An Introduction to Survival Statistics: Kaplan-Meier Analysis

A Comprehensive Pan-Cancer Analysis Reveals Cyclin-Dependent Kinase Inhibitor 2A Gene as a Potential Diagnostic and Prognostic Biomarker in Colon Adenocarcinoma

Introduction Cyclin-dependent kinase inhibitor 2A (CDKN2A) is a suppressor carcinogenic gene that is upregulated across various types of cancer including breast, liver, thyroid, and bile duct cancer due to its crucial role in cell cycle regulation and cell division. Nevertheless, it is mostly investigated at the genetic level, but it is still poorly studied on pan-cancer analysis as a biomarker and this study shows its significant potential diagnostic and prognostic characteristics. However, this study aims to investigate the role of CDKN2A as a diagnostic and prognostic biomarker across various types of cancer focusing primarily on colon adenocarcinoma (COAD). Methods We investigated CDKN2A gene expression in a pan-cancer analysis across different types of cancer to show its diagnostic potential characteristics by using various bioinformatic tools, including Tumor Immune Estimation Resource (TIMER) 2.0, Gene Expression Profiling Interactive Analysis (GEPIA), and University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN) database. TIMER was used to profile gene expression across 32 types of cancer composed of 10,000 RNA-seq samples obtained from the Cancer Genome Atlas (TCGA) and to analyze the tumor-infiltrating immune cells. In addition, GEPIA and UALCAN were further used to analyze gene expression, in terms of gene regulation, pathological stages, and clinical parameters, including gender, age, and race. Therefore, we used GEPIA, UALCAN, and Kaplan-Meier plotter particularly across adenocarcinoma to investigate CDKN2A prognosis by studying its high expression association with the patient's overall survival rate to show the tumor progression. Then, we looked into the genetic alteration of CDKN2A by using the cBio Cancer Genomics Portal (cBioPortal), including 10 pan-cancer studies. We concluded the analysis with gene validation by using a public cohort in Gene Expression Omnibus (GEO). Results CDKN2A showed a trend of upregulation in most cancers and it was significantly upregulated in five cancers, which were commonly identifiable in three databases, including breast invasive carcinoma (p < 0.001), kidney chromophobe (p < 0.001), kidney renal clear cell carcinoma (p < 0.001), kidney renal papillary cell carcinoma (p < 0.001), and COAD (p < 0.001). The upregulation was significantly different in association with pathogenic stages II and III (pr(>F) = 0.00234) which was identifiable significantly in COAD more than in other cancers. The gene showed a high upregulation in association with poor prognosis of patient survival in three cancers, including COAD (log-rank p = 0.011), mesothelioma (log-rank p = 5.9e-07), and liver hepatocellular carcinoma (log-rank p = 0.0045). Therefore, COAD was the only comprehensively analyzed tumor to show a diagnostic and prognostic potential characteristic during high upregulation of CDKN2A. Furthermore, CDKN2A displayed a rare mutation in the form of deep deletion (9%) and revealed an upregulation associated with CD4+ T cells (p = 0.0108), macrophage (p = 0.0073), and neutrophils (p = 0.0272) as immune cells infiltrating COAD.  Conclusion Our study demonstrates the pan-cancer relevance of CDKN2A and revealed a novelty in showing CDKN2A underscores its potential as a diagnostic prognostic biomarker in COAD since CDKN2A is mostly studied at a genetic level across COAD.

The low survival rate of European hare leverets in arable farmland: evidence from the predation experiment

The low survival rate of leverets may significantly contribute to steep population declines and slow recovery of European hares (Lepus europaeus). However, the leveret survival rate in farmlands with different landscape structures is poorly understood, and the existing evidence comes mainly from Western Europe. In this study, we explored the survival of leveret hare dummies along linear semi-natural habitats in homogeneous Central European arable farmland during the main part of the European hare reproduction period (March-April) in 2019 and 2020. The survival rate of hare leverets during the 14-day period was only 22.2%, and all predation events were recorded during the first six days of the experiment. Mammalian predators were responsible for 53.1% of predation events, avian predators for 40.8%, and agricultural operations for 6.1%. The red fox (Vulpes vulpes) was the dominant predator in our study area and was the primary cause of leveret dummy mortality (32.7%), but it also had the highest use-intensity and visit frequency of all of the study plots. Predation by avian predators was associated with patches of lower vegetation height and cover (such as plowed fields) and during daylight hours, whereas the opposite was true for mammalian predators. We propose that improving the habitat quality of arable landscapes by increasing the proportion and quality of extensively used non-farmed habitats (e.g., set-asides, wildflower areas, extensive meadows, fallow land, and semi-natural habitats on arable land) providing cover and shelter for leverets could be an effective management measure for reducing predation risk on leverets.

Factors Impacting Survival After Transarterial Radioembolization in Patients with Unresectable Intrahepatic Cholangiocarcinoma: A Combined Analysis of the Prospective CIRT Studies

PURPOSE

Transarterial radioembolization (TARE) with Yttrium-90 resin microspheres is a treatment option for patients with intrahepatic cholangiocarcinoma (ICC). However, optimising the timing of TARE in relation to systemic therapies and patient selection remains challenging. We report here on the effectiveness, safety, and prognostic factors associated with TARE for ICC in a combined analysis of the prospective observational CIRT studies (NCT02305459 and NCT03256994).

METHODS

A combined analysis of 174 unresectable ICC patients enrolled between 2015 and 2020 was performed. Patient characteristics and treatment-related data were collected at baseline; adverse events and time-to-event data (overall survival [OS], progression-free survival [PFS] and hepatic PFS) were collected at every follow-up visit. Log-rank tests and a multivariable Cox proportional hazard model were used to identify prognostic factors.

RESULTS

Patients receiving a first-line strategy of TARE in addition to any systemic treatment had a median OS and PFS of 32.5 months and 11.3 months. Patients selected for first-line TARE alone showed a median OS and PFS of 16.2 months and 7.4 months, whereas TARE as 2nd or further treatment-line resulted in a median OS and PFS of 12 and 9.3 months (p = 0.0028), and 5.1 and 3.5 months (p = 0.0012), respectively. Partition model dosimetry was an independent predictor for better OS (HR 0.59 [95% CI 0.37-0.94], p = 0.0259). No extrahepatic disease, no ascites, and < 6.1 months from diagnosis to treatment were independent predictors for longer PFS.

