Large Patient Datasets Research Articles

Validation of POD24 As a Robust Early Clinical End Point of Poor Survival in Mantle Cell Lymphoma from 1280 Patients on Clinical Trials

Background The prognosis of mantle cell lymphoma (MCL) has largely improved in the past decade; however, the disease is characterized by a heterogeneous clinical course. Several retrospective studies identified early progression of disease (i.e. within two years, POD24) as a potential overall survival (OS) surrogate, but this has not been validated in cohorts of patients prospectively included in clinical trials in rituximab maintenance era. Methods We performed a pooled analysis of French patients with MCL included in six randomized clinical trials (EU-MCL younger NCT00209222, LyMA NCT00921414, LyMA101 NCT02896582, EU-MCL elderly NCT00209209, MCL-R2 NCT01865110 and RiBVD NCT01457144). Survival analysis using Landmark approach evaluated the association of POD24 status with post-event OS for all patients: starting from POD24 event or two years for patients without POD24 event. Logistic regression models were used to evaluate the association between POD24 status and (1) clinico-biological factors at diagnosis; (2) autologous stem cell transplantation at end-of-induction (ASCT) and anti-CD20 maintenance (RM) in responding patients after induction only. Results Among 1386 MCL patients, 106 censored for clinical follow-up before 24 months were excluded from the analysis, leading to 1280 patients evaluable for POD24 status: 299 with a POD24 event and 981 without. The 299 (23%) patients with a POD24 event had a post-event median OS of 9.3 months (95% CI 8.4-11.8) versus not reached in patients without POD24 event (95% CI 97.8-NR). Within the 981 non-POD24 patients, 314 presented a late relapse with a post-relapse median OS of 49.4 months (95% CI 30.4-56.8), significantly longer than OS of POD24 patients (HR=0.39; 95%CI 0.31-0.48; p<0.001). Compared to patients without a POD24 event, POD24 patients were older, had more frequently a performance status >1, elevated LDH and higher leucocytes leading to higher MIPI scores (high-risk MIPI 61% vs. 29%; p<0.001), more frequent blastoid variant (24% vs. 9%; p<0.001) and Ki67 > 30% (45% vs. 23%, p<0.001). Regarding treatment, POD24 patients had less frequently received high-dose cytarabine (21% vs. 39%, p<0.001) as well as ASCT (26% vs. 47%, p<0.001). In a final model, including baseline factors and treatment strategies, induction was not associated with risk of POD24, and only baseline variables (age, performance status, LDH, leucocytes and Ki67>30%) remained significantly associated with POD24 status. Within responding patients only (CR/CRu/PR at end-of-induction, n=1000), 150 had a POD24 event, and ASCT or RM were not significantly associated with POD24 status whereas age, LDH and Ki67>30% remained significant. Conclusion Using this large dataset of patients included in clinical trials, we confirm that POD24 can be used as a surrogate for OS in MCL. ASCT as well as RM have not a clear benefit to prevent early relapse within two years after the diagnosis in responding patients at end-of-induction.

Genetic risk factors for severe and fatigue dominant long COVID and commonalities with ME/CFS identified by combinatorial analysis

