Peripheral blood inflammatory biomarkers dynamics reflect treatment response and predict prognosis in non-small cell lung cancer patients with neoadjuvant immunotherapy.

Neoadjuvant immunotherapy has significantly changed the therapeutic approach for treating patients with surgically resectable non-small cell lung cancer (NSCLC). Here, peripheral blood inflammation-based biomarkers as well as previously less focused eosinophil fraction, modified Glasgow prognostic score (mGPS), and prognostic nutritional index (PNI) were systematically included to comprehensively analyze their potential in predicting neoadjuvant immunotherapy efficacy and prognosis. We enrolled 189 patients (94 in training and 95 in validation cohorts) with stage I-III B surgically resectable NSCLC treated with neoadjuvant immunotherapy from the National Cancer Center of China. Baseline and post-treatment eosinophils fraction, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), monocyte-to-lymphocyte ratio (MLR), PNI, mGPS, and their changes were calculated and analyzed for correlation with neoadjuvant immunotherapy efficacy and prognosis. In patients in the major pathological response (MPR) group, the post-treatment eosinophil fraction was significantly high, and NLR, PLR, SII, and MLR were significantly lower compared to the non-MPR group in both the training and validation cohorts. The receiver operating characteristic curve showed that post-treatment, eosinophil fraction and SII and their changing were two of the most important factors. Univariate and multivariate logistic regression analyses showed that post-treatment eosinophil fraction, SII, mGPS, and ΔSII could independently predict MPR in patients treated with neoadjuvant immunotherapy. Survival analysis showed a significant correlation between high post-treatment NLR, PLR, SII, mGPS, and their changes in ΔNLR and ΔSII elevation with poor overall survival and event-free survival of patients. Our results suggest that inflammatory biomarkers could predict the patient's response to neoadjuvant immunotherapy and prognosis.

Multi-dimensional characterization of immunological profiles in small cell lung cancer uncovers clinically relevant immune subtypes with distinct prognoses and therapeutic vulnerabilities.

Small-cell lung cancer (SCLC) is generally considered a 'homogenous' disease, with little documented inter-tumor heterogeneity in treatment guidance or prognosis evaluation. The precise identification of clinically relevant molecular subtypes remains incomplete and their translation into clinical practice is limited. In this retrospective cohort study, we comprehensively characterized the immune microenvironment in SCLC by integrating transcriptional and protein profiling of formalin-fixation-and-paraffin-embedded (FFPE) samples from 29 patients. We identified two distinct disease subtypes: immune-enriched (IE-subtype) and immune-deprived (ID-subtype), displaying heterogeneity in immunological, biological, and clinical features. The IE-subtype was characterized by abundant immune infiltrate and elevated levels of interferon-alpha/gamma (IFNα/IFNγ) and inflammatory response, while the ID-subtype featured a complete lack of immune infiltration and a more proliferative phenotype. These two immune subtypes are associated with clinical benefits in SCLC patients treated with adjuvant therapy, with the IE-subtype exhibiting a more favorable response leading to improved survival and reduced disease recurrence risk. Additionally, we identified and validated a personalized prognosticator of immunophenotyping, the CCL5/CXCL9 chemokine index (CCI), using machine learning. The CCI demonstrated superior predictive abilities for prognosis and clinical benefits in SCLC patients, validated in our institute immunohistochemistry cohort and multicenter bulk transcriptomic data cohorts. In conclusion, our study provides a comprehensive and multi-dimensional characterization of the immune architecture of SCLC using clinical FFPE samples and proposes a new immune subtyping conceptual framework enabling risk stratification and the appropriate selection of individualized therapy.

Evaluation of Prognosis in Patients with Lung Adenocarcinoma with Atypical Solid Nodules on Thin-Section CT Images.

