Investigating the role of programmed necrosis in oncolytic adenovirus-induced death

Oncolytic viruses are a group of viruses that preferentially replicate in cancer cells and are a promising cancer treatment. However, how these oncolytic adenoviruses kill cancer cells is not fully understood. It was long thought that DNA viruses utilize apoptosis to induce cell death but there is now evidence that adenovirus and vaccinia cytotoxicity displays features of necrosis-like programmed cell death. In order to investigate the role of necrosis in cell death as a result of oncolytic adenovirus infection, a panel of ovarian cancer cells with varying sensitivities to the oncolytic adenoviral mutant dl922-947 was used. Cells infected with dl922- 947 displayed key features of necrotic death. Using necrosis inhibitors necrostatin-1, necrosulfonamide, GSK2791840B, GSK2399872B and GSK2393843A, as well as RNAi-mediated knockdown of RIPK1, RIPK3 or MLKL, I showed that cells undergo RIPK3-dependent necrosis and that blockage of the downstream effector mixed lineage kinase domain-like (MLKL) attenuated cell death. While Tumour necrosis factor-α (TNF-α)-induced programmed necrosis(Laster, Wood and Gooding 1988) relies on the (RHIM)-dependent interaction of RIPK1 and RIPK3 (Li et al. 2012, Wu et al. 2014), RIPK1 seems to be redundant for adenovirus-induced death. Further, the addition of TNF-α blocking antibody to virus-infected cells showed no effect on either cell death. Using a RIPK3 overexpression model, I showed that the amount adenovirus- induced cell death correlated with the amount of RIPK3 expression and that RIPK3 expression did not affect virus production, infectivity or the expression of viral proteins. Further, in vivo experiments using human xenografts showed that expression of RIPK3 significantly improved anti-tumour activity following intra-tumoural injection of dl922-947

Diagnostic Performance of Ultrasonography-Based Risk Models in Differentiating Between Benign and Malignant Ovarian Tumors in a US Cohort

Importance: Ultrasonography-based risk models can help nonexpert clinicians evaluate adnexal lesions and reduce surgical interventions for benign tumors. Yet, these models have limited uptake in the US, and studies comparing their diagnostic accuracy are lacking. Objective: To evaluate, in a US cohort, the diagnostic performance of 3 ultrasonography-based risk models for differentiating between benign and malignant adnexal lesions: International Ovarian Tumor Analysis (IOTA) Simple Rules with inconclusive cases reclassified as malignant or reevaluated by an expert, IOTA Assessment of Different Neoplasias in the Adnexa (ADNEX), and Ovarian-Adnexal Reporting and Data System (O-RADS). Design, setting, and participants: This retrospective diagnostic study was conducted at a single US academic medical center and included consecutive patients aged 18 to 89 years with adnexal masses that were managed surgically or conservatively between January 2017 and October 2022. Exposure: Evaluation of adnexal lesions using the Simple Rules, ADNEX, and O-RADS. Main outcomes and measures: The main outcome was diagnostic performance, including area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios. Surgery or follow-up were reference standards. Secondary analyses evaluated the models' performances stratified by menopause status and race. Results: The cohort included 511 female patients with a 15.9% malignant tumor prevalence (81 patients). Mean (SD) ages of patients with benign and malignant adnexal lesions were 44.1 (14.4) and 52.5 (15.2) years, respectively, and 200 (39.1%) were postmenopausal. In the ROC analysis, the AUCs for discriminative performance of the ADNEX and O-RADS models were 0.96 (95% CI, 0.93-0.98) and 0.92 (95% CI, 0.90-0.95), respectively. After converting the ADNEX continuous individualized risk into the discrete ordinal categories of O-RADS, the ADNEX performance was reduced to an AUC of 0.93 (95% CI, 0.90-0.96), which was similar to that for O-RADS. The Simple Rules combined with expert reevaluation had 93.8% sensitivity (95% CI, 86.2%-98.0%) and 91.9% specificity (95% CI, 88.9%-94.3%), and the Simple Rules combined with malignant classification had 93.8% sensitivity (95% CI, 86.2%-98.0%) and 88.1% specificity (95% CI, 84.7%-91.0%). At a 10% risk threshold, ADNEX had 91.4% sensitivity (95% CI, 83.0%-96.5%) and 86.3% specificity (95% CI, 82.7%-89.4%) and O-RADS had 98.8% sensitivity (95% CI, 93.3%-100%) and 74.4% specificity (95% CI, 70.0%-78.5%). The specificities of all models were significantly lower in the postmenopausal group. Subgroup analysis revealed high performances independent of race. Conclusions and relevance: In this diagnostic study of a US cohort, the Simple Rules, ADNEX, and O-RADS models performed well in differentiating between benign and malignant adnexal lesions; this outcome has been previously reported primarily in European populations. Risk stratification models can lead to more accurate and consistent evaluations of adnexal masses, especially when used by nonexpert clinicians, and may reduce unnecessary surgeries.</p

