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Objective: Tumour pathology contains rich information, including tissue structure and cell morphology, that reflects disease progression and patient survival. However, phenotypic information is subtle and complex, making the discovery of prognostic indicators from pathological images challenging., Design: An interpretable, weakly supervised deep learning framework incorporating prior knowledge was proposed to analyse hepatocellular carcinoma (HCC) and explore new prognostic phenotypes on pathological whole-slide images (WSIs) from the Zhongshan cohort of 1125 HCC patients (2451 WSIs) and TCGA cohort of 320 HCC patients (320 WSIs). A 'tumour risk score (TRS)' was established to evaluate patient outcomes, and then risk activation mapping (RAM) was applied to visualise the pathological phenotypes of TRS. The multi-omics data of The Cancer Genome Atlas(TCGA) HCC were used to assess the potential pathogenesis underlying TRS., Results: Survival analysis revealed that TRS was an independent prognosticator in both the Zhongshan cohort (p<0.0001) and TCGA cohort (p=0.0003). The predictive ability of TRS was superior to and independent of clinical staging systems, and TRS could evenly stratify patients into up to five groups with significantly different prognoses. Notably, sinusoidal capillarisation, prominent nucleoli and karyotheca, the nucleus/cytoplasm ratio and infiltrating inflammatory cells were identified as the main underlying features of TRS. The multi-omics data of TCGA HCC hint at the relevance of TRS to tumour immune infiltration and genetic alterations such as the FAT3 and RYR2 mutations., Conclusion: Our deep learning framework is an effective and labour-saving method for decoding pathological images, providing a valuable means for HCC risk stratification and precise patient treatment., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Several studies have indicated that acute myocardial infarction (AMI) secondary to coronary artery embolism (CE) has a poor prognosis. However, in the latter studies, CE of tumor origin accounts for a considerable proportion of cases and the clinical features and contribution to overall prognosis of non-tumor CE are unknown and therefore the subject of this study., Methods: We retrospectively studied 2006 consecutive patients with AMI at our medical center from January 2014 to October 2018. Non-tumor CE was diagnosed based on angiographic, biochemical, and imaging criteria. Patients were divided into two groups: patients without CE (control) and patients with non-tumor CE., Results: Atrial fibrillation was the most frequent etiology (n = 32, 69.6%) in the non-tumor CE group (n = 46). Compared with the control group, the non-tumor CE group had (all p < 0.05): higher incidence of atrial fibrillation; larger left atrial diameter, left ventricular end-diastolic diameter and left ventricular end-systolic diameter; lower left ventricular ejection fraction, ST-segment-elevation myocardial infarction incidence and low density lipoprotein cholesterol level; lower incidence of multivessel coronary stenosis, level of culprit lesion stenosis and proportion of angioplasty; higher ratio of manual thrombectomy and antithrombotic drugs alone therapy; lower thrombolysis in myocardial infarction (TIMI) grade and higher corrected TIMI frame counts (CTFC) after reperfusion; and statistically similar overall survival at median 864 (interquartile range, 413-1272) days., Conclusions: The overall incidence of non-tumor CE was 2.3%, with atrial fibrillation as its most common etiology. Midterm overall survival was similar between AMI patients secondary to non-tumor CE and those without CE., Competing Interests: Declaration of competing interest There is no conflict of interest in this study., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Intrahepatic cholangiocarcinoma (ICC) remains a highly heterogeneous disease with poor prognosis. Tumor-infiltrating lymphocytes were predictive in various cancers, but their prognostic value in ICC is less clear. A total of 168 ICC patients who had received liver resection were enrolled and assigned to the derivation cohort. Sixteen immune markers in tumor and peritumor regions were examined by immunohistochemistry. A least absolute shrinkage and selection operator model was used to identify prognostic markers and to establish an immune signature for ICC (IS ICC ). An IS ICC -applied prediction model was built and validated in another independent dataset. Five immune features, including CD3 peritumor (P) , CD57 P , CD45RA P , CD66b intratumoral (T) and PD-L1 P , were identified and integrated into an individualized IS ICC for each patient. Seven prognostic predictors, including total bilirubin, tumor numbers, CEA, CA19-9, GGT, HBsAg and IS ICC , were integrated into the final model. The C-index of the IS ICC -applied prediction model was 0.719 (95% CI, 0.660-0.777) in the derivation cohort and 0.667 (95% CI, 0.581-0.732) in the validation cohort. Compared with the conventional staging systems, the new model presented better homogeneity and a lower Akaike information criteria value in ICC. The IS ICC -applied prediction model may provide a better prediction performance for the overall survival of patients with resectable ICC in clinical practice., (© 2020 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.)