Purpose To evaluate the clinicopathologic characteristics and prognosis of patients with clinical stage IA lung adenocarcinoma with atypical solid nodules (ASNs) on thin-section CT images. Materials and Methods Data from patients with clinical stage IA lung adenocarcinoma who underwent resection between January 2005 and December 2012 were retrospectively reviewed. According to their manifestations on thin-section CT images, nodules were classified as ASNs, subsolid nodules (SSNs), and typical solid nodules (TSNs). The clinicopathologic characteristics of the ASNs were investigated, and the differences across the three groups were analyzed. The Kaplan-Meier method and multivariable Cox analysis were used to evaluate survival differences among patients with ASNs, SSNs, and TSNs. Results Of the 254 patients (median age, 58 years [IQR, 53-66]; 152 women) evaluated, 49 had ASNs, 123 had SSNs, and 82 had TSNs. Compared with patients with SSNs, those with ASNs were more likely to have nonsmall adenocarcinoma (P < .001), advanced-stage adenocarcinoma (P = .004), nonlepidic growth adenocarcinoma (P < .001), and middle- or low-grade differentiation tumors (P < .001). Compared with patients with TSNs, those with ASNs were more likely to have no lymph node involvement (P = .009) and epidermal growth factor receptor mutation positivity (P = .018). Average disease-free survival in patients with ASNs was significantly longer than that in patients with TSNs (P < .001) but was not distinguishable from that in patients with SSNs (P = .051). Conclusion ASNs were associated with better clinical outcomes than TSNs in patients with clinical stage IA lung adenocarcinoma. Keywords: Adenocarcinoma, Atypical Solid Nodules, CT, Disease-free Survival, Lung, Prognosis, Pulmonary Supplemental material is available for this article. Published under a CC BY 4.0 license.

Inhibiting Endothelial Cell-Mediated T Lymphocyte Apoptosis with Integrin-Targeting Peptide-Drug Conjugate Filaments for Chemoimmunotherapy of Triple-Negative Breast Cancer.

Tumor-associated endothelial cells (TECs) limit antitumor immunity via inducing apoptosis of infiltrating T lymphocytes through a Fas ligand (FasL) mediated mechanism. Herein, this work creates a peptide-drug conjugate (PDC) by linking 7-ethyl-10-hydroxycamptothecin (SN38) to hydrophilic segments with either RGDR or HKD motif at their C-terminus through a glutathione-responsive linker. The PDCs spontaneously assemble into filaments in aqueous solution. The PDC filaments containing 1% of SN38-RGDR (SN38-HKD/RGDR) effectively target triple-negative breast cancer (TNBC) cells and TECs with upregulated expression of integrin, and induce immunogenic cell death (ICD) of tumor cells and FasL downregulation of TECs. SN38-HKD/RGDR increases infiltration, activity, and viability of CD8+ T cells, and thus inhibits the growth of primary tumors and pulmonary metastasis. This study highlights the synergistic modulation of cancerous cells and TECs with integrin-targeting PDC filaments as a promising strategy for TNBC chemoimmunotherapy.

Development of an attenuated potato virus Y mutant carrying multiple mutations in helper-component protease for cross-protection.

Tobacco (Nicotiana tabacum) is one of the major cash crops in China. Potato virus Y (PVY), a representative member of the genus Potyvirus, greatly reduces the quality and yield of tobacco leaves by inducing veinal necrosis. Mild strain-mediated cross-protection is an attractive method of controlling diseases caused by PVY. Currently, there is a lack of effective and stable attenuated PVY mutants. Potyviral helper component-protease (HC-Pro) is a likely target for the development of mild strains. Our previous studies showed that the residues lysine at positions 124 and 182 (K124 and K182) in HC-Pro were involved in PVY virulence, and the conserved KITC motif in HC-Pro was involved in aphid transmission. In this study, to improve the stability of PVY mild strains, K at position 50 (K50) in KITC motif, K124, and K182 were separately substituted with glutamic acid (E), leucine (L), and arginine (R), resulting in a triple-mutant PVY-HCELR. The mutant PVY-HCELR had attenuated virulence and did not induce leaf veinal necrosis symptoms in tobacco plants and could not be transmitted by Myzus persicae. Furthermore, PVY-HCELR mutant was genetically stable after six serial passages, and only caused mild mosaic symptoms in tobacco plants even at 90 days post inoculation. The tobacco plants cross-protected by PVY-HCELR mutant showed high resistance to the wild-type PVY. This study showed that PVY-HCELR mutant was a promising mild mutant for cross-protection to control PVY.

