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Background: The advances in deep learning-based pathological image analysis have invoked tremendous insights into cancer prognostication. Still, lack of interpretability remains a significant barrier to clinical application. Methods: We established an integrative prognostic neural network for intrahepatic cholangiocarcinoma (iCCA), towards a comprehensive evaluation of both architectural and fine-grained information from whole-slide images. Then, leveraging on multi-modal data, we conducted extensive interrogative approaches to the models, to extract and visualize the morphological features that most correlated with clinical outcome and underlying molecular alterations. Results: The models were developed and optimized on 373 iCCA patients from our center and demonstrated consistent accuracy and robustness on both internal (n = 213) and external (n = 168) cohorts. The occlusion sensitivity map revealed that the distribution of tertiary lymphoid structures, the geometric traits of the invasive margin, the relative composition of tumor parenchyma and stroma, the extent of necrosis, the presence of the disseminated foci, and the tumor-adjacent micro-vessels were the determining architectural features that impacted on prognosis. Quantifiable morphological vector extracted by CellProfiler demonstrated that tumor nuclei from high-risk patients exhibited significant larger size, more distorted shape, with less prominent nuclear envelope and textural contrast. The multi-omics data (n = 187) further revealed key molecular alterations left morphological imprints that could be attended by the network, including glycolysis, hypoxia, apical junction, mTORC1 signaling, and immune infiltration. Conclusions: We proposed an interpretable deep-learning framework to gain insights into the biological behavior of iCCA. Most of the significant morphological prognosticators perceived by the network are comprehensible to human minds. [ABSTRACT FROM AUTHOR]

We take Graph $g={9.8}\ \textrm {m}\ \textrm {s}^{-2}$, Graph $\alpha ={1\times 10^{-4}}\ \textrm {K}^{{-1}}$ (Sohail I et al. i 2018), Graph $L=1\times 10^{7}\ \textrm {m}$, Graph $\varDelta ={10}\ \textrm {K}$, Graph $\kappa ={1\times 10^{-7}}\ \textrm {m}^2\ \textrm {s}^{-1}$ and Graph $\nu =1\times 10^{-6}\ \textrm {m}^2\ \textrm {s}^{-1}$ (Siggers, Kerswell & Balmforth 2004). The normalized height of topography Graph $h/H$ corresponds to Graph $0$, Graph $0.25$, Graph $0.5$ and Graph $0.75$ in figure 3( I a i - I d i ). Furthermore, as shown in figures 5 and 8, both Graph $\phi \tau$ and Graph $Nu$ increase as Graph $\omega$ decreases, and note that Graph $Nu$ is proportional to Graph $G(APE)$. In the current study, Graph $Ra$, Graph $Pr$ and Graph $\varGamma$ are fixed as Graph $Ra=1\times 10^{10}$, Graph $Pr=8.0$ and Graph $\varGamma =0.2$. Because Graph $\phi i$ is small compared with Graph $G(APE)$ for sufficiently large Graph $Ra$ (Peltier & Caulfield 2003; Gayen I et al. i 2013), Graph $\eta '$ asymptotically approaches its upper limit of 1 as Graph $Ra$ increases. [Extracted from the article]