Collaborative nowcasting of COVID-19 hospitalization incidences in Germany

Real-time surveillance is a crucial element in the response to infectious disease outbreaks. However, the interpretation of incidence data is often hampered by delays occurring at various stages of data gathering and reporting. As a result, recent values are biased downward, which obscures current trends. Statistical nowcasting techniques can be employed to correct these biases, allowing for accurate characterization of recent developments and thus enhancing situational awareness. In this paper, we present a preregistered real-time assessment of eight nowcasting approaches, applied by independent research teams to German 7-day hospitalization incidences during the COVID-19 pandemic. This indicator played an important role in the management of the outbreak in Germany and was linked to levels of non-pharmaceutical interventions via certain thresholds. Due to its definition, in which hospitalization counts are aggregated by the date of case report rather than admission, German hospitalization incidences are particularly affected by delays and can take several weeks or months to fully stabilize. For this study, all methods were applied from 22 November 2021 to 29 April 2022, with probabilistic nowcasts produced each day for the current and 28 preceding days. Nowcasts at the national, state, and age-group levels were collected in the form of quantiles in a public repository and displayed in a dashboard. Moreover, a mean and a median ensemble nowcast were generated. We find that overall, the compared methods were able to remove a large part of the biases introduced by delays. Most participating teams underestimated the importance of very long delays, though, resulting in nowcasts with a slight downward bias. The accompanying prediction intervals were also too narrow for almost all methods. Averaged over all nowcast horizons, the best performance was achieved by a model using case incidences as a covariate and taking into account longer delays than the other approaches. For the most recent days, which are often considered the most relevant in practice, a mean ensemble of the submitted nowcasts performed best. We conclude by providing some lessons learned on the definition of nowcasting targets and practical challenges

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

The glycoprotein CD147 defines miRNA‐enriched extracellular vesicles that derive from cancer cells

Abstract Extracellular vesicles (EVs) are ideal for liquid biopsy, but distinguishing cancer cell‐derived EVs and subpopulations of biomarker‐containing EVs in body fluids has been challenging. Here, we identified that the glycoproteins CD147 and CD98 define subpopulations of EVs that are distinct from classical tetraspanin+ EVs in their biogenesis. Notably, we identified that CD147+ EVs have substantially higher microRNA (miRNA) content than tetraspanin+ EVs and are selectively enriched in miRNA through the interaction of CD147 with heterogeneous nuclear ribonucleoprotein A2/B1. Studies using mouse xenograft models showed that CD147+ EVs predominantly derive from cancer cells, whereas the majority of tetraspanin+ EVs are not of cancer cell origin. Circulating CD147+ EVs, but not tetraspanin+ EVs, were significantly increased in prevalence in patients with ovarian and renal cancers as compared to healthy individuals and patients with benign conditions. Furthermore, we found that isolating miRNAs from body fluids by CD147 immunocapture increases the sensitivity of detecting cancer cell‐specific miRNAs, and that circulating miRNAs isolated by CD147 immunocapture more closely reflect the tumor miRNA signature than circulating miRNAs isolated by conventional methods. Collectively, our findings reveal that CD147 defines miRNA‐enriched, cancer cell‐derived EVs, and that CD147 immunocapture could be an effective approach to isolate cancer‐derived miRNAs for liquid biopsy