BackgroundLong COVID is a debilitating chronic condition that has affected over 100 million people globally. It is characterized by a diverse array of symptoms, including fatigue, cognitive dysfunction and respiratory problems. Studies have so far largely failed to identify genetic associations, the mechanisms behind the disease, or any common pathophysiology with other conditions such as myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) that present with similar symptoms.MethodsWe used a combinatorial analysis approach to identify combinations of genetic variants significantly associated with the development of long COVID and to examine the biological mechanisms underpinning its various symptoms. We compared two subpopulations of long COVID patients from Sano Genetics’ Long COVID GOLD study cohort, focusing on patients with severe or fatigue dominant phenotypes. We evaluated the genetic signatures previously identified in an ME/CFS population against this long COVID population to understand similarities with other fatigue disorders that may be triggered by a prior viral infection. Finally, we also compared the output of this long COVID analysis against known genetic associations in other chronic diseases, including a range of metabolic and neurological disorders, to understand the overlap of pathophysiological mechanisms.ResultsCombinatorial analysis identified 73 genes that were highly associated with at least one of the long COVID populations included in this analysis. Of these, 9 genes have prior associations with acute COVID-19, and 14 were differentially expressed in a transcriptomic analysis of long COVID patients. A pathway enrichment analysis revealed that the biological pathways most significantly associated with the 73 long COVID genes were mainly aligned with neurological and cardiometabolic diseases.Expanded genotype analysis suggests that specific SNX9 genotypes are a significant contributor to the risk of or protection against severe long COVID infection, but that the gene-disease relationship is context dependent and mediated by interactions with KLF15 and RYR3.Comparison of the genes uniquely associated with the Severe and Fatigue Dominant long COVID patients revealed significant differences between the pathways enriched in each subgroup. The genes unique to Severe long COVID patients were associated with immune pathways such as myeloid differentiation and macrophage foam cells. Genes unique to the Fatigue Dominant subgroup were enriched in metabolic pathways such as MAPK/JNK signaling. We also identified overlap in the genes associated with Fatigue Dominant long COVID and ME/CFS, including several involved in circadian rhythm regulation and insulin regulation. Overall, 39 SNPs associated in this study with long COVID can be linked to 9 genes identified in a recent combinatorial analysis of ME/CFS patient from UK Biobank.Among the 73 genes associated with long COVID, 42 are potentially tractable for novel drug discovery approaches, with 13 of these already targeted by drugs in clinical development pipelines. From this analysis for example, we identified TLR4 antagonists as repurposing candidates with potential to protect against long term cognitive impairment pathology caused by SARS-CoV-2. We are currently evaluating the repurposing potential of these drug targets for use in treating long COVID and/or ME/CFS.ConclusionThis study demonstrates the power of combinatorial analytics for stratifying heterogeneous populations in complex diseases that do not have simple monogenic etiologies. These results build upon the genetic findings from combinatorial analyses of severe acute COVID-19 patients and an ME/CFS population and we expect that access to additional independent, larger patient datasets will further improve the disease insights and validate potential treatment options in long COVID.

Comparison of Automated Spike Detection Software in Detecting Epileptiform Abnormalities on Scalp-EEG of Genetic Generalized Epilepsy Patients.

Despite availability of commercial EEG software for automated epileptiform detection, validation on real-world EEG datasets is lacking. Performance evaluation of two software packages on a large EEG dataset of patients with genetic generalized epilepsy was performed. Three epileptologists labelled IEDs manually of EEGs from three centres. All Interictal epileptiform discharge (IED) markings predicted by two commercial software (Encevis 1.11 and Persyst 14) were reviewed individually to assess for suspicious missed markings and were integrated into the reference standard if overlooked during manual annotation during a second phase. Sensitivity, precision, specificity, and F1-score were used to assess the performance of the software packages against the adjusted reference standard. One hundred and twenty-five routine scalp EEG recordings from different subjects were included (total recording time, 310.7 hours). The total epileptiform discharge reference count was 5,907 (including spikes and fragments). Encevis demonstrated a mean sensitivity for detection of IEDs of 0.46 (SD 0.32), mean precision of 0.37 (SD 0.31), and mean F1-score of 0.43 (SD 0.23). Using the default medium setting, the sensitivity of Persyst was 0.67 (SD 0.31), with a precision of 0.49 (SD 0.33) and F1-score of 0.51 (SD 0.25). Mean specificity representing non-IED window identification and classification was 0.973 (SD 0.08) for Encevis and 0.968 (SD 0.07) for Persyst. Automated software shows a high degree of specificity for detection of nonepileptiform background. Sensitivity and precision for IED detection is lower, but may be acceptable for initial screening in the clinical and research setting. Clinical caution and continuous expert human oversight are recommended with all EEG recordings before a diagnostic interpretation is provided based on the output of the software.