CONCLUSION

This combined analysis indicates that in unresectable ICC, TARE in combination with any systemic treatment is a promising treatment option.

LEVEL OF EVIDENCE

level 3, Prospective observational.

Deep learning in ovarian cancer diagnosis: a comprehensive review of various imaging modalities

Ovarian cancer poses a major worldwide health issue, marked by high death rates and a deficiency in reliable diagnostic methods. The precise and prompt detection of ovarian cancer holds great importance in advancing patient outcomes and determining suitable treatment plans. Medical imaging techniques are vital in diagnosing ovarian cancer, but achieving accurate diagnoses remains challenging. Deep learning (DL), particularly convolutional neural networks (CNNs), has emerged as a promising solution to improve the accuracy of ovarian cancer detection. This systematic review explores the role of DL in improving the diagnostic accuracy for ovarian cancer. The methodology involved the establishment of research questions, inclusion and exclusion criteria, and a comprehensive search strategy across relevant databases. The selected studies focused on DL techniques applied to ovarian cancer diagnosis using medical imaging modalities, as well as tumour differentiation and radiomics. Data extraction, analysis, and synthesis were performed to summarize the characteristics and findings of the selected studies. The review emphasizes the potential of DL in enhancing the diagnosis of ovarian cancer by accelerating the diagnostic process and offering more precise and efficient solutions. DL models have demonstrated their effectiveness in categorizing ovarian tissues and achieving comparable diagnostic performance to that of experienced radiologists. The integration of DL into ovarian cancer diagnosis holds the promise of improving patient outcomes, refining treatment approaches, and supporting well-informed decision-making. Nevertheless, additional research and validation are necessary to ensure the dependability and applicability of DL models in everyday clinical settings.

Deep Learning Can Predict Bevacizumab Therapeutic Effect and Microsatellite Instability Directly from Histology in Epithelial Ovarian Cancer

Epithelial ovarian cancer (EOC) remains a significant cause of mortality among gynecologic cancers, with the majority of cases being diagnosed at an advanced stage. Before targeted therapies were available, EOC treatment relied largely on debulking surgery and platinum-based chemotherapy. Vascular endothelial growth factors have been identified as inducing tumor angiogenesis. According to several clinical trials, anti-vascular endothelial growth factor-targeted therapy with bevacizumab was effective in all phases of EOC treatment. However, there are currently no biomarkers accessible for regular therapeutic use despite the importance of patient selection. Microsatellite instability (MSI), caused by a deficiency of the DNA mismatch repair system, is a molecular abnormality observed in EOC associated with Lynch syndrome. Recent evidence suggests that angiogenesis and MSI are interconnected. Developing predictive biomarkers, which enable the selection of patients who might benefit from bevacizumab-targeted therapy or immunotherapy, is critical for realizing personalized precision medicine. In this study, we developed 2 improved deep learning methods that eliminate the need for laborious detailed image-wise annotations by pathologists and compared them with 3 state-of-the-art methods to not only predict the efficacy of bevacizumab in patients with EOC using mismatch repair protein immunostained tissue microarrays but also predict MSI status directly from histopathologic images. In prediction of therapeutic outcomes, the 2 proposed methods achieved excellent performance by obtaining the highest mean sensitivity and specificity score using MSH2 or MSH6 markers and outperformed 3 state-of-the-art deep learning methods. Moreover, both statistical analysis results, using Cox proportional hazards model analysis and Kaplan-Meier progression-free survival analysis, confirm that the 2 proposed methods successfully differentiate patients with positive therapeutic effects and lower cancer recurrence rates from patients experiencing disease progression after treatment (P < .01). In prediction of MSI status directly from histopathology images, our proposed method also achieved a decent performance in terms of mean sensitivity and specificity score even for imbalanced data sets for both internal validation using tissue microarrays from the local hospital and external validation using whole section slides from The Cancer Genome Atlas archive.

Effect of bone density on the survival of 407 sandblasted and acid-etched dental implants: A retrospective multicenter study

Background

This study evaluated the success and survival rate of sandblasted and acid-etched dental implants according to the patient's bone quality.

Methods

A multicenter retrospective study was conducted in five clinical centers between 2016 and March 2019. A total of 407 implants (KONTACTTM S, Biotech Dental, France) placed in 229 patients (61.5±12.9 years old) were included. Bone quality, classified as types D1 to D4 (Misch classification), maximal insertion torque, and bone loss were measured. The implant survival rate was evaluated after one year for the overall cohort and for each bone quality. The overall survival rate after four years was also estimated with a Kaplan-Meier analysis.

Results

After one year (12.8±9.6 months), eight implants were lost out of 407, representing an overall survival rate of 98%. It ranged from 100% for D1 to 89.7% for D4 (n=39), with significantly higher survival rates for D2 (n=93) and D3 (n=165) (98.9% and 98.2%, respectively) compared to D4. According to the Kaplan-Meier analysis, an overall survival rate of 96.5% was estimated after four years. An average maximal insertion torque of 45±12.6 N.cm and bone loss of 0.2±1.2 mm were measured.

Conclusion

The high overall survival rate (98%), the average maximal insertion torque (45 N.cm), and the low marginal bone loss indicated good clinical results with acid-etched implants. Despite the relatively high survival rate for each bone quality, the significantly lower results in the D4 group highlight the expected benefits of bone quality-based implants and surgical protocols.