Background: The prognosis of patients with hepatocellular carcinoma (HCC) without portal vein tumor thrombosis (PVTT) after curative resection is at variance. We identified the risk factors of poor postoperative prognosis and consequently developed prognostic nomograms generating individual risk of death and recurrence for this subgroup of patients with HCC., Methods: The risk factors were identified and nomograms were developed based on a retrospective study of 734 patients in the primary cohort who underwent curative resection for HCC from 2010 to 2012. The predictive accuracy and discriminative ability of the nomograms were determined by concordance index (C-index) and calibration curve and compared with traditional staging systems of HCC. The results were validated in an independent cohort of 349 patients operated at the same institution in 2007., Results: All of the independent factors for survival in multivariate analysis in the primary cohort were selected into the nomograms. The calibration curve for probability of survival showed good agreement between prediction by nomograms and actual observation. The C-indices of the nomograms for predicting overall survival and recurrence-free survival were 0.755 (95% confidence interval [CI], 0.752-0.758) and 0.665 (95% CI, 0.662-0.668), respectively, which were statistically higher than the C-indices of other HCC prognostic models. The results were further confirmed in the validation cohort., Conclusion: The proposed nomograms resulted in more accurate prognostic prediction for patients with HCC without PVTT after curative resection. The Oncologist 2017;22:561-569 IMPLICATIONS FOR PRACTICE: Hepatocellular carcinoma (HCC) poses a great therapeutic challenge due to the poor prognosis in patients underwent surgical resection. The portal vein tumor thrombosis (PVTT) as a robust risk factor for survival has been routinely integrated to staging systems. Nonetheless, the prognosis stratification for patients without PVTT was neglected to some extent. Herein, independent risk factors of OS and RFS in HCC patients without PVTT were reconfirmed. A predictive nomogram was constructed on these risk factors and was demonstrated to be a more accurate predictive model in HCC patients without PVTT, compared with the traditional staging systems., Competing Interests: Disclosures of potential conflicts of interest may be found at the end of this article., (© AlphaMed Press 2017.)

The loss of 5-hydroxymethylcytosine (5-hmC) has been identified as an epigenetic hallmark in several malignancies. However, its role in intrahepatic cholangiocarcinoma (ICC) is still unknown. Our study aims to investigate the level of 5-hmC in diagnosis and prognosis prediction of ICC. The 5-hmC levels were detected using dot blot, tissue microarray technique and immunohistochemical method, and the correlation between 5-hmC level and ICC clinicopathological parameters was analysed. Compared with matched liver tissues, most of ICC tissues presented with the loss of 5-hmC. Furthermore, the subgroups of cirrhotic and poor differentiation tissues showed the lowest level of 5-hmC. We found that 5-hmC level in non-elevated ICC patients was significantly related to lymph node metastasis and TNM stage and not related to vessel invasion, sex, age, HBV, cirrhosis or degree of differentiation. ICC patients with high TNM stage (stages III and IV) and lymph node metastases had significantly lower 5-hmC level than those with low TNM stage (stages I and II) and no lymph node metastases. Further analysis showed that low 5-hmC level is significantly correlated with worse overall survival (OS) and disease-free survival (DFS). Importantly, multivariate analysis indicated that 5-hmC level, tumour diameter, lymphatic metastasis and tumour differentiation could be used as independent prognostic factors for ICC. The loss of 5-hmC is implicated in the progression of ICC. Our results can contribute to the diagnostic ability and postoperative surveillance of ICC patients.

Background: Sirtuin 3 (Sirt3), one of the seven Sirtuins family members, plays critical roles in the progression of multiple cancer types. However, its role in the prognosis of hepatocellular carcinoma (HCC) has not yet been investigated systematically., Methods: The correlation of Sirtuins expression with prognosis of HCC was determined by immunohistochemistry (IHC) in a large HCC patient cohort (n = 342). Expression of Sirt3 in tumoral and peritumoral tissues of HCC patients were further determined by western blotting (WB)., Results: IHC and WB studies both showed a decreased expression of Sirt3 in tumoral tissues compared with peritumoral tissues (P = 0.003 for IHC, P = 0.0042 for WB). Decreased expression of Sirt3 in both tumoral and peritumoral tissues was associated with increased recurrence probability and decreased overall survival rate by univariate analyses (intratumoral Sirt3: P = 0.011 for TTR, P = 0.001 for OS; peritumoral Sirt3: P = 0.017 for TTR, P = 0.023 for OS), the prognostic value was strengthened by multivariate analyses (intratumoral Sirt3: P = 0.031 for TTR, P = 0.001 for OS; peritumoral Sirt3: P = 0.047 for TTR, P = 0.031 for OS). Intratumoral Sirt3 also showed a favorable prognostic value in patients with BCLC stage A (TTR, P = 0.011; OS, P < 0.001). In addition, we found that IHC studies of other sirtuin members showed a decreased expression of Sirt2, Sirt4 and Sirt5 and an increased expression of Sirt1, Sirt6 and Sirt7 in intratumoral tissues compared with peritumoral tissues. In contrast to Sirt3, other members did not showed a remarkable correlation with HCC prognosis., Conclusions: Down-regulation of intratumoral and peritumoral Sirt3 were both associated with poor outcome in HCC, moreover, intratumoral Sirt3 was a favorable prognostic predictor in early stage patients.

