Liver cancer is one of the world’s largest causes of death to humans. It is a difficult task and time consuming to identify the cancer tissue manually in the present scenario. The segmentation of liver lesions in CT images can be used to assess the tumor load, plan treatments predict, and monitor the clinical response. In this paper, the Hybridized Fully Convolutional Neural Network (HFCNN) has been proposed for liver tumor segmentation, which has been modeled mathematically to resolve the current issue of liver cancer. For semantic segmentation, HFCNN has been used as a powerful tool for liver cancer analysis. Whereas the CT-based lesion-type definition defines the diagnosis and therapeutic strategy, the distinction between cancer and non-cancer lesions is crucial. It demands highly qualified experience, expertise, and resources. However, a deep end-to-end learning approach to help discrimination in abdominal CT images of the liver between liver metastases of colorectal cancer and benign cysts has been analyzed. Our method includes the successful extraction of features from Inception combined with residual and pre-trained weights. Feature maps have been consistent with the original image voxel features, and The importance of features seemed to represent the most relevant imaging criteria for every class. This deep learning system shows the concept of illumination portions of the decision-making process of a pre-trained deep neural network, through an analysis of inner layers and the description of features that lead to predictions.

Prospective epidemiological studies have consistently suggested that pancreatic cancer-associated new-onset diabetes mellitus (PC-DM) represents a potential platform for early diagnose of pancreatic cancer (PC). Despite the studies performed, the mechanism behind this phenomenon remains ambiguous. In this study, we explored the effects of two types of exosomes released by murine pancreatic cancer and ductal epithelial cells on murine skeletal muscle cells. The results show that PC-derived exosomes can readily enter C2C12 myotubes, triggering lipidosis and glucose intake inhibition. We also demonstrate that PC-derived exosomes can inhibit insulin and PI3K/Akt signalling, in which insulin-induced FoxO1 nuclear exclusion is preserved and Glut4 trafficking is impaired. Microarray and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses show that exosomal microRNAs (miRNAs) probably play key roles in this process, an assumption that is corroborated by in vitro studies. These results confirm that the insulin resistance (IR) of skeletal muscle cells is governed by PC-derived exosomes through the insulin and PI3K/Akt/FoxO1 signalling pathways, where exosomal miRNAs potentially contribute to this phenomenon. These novel findings pave the way towards a comprehensive understanding of the cancer theories: “metabolic reprogramming” and “metabolic crosstalk”.

Background: The intricacies of nucleotide metabolism within tumor cells specific to colorectal cancer (CRC) remain insufficiently characterized. A nuanced examination of particular tumor clusters and their dynamic interplay with the tumor microenvironment (TME) may yield profound insights into these therapeutically auspicious communicative networks. Methods: By integrating ten types of single-cell enrichment scoring methods, we carried out enrichment analysis on CRC cell types, which was validated through four additional single-cell cohorts. Groups of tumor cells were determined using the average values of the scores. Using cellphonedb, monocle, inferCNV, SCENIC, and Cytotrace, functional analyses were performed. Utilizing the RCTD approach, single-cell groupings were mapped onto spatial transcriptomics, analyzing cell dependency and pathway activity to distinguish between tumor cell subtypes. Differential expression analysis identified core genes in nucleotide metabolism, with single-cell and spatial transcriptomics analyses elucidating the function of these genes in tumor cells and the immune microenvironment. Prognostic models were developed from bulk transcriptome cohorts to forecast responses to immune therapy. Laboratory experiments were conducted to verify the biological function of the core gene. Results: Nucleotide metabolism is significantly elevated in tumor cells, dividing them into two groups: NUhighepi and NUlowepi. The phenotype NUhighepi was discerned to exhibit pronounced malignant attributes. Utilizing the analytical tool stlearn for cell-to-cell communication assessment, it was ascertained that NUhighepi engages in intimate interactions with fibroblasts. Corroborating this observation, spatial transcriptome cell interaction assessment through MISTy unveiled a particular reliance of NUhighepi on fibroblasts. Subsequently, we pinpointed NME1, a key gene in nucleotide metabolism, affirming its role in thwarting metastasis via in vitro examination. Utilizing multiple machine learning algorithms, a stable prognostic model (NRS) has been developed, capable of predicting survival and responses to immune therapy. In addition, targeted drugs have been identified for both high and low scoring groups. Laboratory experiments have revealed that NME1 can inhibit the proliferation and invasion of CRC tumor cells. Conclusion: Our study elucidates the potential pro-tumor mechanism of NUhighepi and the role of NME1 in inhibiting metastasis, further deepening the understanding of the role of nucleotide metabolism in colorectal cancer, and providing valuable targets for disrupting its properties.