Identification, characterization, and prognosis investigation of pivotal genes shared in different stages of breast cancer

One of the leading causes of death (20.1 per 100,000 women per year), breast cancer is the most prevalent cancer in females. Statistically, 95% of breast cancer are categorized as adenocarcinomas, and 55% of all patients may go into invasive phases; however, it can be successfully treated in approximately 70-80% of cases if diagnosed in the nascent stages. The emergence of breast tumor cells which are intensely resistant to conventional therapies, along with the high rate of metastasis occurrence, has highlighted the importance of finding novel strategies and treatments. One of the most advantageous schemes to alleviate this complication is to identify the common differentially expressed genes (DEGs) among primary and metastatic cancerous cells to use resultants for designing new therapeutic agents which are able to target both primary and metastatic breast tumor cells. In this study, the gene expression dataset with accession number GSE55715 was analyzed containing two primary tumor samples, three bone-metastatic samples, and three normal samples to distinguish the up- and down regulated genes in each stage compared to normal cells as control. In the next step, the common upregulated genes between the two experimental groups were detected by Venny online tool. Moreover, gene ontology, functions and pathways, gene-targeting microRNA, and influential metabolites were determined using EnrichR 2021 GO, KEGG pathways miRTarbase 2017, and HMDB 2021, respectively. Furthermore, elicited from STRING protein-protein interaction networks were imported to Cytoscape software to identify the hub genes. Then, identified hub genes were checked to validate the study using oncological databases. The results of the present article disclosed 1263 critical common DEGs (573 upregulated + 690 downregulated), including 35 hub genes that can be broadly used as new targets for cancer treatment and as biomarkers for cancer detection by evaluation of expression level. Besides, this study opens a new horizon to reveal unknown aspects of cancer signaling pathways by providing raw data evoked from in silico experiments. This study's outcomes can also be widely utilized in further lab research since it contains diverse information on common DEGs of varied stages and metastases of breast cancer, their functions, structures, interactions, and associations.

Survival analysis of implants after surgical treatment of peri-implantitis based on bone loss severity and surgical technique: a retrospective study

BACKGROUND

Few trials have compared the results of surgical treatment for peri-implantitis based on severity of peri-implantitis and surgical method. This study investigated the survival rate of implants based on type of surgical method used and initial severity of peri-implantitis. Classification of severity was determined based on bone loss rate relative to fixture length.

METHODS

Medical records of patients who underwent peri-implantitis surgery from July 2003 to April 2021 were identified. Classification of peri-implantitis was divided into 3 groups (stage 1: bone loss < 25% (of fixture length), stage 2: 25% < bone loss < 50%, stage 3: bone loss > 50%) and performance of resective or regenerative surgery was investigated. Kaplan-Meier survival curves and Cox hazards proportional models were used to analyze the cumulative survival rate of implants. Median survival time, predicted mean survival time, hazard ratio (HR), and 95% confidence interval (CI) were calculated.

RESULTS

Based on Kaplan-Meier analysis, 89 patients and 227 implants were included, and total median postoperative survival duration was 8.96 years. Cumulative survival rates for stage 1, 2, and 3 were 70.7%, 48.9%, and 21.3%, respectively. The mean survival time for implants in stage 1, 2, and 3 was 9.95 years, 7.96 years, and 5.67 years, respectively, with statistically significant difference (log-rank p-value < 0.001). HRs for stage 2 and stage 3 were 2.25 and 4.59, respectively, with stage 1 as reference. Significant difference was not found in survival time between resective and regenerative surgery groups in any peri-implantitis stage.

CONCLUSIONS

The initial bone loss rate relative to the fixture length significantly correlated with the outcome after peri-implantitis surgery, demonstrating a notable difference in the long-term survival rate. Difference was not found between resective surgery and regenerative surgery in implant survival time. Bone loss rate could be utilized as a reliable diagnostic tool for evaluating prognosis after surgical treatment, regardless of surgical method used.

TRIAL REGISTRATION

Retrospectively registered. (KCT0008225).

Association between dietary intake networks identified through a Gaussian graphical model and the risk of cancer: a prospective cohort study

PURPOSE

In this study, we aimed to investigate the association between dietary communities identified by a Gaussian graphical model (GGM) and cancer risk.

METHODS

We performed GGM to identify the dietary communities in a Korean population. GGM-derived communities were then scored and investigated for their association with cancer incidence in the entire population as well as in the 1:1 age- and sex-matched subgroup using a Cox proportional hazards model. In the sensitivity analysis, GGM-derived communities were compared to dietary patterns (DPs) that were identified by principal component analysis (PCA) and reduced rank regression (RRR).

RESULTS

During a median time to follow-up of 6.6 years, 397 cancer cases were newly diagnosed. The GGM identified 17 and 16 dietary communities for the total and matched populations, respectively. For each one-unit increase in the standard deviation of the community-specific score of the community that was composed of dairy products and bread, there was a reduced risk of cancer according to the fully adjusted model (HR: 0.80, 95% CI: 0.66-0.96). In the matched population, the third tertile of the community-specific score of the community composed of poultry, seafood, bread, cakes and sweets, and meat by-products showed a significantly reduced risk of cancer compared to that of the lowest tertile in the fully adjusted model (HR: 0.66, 95% CI: 0.50-0.86, p-trend = 0.002).

CONCLUSION

We found that the GGM-identified community composed of dairy products and bread showed a reduced risk of cancer. Further population-based prospective studies should be conducted to examine possible associations of dietary intake and specific cancer types.

Service Innovation and Quality Assessment of Industry 4.0 Microservice through Data Modeling and System Simulation Evaluation Approaches

This study proposes a system construction approach under Industry 4.0 infrastructure that is validated by the proposed framework of microservice quality assessment with framework with data modeling and simulation methodology to achieve innovation and value cocreation goals. The framework, which combines a dynamic process flow with service-dominant logic design and reliability assessment using a multilayer perceptron (MLP) prediction model can assist decision makers in optimizing their service innovation and decision-making processes. The service innovation and evaluation approaches have implications for optimizing the corporation cooperation. The corporation can form a much more comprehensive manufacturing infrastructure or system by considering the requirements and assessment results of third parties. To help the corporation redefine its value proposition and system structure, we must examine the system interaction between different hierarchical layers within the Industry 4.0 system infrastructure. This study used a production dataset from the NASDAQ-listed electronics corporation and two top German and Japanese automobile firms. The proposed system framework had already been validated and introduced to improve 12% of service quality. The system integrated with anticipated functions will accelerate service innovation and optimization by combining MLP and Kaplan–Meier estimation methodologies by extracting the characteristics of realistic datasets.