Background: Microvascular invasion (MVI) is recognized as a prognostic factor associated with poor outcome in hepatocellular carcinoma (HCC) patients after curative resection. It remains unclear, however, whether MVI can provide prognostic information for patients at a specific tumor stage.Methods: Consecutive HCC patients who underwent curative resection in years of 2007 and 2008 (discovery cohort) were enrolled in this retrospective study. Patients were stratified by the Barcelona Clinic Liver Cancer (BCLC) staging system. The prognostic significance of MVI for overall survival (OS) and recurrence-free survival (RFS) was studied in each subgroup. The clinical significance of MVI was validated in another cohort of patients underwent curative surgery in the year of 2006 (validation cohort).Results: Of the 1540 patients in the discovery cohort, 389 (25.3%) patients had detectable MVI. Occurrence rates of MVI in the BCLC stage 0, A, and B subgroups were 12.4, 26.2, and 34.4%, respectively. In univariate analysis, MVI was associated with poor OS and RFS (P < 0.001 for both) in HCC patients at stage A, with poor OS in patients at stage 0 (P = 0.028), and with poor RFS at stage B (P = 0.039). In multivariate analysis, MVI was an independent risk factor for OS (HR = 1.431, 95% CI, 1.163-1.761, P < 0.001) and RFS (HR = 1.400, 95% CI, 1.150-1.705, P = 0.001) in patients at stage A; and an independent risk factor for RFS (P = 0.043) in patients at stage B. A similar clinical significance of MVI was found in the validation cohort.Conclusions: MVI has limited prognostic value for HCC patients at BCLC stages 0 and B. For those at stage A, MVI was associated with patient survival and may help to select patients with high risk of disease recurrence. [ABSTRACT FROM AUTHOR]

Recent studies have found that selenium-binding protein 1 (SBP1) is downregulated in various malignant tumors. Nevertheless, the role of SBP1 in intrahepatic cholangiocarcinoma (ICC) is largely unknown. In the present study, we aimed to explore the clinical significance and biological function of SBP1 in ICC. Western blotting and immunohistochemistry were performed to evaluate SBP1 expression in ICC tissues, and correlations between SBP1 and clinicopathological parameters were further assessed. The prognostic significance of SBP1 in ICC patients was evaluated via Kaplan-Meier and Cox regression analyses. Moreover, we used RBE, a human ICC cell line, to study the effects of SBP1 knockdown on ICC cell proliferation, migration and invasion. Finally, the expression levels of epithelial-mesenchymal transition-related markers, including snail, vimentin, and E-cadherin, were investigated via Western blotting and immunohistochemistry. The results showed that SBP1 expression was significantly downregulated in ICC tumor tissues, especially in tumor tissues from ICC patients with recurrence or tumor vascular invasion, compared with that in peritumoral tissues (all P < 0.05). In addition, the reduction in SBP1 expression was related to microvascular invasion, lymphatic metastasis, and tumor-node-metastasis (TNM) stage (all P < 0.05). Furthermore, the SBP1 expression level was an independent prognostic factor in ICC ( P < 0.05). Knockdown of SBP1 resulted in decreased in vitro proliferation, migration and invasion ability. Low SBP1 expression also resulted in the upregulation of mesenchymal markers such as vimentin and snail. In conclusion, SBP1 may be a prognostic indicator for patients with ICC as well as a potential target for ICC treatment., Competing Interests: None.

Decreased selenium-binding protein 1 (SBP1) is associated with increased invasion and poor prognosis of hepatocellular carcinoma (HCC). However, the underlying mechanism remains unknown. To unravel this mechanism, HCC cells expressing SBP1 were constructed and the impact on migration, invasion, and epithelial-mesenchymal transition (EMT) was evaluated. SBP1 expression reduced HCC cell migration and invasion by inhibiting EMT. Gene expression profiles of control and SBP1 expressing HCC cells revealed 186 differentially expressed genes, of which fibroblast growth factor 5, vascular endothelial growth factor receptor 1, and C-X-C motif chemokine receptor 4 ( CXCR4 ) showed the greatest differences. CXCR4 expression was inhibited by SBP1 and restored the migration and invasion ability of HCC cells through activation of AKT signaling. Tumor samples from 200 HCC patients supported our in vitro findings and revealed an inverse correlation between SBP1 and CXCR4 expression. Patients with low SBP1 and high CXCR4 expression had the poorest prognosis and survival rate. Our results suggest that downregulation of SBP1 induces increased CXCR4 expression and results in EMT of HCC cells. Together, SBP1 and CXCR4 are promising potential biomarkers and therapeutic targets for HCC patients., Competing Interests: None.