Background: Calpain small subunit 1 (Capn4) has been shown to correlate with the metastasis/invasion of hepatocellular carcinoma. This study aimed to investigate the role of Capn4 in intrahepatic cholangiocarcinoma (ICC)., Methods: Capn4 expression was measured in 33 ICC tissues by quantitative real-time polymerase chain reaction and western blot. The role of Capn4 in the migration, invasion and proliferation of ICC cells and matrix metalloproteinase 2 (MMP2) expression were assessed after Capn4 depletion by specific small interfering RNA. Capn4 expression was further examined by immunohistochemistry in a tissue microarray consisting of 140 ICC patients and 13 normal liver tissues, and the prognostic role of Capn4 in ICC was evaluated by Kaplan-Meier and Cox regression analyses., Results: Capn4 expression was significantly higher in the ICC tissues compared to the peritumor tissues. Capn4 down-regulation impaired the migration/invasion ability of HCCC-9810 and QBC939 cells in vitro and decreased MMP2 expression. Capn4 overexpression significantly correlated with the presence of lymphatic metastasis of ICC (p = 0.026) and the tumor-node-metastasis (TNM) stage (p = 0.009). The postoperative 2- and 5-year overall survivals in patients with Capn4(low) were higher than those in the Capn4(high) group. The cumulative recurrence rate in patients with Capn4(low) was much lower than in the Capn4(high) group. Multivariate analysis showed that Capn4 overexpression was an independent prognostic marker in ICC., Conclusions: Capn4 overexpression was implicated in ICC metastasis/invasion, and Capn4 overexpression may be used as a molecular therapeutic target for ICC.

Objective To investigate the clinical efficacy and prognostic factors of autologous hematopoietic stem cell transplantation (ASCT) for Hodgkin's lymphoma (HL). Methods We retrospectively analyzed the data of 38 patients with HL who underwent ASCT. Kaplan-Meier and Cox methods were used to analyze the curative effect and prognostic factors after transplantation. Results All 38 transplanted patients obtained hematopoietic reconstitution. The CR rates before and after transplantation were 55.3% and 81.6%, respectively, and the 5-year PFS and OS were 76.1% and 79.0%, respectively. Univariate analysis showed that B symptoms, IPS score, pre-transplant remission status, extranodal invasion, and pretreatment regimen were the factors affecting the prognosis of ASCT in patients with HL. Multivariate analysis showed that B symptom was an independent risk factor affecting 5-year PFS. Conclusion ASCT is effective in the treatment of high-risk, relapsed, and refractory patients with HL. B symptom is an independent risk factor affecting the prognosis of transplantation.

The complement cascade plays a “complementing” role in human immunity. However, the potential roles of complement system in impacting molecular and clinical features of hepatocellular carcinoma (HCC) remain unclear. In this study, eleven public datasets are analyzed to compare the complement status between normal and cancerous samples based on 18 classical complement-associated genes. The complement scores are constructed to quantify complement signatures of individual tumors. HCC patients in the The Cancer Genome Atlas (TCGA) cohort are focused to perform systematical analyses between complement status and immune infiltration, miRNA expression, DNA methylation, clinicopathological features, and drug response. The results show that the complement scores in normal tissues are dramatically higher than those of tumor tissues. Tumor samples in the TCGA cohort are classified into complement score-low and score-high groups. Pathway analysis reveals that tumor-promoting pathways are typically inhibited in complement score-high group. This study also shows that tumor-killing immune cells, such as CD8 + T cells and natural killer cells are abundant and tumor-suppressing miRNAs are upregulated in complement score-high samples. In addition, we identify that complement scores are negatively correlated with certain clinical features, including pathological grade, clinical-stage, and portal vein invasion. Moreover, various molecular features together with complement scores are found to be correlated with response to anti-cancer drugs. This study provides a comprehensive and multidimensional analysis conducive to understanding the role of complement in cancer.