Associations of APOE Gene Variants rs429358 and rs7412 with Parameters of the Blood Lipid Profile and the Risk of Myocardial Infarction and Death in a White Population of Western Siberia

The present study aimed to analyze possible associations of rs7412 and rs429358 of the APOE gene with lipid profile parameters, the risk of myocardial infarction, and death in the mostly white population of Western Siberia (Russia). The study population was selected from a sample surveyed within the framework of the Health, Alcohol and Psychosocial Factors In Eastern Europe (HAPIEE) study (9360 subjects, age 53.8 ± 7.0 years, males/females 50/50). PCR was conducted with fluorescence detection according to the TaqMan principle on a real-time PCR machine. The frequency of a minor allele (C) of rs429358 was 0.13, and the frequency of a minor allele (T) of rs7412 was 0.09. In our study, the woman with the rare ɛ1/ɛ4 genotype had substantial aberrations in blood lipid levels. In Kaplan–Meier curves, statistically significant differences were revealed in the prognosis of survival within the subgroup of females who had a myocardial infarction (p = 0.0006): the prognosis was worse for carriers of the ɛ2/ɛ2 genotype and for ɛ4/ɛ4 carriers. Survival analysis regarding deaths from all causes showed (p = 0.0238) that female carriers of the ɛ2/ɛ4 genotype had a worse prognosis than did carriers of other genotypes. Thus, in the population of Western Siberia (Russia), we confirmed statistically significant associations between rs7412 & rs429358 genotypes and lipid profile parameters.

A Weakly Supervised Deep Learning Method for Guiding Ovarian Cancer Treatment and Identifying an Effective Biomarker

Ovarian cancer is a common malignant gynecological disease. Molecular target therapy, i.e., antiangiogenesis with bevacizumab, was found to be effective in some patients of epithelial ovarian cancer (EOC). Although careful patient selection is essential, there are currently no biomarkers available for routine therapeutic usage. To the authors’ best knowledge, this is the first automated precision oncology framework to effectively identify and select EOC and peritoneal serous papillary carcinoma (PSPC) patients with positive therapeutic effect. From March 2013 to January 2021, we have a database, containing four kinds of immunohistochemical tissue samples, including AIM2, c3, C5 and NLRP3, from patients diagnosed with EOC and PSPC and treated with bevacizumab in a hospital-based retrospective study. We developed a hybrid deep learning framework and weakly supervised deep learning models for each potential biomarker, and the experimental results show that the proposed model in combination with AIM2 achieves high accuracy 0.92, recall 0.97, F-measure 0.93 and AUC 0.97 for the first experiment (66% training and 34%testing) and high accuracy 0.86 ± 0.07, precision 0.9 ± 0.07, recall 0.85 ± 0.06, F-measure 0.87 ± 0.06 and AUC 0.91 ± 0.05 for the second experiment using five-fold cross validation, respectively. Both Kaplan-Meier PFS analysis and Cox proportional hazards model analysis further confirmed that the proposed AIM2-DL model is able to distinguish patients gaining positive therapeutic effects with low cancer recurrence from patients with disease progression after treatment (p < 0.005).

RAB42 Promotes Glioma Pathogenesis via the VEGF Signaling Pathway

Angiogenesis plays an important role in tumor initiation and progression of glioma. Seeking for biomarkers associated with angiogenesis is important in enhancing our understanding of glioma biologically and identifying its new drug targets. RNA-sequencing (RNA-seq) data and matched clinical data were downloaded from the CGGA database. A series of filtering analyses were performed to screen for reliable genes: survival, multivariate Cox, ROC curve filtration, and clinical correlation analyses. After immunohistochemical verification, RAB42 was identified as a reliable gene for further single gene analysis. Afterwards, we performed gene set enrichment analysis (GSEA) and co-expression analysis to establish the related molecular mechanisms and signal pathways in glioma. Finally, the gene functions and the mechanisms were investigated in vitro experiments. A total of 23270 mRNA expression and 1018 glioma samples were included in this study. After the three filtering analyses, we selected ten genes for immunohistochemical verification: KLHDC8A, IKIP, HIST1H2BK, HIST1H2BJ, GNG5, FAM114A1, TMEM71, RAB42, CCDC18, and GAS2L3. Immunostaining demonstrated that RAB42 was significantly expressed on the membrane of glioma tissues but not in normal tissues. These results were verified and validated in GEPIA datasets, and the association between RAB42 with clinical features was also evaluated. Analysis of gene functions indicated that RAB42 activated VEGF signaling pathways and the mechanism was associated with natural killer cell mediated cytotoxicity, JAK-STAT signaling pathway and apoptosis pathways by PI3K/AKT in gliomas. Experiments in vitro suggested that the proliferation and invasion of glioma cells might be inhibited after downregulating of RAB42. And the tumorigenesis promotion of RAB42 may relate to the activation of VEGF signaling pathway. Taken together, this study shows that the overexpression of RAB42 is an independent prognostic factor of adverse prognosis. Its pro-oncogenic mechanism may be associated with the activation of VEGF signaling pathways.

The Impasse on Overall Survival in Oncology Reimbursement Decision-Making: How Can We Resolve This?

Mature overall survival (OS) data are often unavailable at the time of regulatory and reimbursement decisions for a new cancer treatment. For patients with early-stage cancers treated with potentially curative treatments, demonstrating an OS benefit may take years and may be confounded by subsequent lines of therapy or crossover to the investigational treatment. For patients with advanced-stage cancers, mature OS data may be available but difficult to interpret for similar reasons. There are strong opinions about approval and reimbursement in the absence of mature OS data, with concerns over delay in patient access set against concerns about uncertainty in long-term benefit. This position paper reflects our individual views as patient advocate, clinician or health economist on one aspect of this debate. We look at payer decisions in the absence of mature OS data, considering when and how non-OS trial outcomes could inform decision-making and how uncertainty can be addressed beyond the trial, supporting these views with evidence from the literature. We consider when it is reasonable for payers to expect or not expect mature OS data at the initial reimbursement decision (based on criteria such as cancer stage and treatment efficacy) acknowledging that there are settings in which mature OS data are expected. We propose flexible strategies for generating and appraising patient-relevant evidence, including context-relevant endpoints and quality of life measures, when survival rates are good and mature OS data are not expected. We note that fair reimbursement is important; this means valuing patient benefit as shown through prespecified endpoints and reappraising if there is ongoing uncertainty or failure to show a sustained benefit. We suggest that reimbursement systems continue to evolve to align with scientific advances, because innovation is only meaningful if readily accessible to patients. The proposed strategies have the potential to promote thorough assessment of potential benefit to patients and lead to timely access to effective medicines.