Spatial Transcriptome-Wide Profiling of Small Cell Lung Cancer Reveals Intra-Tumoral Molecular and Subtype Heterogeneity.

Small cell lung cancer (SCLC) is a highly aggressive malignancy characterized by rapid growth and early metastasis and is susceptible to treatment resistance and recurrence. Understanding the intra-tumoral spatial heterogeneity in SCLC is crucial for improving patient outcomes and clinically relevant subtyping. In this study, a spatial whole transcriptome-wide analysis of 25 SCLC patients at sub-histological resolution using GeoMx Digital Spatial Profiling technology is performed. This analysis deciphered intra-tumoral multi-regional heterogeneity, characterized by distinct molecular profiles, biological functions, immune features, and molecular subtypes within spatially localized histological regions. Connections between different transcript-defined intra-tumoral phenotypes and their impact on patient survival and therapeutic response are also established. Finally, a gene signature, termed ITHtyper, based on the prevalence of intra-tumoral heterogeneity levels, which enables patient risk stratification from bulk RNA-seq profiles is identified. The prognostic value of ITHtyper is rigorously validated in independent multicenter patient cohorts. This study introduces a preliminary tumor-centric, regionally targeted spatial transcriptome resource that sheds light on previously unexplored intra-tumoral spatial heterogeneity in SCLC. These findings hold promise to improve tumor reclassification and facilitate the development of personalized treatments for SCLC patients.

Combination of miR159 Mimics and Irinotecan Utilizing Lipid Nanoparticles for Enhanced Treatment of Colorectal Cancer.

Colorectal cancer (CRC) ranks as the third most prevalent global malignancy, marked by significant metastasis and post-surgical recurrence, posing formidable challenges to treatment efficacy. The integration of oligonucleotides with chemotherapeutic drugs emerges as a promising strategy for synergistic CRC therapy. The nanoformulation, lipid nanoparticle (LNP), presents the capability to achieve co-delivery of oligonucleotides and chemotherapeutic drugs for cancer therapy. In this study, we constructed lipid nanoparticles, termed as LNP-I-V by microfluidics to co-deliver oligonucleotides miR159 mimics (VDX05001SI) and irinotecan (IRT), demonstrating effective treatment of CRC both in vitro and in vivo. The LNP-I-V exhibited a particle size of 118.67 ± 1.27 nm, ensuring excellent stability and targeting delivery to tumor tissues, where it was internalized and escaped from the endosome with a pH-sensitive profile. Ultimately, LNP-I-V significantly inhibited CRC growth, extended the survival of tumor-bearing mice, and displayed favorable safety profiles. Thus, LNP-I-V held promise as an innovative platform to combine gene therapy and chemotherapy for improving CRC treatment.

Histopathology images-based deep learning prediction of prognosis and therapeutic response in small cell lung cancer.

Small cell lung cancer (SCLC) is a highly aggressive subtype of lung cancer characterized by rapid tumor growth and early metastasis. Accurate prediction of prognosis and therapeutic response is crucial for optimizing treatment strategies and improving patient outcomes. In this study, we conducted a deep-learning analysis of Hematoxylin and Eosin (H&E) stained histopathological images using contrastive clustering and identified 50 intricate histomorphological phenotype clusters (HPCs) as pathomic features. We identified two of 50 HPCs with significant prognostic value and then integrated them into a pathomics signature (PathoSig) using the Cox regression model. PathoSig showed significant risk stratification for overall survival and disease-free survival and successfully identified patients who may benefit from postoperative or preoperative chemoradiotherapy. The predictive power of PathoSig was validated in independent multicenter cohorts. Furthermore, PathoSig can provide comprehensive prognostic information beyond the current TNM staging system and molecular subtyping. Overall, our study highlights the significant potential of utilizing histopathology images-based deep learning in improving prognostic predictions and evaluating therapeutic response in SCLC. PathoSig represents an effective tool that aids clinicians in making informed decisions and selecting personalized treatment strategies for SCLC patients.