Membranous nephropathy (MN) is a rare complication that can occur after allogeneic hematopoietic stem cell transplantation (allo-HSCT). MN patients may develop nephrotic syndrome or even kidney failure, which greatly affects their quality of life and prognosis. However, current knowledge regarding MN after allo-HSCT is limited. Thus, a multicenter nested case‒control study was conducted. Patients who had been diagnosed with MN after allo-HSCT were retrospectively identified at 8 HSCT centers. A total of 51 patients with MN after allo-HSCT were included. The median age of MN patients after allo-HSCT was 38 years, and the median duration from HSCT to MN was 18 months. The use of HLA-matched donors (P = 0.0102) and peripheral blood as the graft source (P = 0.0060) were identified as independent predisposing risk factors for the onset of MN after allo-HSCT. Compared to those in the control group, the incidence of extensive chronic graft-versus-host disease was greater in the MN patients (P = 0.0002). A total of 31 patients developed nephrotic syndrome. Patients receiving combination treatments of corticosteroids and immunosuppressants appeared to have better outcomes. In conclusion, MN is a rare but occasionally severe complication following HSCT and may require active treatment. [ABSTRACT FROM AUTHOR]

Background: Extracellular vesicles (EVs) facilitate cell–cell interactions in the tumour microenvironment. However, standard and efficient methods to isolate tumour tissue‐derived EVs are lacking, and their biological functions remain elusive. Methods: To determine the optimal method for isolating tissue‐derived EVs, we compared the characterization and concentration of EVs obtained by three previously reported methods using transmission electron microscopy, nanoparticle tracking analysis, and nanoflow analysis (Nanoflow). Additionally, the differential content of small RNAs, especially tsRNAs, between hepatocellular carcinoma (HCC) and adjacent normal liver tissues (ANLTs)‐derived EVs was identified using Arraystar small RNA microarray. The targets of miRNAs and tsRNAs were predicted, and downstream functional analysis was conducted using Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, non‐negative matrix factorization and survival prediction analysis. Results: A differential centrifugation‐based protocol without cell cultivation (NC protocol) yielded higher EV particles and higher levels of CD9+ and CD63+ EVs compared with other isolation protocols. Interestingly, the NC protocol was also effective for isolating frozen tissue‐derived EVs that were indistinguishable from fresh tissue. HCC tissues showed significantly higher EV numbers compared with ANLTs. Furthermore, we identified different types of small RNAs in HCC tissue‐derived EVs, forming a unique multidimensional intercellular communication landscape that can differentiate between HCC and ANLTs. ROC analysis further showed that the combination of the top 10 upregulated small RNAs achieved better diagnostic performance (AUC =.950 [.895–1.000]). Importantly, most tsRNAs in HCC tissue‐derived EVs were downregulated and mitochondria‐derived, mainly involving in lipid‐related metabolic reprogramming. Conclusion: The NC protocol was optimal for isolating EVs from HCC, especially from frozen tissues. Our study emphasized the different roles of small‐RNA in regulating the HCC ecosystem, providing insights into HCC progression and potential therapeutic targets. [ABSTRACT FROM AUTHOR]

Purpose: Molecular residual disease (MRD) is a promising biomarker in colorectal cancer (CRC) for prognosis and guiding treatment, while the whole-exome sequencing (WES) based tumor-informed assay is standard for evaluating MRD based on circulating tumor DNA (ctDNA). In this study, we assessed the feasibility of a fixed-panel for evaluating MRD in CRC. Materials and Methods: Seventy-five patients with resectable stage I-III CRC were enrolled. Tumor tissues obtained by surgery, and preoperative and postoperative day 7 blood samples were collected. The ctDNA was evaluated using the tumor-agnostic and tumor-informed fixed assays, as well as the WES-based and panel-based personalized assays in randomly selected patients. Results: The tumor-informed fixed assay had a higher preoperative positive rate than the tumor-agnostic assay (73.3% vs. 57.3%). The preoperative ctDNA status failed to predict disease-free survival (DFS) in either of the fixed assays, while the tumor-informed fixed assay-determined postoperative ctDNA positivity was significantly associated with worse DFS (hazard ratio [HR], 20.74; 95% confidence interval [CI], 7.19 to 59.83; p < 0.001), which was an independent predictor by multivariable analysis (HR, 28.57; 95% CI, 7.10 to 114.9; p < 0.001). Sub-cohort analysis indicated the WES-based personalized assay had the highest preoperative positive rate (95.1%). The two personalized assays and the tumor-informed fixed assay demonstrated same results in postoperative landmark (HR, 26.34; 95% CI, 6.01 to 115.57; p < 0.001), outperforming the tumor-agnostic fixed panel (HR, 3.04; 95% CI, 0.94 to 9.89; p=0.052). Conclusion: Our study confirmed the prognostic value of the ctDNA positivity at postoperative day 7 by the tumor-informed fixed panel. The tumor-informed fixed panel may be a cost-effective method to evaluate MRD, which warrants further studies in future. [ABSTRACT FROM AUTHOR]

