Limited previous studies focused on the death and progression risk stratification of colorectal cancer (CRC) lung metastasis patients. The aim of this study is to construct a nomogram model combing ...machine learning-pathomics, radiomics features, Immunoscore and clinical factors to predict the postoperative outcome of CRC patients with lung metastasis. In this study, a total of 103 CRC patients having metastases limited to lung and undergoing radical lung resection were identified. Patch-level convolutional neural network training in weakly supervised manner was used to perform whole slides histopathological images survival analysis. Synthetic minority oversampling technique and support vector machine classifier were used to identify radiomics features and build predictive signature. The Immunoscore for each patient was calculated from the density of CD3+ and CD8+ cells at the invasive margin and the center of metastatic tumor which were assessed on consecutive sections of automated digital pathology. Finally, pathomics and radiomics signatures were successfully developed to predict the overall survival (OS) and disease free survival (DFS) of patients. The predicted pathomics and radiomics scores are negatively correlated with Immunoscore and they are three independent prognostic factors for OS and DFS prediction. The combined nomogram showed outstanding performance in predicting OS (AUC = 0.860) and DFS (AUC = 0.875). The calibration curve and decision curve analysis demonstrated the considerable clinical usefulness of the combined nomogram. Taken together, the developed nomogram model consisting of machine learning-pathomics signature, radiomics signature, Immunoscore and clinical features could be reliable in predicting postoperative OS and DFS of colorectal lung metastasis patients.
Barrett's esophagus (BE) is a precancerous lesion of esophageal adenocarcinoma (EAC), with approximately 3-5% of patients developing EAC. Cuproptosis is a kind of programmed cell death phenomenon ...discovered in recent years, which is related to the occurrence and development of many diseases. However, its role in BE and EAC is not fully understood. We used single sample Gene Set Enrichment Analysis (ssGSEA) for differential analysis of BE in the database, followed by enrichment analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO) and GSEA, Protein-Protein Interaction (PPI), Weighted Gene Co-expression Network Analysis (WGCNA), Receiver Operating Characteristic Curve (ROC) and finally Quantitative Real Time Polymerase Chain Reaction (qRT-PCR) and immunohistochemistry (IHC) of clinical tissues. Two hub genes can be obtained by intersection of the results obtained from the cuproptosis signal analysis based on BE. The ROC curves of these two genes predicted EAC, and the Area Under the Curve (AUC) values could reach 0.950 and 0.946, respectively. The mRNA and protein levels of Centrosome associated protein E (CENPE) and Shc SH2 domain binding protein 1 (SHCBP1) were significantly increased in clinical EAC tissues. When they were grouped by protein expression levels, high expression of CENPE or SHCBP1 had a poor prognosis. The CENPE and SHCBP1 associated with cuproptosis may be a factor promoting the development of BE into EAC which associated with the regulation of NK cells and T cells.
Zinc finger protein 143(ZNF143), a member of the Krüppel C2H2-type zinc finger protein family, is strongly associated with cell cycle regulation and cancer development. A recent study suggested that ...ZNF143 plays as a transcriptional activator that promotes hepatocellular cancer (HCC) cell proliferation and cell cycle transition. However, the exact biological role of ZNF143 in liver regeneration and normal liver cell proliferation has not yet been investigated. In our study, we constructed a stable rat liver cell line (BRL-3A) overexpressing ZNF143 and then integrated RNA-seq and Cleavage Under Targets and Tagmentation (CUT&Tag) data to identify the mechanism underlying differential gene expression. Our results show that ZNF143 expression is upregulated during the proliferation phase of liver regeneration after 2/3 partial hepatectomy (PH). The cell counting kit-8 (CCK-8) assay, EdU staining and RNA-seq data analyses revealed that ZNF143 overexpression (OE) significantly inhibited BRL-3A cell proliferation and cell cycle progression. We then performed CUT&Tag assays and found that approximately 10% of ZNF143-binding sites (BSs) were significantly changed genome-wide by ZNF143 OE. However, CCCTC-binding factor (CTCF) binding to chromatin was not affected. Interestingly, the integration analysis of RNA-seq and CUT&Tag data showed that some of genes affected by ZNF143 differential BSs are in the center of each gene regulation module. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses indicated that these genes are critical in the maintenance of cell identity. These results indicated that the expression level of ZNF143 in the liver is important for the maintenance of cell identity. ZNF143 plays different roles in HCC and normal liver cells and may be considered as a potential therapeutic target in liver disease.