Refreshed academic viewpoint on patient data ownership in digital health context

Abstract Background Digital health involves generating and communicating large sensitive patient data sets. There is significant potential in its applications, but also some impediments. Our previous study showed that ownership of patient data is a problem in digital health context, not fully understood and often neglected. However, in the last two years, increased attention to this issue is observed and we aim to find if the medical academic community changed its viewpoint on patient data ownership in the context of digital health. Methods Our previous study (2014-2020) identified 27 relevant to the problem articles. A comprehensive search of PubMed, ScienceDirect and Scopus, performed between January 2021 and April 2023, identified 21 appropriate full-text publications focused on patient data ownership (problem) in digital health (context). Research questions included scientific area of publication, perception and aspects of ownership, possible solutions. Results The publications are in medical and public health (43%), digital health and medical informatics (29%), technical (19%), law and ethics (9%) journals; 71% with impact factor; authored by 38% EU, 24% USA, 9% UK, 9% Brazilian academicians. The majority (86%) are in the area of medical research - access, control, patient data sharing and use, secondary and passive data use, registries, AI, wearables, sensors; ethical challenges to digital health; 90% still perceive ownership as a challenge, arising in relation to medical research and data generated from the IoT, wearables, sensors, apps and social media. All publications discuss ownership in ethical and legal aspects and find the solution in proper legislation. Conclusions Digital health with its huge amounts of generated data brings forward the overlooked issue of patient data ownership as a challenge to medical research. Academic attention is rising, and addressing this challenge requires the combined efforts of all stakeholders for suitable amendments in the legislation. Key messages • Ownership of patient data in the context of digital health is a problem, especially for medical research, that should not be neglected and needs a comprehensive attitude from all stakeholders. • Proper legislation concerning patient data ownership may help in improving international academic medical and public health research, healthcare services, and the health of the population as a whole.

Health economic analysis of inpatient prostate cancer treatment in Austrian hospitals

Abstract Background Prostate cancer (PrC) is the fourth most prevalent type of cancer worldwide. Its high incidence and 5-year survival rates contributing to high inpatient care costs make it an important public health issue. In Austria, surgery has been the most common inpatient procedure for PrC, despite clinical recommendations not clearly indicating its benefits over alternatives. No health economic comparison of these procedures has considered the period after treatment yet. We bridge this gap by analysing the health economic impact of treatment pathways. Methods We use a large administrative dataset of all inpatient PrC patients in Austria who received either only surgery or only radiation therapy from 2005-2014 (n = 34,286). To assess the health economic impact, we used diagnosis-related-group (DRG) points and length of stay (LOS). Monthly DRG points and LOS for each patient ±12-months around the index procedure were analysed using the difference in difference (DID) method. We controlled for age, and physical comorbidity burden using Charlson Comorbidity Index (CCI) scores. Results Looking at unadjusted averages, patients in the surgery group were significantly younger and had a lower CCI compared to the radiation group. Consequently, the surgery group had lower nominal average DRG points and LOS. However, when controlling for age and CCI, we found that radiation treatment was less resource intensive. A DID estimation found a shorter average LOS and lower DRG points for the radiation group compared to surgery for the 12 months post index. Conclusions We found significant additional costs and LOS times for surgical pathways following risk adjustment in Austria. This implies a potential excess burden of ∼4,400 hospitalisation days and ∼4 million DRG points (€4.8m) a year for the healthcare system during the observed period. Considering international evidence on higher patient burden in surgical pathways, these findings may call for clinical reconsiderations of PrC care. Key messages • Patient characteristics of different inpatient treatment pathways for PrC in Austria were very heterogenous. • Health economic outcomes in the post treatment period for PrC inpatient treatment were significantly better for radiation treatment compared to surgery.

A supplementary analysis of a large scale 16S ribosomal RNA gene amplicon dataset of hand, foot and mouth patients and healthy individuals

A supplementary analysis of a large scale 16S ribosomal RNA gene amplicon dataset of hand, foot and mouth patients and healthy individuals

Impact of domiciliary administration of NSAIDs on COVID-19 hospital outcomes: an unCoVer analysis.

Background: Effective domiciliary treatment can be useful in the early phase of COVID-19 to limit disease progression, and pressure on hospitals. There are discrepant data on the use of non-steroidal anti-inflammatory drugs (NSAIDs). Aim of this study is to evaluate whether the clinical outcome of patients who were hospitalized for COVID-19 is influenced by domiciliary treatment with NSAIDs. Secondary objective was to explore the association between other patient characteristics/therapies and outcome. Methods: A large dataset of COVID-19 patients was created in the context of a European Union-funded project (unCoVer). The primary outcome was explored using a study level random effects meta-analysis for binary (multivariate logistic regression models) outcomes adjusted for selected factors, including demographics and other comorbidities. Results: 218 out of 1,144 patients reported use of NSAIDs before admission. No association between NSAIDs use and clinical outcome was found (unadj. OR: 0.96, 95%CI: 0.68-1.38). The model showed an independent upward risk of death with increasing age (OR 1.06; 95% CI 1.05-1.07) and male sex (1.36; 95% CI 1.04-1.76). Conclusion: In our study, the domiciliary use of NSAIDs did not show association with clinical outcome in patients hospitalized with COVID-19. Older ages and male sex were associated to an increased risk of death.