Although Metavir and Fibrosis-4 (FIB-4) scores are typically used to assess the severity of liver fibrosis, the relationship between these scores and patient outcome in hepatocellular carcinoma (HCC) is unclear. The aim of this study was to evaluate the prognostic value of the severity of hepatic fibrosis in HBV-related HCC patients after curative resection. We examined the prognostic roles of the Metavir and preoperative FIB-4 scores in 432 HBV-HCC patients who underwent curative resection at two different medical centers located in western (Chongqing) and eastern (Shanghai) China. In the testing set (n = 108), the Metavir, FIB-4, and combined Metavir/FIB-4 scores were predictive of overall survival (OS) and recurrence-free survival (RFS). Additionally, they were associated with several clinicopathologic variables. In the validation set (n = 324), the Metavir, FIB-4, and combined Metavir/FIB-4 scores were associated with poor prognosis in HCC patients after curative resection. Importantly, in the negative alpha-fetoprotein subgroup (≤ 20 ng/mL), the FIB-4 index (I vs. II) could discriminate between patient outcomes (high or low OS and RFS). Thus Metavir, preoperative FIB-4, and combined Metavir/FIB-4 scores are prognostic markers in HBV-HCC patients after curative hepatectomy.

Background: Early diagnosis of hepatocellular carcinoma (HCC) can significantly improve patient survival. We aimed to develop a blood‐based assay to aid in the diagnosis, detection and prognostic evaluation of HCC. Methods: A three‐phase multicentre study was conducted to screen, optimise and validate HCC‐specific differentially methylated regions (DMRs) using next‐generation sequencing and quantitative methylation‐specific PCR (qMSP). Results: Genome‐wide methylation profiling was conducted to identify DMRs distinguishing HCC tumours from peritumoural tissues and healthy plasmas. The twenty most effective DMRs were verified and incorporated into a multilocus qMSP assay (HepaAiQ). The HepaAiQ model was trained to separate 293 HCC patients (Barcelona Clinic Liver Cancer (BCLC) stage 0/A, 224) from 266 controls including chronic hepatitis B (CHB) or liver cirrhosis (LC) (CHB/LC, 96), benign hepatic lesions (BHL, 23), and healthy controls (HC, 147). The model achieved an area under the curve (AUC) of 0.944 with a sensitivity of 86.0% in HCC and a specificity of 92.1% in controls. Blind validation of the HepaAiQ model in a cohort of 523 participants resulted in an AUC of 0.940 with a sensitivity of 84.4% in 205 HCC cases (BCLC stage 0/A, 167) and a specificity of 90.3% in 318 controls (CHB/LC, 100; BHL, 102; HC, 116). When evaluated in an independent test set, the HepaAiQ model exhibited a sensitivity of 70.8% in 65 HCC patients at BCLC stage 0/A and a specificity of 89.5% in 124 patients with CHB/LC. Moreover, HepaAiQ model was assessed in paired pre‐ and postoperative plasma samples from 103 HCC patients and correlated with 2‐year patient outcomes. Patients with high postoperative HepaAiQ score showed a higher recurrence risk (Hazard ratio, 3.33, p <.001). Conclusions: HepaAiQ, a noninvasive qMSP assay, was developed to accurately measure HCC‐specific DMRs and shows great potential for the diagnosis, detection and prognosis of HCC, benefiting at‐risk populations. [ABSTRACT FROM AUTHOR]