Noble Pen Shell (Pinna nobilis) Mortalities along the Eastern Adriatic Coast with a Study of the Spreading Velocity

Noble pen shells (Pinna nobilis) along the Eastern Adriatic coast were affected by mass mortalities similarly to the populations across the Mediterranean basin. Samples of live animals and organs originating from sites on Mljet Island on the south and the Istrian peninsula on the north of the Croatian Adriatic coast were analyzed using histology and molecular techniques to detect the presence of the previously described Haplosporidium pinnae and Mycobacterium spp. as possible causes of these mortalities. To obtain more information on the pattern of the spread of the mortalities, a study was undertaken in Mljet National Park, an area with a dense population of noble pen shells. The results of the diagnostic analysis and the velocity of the spread of the mortalities showed a significant correlation between increases in water temperature and the onset of mortality. Moderate to heavy lesions of the digestive glands were observed in specimens infected with H. pinnae. A phylogenetic analysis of the detected Haplosporidium pinnae showed an identity of 99.7 to 99.8% with isolates from other Mediterranean areas, while isolated Mycobacterium spp. showed a higher heterogeneity among isolates across the Mediterranean. The presence of Mycobacterium spp. in clinically healthy animals a few months before the onset of mortality imposes the need for further clarification of its role in mortality events.

High Level of METTL7B Indicates Poor Prognosis of Patients and Is Related to Immunity in Glioma

Glioma is the most common primary intracranial malignant tumor in adults. Although there have been many efforts on potential targeted therapy of glioma, the patient’s prognosis remains dismal. Methyltransferase Like 7B (METTL7B) has been found to affect the development of a variety of tumors. In this study, we collected RNA-seq data of glioma in CGGA and TCGA, analyzed them separately. Then, Kaplan-Meier survival analysis, univariate and multivariate Cox analysis, and receiver operating characteristic curve (ROC curve) analysis were used to evaluate the effect of METTL7B on prognosis. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA) enrichment analyses were used to identify the function or pathway associated with METTL7B. Moreover, the ESTIMATE algorithm, Cibersort algorithm, Spearman correlation analysis, and TIMER database were used to explore the relationship between METTL7B and immunity. Finally, the role of METTL7B was explored in glioma cells. We found that METTL7B is highly expressed in glioma, and high expression of METTL7B in glioma is associated with poor prognosis. In addition, there were significant differences in immune scores and immune cell infiltration between the two groups with different expression levels of METTL7B. Moreover, METTL7B was also correlated with immune checkpoints. Knockdown of METTL7B revealed that METTL7B promoted the progression of glioma cells. The above results indicate that METTL7B affects the prognosis of patients and is related to tumor immunity, speculating that METTL7B may be a new immune-related target for the treatment of glioma.

Sugammadex is associated with shorter hospital length of stay after open lobectomy for lung cancer: a retrospective observational study

Background

Sugammadex is associated with few postoperative complications. Postoperative pulmonary complications (PPC) are related to prolonged hospitalizations. Present study explored whether the use of sugammadex could reduce PPCs and thereby reduce hospital length of stay (LOS) after lung surgery.

Methods

We reviewed the medical records of patients who underwent elective open lobectomy for lung cancer from January 2010 to December 2015. Patients were divided into the sugammadex group and pyridostigmine group.

The primary outcome was hospital LOS and secondary outcomes were postoperative complications and overall survival at 1 year. The cohort was subdivided into patients with and without prolonged LOS to explore the effects of sugammadex on outcomes in each group. Risk factors for LOS were determined via multivariate analyses. After propensity score matching, 127 patients were assigned to each group.

Results

Median hospital LOS was shorter (10.0 vs. 12.0 days) and the incidence of postoperative atelectasis was lower (18.1 vs. 29.9%) in the sugammadex group. However, no significant difference in overall survival between the groups was seen over 1 year (hazard ratio, 0.967; 95% confidence interval, 0.363 to 2.577). Sugammadex was a predictor related to LOS (exponential coefficient 0.88; 95% CI 0.82–0.95).

Conclusions

Our data suggest that sugammadex is a preferable agent for neuromuscular blockade (NMB) reversal than cholinesterase inhibitors in this patient population.

Trial registration

This study registered in the Clinical Research Information Service of the Korea National Institute of Health (approval number: KCT0004735, Date of registration: 21 January 2020, Retrospectively registered).

Comprehensive Analysis of the Expression of Key Genes Related to Hippo Signaling and Their Prognosis Impact in Ovarian Cancer

The Hippo signaling pathway, one of the most conserved in humans, controlling dimensions of organs and tumor growth, is frequently deregulated in several human malignancies, including ovarian cancer (OC). The alteration of Hippo signaling has been reported to contribute to ovarian carcinogenesis and progression. However, the prognostic roles of individual Hippo genes in OC patients remain elusive. Herein we investigated the expression level and prognostic value of key Hippo genes in OC using online databases, followed by a qRT-PCR validation step in an additional patient cohort. Using the GEPIA database, we observed an increased level for TP53 and reduced expression level for LATS1, LATS2, MST1, TAZ, and TEF in tumor tissue versus normal adjacent tissue. Moreover, LATS1, LATS2, TP53, TAZ, and TEF expression levels have prognostic significance correlated with progression-free survival. The qRT-PCR validation step was conducted in an OC patient cohort comprising 29 tumor tissues and 20 normal adjacent tissues, endorsing the expression level for LATS1, LATS2, and TP53, as well as for two of the miRNAs targeting the TP53 gene, revealing miR-25-3p upregulation and miR-181c-5p downregulation. These results display that there are critical prognostic value dysregulations of the Hippo genes in OC. Our data demonstrate the major role the conserved Hippo pathway presents in tumor control, underlying potential therapeutic strategies and controlling several steps modulated by miRNAs and their target genes that could limit ovarian cancer progression.