Accurate segmentation of lung nodules from pulmonary computed tomography (CT) slices plays a vital role in the analysis and diagnosis of lung cancer. Convolutional Neural Networks (CNNs) have ...achieved state-of-the-art performance in the automatic segmentation of lung nodules. However, they are still challenged by the large diversity of segmentation targets, and the small inter-class variances between the nodule and its surrounding tissues. To tackle this issue, we propose a features complementary network according to the process of clinical diagnosis, which made full use of the complementarity and facilitation among lung nodule location information, global coarse area, and edge information. Specifically, we first consider the importance of global features of nodules in segmentation and propose a cross-scale weighted high-level feature decoder module. Then, we develop a low-level feature decoder module for edge feature refinement. Finally, we construct a complementary module to make information complement and promote each other. Furthermore, we weight pixels located at the nodule edge on the loss function and add an edge supervision to the deep supervision, both of which emphasize the importance of edges in segmentation. The experimental results demonstrate that our model achieves robust pulmonary nodule segmentation and more accurate edge segmentation.
The COVID-19 pandemic has resulted in great morbidity and mortality worldwide and human genetic factors have been implicated in the susceptibility and severity of COVID-19. However, few replicate ...researches have been performed, and studies on associated genes mainly focused on genic regions while regulatory regions were a lack of in-depth dissection. Here, based on previously reported associated variants and genes, we designed a capture panel covering 1,238 candidate variants and 25 regulatory regions of 19 candidate genes and targeted-sequenced 96 mild and 145 severe COVID-19 patients. Genetic association analysis was conducted between mild and severe COVID-19 patients, between all COVID-19 patients and general population, or between severe COVID-19 patients and general population. A total of 49 variants were confirmed to be associated with susceptibility or severity of COVID-19 (
< 0.05), corresponding to 18 independent loci. Specifically, rs1799964 in the promoter of inflammation-related gene
, rs9975538 in the intron of interferon receptor gene
, rs429358 in the exon of
, rs1886814 in the intron of
and a list of variants in the widely reported 3p21.31 and
gene were confirmed. It is worth noting that, for the confirmed variants, the phenotypes of the cases and controls were highly consistent between our study and previous reports, and the confirmed variants identified between mild and severe patients were quite different from those identified between patients and general population, suggesting the genetic basis of susceptibility and severity of SARS-CoV-2 infection might be quite different. Moreover, we newly identified 67 significant associated variants in the 12 regulatory regions of 11 candidate genes (
< 0.05). Further annotation by RegulomeDB database and GTEx eQTL data filtered out two variants (rs11246060 and rs28655829) in the enhancer of broad-spectrum antiviral gene
that might affect disease severity by regulating the gene expression. Collectively, we confirmed a list of previously reported variants and identified novel regulatory variants associated with susceptibility and severity of COVID-19, which might provide biological and clinical insights into COVID-19 pathogenesis and treatment.
Our previous work have shown that certain subpopulations of
Klebsiella pneumoniae
exhibit significant phenotypic changes under simulated microgravity (SMG), including enhanced biofilm formation and ...cellulose synthesis, which may be evoked by changes in gene expression patterns. It is well known that prokaryotic cells genomic DNA can be hierarchically organized into different higher-order three-dimensional structures, which can highly influence gene expression. It is remain elusive whether phenotypic changes induced by SMG in the subpopulations of
K. pneumoniae
are driven by genome higher-order structural changes. Here, we investigated the above-mentioned issue using the wild-type (WT)
K. pneumoniae
(WT was used as a control strain and continuously cultivated for 2 weeks under standard culture conditions of normal gravity) and two previous identified subpopulations (M1 and M2) obtained after 2 weeks of continuous incubation in a SMG device. By the combination of genome-wide chromosome conformation capture (Hi-C), RNA-seq and whole-genome methylation (WGS) analyses, we found that the along with the global chromosome interactions change, the compacting extent of M1, M2 subpopulations were much looser under SMG and even with an increase in active, open chromosome regions. In addition, transcriptome data showed that most differentially expressed genes (DEGs) were upregulated, whereas a few DEGs were downregulated in M1 and M2. The functions of both types DEGs were mainly associated with membrane fractions. Additionally, WGS analysis revealed that methylation levels were lower in M1 and M2. Using combined analysis of multi-omics data, we discovered that most upregulated DEGs were significantly enriched in the boundary regions of the variable chromosomal interaction domains (CIDs), in which genes regulating biofilm formation were mainly located. These results suggest that
K. pneumoniae
may regulate gene expression patterns through DNA methylation and changes in genome structure, thus resulting in new phenotypes in response to altered gravity.