Background: Uterine sarcoma (US) is a highly malignant cancer with poor prognosis and high mortality in women. In this study, we evaluated the expression of human fibroblast growth factor 23 (FGF23) in different US subtypes and the relationship between survival and clinicopathological characteristics. Methods: We conducted a comparative analysis of FGF23 gene expression in different pathological types of US. Utilizing a cohort from The Cancer Genome Atlas of 57 patients, a 50-patient microarray dataset (GSE119043) from the Gene Expression Omnibus and a Suining cohort of 44 patients, we analyzed gene expression profiles and corresponding clinicopathological information. Immunohistochemistry was used to examine the expression level of FGF23 in four US subtypes. Survival analysis was used to assess the relationship between FGF23 expression and prognosis in US patients. Results: Compared with uterine normal smooth muscle and uterine leiomyoma, FGF23 expression was significantly upregulated in US and was differentially expressed in four US subtypes. Uterine carcinosarcoma exhibited the highest expression of FGF23 among the subtypes. Survival analysis revealed no correlation between FGF23 expression and either overall survival or progression-free survival in US (P > 0.05). Similar results were obtained from the validation cohorts. Univariate and multivariate analyses showed no significant correlation between FGF23 expression and the US prognosis. Tumor stage, CA125, and tumor recurrence were independent prognostic factors for survival of US patients. Conclusion: FGF23 was highly expressed in US and was promising as a novel potential biomarker for the diagnosis and prognosis of US. [ABSTRACT FROM AUTHOR]

Purpose: Spontaneous rupture is a fatal complication of hepatocellular carcinoma (HCC). This study compared the prognosis of spontaneously ruptured HCC (srHCC) with that of non-ruptured HCC (nrHCC). Methods: A total of 185 srHCC patients and 1085 nrHCC patients treated by hepatectomy between February 2005 and December 2017 at Zhongshan Hospital were retrospectively reviewed and enrolled. The overall survival (OS) and time to recurrence (TTR) were evaluated. A 1:2 propensity score matching (PSM) analysis was performed using the nearest neighbor matching with a caliper of 0.2. Results: Before PSM, patients with srHCC who underwent hepatectomy (n = 185) had a poorer prognosis than those with nrHCC (n = 1085; 5-year OS, 39.1% vs 59.2%, P < 0.001; 5-year TTR, 83.8% vs 54.9%, P < 0.001). After PSM, patients with srHCC (n = 156) had higher 5-year TTR (83.2% vs 69.0%, P < 0.001) but comparable 5-year OS with those with nrHCC (n = 312, 44.0% vs 46.0%, P = 0.600). Univariate and multivariate analyses demonstrated spontaneous rupture as an independent risk factor for TTR (hazard ratio [HR], 1.681; 95% confidence interval [CI] 1.326–2.132; P < 0.001), but not for OS (HR: 1.074; 95% CI 0.823–1.401; P = 0.600). Further analysis revealed that srHCC was not appropriate to be assigned as T4 stage in American Joint Committee on Cancer classification. Conclusion: Spontaneous rupture of HCC is not a risk factor for survival. If resected eventually, srHCC may achieve comparable survival with nrHCC. [ABSTRACT FROM AUTHOR]

Objective: To develop an imaging-derived biomarker for prediction of overall survival (OS) of pancreatic cancer by analyzing preoperative multiphase contrast-enhanced computed topography (CECT) using deep learning. Background: Exploiting prognostic biomarkers for guiding neoadjuvant and adjuvant treatment decisions may potentially improve outcomes in patients with resectable pancreatic cancer. Methods: This multicenter, retrospective study included 1516 patients with resected pancreatic ductal adenocarcinoma (PDAC) from 5 centers located in China. The discovery cohort (n=763), which included preoperative multiphase CECT scans and OS data from 2 centers, was used to construct a fully automated imaging-derived prognostic biomarker—DeepCT-PDAC—by training scalable deep segmentation and prognostic models (via self-learning) to comprehensively model the tumor-anatomy spatial relations and their appearance dynamics in multiphase CECT for OS prediction. The marker was independently tested using internal (n=574) and external validation cohorts (n=179, 3 centers) to evaluate its performance, robustness, and clinical usefulness. Results: Preoperatively, DeepCT-PDAC was the strongest predictor of OS in both internal and external validation cohorts [hazard ratio (HR) for high versus low risk 2.03, 95% confidence interval (CI): 1.50–2.75; HR: 2.47, CI: 1.35–4.53] in a multivariable analysis. Postoperatively, DeepCT-PDAC remained significant in both cohorts (HR: 2.49, CI: 1.89–3.28; HR: 2.15, CI: 1.14–4.05) after adjustment for potential confounders. For margin-negative patients, adjuvant chemoradiotherapy was associated with improved OS in the subgroup with DeepCT-PDAC low risk (HR: 0.35, CI: 0.19–0.64), but did not affect OS in the subgroup with high risk. Conclusions: Deep learning-based CT imaging-derived biomarker enabled the objective and unbiased OS prediction for patients with resectable PDAC. This marker is applicable across hospitals, imaging protocols, and treatments, and has the potential to tailor neoadjuvant and adjuvant treatments at the individual level. [ABSTRACT FROM AUTHOR]