Change in Blood Counts after Palliative Radiotherapy for Multiple Myeloma

Radiation therapy (RT) can provide effective palliation and prevent symptomatic local progression of multiple myeloma (MM). However, RT is sometimes avoided due to concerns for secondary impact to bone marrow, potentially decreasing blood cell counts and precluding ability to receive future systemic therapies. We reviewed a series of MM patients who received palliative RT to assess changes in blood counts from pre-RT to post-RT, hypothesizing that blood counts would not significantly decline after treatment with modern RT volumes and techniques. We utilized a prospectively maintained departmental database and included patients who received palliative RT for MM from 2015 to 2020. Lab values immediately pre-RT (within one month of RT start date) and post-RT (within three months of RT completion) including hemoglobin, lymphocytes, neutrophils, and platelets were collected. Statistical differences from pre-RT to post-RT were assessed using t-tests. ANOVA was used to compare change in blood counts between common dose fractionation regimens (30 Gy in 10 Fractions, 20 Gy in 5, and 8 Gy in 1). A total of 334 MM patients receiving 424 courses of RT were included in this analysis. The median age at start of first treatment was 67 (IQR: 60-76) years. One-hundred ninety-five (58%) were male. Median RT dose was 20 (IQR: 8-24.5) Gy delivered over a median 5 (IQR: 1-5) fractions. Between pre-RT and post-RT, there was no significant change in hemoglobin (+0.1 g/dL (IQR: -0.8, +0.5), p = .076), lymphocyte counts (-0.3*10^9 cells/L (IQR: -0.6, 0), p = .435), or neutrophil counts (-0.1*10^9 cells/L (IQR: -1.1, +0.9), p = .310). In contrast, platelet counts significantly decreased from pre-RT (median 165*10^9 cells/L, IQR: 112-210) to post-RT (median 146, IQR: 93-194) by a median of 17.5 *10^9 cells/L (IQR: -52.5, +14.0, p<0.0001). There were no differences in changes in hemoglobin, neutrophils, or platelets between the common dose fractionations. However, there was a significantly greater drop in lymphocytes after 30 Gy in 10 fractions (p = .039, mean lymphocyte count change (in 10^9 cells/L) for 30 Gy in 10: -0.87, 20 Gy in 5: -0.47, and 8 Gy in 1: -0.27). In this large dataset of patients receiving modern palliative RT for MM, hemoglobin, lymphocytes, and neutrophils did not significantly decline from pre-RT to post-RT. In contrast, there was a statistically significant drop in platelet count by a median 17.5*10^9 cells/L from pre-RT to post-RT, which may or may not be clinically significant depending on clinical context. Patients receiving 30 Gy in 10 fractions had greater drops in lymphocytes than those receiving lower doses. Further analyses will be performed to determine clinical, dosimetric, and volumetric predictors of decline in blood counts after radiation.

Radiomic markers of intracerebral hemorrhage expansion on non-contrast CT: independent validation and comparison with visual markers.