Proposed novel grading system for stage I invasive lung adenocarcinoma and a comparison with the 2020 IASLC grading system.

BACKGROUND: Several studies have proposed grading systems for risk stratification of early-stage lung adenocarcinoma based on histological patterns. However, the reproducibility of these systems is poor in clinical practice, indicating the need to develop a new grading system which is easy to apply and has high accuracy in prognostic stratification of patients. METHODS: Patients with stage I invasive nonmucinous lung adenocarcinoma were retrospectively collected from pathology archives between 2009 and 2016. The patients were divided into a training and validation set at a 6:4 ratio. Histological features associated with patient outcomes (overall survival [OS] and progression-free survival [PFS]) identified in the training set were used to construct a new grading system. The newly proposed system was validated using the validation set. Survival differences between subgroups were assessed using the log-rank test. The prognostic performance of the novel grading system was compared with two previously proposed systems using the concordance index. RESULTS: A total of 539 patients were included in this study. Using a multioutcome decision tree model, four pathological factors, including the presence of tumor spread through air space (STAS) and the percentage of lepidic, micropapillary and solid subtype components, were selected for the proposed grading system. Patients were accordingly classified into three groups: low, medium, and high risk. The high-risk group showed a 5-year OS of 52.4% compared to 89.9% and 97.5% in the medium and low-risk groups, respectively. The 5-year PFS of patients in the high-risk group was 38.1% compared to 61.7% and 90.9% in the medium and low-risk groups, respectively. Similar results were observed in the subgroup analysis. Additionally, our proposed grading system provided superior prognostic stratification compared to the other two systems with a higher concordance index. CONCLUSION: The newly proposed grading system based on four pathological factors (presence of STAS, and percentage of lepidic, micropapillary, and solid subtypes) exhibits high accuracy and good reproducibility in the prognostic stratification of stage I lung adenocarcinoma patients.

Pathological response and tumor stroma immunogenic features predict long-term survival in non-small cell lung cancer after neoadjuvant chemotherapy.

PURPOSE: Major pathological response (MPR) has become a surrogate endpoint for overall survival (OS) in non-small cell lung cancer (NSCLC) after neoadjuvant therapy, however, the prognostic histologic features and optimal N descriptor after neoadjuvant therapy are poorly defined. METHODS: We retrospectively analyzed data from 368 NSCLC patients who underwent surgery after neoadjuvant chemotherapy (NAC) from January 2010 to December 2020. The percentage of residual viable tumors in the primary tumor, lymph nodes (LN), and inflammation components within the tumor stroma were comprehensively reviewed. The primary endpoint was OS. RESULTS: Of the 368 enrolled patients, 12.0% (44/368) achieved MPR in the primary tumor, which was associated with significantly better OS (HR, 0.36 0.17-0.77, p = 0.008) and DFS (HR = 0.59, 0.36-0.92, p = 0.038). In patients who did not have an MPR, we identified an immune-activated phenotype in primary tumors, characterized by intense tumor-infiltrating lymphocyte or multinucleated giant cell infiltration, that was associated with similar OS and DFS as patients who had MPR. Neoadjuvant pathologic grade (NPG), consisting of MPR and immune-activated phenotype, identified 30.7% (113/368) patients that derived significant OS (HR 0.28, 0.17-0.46, p < 0.001) and DFS (HR 0.44, 0.31-0.61, p < 0.001) benefit from NAC. Moreover, the combination of NPG and the number of positive LN stations (nS) in the multivariate analysis had a higher C-index (0.711 vs. 0.663, p < 0.001) than the ypTNM Stage when examining OS. CONCLUSION: NPG integrated with nS can provide a simple, practical, and robust approach that may allow for better stratification of patients when evaluating neoadjuvant chemotherapy in clinical practice.

MR radiomics predicts pathological complete response of esophageal squamous cell carcinoma after neoadjuvant chemoradiotherapy: a multicenter study.