To investigate the value of magnetic resonance imaging (MRI) including diffusion-weighted imaging (DWI) findings in predicting mesenchymal transition (MT) high-grade serous ovarian cancer (HGSOC). Patients with HGSOC were enrolled from May 2017 to December 2020, who underwent pelvic MRI including DWI (b = 0,1000 s/mm2) before surgery, and were assigned to the MT HGSOC or non-MT HGSOC group according to histopathology results. Clinical characteristics and MRI features including DWI-based histogram metrics were assessed and compared between the two groups. Univariate and multivariate analyses were performed to identify the significant variables associated with MT HGSOC – these variables were then incorporated into a predictive nomogram, and ROC curve analysis was subsequently carried out to evaluate diagnostic performance. A total of 81 consecutive patients were recruited for pelvic MRI before surgery, including 37 (45.7%) MT patients and 44 (54.3%) non-MT patients. At univariate analysis, the features significantly related to MT HGSOC were identified as absence of discrete primary ovarian mass, pouch of Douglas implants, ovarian mass size, tumor volume, mean, SD, median, and 95th percentile apparent diffusion coefficient (ADC) values (all p < 0.05). At multivariate analysis, the absence of discrete primary ovarian mass {odds ratio (OR): 46.477; p = 0.025}, mean ADC value ≤ 1.105 (OR: 1.023; p = 0.009), and median ADC value ≤ 1.038 (OR: 0.982; p = 0.034) were found to be independent risk factors associated with MT HGSOC. The combination of all independent criteria yielded the largest AUC of 0.82 with a sensitivity of 83.87% and specificity of 66.67%, superior to any of the single predictor alone (p ≤ 0.012). The predictive C-index nomogram performance of the combination was 0.82. The combination of absence of discrete primary ovarian mass, lower mean ADC value, and median ADC value may be helpful for preoperatively predicting MT HGSOC. [ABSTRACT FROM AUTHOR]

T2N0M0 glottic laryngeal squamous cell carcinoma (LSCC) is a common type of laryngeal cancer. The objective of this research was to assess the predictive value of tumor size for the rates of overall survival (OS) and disease-free survival (DFS) as determined by postoperative pathological examination in patients with T2 LSCC. A retrospective study was conducted on 535 successive patients with T2 glottic LSCC who underwent operation from 2005 to 2010. The effect of tumor size on OS and DFS results was evaluated by the affected area. Of the cohort, 528 (98.7%) were male, and 7 (1.3%) were female, with an average age of 60.1 ± 9.4 years. The 10-year DFS and OS rates were 72.1% and 76.3%, respectively. The tumor diameter and area cut-off values that best discriminated OS and DFS rates were 1.35 cm and 1 cm2, respectively. Patients with glottis carcinoma with a longer tumor diameter and larger tumor area had inferior OS and DFS rates. Tumor diameter and tumor area were independent predictive factors for the rates of OS and DFS in patients with T2 glottic LSCC. This research showed that patients with T2 glottic LSCC with a carcinoma diameter >1.35 cm or a tumor area >1 cm2 have worse survival outcomes. These factors independently predict survival outcomes in patients. [ABSTRACT FROM AUTHOR]