Expression Patterns of Coagulation Factor XIII Subunit A on Leukemic Lymphoblasts Correlate with Clinical Outcome and Genetic Subtypes in Childhood B-cell Progenitor Acute Lymphoblastic Leukemia

BACKGROUND

Based on previous retrospective results, we investigated the association of coagulation FXIII subunit A (FXIII-A) expression pattern on survival and correlations with known prognostic factors of B-cell progenitor (BCP) childhood acute lymphoblastic leukemia (ALL) as a pilot study of the prospective multi-center BFM ALL-IC 2009 clinical trial.

METHODS

The study included four national centers (n = 408). Immunophenotyping by flow cytometry and cytogenetic analysis were performed by standard methods. Copy number alteration was studied in a subset of patients (n = 59). Survival rates were estimated by Kaplan-Meier analysis. Correlations between FXIII-A expression patterns and risk factors were investigated with Cox and logistic regression models.

RESULTS

Three different patterns of FXIII-A expression were observed: negative (<20%), dim (20-79%), and bright (≥80%). The FXIII-A dim expression group had significantly higher 5-year event-free survival (EFS) (93%) than the FXIII-A negative (70%) and FXIII-A bright (61%) groups. Distribution of intermediate genetic risk categories and the "B-other" genetic subgroup differed significantly between the FXIII-A positive and negative groups. Multivariate logistic regression confirmed independent association between the FXIII-A negative expression characteristics and the prevalence of intermediate genetic risk group.

CONCLUSIONS

FXIII-A negativity is associated with dismal survival in children with BCP-ALL and is an indicator for the presence of unfavorable genetic alterations.

Preclinical Assessment of Efficacy and Safety Analysis of CAR-T Cells (ISIKOK-19) Targeting CD19-Expressing B-Cells for the First Turkish Academic Clinical Trial with Relapsed/Refractory ALL and NHL Patients

Objective:

Relapsed and refractory CD19-positive B-cell acute lymphoblastic leukemia (ALL) and non-Hodgkin lymphoma (NHL) are the focus of studies on hematological cancers. Treatment of these malignancies has undergone recent transformation with the development of new gene therapy and molecular biology techniques, which are safer and well-tolerated therapeutic approaches. The CD19 antigen is the most studied therapeutic target in these hematological cancers. This study reports the results of clinical-grade production, quality control, and in vivo efficacy processes of ISIKOK-19 cells as the first academic clinical trial of CAR-T cells targeting CD19-expressing B cells in relapsed/refractory ALL and NHL patients in Turkey.

Materials and Methods:

We used a lentiviral vector encoding the CD19 antigen-specific antibody head (FMC63) conjugated with the CD8-CD28-CD3ζ sequence as a chimeric antigen receptor (CAR) along with a truncated form of EGFR (EGFRt) on human T-lymphocytes (CAR-T). We preclinically assessed the efficacy and safety of the manufactured CAR-T cells, namely ISIKOK-19, from both healthy donors’ and ALL/NHL patients’ peripheral blood mononuclear cells.

Results:

We showed significant enhancement of CAR lentivirus transduction efficacy in T-cells using BX-795, an inhibitor of the signaling molecule TBK1/IKKƐ, in order to cut the cost of CAR-T cell production. In addition, ISIKOK-19 cells demonstrated a significantly high level of cytotoxicity specifically against a CD19+ B-lymphocyte cancer model, RAJI cells, in NOD/SCID mice.

Conclusion:

This is the first report of preclinical assessment of efficacy and safety analysis of CAR-T cells (ISIKOK-19) targeting CD19-expressing B cells in relapsed/refractory ALL and NHL patients in Turkey.

Early treatment-related neutropenia predicts response to palbociclib

BACKGROUND

Palbociclib is highly active in oestrogen-receptor positive (ER+) metastatic breast cancer, but neutropenia is dose limiting. The goal of this study was to determine whether early neutropenia is associated with disease response to single-agent palbociclib.

METHODS

Blood count and disease-response data were analysed from two Phase 2 clinical trials at different institutions using single-agent palbociclib: advanced solid tumours positive for retinoblastoma protein and advanced liposarcoma. The primary endpoint was PFS. The primary exposure variable was the nadir absolute neutrophil count (ANC) during the first two cycles of treatment.

RESULTS

One hundred and ninety-six patients (61 breast, 135 non-breast) were evaluated between the two trials. Development of any grade neutropenia was significantly associated with longer median PFS in both the breast cancer (HR 0.29, 95% CI 0.11-0.74, p = 0.010) and non-breast cancer (HR 0.57, 95% CI 0.38-0.85, p = 0.006) cohorts. Grade 3-4 neutropenia was significantly associated with prolonged PFS in the non-breast cohort (HR 0.57, 95% CI 0.38-0.85, p = 0.006) but not in the breast cohort (HR 0.87, 95% CI 0.51-1.47, p = 0.596). Multivariate analysis yielded similar results.

CONCLUSIONS

Treatment-related neutropenia in the first two cycles was significantly and independently associated with prolonged PFS, suggesting that neutropenia may be a useful pharmacodynamic marker to guide individualised palbociclib dosing.

CLINICAL TRIALS REGISTRATION INFORMATION

Basket Trial: NCT01037790; Sarcoma Trial: NCT01209598.

Transcriptome analysis reveals a reprogramming energy metabolism-related signature to improve prognosis in colon cancer

Although much progress has been made to improve treatment, colon cancer remains a leading cause of cancer death worldwide. Metabolic reprogramming is a significant ability of cancer cells to ensure the necessary energy supply in uncontrolled proliferation. Since reprogramming energy metabolism has emerged as a new hallmark of cancer cells, accumulating evidences have suggested that metabolism-related genes may serve as key regulators of tumorigenesis and potential biomarkers. In this study, we analyzed a set of reprogramming energy metabolism-related genes by transcriptome analysis in colon cancer and revealed a five-gene signature that could significantly predict the overall survival. The reprogramming energy metabolism-related signature could distinguish patients into high-risk and low-risk groups with significantly different survival times (P = 0.0011; HR = 1.92; 95% CI [1.29–2.87]). Its prognostic value was confirmed in another two independent colon cancer cohorts (P = 5.2e–04; HR = 2.09, 95%; CI [1.37–3.2] for GSE17538 and P = 3.8e−04; HR = 2.08, 95% CI [1.37–3.16] for GSE41258). By multivariable analysis, we found that the signature was independent of clinicopathological features. Its power in promoting risk stratification of the current clinical stage was then evaluated by stratified analysis. Moreover, the signature could improve the power of the TNM stage for the prediction of overall survival and could be used in patients who received adjuvant chemotherapy. Overall, our results demonstrated the important role of the reprogramming energy metabolism-related signature in promoting stratification of high-risk patients, which could be diagnostic of adjuvant therapy benefit.