BACKGROUND: More than 40% of patients with resectable esophageal squamous cell cancer (ESCC) achieve pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT), who have favorable prognosis and may benefit from an organ-preservation strategy. Our study aims to develop and validate a machine learning model based on MR radiomics to accurately predict the pCR of ESCC patients after nCRT. METHODS: In this retrospective multicenter study, eligible patients with ESCC who underwent baseline MR (T2-weighted imaging) and nCRT plus surgery were enrolled between September 2014 and September 2022 at institution 1 (training set) and between December 2017 and August 2021 at institution 2 (testing set). Models were constructed using machine learning algorithms based on clinical factors and MR radiomics to predict pCR after nCRT. The area under the curve (AUC) and cutoff analysis were used to evaluate model performance. RESULTS: A total of 155 patients were enrolled in this study, 82 in the training set and 73 in the testing set. The radiomics model was constructed based on two radiomics features, achieving AUCs of 0.968 (95%CI 0.933-0.992) in the training set and 0.885 (95%CI 0.800-0.958) in the testing set. The cutoff analysis resulted in an accuracy of 82.2% (95%CI 72.6-90.4%), a sensitivity of 75.0% (95%CI 58.3-91.7%), and a specificity of 85.7% (95%CI 75.5-96.0%) in the testing set. CONCLUSION: A machine learning model based on MR radiomics was developed and validated to accurately predict pCR after nCRT in patients with ESCC.

Breaking Tumor Immunosuppressive Network by Regulating Multiple Nodes with Triadic Drug Delivery Nanoparticles.

Inside the tumor microenvironment, a complicated immunosuppressive network is constituted by tumor cells and suppressive immune cells as its nodes, including myeloid-derived suppressor cells (MDSCs), tumor-associated macrophages (TAMs), and regulatory T cells, which have mutual promotion on each other and superimposed inhibition on natural killer (NK) cells and cytotoxic T cells. Breaking the whole balance of this web is critical to tumor immunotherapy since modulation on a single node may be diluted by other factors in the network. To achieve multifaceted regulation on antitumor immunity against triple-negative breast cancer, in this work, a micelle, termed BEM, co-delivering the MDSC inhibitor, entinostat (ENT), and the immune checkpoint inhibitor, BMS-1, was constructed with pH-sensitive amphiphilic poly(ß-amino ester) derivatives. Then, BEM and the scavenger receptor A (SR-A) ligand dextran sulfate (DXS) formed a negatively charged nanoparticle (BEN). DXS detached from BEN in the weakly acidic tumor microenvironment and blocked SR-A on TAMs, reprogramming TAMs toward the M1 type. The positively charged BEM with facilitated intratumoral penetration and cellular uptake dissociated in the lysosomes, accompanied by the release of ENT and BMS-1 to suppress MDSCs and block the programmed cell death protein (PD)-1/PD-ligand 1 pathway, respectively. As a result, NK cells and CD8+ T cells in tumors were increased, as were their effector cytokines. The activated innate and adaptive antitumor immune responses suppressed the growth and metastasis of tumors and prolonged survival of 4T1 tumor-bearing mice. BEN provides a reliable approach for improving cancer immunotherapy by destroying the immunosuppression web in tumors via multinode regulation.

Explainable survival analysis with uncertainty using convolution-involved vision transformer.

Image-based precision medicine research is able to help doctors make better decisions on treatments. Among all kinds of medical images, a special form is called Whole Slide Image (WSI), which is used for diagnosing patients with cancer, aiming to enable more accurate survival prediction with its high resolution. However, One unique challenge of the WSI-based prediction models is processing the gigabyte-size or even terabyte-size WSIs, which would make most models computationally infeasible. Although existing models mostly use a pre-selected subset of key patches or patch clusters as input, they might discard some important morphology information, making the prediction inferior. Another challenge is improving the prediction models' explainability, which is crucial to help doctors understand the predictions given by the models and make faithful decisions with high confidence. To address the above two challenges, in this work, we propose a novel explainable survival prediction model based on Vision Transformer. Specifically, we adopt dual-channel convolutional layers to utilize the complete WSIs for more accurate predictions. We also introduce the aleatoric uncertainty into our model to understand its limitation and avoid overconfidence in using the prediction results. Additionally, we present a post-hoc explainable method to identify the most salient patches and distinct morphology features as supporting evidence for predictions. Evaluations of two large cancer datasets show that our proposed model is able to make survival predictions more effectively and has better explainability for cancer diagnosis.