To devise and validate radiomic signatures of impending hematoma expansion (HE) based on admission non-contrast head computed tomography (CT) of patients with intracerebral hemorrhage (ICH). Utilizing a large multicentric clinical trial dataset of hypertensive patients with spontaneous supratentorial ICH, we developed signatures predictive of HE in a discovery cohort (n = 449) and confirmed their performance in an independent validation cohort (n = 448). In addition to n = 1,130 radiomic features, n = 6 clinical variables associated with HE, n = 8 previously defined visual markers of HE, the BAT score, and combinations thereof served as candidate variable sets for signatures. The area under the receiver operating characteristic curve (AUC) quantified signatures' performance. A signature combining select radiomic features and clinical variables attained the highest AUC (95% confidence interval) of 0.67 (0.61-0.72) and 0.64 (0.59-0.70) in the discovery and independent validation cohort, respectively, significantly outperforming the clinical (pdiscovery = 0.02, pvalidation = 0.01) and visual signature (pdiscovery = 0.03, pvalidation = 0.01) as well as the BAT score (pdiscovery < 0.001, pvalidation < 0.001). Adding visual markers to radiomic features failed to improve prediction performance. All signatures were significantly (p < 0.001) correlated with functional outcome at 3-months, underlining their prognostic relevance. Radiomic features of ICH on admission non-contrast head CT can predict impending HE with stable generalizability; and combining radiomic with clinical predictors yielded the highest predictive value. By enabling selective anti-expansion treatment of patients at elevated risk of HE in future clinical trials, the proposed markers may increase therapeutic efficacy, and ultimately improve outcomes.

A Comprehensive Comparison of Six Publicly Available Algorithms for Localization of QRS Complex on Electrocardiograph.

The QRS complex is the most prominent feature of the electrocardiogram (ECG) that is used as a marker to identify the cardiac cycles. Identification of QRS complex locations enables arrhythmia detection and heart rate variability estimation. Therefore, accurate and consistent localization of the QRS complex is an important component of automated ECG analysis which is necessary for the early detection of cardiovascular diseases. This study evaluates the performance of six popular publicly available QRS complex detection methods on a large dataset of over half a million ECGs in a diverse population of patients. We found that a deep-learning method that won first place in the 2019 Chinese physiological challenge (CPSC-1) outperforms the remaining five QRS complex detection methods with an F1 score of 98.8% and an absolute sdRR error of 5.5 ms. We also examined the stratified performance of the studied methods on various cardiac conditions. All six methods had a lower performance in the detection of QRS complexes in ECG signals of patients with pacemakers, complete atrioventricular block, or indeterminate cardiac axis. We also concluded that, in the presence of different cardiac conditions, CPSC-1 is more robust than Pan-Tompkins which is the most popular model for QRS complex detection. We expect that this study can potentially serve as a guide for researchers on the appropriate QRS detection method for their target applications.Clinical Relevance-This study highlights the overall performance of publicly available QRS detection algorithms in a large dataset of diverse patients. We showed that there are specific cardiac conditions that are associated with the poor performance of QRS detection algorithms and may adversely influence the performance of algorithms that rely on accurate and reliable QRS detection.

Lipid profiles and their relation to glycemic control in Saudi Arabia: The role of altitudes and environmental factor.

The height from sea levels, environmental factors, human-environment interactions, and lifestyle significantly influence the lipid profile and glycemic control of a population. This study aims to explore the influence of altitude on lipid profiles and glycemic control among the Saudi population at sea level and high altitude. In this retrospective cross-sectional study, a large dataset of patients of both gender and over 30 years old attending internal medicine clinics from two different regions at different heights from sea level, Jeddah (sea level) and Asir region (high altitudes) and referred to commercial laboratories for glycated haemoglobin (HbA1c) and lipids profile. Compared to the Asir region, the Jeddah region had significantly higher mean values for fasting blood sugar (FBG), total cholesterol (TC), low-density lipoprotein (LDL-C), and triglycerides (TG) (P < 0.05). Every 1 mg/dL increase in FBG results in a 0.662 mg/dL increase in TG from the Jeddah region. However, it was a 0.318 mg/dL increase in TG from the Asir region. HbA1c demonstrated a significant (P < 0.05) strong positive correlation with TC, low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), and lipid ratio. FBG levels were also associated with a high level of TC/HDL-C (β = 0.137 95% confidence interval [CI]: 0.11-0.21; P < 0.05), LDL-C/high-density lipoprotein cholesterol (HDL-C) (β = 0.50; 95% CI: 0.31-1.49; P < 0.05), and TG/HDL-C (β = 0.14; 95% CI = 0.12-0.15; P < 0.05) in Jeddah region. However, significantly high blood pressure was observed in the population from high altitudes. Our results demonstrated a significant positive correlation between lipid profile and glycemic control with high prevalence at sea level.