High Levels of HIST1H2BK in Low-Grade Glioma Predicts Poor Prognosis: A Study Using CGGA and TCGA Data

A number of biomarkers have been identified for various cancers. However, biomarkers associated with glioma remain largely to be explored. In the current study, we investigated the relationship between the expression and prognostic value of the HIST1H2BK gene in glioma. Sequential data filtering (survival analysis, independent prognostic analysis, ROC curve analysis, and clinical correlation analysis) was performed, which resulted in identification of the association between the HIST1H2BK gene and glioma. Then, the HIST1H2BK gene was analyzed using bioinformatics (Kaplan–Meier survival analysis, univariate Cox analysis, multivariate Cox analysis, and ROC curve analysis). The results showed that low expression of HIST1H2BK was associated with better prognosis, and high expression of HIST1H2BK was associated with poor prognosis. In addition, HIST1H2BK was an independent prognostic indicator for patients with glioma. We also evaluated the association between HIST1H2BK and clinical characteristics. Furthermore, gene set enrichment analysis (GSEA) and analysis of immune infiltration were performed. The results showed that HIST1H2BK was associated with intensity of immune infiltration in glioma. Finally, co-expression analysis was performed. The results showed that HIST1H2BK was positively correlated with HIST1H2AG, HIST2H2AA4, HIST1H2BJ, HIST2H2BE, and HIST1H2AC, and negatively correlated with PDZD4, CRY2, GABBR1, rp5-1119a7.17, and KCNJ11. This study showed that upregulation of HIST1H2BK in low-grade glioma (LGG) tissue was an indicator of poor prognosis. Moreover, this study demonstrated that HIST1H2BK may be a promising biomarker for the treatment of LGG.

Effect of nitazoxanide and spiramycin metronidazole combination in acute experimental toxoplasmosis

Successful treatment of Toxoplasma gondii infection is difficult to attain. This study was designed to evaluate the efficacy of sulfamethoxazole-trimethoprim (SMZ-TMP), as the reference drug, nitazoxanide (NTZ), spiramycin (SP) and SP-metronidazole against the virulent RH T. gondii strain in acute experimental toxoplasmosis. One hundred Swiss albino mice were divided into control and experimental groups. Each mouse was infected with 2500 tachyzoites. Twenty infected untreated mice were used as control. The experimental group was subdivided into four subgroups (20 mice each); IIa SMZ-TMP, IIb NTZ, IIc SP and IId SP-metronidazole. All drugs were in tablet form, and were administered orally in suspension, for a period of seven days. Assessment of each drug efficacy was achieved through the study of mice survival time, mortality rate, parasite load, viability and morphological studies of tachyzoites by scanning electron microscope (SEM). The obtained results showed that SMZ-TMP, SP and SP-metronidazole were effective against acute murine toxoplasmosis and caused deformities in the tachyzoites ultrastructure. SP-metronidazole gave the best results on both mice survival rate and parasite load in the brain and liver. SMZ-TMP induced formation of prominent filaments extending from the deformed tachyzoites. NTZ showed little effect. In conclusion, all used drugs succeeded to prolong the survival time of the mice. SP-metronidazole gave the foremost effect on both mice survival rate and parasite load in the liver, spleen and brain. As this combination is nontoxic to human, it is promising for the treatment of human toxoplasmosis.

Environmental Correlates of Reaching a Centenarian Age: Analysis of 144,665 Deaths in Washington State for 2011-2015

Objective: This study examined the association of several social and environmental factors on the likelihood of reaching centenarian age for older adults in Washington State. Methods: A survival analysis of reaching centenarian age for older adults aged 75 years and above was performed using Washington State mortality data from 2011−2015. Models were adjusted for sex, race, education, marital status, and neighborhood level social and environmental variables at the block group level. Geographic clusters of increased chance of becoming a centenarian were also mapped. Results: In the adjusted model, increased neighborhood walkability, lower education level, higher socioeconomic status, and a higher percent of working age population were positively associated with reaching centenarian age. Being widowed, divorced/separated, or never married were also positively correlated compared to being married. Additionally, being white or female were positively correlated with reaching centenarian status. Discussion: Several social and environmental factors are correlated with becoming a centenarian in Washington State. In this study, we explore findings that are consistent with previous research, as well as some that have not been previously explained. More research is needed to expand upon these findings in this rapidly growing field.

Classifying Patients with Amyotrophic Lateral Sclerosis by Changes in FVC. A Group-based Trajectory Analysis

Rationale: A model for stratifying progression of respiratory muscle weakness in amyotrophic lateral sclerosis (ALS) would identify disease mechanisms and phenotypes suitable for future investigations. This study sought to categorize progression of FVC after presentation to an outpatient ALS clinic.Objectives: To identify clinical phenotypes of ALS respiratory progression based on FVC trajectories over time.Methods: We derived a group-based trajectory model from a single-center cohort of 837 patients with ALS who presented between 2006 and 2015. We applied our model to the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database with 7,461 patients with ALS. Baseline characteristics at first visit were used as predictors of trajectory group membership. The primary outcome was trajectory of FVC over time in months.Measurements and Main Results: We found three trajectories of FVC over time, termed "stable low," "rapid progressor," and "slow progressor." Compared with the slow progressors, the rapid progressors had shorter diagnosis delay, more bulbar-onset disease, and a lower ALS Functional Rating Scale-Revised (ALSFRS-R) total score at baseline. The stable low group had a shorter diagnosis delay, lower body mass index, more bulbar-onset disease, lower ALSFRS-R total score, and were more likely to have an ALSFRS-R orthopnea score lower than 4 compared with the slow progressors. We found that projected group membership predicted respiratory insufficiency in the PRO-ACT cohort (concordance statistic = 0.78, 95% CI, 0.76-0.79).Conclusions: We derived a group-based trajectory model for FVC progression in ALS, which validated against the outcome of respiratory insufficiency in an external cohort. Future studies may focus on patients predicted to be rapid progressors.