Clinical significance of ALDH1A1 expression and its association with E-cadherin and N-cadherin in resected large cell neuroendocrine carcinoma.

BACKGROUND: The roles of cancer stem cells (CSCs) and epithelial-mesenchymal transition (EMT) in solid tumors are well established. However, the interaction between CSCs and EMT in pulmonary large cell neuroendocrine carcinoma (LCNEC) remains unknown. The aim of this study was to investigate the expression and clinical significance of a CSC marker (ALDH1A1) and its correlation with Epithelial-like phenotype marker (E-cadherin) and Mesenchymal-like phenotype marker (N-cadherin) in LCNEC patients. METHODS: Immunohistochemistry (IHC) for ALDH1A1, E-cadherin and N-cadherin expression was conducted on tissue microarrays made from 79 resected LCNEC patient samples. ALDH1A1 protein expression was evaluated by the IHC score, and its correlations with the expression of E-cadherin, N-cadherin and clinicopathological features were determined based on IHC data. Survival analyses were also performed. RESULTS: ALDH1A1 was positively expressed in 75.9% (60/79 cases) of LCNEC patients. No significant difference in clinicopathological variables was observed between the ALDH1A1-negative and ALDH1A1-positive groups. However, ALDH1A1 expression was positively correlated with E-cadherin (Spearman's rho = 0.229, p-value = 0.007), which represents the epithelial-like phenotype, but not with N-cadherin. Patients with expression of ALDH1A1 had significantly longer disease-free survival (DFS) and overall survival (OS) than those who were ALDH1A1 negative (median DFS: 52 vs 12 months, p = 0.028; median OS: not reached; p = 0.027). Multivariate analysis showed that ALDH1A1 was an independent favorable prognostic factor for DFS (p = 0.032, HR: 0.438, 95% CI: 0.206-0.932) and OS (p = 0.025, HR: 0.279, 95% CI: 0.091-0.852) in LCNEC patients. CONCLUSION: This study suggests that ALDH1A1 can act as a favorable independent prognostic factor for LCNEC, which related to the epithelioid phenotype in EMT, and its internal mechanism needs further study.

ASCL1 and DLL3 expressions and their clinicopathological implications in surgically resected pure small cell lung cancer: A study of 247 cases from the National Cancer Center of China.

OBJECTIVE: Small cell lung cancer (SCLC) is one of the most aggressive malignancies characterized by neuroendocrine (NE) differentiation. The Delta-like protein 3 (DLL3), as a direct downstream target of ASCL1, is involved in NE differentiation and carcinogenesis of SCLC. This study aims to investigate the relationship between ASCL1 and DLL3 expressions and their clinicopathological implications in SCLC. METHODS: A total of 247 surgically resected pure SCLC samples with limited clinical stage and follow-up data were retrieved in this retrospective study. ASCL1 and DLL3 protein expression was detected by immunohistochemistry staining. The correlations between ASCL1 and DLL3 expressions, as well as their clinicopathological features, were analyzed by χ2 tests. Disease-free survival (DFS) and overall survival (OS) in SCLC patients with ASCL1/DLL3 low and high expressions were compared by the Kaplan-Meier method and log-rank tests. RESULTS: ASCL1 high expression was detected in 105 (42.5%) patients. Its expression was positively correlated with the clinical stage (p = 0.02) and nerve invasion (p = 0.03). DLL3 high expression was observed in 188 (72.8%) patients and was correlated with vascular invasion (p = 0.04). ASCL1 expression was positively associated with DLL3 expression (p = 0.03). In addition, DLL3 expression has a strong correlation with the expression of thyroid transcription factor-1 (TTF1) and conventional NE markers. CONCLUSION: ASCL1 and DLL3 were highly expressed in SCLC tumor samples, and a positive correlation between these two markers was observed. Co-analysis of ASCL1 and DLL3 may identify a distinct SCLC subgroup benefit from targeted therapy. Therefore, ASCL1 and DLL3 could be potential biomarkers served for the selection of related patients.