IGL CDR3 Hydropathy and Antigen Chemical Complementarity Associated with Greater Disease-Free Survival in Lung Adenocarcinoma: Implications for Gender Disparities.

With lung cancer remaining a challenging disease, new approaches to biomarker discovery and therapy development are needed. Recent immunogenomics, adaptive immune receptor approaches have indicated that it is very likely that B cells play an important role in mediating better overall outcomes. As such, we assessed physicochemical features of lung adenocarcinoma resident IGL complementarity determining region-3 (CDR3) amino acid (AA) sequences and determined that hydrophobic CDR3 AA sequences were associated with a better disease-free survival (DFS) probability. Further, using a recently developed chemical complementarity scoring algorithm particularly suitable for the evaluation of large patient datasets, we determined that IGL CDR3 chemical complementarity with certain cancer testis antigens was associated with better DFS. Chemical complementarity scores for IGL CDR3-MAGEC1 represented a gender bias, with an overrepresentation of males among the higher IGL-CDR3-CTA complementarity scores that were in turn associated with better DFS (logrank p < 0.065). Overall, this study pointed towards potential biomarkers for prognoses that, in some cases are likely gender-specific; and towards biomarkers for guiding therapy, e.g., IGL-based opportunities for antigen targeting in the lung cancer setting.

Do outcomes for patients with hospital-acquired Acute Kidney Injury (H-AKI) vary across specialties in England?

BackgroundAcute Kidney Injury (AKI) is a common and serious clinical syndrome. There is increasing recognition of heterogeneity in observed AKI across different clinical settings. In this analysis we have utilised a large national dataset to outline, for the first time, differences in burden of hospital acquired AKI (H-AKI) and mortality risk across different treatment specialities in the English National Health Service (NHS).MethodsA retrospective observational study was conducted using a large national dataset of patients who triggered a biochemical AKI alert in England during 2019. This dataset was enriched through linkage with NHS hospitals administrative and mortality data. Episodes of H-AKI were identified and attributed to the speciality of the supervising consultant during the hospitalisation episode in which the H-AKI alert was generated. Associations between speciality and death in hospital or within 30 days of discharge (30-day mortality) was modelled using logistic regression, adjusting for patient age, sex, ethnicity, socioeconomic status, AKI severity, season and method of admission.ResultsIn total, 93,196 episodes of H-AKI were studied. The largest number of patients with H-AKI were observed under general medicine (21.9%), care of the elderly (18.9%) and general surgery (11.2%). Despite adjusting for differences in patient case-mix, 30-day mortality risk was consistently lower for patients in surgical specialities compared to general medicine, including general surgery (OR 0.65, 95% CI 0.61 to 0.7) and trauma and orthopaedics (OR 0.52, 95% CI 0.48 to 0.56). Mortality risk was highest in critical care (OR 1.78, 95% CI 1.56 to 2.03) and oncology (OR 1.74, CI 1.54 to 1.96).ConclusionsSignificant differences were identified in the burden of H-AKI and associated mortality risk for patients across different specialities in the English NHS. This work can help inform future service delivery and quality improvement activity for patients with AKI across the NHS.

High-resolution analyses of associations between medications, microbiome, and mortality in cancer patients

Discerning the effect of pharmacological exposures on intestinal bacterial communities in cancer patients is challenging. Here, we deconvoluted the relationship between drug exposures and changes in microbial composition by developing and applying a new computational method, PARADIGM (parameters associated with dynamics of gut microbiota), to a large set of longitudinal fecal microbiome profiles with detailed medication-administration records from patients undergoing allogeneic hematopoietic cell transplantation. We observed that several non-antibiotic drugs, including laxatives, antiemetics, and opioids, are associated with increased Enterococcus relative abundance and decreased alpha diversity. Shotgun metagenomic sequencing further demonstrated subspecies competition, leading to increased dominant-strain genetic convergence during allo-HCT that is significantly associated with antibiotic exposures. We integrated drug-microbiome associations to predict clinical outcomes in two validation cohorts on the basis of drug exposures alone, suggesting that this approach can generate biologically and clinically relevant insights into how pharmacological exposures can perturb or preserve microbiota composition. The application of a computational method called PARADIGM to a large dataset of cancer patients' longitudinal fecal specimens and detailed daily medication records reveals associations between drug exposures and the intestinal microbiota that recapitulate invitro findings and are also predictive of clinical outcomes.

