Use Google Scholar, Scifinder, PubMed, Springer, Elsevier, Wiley, Web of Science and other online database search to collect the literature on extraction, separation, structural analysis and pharmacological activity of nuciferine published before November 2023. The key words are "extraction", "isolation", "purification" and "pharmacological action" and "nuciferine". RESULTS: Nuciferine has been widely used in the treatment of ameliorating hyperlipidemia and lose weight, Nuciferine is a monomeric aporphine alkaloid extracted from the leaves of the plant Nymphaea caerulea and Nelumbo nucifera Gaertn. Nuciferine has pharmacological activities such as relaxing smooth muscles, improving hyperlipidemia, stimulating insulin secretion, vasodilation, inducing hypotension, antiarrhythmic effects, and antimicrobial and anti-HIV activities. These pharmacological properties lay a foundation for the treatment of tumors, inflammation, hyperglycemia, lipid-lowering and weight-loss, oxidative stress and other diseases with nuciferine. CONCLUSION: Nuciferine has been clinically used to treat hyperlipidemia and aid in weight loss due to its effects on lipid levels, insulin secretion, vasodilation, blood pressure reduction, anti-tumor properties, and immune enhancement. However, other potential benefits of nuciferine have not yet been fully explored in clinical practice. Future research should delve deeper into its molecular structure, toxicity, side effects, and clinical pharmacology to uncover its full range of effects and pave the way for its safe and expanded clinical use.

A Dual-Channel MoS2-Based Selective Gas Sensor for Volatile Organic Compounds.

Significant progress has been made in two-dimensional material-based sensing devices over the past decade. Organic vapor sensors, particularly those using graphene and transition metal dichalcogenides as key components, have demonstrated excellent sensitivity. These sensors are highly active because all the atoms in the ultra-thin layers are exposed to volatile compounds. However, their selectivity needs improvement. We propose a novel gas-sensing device that addresses this challenge. It consists of two side-by-side sensors fabricated from the same active material, few-layer molybdenum disulfide (MoS2), for detecting volatile organic compounds like alcohol, acetone, and toluene. To create a dual-channel sensor, we introduce a simple step into the conventional 2D material sensor fabrication process. This step involves treating one-half of the few-layer MoS2 using ultraviolet-ozone (UV-O3) treatment. The responses of pristine few-layer MoS2 sensors to 3000 ppm of ethanol, acetone, and toluene gases are 18%, 3.5%, and 49%, respectively. The UV-O3-treated few-layer MoS2-based sensors show responses of 13.4%, 3.1%, and 6.7%, respectively. This dual-channel sensing device demonstrates a 7-fold improvement in selectivity for toluene gas against ethanol and acetone. Our work sheds light on understanding surface processes and interaction mechanisms at the interface between transition metal dichalcogenides and volatile organic compounds, leading to enhanced sensitivity and selectivity.

A comprehensive exploration of twist1 to identify a biomarker for tumor immunity and prognosis in pan-cancer.

Twist1 has been identified as a critical gene in tumor, but current study of this gene remains limitative. This study aims to investigate its roles and potential mechanisms across pan-cancer. The study used various databases and computational techniques to analyze twist's RNA expression, clinical data, gene mutations, tumor stemness, tumor microenvironment, immune regulation. Furthermore, the experimental method of fluorescence staining was carried out to identify twist1 expression in various tumor masses. After analyzing the protein-protein interaction of TWIST, enrichment analysis and predictive potential drugs were performed, and molecular docking was conducted to validate. We found that twist1 expression was significantly higher in various types of cancer and associated with tumor stage, grade, and poor prognosis in multiple cancers. Differential expression of twist1 was linked to gene mutation, RNA modifications, and tumor stemness. Additionally, twist1 expression was positively associated with tumor immunoregulation and immune checkpoint. Salinomycin, klugline, isocephaelince, manassantin B, and pimonidazole are predictive potential drugs targeting TWIST1. This study revealed that twist1 plays an important role in tumor, and might be a curial marker in tumor diagnose and prognosis. The study also highlighted twist1 as a promising therapeutic target for cancer treatment and provided a foundation for future research.

Systematic investigation of chemo-immunotherapy synergism to shift anti-PD-1 resistance in cancer.

Chemo-immunotherapy combinations have been regarded as one of the most practical ways to improve immunotherapy response in cancer patients. In this study, we integrate the transcriptomics data from anti-PD-1-treated tumors and compound-treated cancer cell lines to systematically screen for chemo-immunotherapy synergisms in silico. Through analyzing anti-PD-1 induced expression changes in patient tumors, we develop a shift ability score to measure if a chemotherapy or a small molecule inhibitor treatment can shift anti-PD-1 resistance in tumor cells. By applying shift ability analysis to 41,321 compounds and 16,853 shRNA treated cancer cell lines transcriptomic data, we characterize the landscape of chemo-immunotherapy synergism and experimentally validated a mitochondrial RNA-dependent mechanism for drug-induced immune activation in tumor. Our study represents an effort to mechanistically characterize chemo-immunotherapy synergism and will facilitate future pre-clinical and clinical studies.

Endometrial microbiota alteration in female patients with endometrial polyps based on 16S rRNA gene sequencing analysis.