Micronodular thymoma with lymphoid stroma: Contrast-enhanced CT features with histopathological correlation in 10 patients.

Objectives: This study aimed to evaluate and summarize the contrast-enhanced computed tomography (CECT) imaging features of micronodular thymoma with lymphoid stroma (MTWLS) based on all MTWLS patients at our institution and was the first imaging study of MTWLS worldwide. Methods: This retrospective study included 10 MTWLS patients who underwent CECT between April 2012 and November 2021. We collected and analyzed the CECT imaging features, including the location, size, shape, tumor density, classification, and CT value of the solid component. Descriptive statistical analysis was performed using the SPSS software (version 26.0; IBM). Results: Ten patients (five males [50%], five females [50%]; median age, 61.4 years; range, 54-72 years) underwent CECT. Of the 10 cases, one case was purely cystic, seven cases were cystic-solid, and two cases were purely solid. Six cases were round/oval in shape, and four cases were irregularly shaped. Excluding a purely cystic tumor with an unmeasurable degree of enhancement, two cases showed moderate enhancement, and seven cases showed significant enhancement. Among the solid or cystic-solid cases, the mean CT value of the measurable solid component on the enhanced scan was 93.9 HU. Nine masses were located adjacent to the mediastinal pleura, pericardium, or large vessels. Additionally, there were no malignant tumor signs in any patient, including penetration of the mediastinal pleura or involvement of the pericardium, pleural effusion, elevation of the diaphragm, or direct vascular invasion. Conclusion: MTWLS demonstrates certain features on CECT, such as a high rate of cystic change, significant solid component enhancement, and no malignant, invasive imaging features. These CECT features are helpful for diagnosing MTWLS.

Prognostic significance of YAP1 expression and its association with neuroendocrine markers in resected pulmonary large cell neuroendocrine carcinoma (LCNEC).

BACKGROUND: YAP1 (Yes-associated protein 1), an important effector of the Hippo pathway, acts as an oncogene and is overexpressed in various malignant tumors. However, the function and expression pattern of YAP1 in pulmonary large cell neuroendocrine carcinoma (LCNEC) have not been systematically established. This study aimed to explore the relationship between YAP1 expression and neuroendocrine differentiation markers and their prognostic significance in LCNEC. MATERIALS AND METHODS: YAP1 protein and neuroendocrine markers (INSM1, NeuroD1 and DLL3) expression were examined by immunohistochemical (IHC) staining in 80 resected pulmonary LCNEC cases. The possible association between these markers and clinicopathological features was evaluated and survival analyses were performed. RESULTS: YAP1 was highly expressed in 25% LCNECs (20/80) , especially at a relatively higher T stage (p = 0.015). YAP1 expression was negatively correlated with INSM1 (χ2=11.53, p = 0.001) and DLL3(χ2=8.55, p = 0.004), but not with NeuroD1 (p = 0.482). For survival analyses, YAP1 expression was associated with worse disease-free survival (DFS) and overall survival (OS) (median DFS: 13 months vs. not reached (NR), p = 0.0096; median OS: not reached, NR vs. NR, p = 0.038), and was an unfavorable prognostic factor for DFS (HR:3.285; 95%CI: 1.526-7.071, p = 0.002) and OS (HR: 2.864, 95% CI: 0.932-8.796, p = 0.066). CONCLUSIONS: YAP1 was found to be conversely correlated with neuroendocrine markers and a prognostic factor for worse survival in resected LCNEC patients, and mechanisms need to be further investigated.

Pooled analysis of efficacy and safety of ureteral stent removal using an extraction string.