Antonio Bonet: edifici Paraguay-Suipacha

Postprint (published version

Neoadjuvant chemotherapy induces genomic and transcriptomic changes in ovarian cancer

The growing use of neoadjuvant chemotherapy to treat advanced stage high-grade serous ovarian cancer (HGSOC) creates an opportunity to better understand chemotherapy-induced mutational and gene expression changes. Here we performed a cohort study including 34 patients with advanced stage IIIC or IV HGSOC to assess changes in the tumor genome and transcriptome in women receiving neoadjuvant chemotherapy. RNA sequencing and panel DNA sequencing of 596 cancer-related genes was performed on paired formalin-fixed paraffin-embedded specimens collected before and after chemotherapy, and differentially expressed genes (DEG) and copy-number variations (CNV) in pre- and post-chemotherapy samples were identified. Following tissue and sequencing quality control, the final patient cohort consisted of 32 paired DNA and 20 paired RNA samples. Genomic analysis of paired samples did not reveal any recurrent chemotherapy-induced mutations. Gene expression analyses found that most DEGs were upregulated by chemotherapy, primarily in the chemotherapy-resistant specimens. AP-1 transcription factor family genes (FOS, FOSB, FRA-1) were particularly upregulated in chemotherapy-resistant samples. CNV analysis identified recurrent 11q23.1 amplification, which encompasses SIK2. In vitro, combined treatment with AP-1 or SIK2 inhibitors with carboplatin or paclitaxel demonstrated synergistic effects. These data suggest that AP-1 activity and SIK2 copy-number amplification are induced by chemotherapy and may represent mechanisms by which chemotherapy resistance evolves in HGSOC. AP-1 and SIK2 are druggable targets with available small molecule inhibitors and represent potential targets to circumvent chemotherapy resistance

Collaborative nowcasting of COVID-19 hospitalization incidences in Germany.

Real-time surveillance is a crucial element in the response to infectious disease outbreaks. However, the interpretation of incidence data is often hampered by delays occurring at various stages of data gathering and reporting. As a result, recent values are biased downward, which obscures current trends. Statistical nowcasting techniques can be employed to correct these biases, allowing for accurate characterization of recent developments and thus enhancing situational awareness. In this paper, we present a preregistered real-time assessment of eight nowcasting approaches, applied by independent research teams to German 7-day hospitalization incidences during the COVID-19 pandemic. This indicator played an important role in the management of the outbreak in Germany and was linked to levels of non-pharmaceutical interventions via certain thresholds. Due to its definition, in which hospitalization counts are aggregated by the date of case report rather than admission, German hospitalization incidences are particularly affected by delays and can take several weeks or months to fully stabilize. For this study, all methods were applied from 22 November 2021 to 29 April 2022, with probabilistic nowcasts produced each day for the current and 28 preceding days. Nowcasts at the national, state, and age-group levels were collected in the form of quantiles in a public repository and displayed in a dashboard. Moreover, a mean and a median ensemble nowcast were generated. We find that overall, the compared methods were able to remove a large part of the biases introduced by delays. Most participating teams underestimated the importance of very long delays, though, resulting in nowcasts with a slight downward bias. The accompanying prediction intervals were also too narrow for almost all methods. Averaged over all nowcast horizons, the best performance was achieved by a model using case incidences as a covariate and taking into account longer delays than the other approaches. For the most recent days, which are often considered the most relevant in practice, a mean ensemble of the submitted nowcasts performed best. We conclude by providing some lessons learned on the definition of nowcasting targets and practical challenges