Introduction: The potential role of the endometrial microbiota in the pathogenesis of endometrial polyps (EPs) warrants further investigation, given the current landscape of limited and inconclusive research findings. We aimed to explore the microecological characteristics of the uterine cavity in patients with EPs and investigate the potential of endometrial microbiota species as novel biomarkers for identifying EPs. Methods: Endometrial samples were collected from 225 patients who underwent hysteroscopies, of whom 167 had EPs, whereas 58 had non- hyperproliferative endometrium status. The endometrial microbiota was assessed using 16S rRNA gene sequencing. We characterized the endometrial microbiota and identified microbial biomarkers for predicting EPs. Results: The endometrial microbial diversity and composition were significantly different between the EP and control groups. Predictive functional analyses of the endometrial microbiota demonstrated significant alterations in pathways involved in sphingolipid metabolism, steroid hormone biosynthesis, and apoptosis between the two groups. Moreover, a classification model based on endometrial microbial ASV-based biomarkers along with the presence of abnormal uterine bleeding symptoms achieved powerful classification potential in identifying EPs in both the discovery and validation cohorts. Conclusion: Our study indicates a potential association between altered endometrial microbiota and EPs. Endometrial microbiota-based biomarkers may prove valuable for the diagnosis of EPs. Clinical trial registration: Chinese Clinical Trial Registry (ChiCTR2100052746).

CT radiomics based on the peritumoral adipose region of gastric adenocarcinoma for preoperative prediction of lymph node metastasis.

PURPOSE: To construct and validate CT radiomics model based on the peritumoral adipose region of gastric adenocarcinoma to preoperatively predict lymph node metastasis (LNM). METHODS AND METHODS: 293 consecutive gastric adenocarcinoma patients receiving radical gastrectomy with lymph node dissection in two medical institutions were stratified into a development set (from Institution A, n = 237), and an external validation set (from Institution B, n = 56). Volume of interest of peritumoral adipose region was segmented on preoperative portal-phase CT images. The least absolute shrinkage and selection operator method and stepwise logistic regression were used to select features and build radiomics models. Manual classification was performed according to routine CT characteristics. A classifier incorporating the radiomics score and CT characteristics was developed for predicting LNM. Area under the receiver operating characteristic curve (AUC) was used to show discrimination between tumors with and without LNM, and the calibration curves and Brier score were used to evaluate the predictive accuracy. Violin plots were used to show the distribution of radiomics score. RESULTS: AUC values of radiomics model to predict LNM were 0.938, 0.905, and 0.872 in the training, internal test, and external validation sets, respectively, higher than that of manual classification (0.674, all P values < 0.01). The radiomics score of the positive LNM group were higher than that of the negative group in all sets (both P-values < 0.001). The classifier showed no improved predictive power compared with the radiomics signature alone with AUC values of 0.916 and 0.872 in the development and external validation sets, respectively. Multivariate analysis showed that radiomics score was an independent predictor. CONCLUSIONS: Radiomics model based on peritumoral adipose region could be a useful approach for preoperative LNM prediction in gastric adenocarcinoma.

Tumor regression and safe distance of distal margin after neoadjuvant therapy for rectal cancer.

Neoadjuvant therapy has been widely employed in the treatment of rectal cancer, demonstrating its utility in reducing tumor volume, downstaging tumors, and improving patient prognosis. It has become the standard preoperative treatment modality for locally advanced rectal cancer. However, the efficacy of neoadjuvant therapy varies significantly among patients, with notable differences in tumor regression outcomes. In some cases, patients exhibit substantial tumor regression, even achieving pathological complete response. The assessment of tumor regression outcomes holds crucial significance for determining surgical approaches and establishing safe margins. Nonetheless, current research on tumor regression patterns remains limited, and there is considerable controversy surrounding the determination of a safe margin after neoadjuvant therapy. In light of these factors, this study aims to summarize the primary patterns of tumor regression observed following neoadjuvant therapy for rectal cancer, categorizing them into three types: tumor shrinkage, tumor fragmentation, and mucinous lake formation. Furthermore, a comparison will be made between gross and microscopic tumor regression, highlighting the asynchronous nature of regression in the two contexts. Additionally, this study will analyze the safety of non-surgical treatment in patients who achieve complete clinical response, elucidating the necessity of surgical intervention. Lastly, the study will investigate the optimal range for safe surgical resection margins and explore the concept of a safe margin distance post-neoadjuvant therapy.

Predicting the risk of lung cancer using machine learning: A large study based on UK Biobank.

In response to the high incidence and poor prognosis of lung cancer, this study tends to develop a generalizable lung-cancer prediction model by using machine learning to define high-risk groups and realize the early identification and prevention of lung cancer. We included 467,888 participants from UK Biobank, using lung cancer incidence as an outcome variable, including 49 previously known high-risk factors and less studied or unstudied predictors. We developed multivariate prediction models using multiple machine learning models, namely logistic regression, naïve Bayes, random forest, and extreme gradient boosting models. The performance of the models was evaluated by calculating the areas under their receiver operating characteristic curves, Brier loss, log loss, precision, recall, and F1 scores. The Shapley additive explanations interpreter was used to visualize the models. Three were ultimately 4299 cases of lung cancer that were diagnosed in our sample. The model containing all the predictors had good predictive power, and the extreme gradient boosting model had the best performance with an area under curve of 0.998. New important predictive factors for lung cancer were also identified, namely hip circumference, waist circumference, number of cigarettes previously smoked daily, neuroticism score, age, and forced expiratory volume in 1 second. The predictive model established by incorporating novel predictive factors can be of value in the early identification of lung cancer. It may be helpful in stratifying individuals and selecting those at higher risk for inclusion in screening programs.