It has been reported that kidney retransplant patients had high rates of early acute rejection due to previous sensitization. In addition to the acute antibody-mediated rejection (ABMR) that has ...received widespread attention, the early acute T-cell-mediated rejection (TCMR) may be another important issue in renal retransplantation. In the current single-center retrospective study, we included 33 retransplant patients and 90 first transplant patients with similar protocols of induction and maintenance therapy. Analysis focused particularly on the incidence and patterns of early acute rejection episodes, as well as one-year graft and patient survival. Excellent short-term clinical outcomes were obtained in both groups, with one-year graft and patient survival rates of 93.9%/100% in the retransplant group and 92.2%/95.6% in the first transplant group. Impressively, with our strict immunological selection and desensitization criteria, the retransplant patients had a very low incidence of early acute ABMR (6.1%), which was similar to that in the first transplant patients (4.4%). However, a much higher rate of early acute TCMR was observed in the retransplant group than in the first transplant group (30.3% versus 5.6%, P<0.001). Acute TCMR that develops early after retransplantation should be monitored in order to obtain better transplant outcomes.
To compare the safety and effectiveness between antithymocyte globulin (ATG) and basiliximab in deceased donor renal transplantation within matched groups where paired recipients received graft ...donations from same donors.
A total of 124 cases of deceased donor kidney transplantation performed at Wuhan Tongji Hospital from January 2013 to November 2015 were retrospectively analyzed. Based upon their induction therapies, the recipients receiving graft donations from same donors were divided into two groups, namely ATG group (
=62) and basiliximab group (
=62). Clinical data were gathered and comparisons were made between the two groups.
Delayed graft function (DGF) implicated less patients in the ATG group (11, 17.7%) compared with basiliximab group (21, 33.9%) (
=0.040). Duration of DGF was also significantly shorter in the ATG group than in the basiliximab group(14.92±6.23) vs(20.26±7.89)days,
=0.048. The rates of DGF were 5/18 in the ATG group and 10/15 in the basiliximab group (
=0.025), when subgrouping
Lung cancer is a leading cause of cancer death, but its mortality continues to decline substantially, benefiting from early screening and/or treatment of lung nodules. Therefore, the accurate and ...robust segmentation of pulmonary nodules from lung computed tomography (CT) is an essential task. However, automated solution is still challenging due to the high variability, blurred edges, and complex background of pulmonary nodules in CT scans. In this article, we propose a novel scale-aware-based multiattention-guided reverse network (SM-RNet) for pulmonary nodules segmentation, which makes full use of the complementary information from different attention dimensions and scales and progressively obtains the complete object by reverse erasure (RE) manner, consisting of two stages. Stage I performs weighted cross-scale fusion for features with different scale attentions to extract the intermediate multiscale features (MFs) with channel and scale awareness, and stage II adaptively selects features from the most appropriate scale for the target and sequentially mines the details required for the segmentation task by a new scale-guided spatial attention (SSA) block and a new RE block. In addition, the model is equipped with two-stage deep supervision. We evaluate the segmentation accuracy of our method by calculating the dice similarity coefficient (DI), Jaccard index (JI), Hausdorff distance (HD), recall, specificity (SPE), and precision (PRE) on an internal institution dataset from the Fudan University Shanghai Cancer Center (FUSCC) and a public dataset LUng Nodule Analysis 2016 (LUNA16). Our proposed SM-RNet achieves the Dice scores of 89.290% ± 0.040% and 86.496% ± 0.076% and an HD of 5.532 ± 0.186 and 6.131 ± 0.288 for FUSCC and LUNA, respectively. SM-RNet significantly outperforms other state-of-the-art (SOTA) networks. In addition, the visualization results of qualitative analysis show that the network has strong robustness.
Lung cancer is a common life-threatening tumor with high malignancy and high invasiveness. Long non-coding RNAs (lncRNAs) are involved in almost every stage of tumor initiation and progression. Here, ...we identified an antisense lncRNA, MetaLnc9 antisense (Metalnc9-AS), which arises from the antisense strand of Metalnc9, located on chr9q34.11, while its biological function and mechanism are not clear in lung cancer. In this study, we demonstrated that the expression of Metalnc9-AS was upregulated in non-small cell lung cancer (NSCLC) tissues compared with corresponding non-tumorous tissues. The gain of MetaLnc9-AS was highly associated with the malignant features of NSCLC. Overexpression of MetaLnc9-AS enhanced tumor metastasis
and
. Mechanically, MetaLnc9-AS could form an RNA-RNA hybrid with its cognate sense counterpart, MetaLnc9, to regulate its expression in NSCLC cells, and that such complexes were protected from ribonuclease degradation. Thus, Metalnc9-AS might be a potential and effective treatment for NSCLC.
PDF