Monitoring methylation-driven genes as prognostic biomarkers in patients with lung squamous cell cancer

Aberrant DNA methylations have been reported to be significantly associated with lung squamous cell cancer (LUSC). The aim of this study was to investigate the DNA methylation-driven genes in LUSC by integrative bioinformatics analysis. In the present study, methylation-driven genes in LUSC were screened out, and survival analysis related to these genes was performed to confirm their value in prognostic assessment. Gene expression and methylation data were downloaded from The Cancer Genome Atlas (TCGA), and the MethylMix algorithm was used to identify methylation-driven genes. ConsensusPathDB was used to perform Gene Ontology and pathway enrichment analysis of methylation-driven genes. Survival analysis was performed to investigate the correlation with prognosis. In total, 52 differentially expressed methylation-driven genes were identified in LUSC and adjacent tissues. Survival analysis showed that DQX1, GPR75, STX12, and TRIM61 could serve as independent prognostic biomarkers. In addition, the combined methylation and gene expression survival analysis revealed that the combined expression level of the genes ALG1L, DQX1, and ZNF418 alone can be used as a prognostic marker or drug target. Methylation of four sites of gene ZNF418, four sites of ZNF701, two sites of DQX1, and four sites of DCAF4L2 was significantly associated with survival. The present study provides an important bioinformatic and relevant theoretical basis for subsequent early diagnosis and prognostic assessment of LUSC.

Survival analysis of confirmed elephant endotheliotropic herpes virus cases in Thailand from 2006 - 2018

The elephant endotheliotropic herpesvirus (EEHV) has been a known cause of death of young elephants in Thailand for over a decade. In this study, we report on the demography, disease characteristics and mortality of 58 elephants with confirmed EEHV hemorrhagic disease between January 2006 and August 2018 using retrospective data subjected to survival analysis. Median age of EEHV presentation was 29 months, and the mortality rate was 68.97% with a median survival time of 36 h. Most EEHV cases occurred in the north of Thailand, the region where most of the country’s captive elephants reside. The hazard ratio analysis identified application of medical procedures and antiviral medications as being significant factors correlated to the risk of death. Our results indicate a need to focus EEHV monitoring efforts on young elephants and to follow current protocols that advise starting treatments before clinical signs appear.

How the discovery of rituximab impacted the treatment of B-cell non-Hodgkin's lymphomas

Non-Hodgkin's lymphoma (NHL) is the sixth-most common cancer in the UK, accounting for around 13,700 new cases every year. Until the late 1990s, treatment relied on intensive chemotherapy, such as CHOP (cyclophosphamide-doxorubicin HCl-vincristine [Oncovin]-prednisone). The use of standard CHOP therapy and its variations had resulted in poor five-year survival rates (as low as 26%), particularly in patients with aggressive NHL. Rituximab (Rituxan) was the first chimeric (mouse/human) monoclonal antibody approved for the treatment of NHL. It was approved by the US Food and Drug Administration in 1997 for indolent forms of NHL. It subsequently received EU approval in June 1998, and was licensed under the trade name Mabthera (Roche, Basel, Switzerland). It then went on to be approved for the first-line treatment of aggressive forms of NHL, such as diffuse large B-cell lymphoma (to be used in combination with CHOP or other anthracycline-based chemotherapy) in 2006. It is directed against the CD20 protein, an antigen found on the surface of B-cell lymphomas. With minimal toxicity, activity as a single-agent (for indolent forms of NHL) and safety when combined with chemotherapy (for aggressive forms), it represents great progress in this field. Here, we analyze how this antibody therapeutic was developed from basic molecular and cellular considerations through to preclinical and clinical evaluations and how it came to be a first-line treatment for NHL, and we discuss the impacts the advent of rituximab had on treatment outcomes for patients with DLBCL compared with the pre-rituximab era.

Incidence and predictors of total knee arthroplasty following knee arthroscopy

OBJECTIVE

The purpose of this study was to determine the effectiveness of knee arthroscopy (KA) in patients with symptomatic meniscal tears or mechanical symptoms and OA, by using conversion to TKA as a final outcome measure.

METHODS

Retrospective review of all patients with OA who underwent KA in our practice.

RESULTS

1215 KAs were reviewed; 3.9% underwent conversion to TKA at an average of 3.2 years.

CONCLUSION

KA plays a role in delaying TKA in knees with meniscal tears and mechanical symptoms with concurrent OA.

Depression Risk in Patients with Rheumatoid Arthritis in the United Kingdom

Introduction

Rheumatoid arthritis (RA) is one of the most common chronic inflammatory diseases. The goal of this study was to analyze the risk of depression in patients diagnosed with RA and treated by general practitioners in the UK.

Methods

The present study included patients first diagnosed with RA between 2000 and 2014 (index date). Individuals were excluded if they had also been diagnosed with depression or if they had received therapy for depression at or prior to the index date. The primary outcome measure was the rate of patients with depression (ICD 10: F32, 33) within 5 years of the RA diagnosis. Demographic data included gender and age. Furthermore, a revised version of the Charlson comorbidity index was used as a generic marker of comorbidity.

Results

A total of 4187 patients were included in the study. After 5 years of follow-up, 23.7% of men and 36.5% of women had developed depression (log rank p value <0.001). Women were more likely to develop depression than men (HR 1.61, 95% CI 1.42–1.84). Age and Charlson comorbidity score had no significant impact on the risk of being diagnosed with this psychiatric disorder.

Conclusion

Around 30% of RA patients developed depression within 5 years of the RA diagnosis. The depression risk was higher in women than in men. The current findings also indicate that improved detection and treatment of patients with both RA and depression are important.