OBJECTIVE: We conducted a Pooled analysis to investigate the efficacy and safety of ureteral stent removal using an extraction string. METHODS: A systematic review was performed by using the Preferred Reporting Items for Systematic Reviews and Pooled analyses. The sources including EMBASE, MEDLINE, and the Cochrane Controlled Trials Register were retrieved to gather randomized controlled trials of ureteral stent removal using an extraction string. The reference of included literature was also searched. RESULTS: Four randomized controlled trials containing a amount of 471 patients were involved in the analysis. We found that the ureteral stent removal using an extraction string group had a greater decrease of visual analog scale (VAS) (Mean difference (MD) -1.40, 95% confidence interval (CI) -1.99 to -0.81, P < .00001) compared with the no string group. The string group did not show a significant differences in Ureteric Stent Symptom Questionnaire (USSQ) (P = .15), general health (P = .77), stent dwell time (P = .06), and urinary tract infection (UTI) (P = .59) with exception of stent dislodgement (Odds Ratio (OR) 10.36, 95% CI 2.40 to 44.77, P = .002) compared with the no string group. CONCLUSIONS: Ureteral stent removal by string significantly provides less pain than those by cystoscope for patients without increasing stent-related urinary symptoms or UTI. However, this must be balanced against a risk of stent dislodgement and, hence, may not be a good option in all patients.

Efficacy and Adverse Events Associated With Use of OnabotulinumtoxinA for Treatment of Neurogenic Detrusor Overactivity: A Meta-Analysis.

PURPOSE: OnabotulinumtoxinA is used widely for the treatment of neurogenic detrusor overactivity. We conducted a systematic review and meta-analysis to assess its efficacy and safety for neurogenic detrusor overactivity treatment. METHODS: A systematic literature review was performed to identify all published randomized double-blind, placebo-controlled trials of onabotulinumtoxinA for neurogenic detrusor overactivity treatment. MEDLINE, Embase, and the CENTRAL were employed. Reference lists of retrieved studies were reviewed carefully. RESULTS: Six publications involving 871 patients, which compared onabotulinumtoxinA with a placebo were analyzed. Efficacy of onabotulinumtoxinA treatment was shown as a reduction of the mean number of urinary incontinence episodes per day (mean difference, -1.41; 95% confidence interval [CI], -1.70 to -1.12; P<0.00001), maximum cystometric capacity (135.48; 95% CI, 118.22-152.75; P<0.00001), and maximum detrusor pressure (-32.98; 95% CI, -37.33 to -28.62; P<0.00001). Assessment of adverse events revealed that complications due to onabotulinumtoxinA injection were localized primarily to the urinary tract. CONCLUSIONS: This meta-analysis suggests that onabotulinumtoxinA is an effective treatment for neurogenic detrusor overactivity with localized advent events.

Primary bone lymphoma: A case report and review of the literature.

Primary lymphoma of the bone (PLB) primarily arising from the medullary cavity is an extremely rare entity, with only retrospective studies and sporadic cases reported in the literature. The current study presents one case of PLB treated with chemotherapy and radiotherapy, and a review of the literature to elucidate the optimal treatment of PLB. A 73-year-old female presented with pain in the left hip that had persisted for two months. Plain X-ray and magnetic resonance imaging of the left hip showed lytic areas involving the left innominatum. Technetium-99m radionuclide imaging showed increased tracer uptake in the ilium, acetabulum and ischium. An 18F-fluorodeoxyglucose-positron emission tomography-computed tomography (FDG-PET-CT) scan showed high FDG uptake. A fine-needle aspiration biopsy of the lesion was performed, and histopathological and immunohistochemical examination confirmed a diagnosis of B-cell lymphoma. The patient received radiation therapy followed by six cycles of CHOP regimen (1,000 mg cyclophosphamide, 80 mg epirubicine and 2 mg vincristine on day one, and 100 mg prednisone on days one to five, every three weeks) and achieved a complete response, as confirmed by FDG-PET-CT. At present, the patient is in a good condition. This case is noteworthy, as it is a well-documented case in which the patient received successful treatment. This case demonstrates that PLB has an improved prognosis compared with primary lymphoma of other sites; however, combined therapy may further improve the patient outcome.