Background: Cancers trigger systemic metabolic disorders usually associated with glucose intolerance, which is an initially apparent phenomenon. One of the features of pancreatic cancer (PC) metabolic reprogramming is the crosstalk between PC and peripheral tissues (skeletal muscle and adipose tissues), emphasized by insulin resistance (IR). Our previous study reported that mice pancreatic cancer-derived exosomes could induce skeletal muscle cells (C2C12) IR, and exosomal microRNAs (miRNAs) may exert an important effect. However, the underlying mechanism remains to be further elucidated. Methods: qPCR was used to determine the expression of let-7b-5p in normal pancreatic islet cells and PC cells. Exosomes were purified from PC cell culture medium by ultracentrifugation. The role let-7b-5p on IR-mediated by PC cells-derived exosomes was asses by Oil Red O staining using miRNA inhibitor. Western blot assay was performed to examine the expression of IR-related genes and the activation of signaling pathways. A Luciferase experiment was applied to confirm how let-7b-5p regulated the expression of RNF20. IP/WB analysis further determined whether RNF20 promoted STAT3 ubiquitination. Rescue experiment using RNF20 overexpression plasmid was performed to confirm the role of RNF20 on IR-mediated using PC cell-derived exosomes in C2C12 myotube cells. Results: miRNA-let-7b-5p was identified as the key exosomal miRNA, which could promote the IR in C2C12 myotube cells supported the lipid accumulation, the activation of STAT3/FOXO1 axis, and the decreased expression of IRS-1 and GLUT4. RNF20, an E3 ubiquitin ligase, was confirmed as the target gene of let-7b-5p and was found to improve IR by downregulating STAT3 protein expression via ubiquitination-mediated protein degradation. The ectopic expression of RNF20 could effectively attenuate the IR mediated by the pancreatic cancer-derived exosomes in C2C12 myotube cells. Conclusion: Our data suggest that exosomal miRNA-let-7b-5p may promote IR in C2C12 myotube cells by targeting RNF20 to activate the STAT3/FOXO1 axis. Graphical Abstract:

Purpose: Hepatic metastasis frequently occurs in patients who have undergone radical pancreatic resection for pancreatic cancer. Besides chemotherapy, various local treatment approaches targeting hepatic lesions have been explored. However, research on radiofrequency ablation (RFA) as a localized therapy for hepatic metastasis is limited. Therefore, we conducted this retrospective study to provide clinical evidence. Methods: This is a single-center, retrospective, cohort study. After radical pancreaticoduodenectomy, 32 patients developed metachronous hepatic metastasis with fewer than 3 lesions, the largest of which was less than 3 cm in diameter. These patients underwent combined treatment with chemotherapy and RFA. After 8 weeks of chemotherapy, patients received RFA for hepatic lesions. Additional chemotherapy was administered, and the patients’ tumor status and survival were monitored. The primary endpoint of this study was overall survival (OS). Factors affecting OS were analyzed using the Cox risk model. Results: Among the 32 patients, the mean OS was 28.4 months. Univariate and multivariate Cox regression analysis revealed that the time (in months) of liver metastasis (HR = 0.04, 95% CI: 0.01 to 0.19; P < 0.001), the number of liver metastases (HR = 7.08, 95% CI: 1.85 to 27.08, P = 0.004), and PD (progressive disease) response to the second round of chemotherapy (HR = 29.50, 95% CI: 1.46 to 597.27; P = 0.027) were independent predictors of poorer survival. Conclusion: Combined therapy with RFA and chemotherapy is safe in patients with hepatic metastasis after radical pancreaticoduodenectomy. Early recurrence (≤12 months), three liver metastatic lesions, and a poor response to the second round of chemotherapy were associated with poor survival.

Background Cancers trigger systemic metabolic disorder usually associated glucose intolerance, which as initial apparent phenomenon. One of the features of pancreatic cancer (PC) metabolic reprogramming is the crosstalk between PC and peripheral tissues (skeletal muscle and adipose tissues), emphasized by insulin resistance (IR). In our previous study (Sci Rep. 2017;7(1):5384), we reported that mice pancreatic cancer derived exosomes could induce skeletal muscle cells(C2C12) IR and exosomal microRNAs (miRNAs) may exert an important effect. This work was carried out to investigate whether there exist a direct functional relationship between PC exosomal miRNAs and C2C12 cell genes, in the pathological process of IR.Methods The expression profiles of exosomal miRNAs were evaluated using the Agilent Mouse miRNA V21.0 chip (GSE95741). The differentially expressed genes were screened through Agilent SurePrint G3 Mouse GE V2.0 chip (GSE174058). TargetScan and miRbase databases were used for target genes prediction and the prediction results were verified by dual-luciferase reporter gene assay.Results The biochips (GSE95741 and GSE174058) revealed that exosomes derived from mouse pancreatic cancer cells had higher levels of miRNA-let-7b-5p (Log FC 8.6); SLC6A15 gene expression was down-regulated in C2C12 cells (Log FC -4.7). Related mice and human studies has showed that SLC6A15 is associated with IR of metabolic disorder. In this work, luciferase assays confirmed that a direct interaction between miRNA-let-7b-5p and the SLC6A15 3΄-untranslated region (3΄-UTR) was established, as predicted by the TargetScan and miRbase.Conclusions Our data suggest that exosomal miRNA-let-7b-5p may promote IR in C2C12 myotube cells targeting SLC6A15.