Objective: To determine the predictors and the long-term outcomes of patients with seizures following surgery for dysembryoplastic neuroepithelial tumors (DNTs); Methods: Clinical data were collected from medical records of consecutive patients of the Department of Neurosurgery of Sanbo Brain Hospital of Capital Medical University with a pathological diagnosis of DNT and who underwent surgery from January 2008 to July 2021. All patients were followed up after surgery for at least one year. We estimated the cumulative rate of seizure recurrence-free and generated survival curves. A log-rank (Mantel–Cox) test and a Cox proportional hazard model were performed for univariate and multivariate analysis to analyze influential predictors; Results: 63 patients (33 males and 30 females) were included in this study. At the final follow-up, 49 patients (77.8%) were seizure-free. The cumulative rate of seizure recurrence-free was 82.5% (95% confidence interval (CI) 71.8–91.3%), 79.0% (95% CI 67.8–88.6%) and 76.5% (95% CI 64.8–87.0%) at 2, 5, and 10 years, respectively. The mean time for seizure recurrence-free was 6.892 ± 0.501 years (95% CI 5.91–7.87). Gross total removal of the tumor and a short epilepsy duration were significant predictors of seizure freedom. Younger age of seizure onset, bilateral interictal epileptiform discharges, and MRI type 3 tumors were risk factors for poor prognosis; Conclusions: A favorable long-term seizure outcome was observed for patients with DNT after surgical resection. Predictor analysis could effectively guide the clinical work and evaluate the prognosis of patients with DNT associated with epilepsy. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to evaluate the surgical outcomes and relevant prognostic factors in patients with low‐grade epilepsy‐associated neuroepithelial tumors (LEAT) and, especially, to develop a scoring system to predict postoperative seizure outcomes. Methods: The clinical data of patients who underwent epilepsy surgery for LEAT were retrospectively studied. The surgical outcomes of seizure and neurological statuses in patients were evaluated using Engel classification and modified Rankin Scale (mRS) scoring, respectively. A scoring system of seizure outcomes was constructed based on the weight of the β‐coefficient estimate of each predictor in the final multivariate predicting model of seizure outcomes. Results: Of the 287 patients (106 female) enrolled, the median age was 19 years at surgery and 10 years at seizure onset, with a median duration of epilepsy of 60 months. Among 258 patients who were followed up for at least 12 months, 215 (83.3%) patients had a favorable seizure outcome (Engel class I) after surgery, and 43 (16.7%) patients had an unfavorable seizure outcome; longer duration of epilepsy, discordant magnetoencephalography (MEG) findings, and acute postoperative seizures were significantly included in the scoring system to predict unfavorable seizure outcomes, and in the scoring system, accumulated scoring of 0–19 scores was recorded, which were finally grouped into three risk levels: low risk (risk < 30%), medium risk (30% ≤ risk < 70%), and high risk (risk ≥ 70%). In addition, favorable neurological outcomes (mRS score 0–1) were recorded in 187 (72.5%) patients, while unfavorable neurological outcomes were recorded in 71 (27.5%) patients, which were significantly related to poor seizure control, older age at surgery, and longer duration of epilepsy and hospitalization time. Significance: The long‐term surgical outcomes of LEAT after surgery were satisfactory. A scoring system for predicting unfavorable seizure outcomes with different risk levels was developed, which could partly guide clinical treatments of LEAT. [ABSTRACT FROM AUTHOR]

To identify and utilize gene signatures for the prognostic evaluation of postoperative patients with hepatocellular carcinoma (HCC). The gene mRNA expression profiles and corresponding clinicopathological data of postoperative patients with HCC were downloaded from The Cancer Genome Atlas (TCGA) database. Highly differentially expressed genes (DEGs) in tumor tissues compared to adjacent tissues were identified, and their associations with the overall survival (OS) of HCC patients were analyzed. The strongly associated genes were used to develop a prognostic score for the survival stratification of HCC, and the underlying mechanisms were analyzed using bioinformatics. A total of 376 DEGs were identified and four DEGs (ADH4, COL15A1, RET and KCNJ16) were independently associated with OS. A prognostic score derived from the four genes could effectively stratify HCC patients with different OS outcomes, independent of clinical parameters. Patients with high scores exhibited poorer OS than patients with low scores (HR 5.526, 95% CI: 2.451–12.461, p <.001). The four genes were involved in cancer-related biological processes and were independent of each other in bioinformatics analyses. Four genes strongly associated with the prognosis of postoperative patients with HCC were identified, and the derived prognostic score was simple and valuable for overall survival prediction. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: Conventional chemotherapy has limited benefit in pancreatic ductal adenocarcinoma (PDAC), necessitating identification of novel therapeutic targets. Radiomics may enable non-invasive prediction of CD20 expression, a hypothesized therapeutic target in PDAC. To develop a machine learning classifier based on noncontrast magnetic resonance imaging for predicting CD20 expression in PDAC.Materials and Methods: Retrospective study was conducted on preoperative noncontrast magnetic resonance imaging of 156 patients with pathologically confirmed PDAC from January 2017 to April 2018. For each patient, 1409 radiomics features were selected using minimum absolute contraction and selective operator logistic regression algorithms. CD20 expression was quantified using immunohistochemistry. A multilayer perceptron network classifier was developed using the training and validation set.Results: A log-rank test showed that the CD20-high group (22.37 months, 95% CI: 19.10-25.65) had significantly longer survival than the CD20-low group (14.9 months, 95% CI: 10.96-18.84). The predictive model showed good differentiation in training (area under the curve [AUC], 0.79) and validation (AUC, 0.79) sets. Sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 73.21%, 75.47%, 0.74, 0.76, and 0.73, respectively, for the training set and 69.23%, 80.95%, 0.74, 0.82, and 0.68, respectively, for the validation set.Conclusion: Multilayer perceptron classifier based on noncontrast magnetic resonance imaging scanning can predict the level of CD20 expression in PDAC patients. [ABSTRACT FROM AUTHOR]