Effect of germline mutations on somatic alteration landscapes in BRCA-associated cancers.

10509 Background: The interaction between germline alterations in homologous recombination repair (gHRR) genes and tumoral genomic landscapes is poorly understood. We hypothesized that gHRR alterations may influence somatic mutational landscapes in BRCA-associated cancers. Methods: Using a large de-identified real-world dataset of patients undergoing matched tumor/normal next-generation DNA sequencing (Tempus xT), we compared somatic genomic landscapes of tumors arising in individuals with germline HRR mutations (g BRCA1, g BRCA2, g PALB2, g ATM, g CHEK2) versus their sporadic counterparts, across four BRCA-associated cancers (breast, ovary, pancreas, prostate). Results: In breast cancer (N = 6955; gHRR-altered 5.9%, sporadic 94.1%), somatic TP53 muts were enriched in g BRCA1 pts, and depleted in g ATM and g CHEK2 pts (all P &lt; 0.001). ESR1 muts were depleted in g BRCA1 pts, and enriched in g ATM and g CHEK2 pts (all P &lt; 0.05). PIK3CA muts were depleted in g BRCA1/ 2 pts, and enriched in g ATM and g CHEK2 pts (all P &lt; 0.05). FGFR1 muts were depleted in g BRCA1/2 and g PALB2 pts, and enriched in g ATM pts (all P &lt; 0.01). HER2 and CDH1 alterations were depleted in g BRCA1 pts (P &lt; 0.05). In ovarian cancer (N = 4244; gHRR-altered 6.2%, sporadic 93.8%), somatic TP53 muts were enriched in g BRCA1/ 2 pts, and depleted in g ATM and g CHEK2 pts (all P &lt; 0.05). ESR1 muts were enriched in g ATM pts (P &lt; 0.001). PIK3CA muts were depleted in g BRCA1/ 2 pts, and enriched in g ATM pts (all P &lt; 0.05). KRAS muts were depleted in g BRCA1/ 2 pts (P &lt; 0.05). In pancreatic cancer (N = 5386; gHRR-altered 3.9%, sporadic 96.1%), somatic TP53 muts were enriched in g BRCA1 pts, and depleted in g ATM and g PALB2 pts (all P &lt; 0.05). KRAS muts were enriched in g BRCA1/2 and g ATM pts (P &lt; 0.05). Unexpectedly, ESR1 muts were enriched in g PALB2 and g CHEK2 pts (P &lt; 0.05). In prostate cancer (N = 4378; gHRR-altered 4.5%, sporadic 95.5%), somatic TP53 muts trended higher in g BRCA1 pts, and lower in g ATM and g PALB2 pts (P = NS). TMPRSS2-ERG fusions were depleted in g BRCA1 and g BRCA2 pts (P &lt; 0.05). FOXA1 muts were enriched in g BRCA2 pts (P &lt; 0.05), while BRAF and CDK12 muts were enriched in g CHEK2 pts (P &lt; 0.05 and P = 0.07). Median TMB was higher in BRCA-associated cancers with g BRCA1/2 and gPALB2 muts relative to sporadic cancers (all P &lt; 0.05), but not in pts with g ATM or g CHEK2 muts. There were no differences in MMR mutations or MSI status. Conclusions: Across four BRCA-associated cancers, TP53 muts are enriched in BRCA1 pts and depleted in g ATM pts. In breast/ovarian cancers, PIK3CA muts are depleted in g BRCA1/ 2 pts, while ESR1 muts are enriched in g ATM pts. KRAS muts are enriched in g BRCA1/2-altered pancreas cancers, but are depleted in g BRCA1/2-altered ovarian cancers. g BRCA2-altered prostate cancers are enriched in FOXA1 muts, and depleted in ERG fusions. These data suggest that gHRR-mutated cancers have distinct genomic landscapes compared to their sporadic counterparts; this may influence therapeutic considerations.

Molecular and immune analysis of adrenocortical carcinoma (ACC): Implications for immune checkpoint inhibition (ICI).

e16617 Background: ACC is a rare and aggressive malignancy. Response rates to ICI are low with scarce yet promising durable responses. Molecular ACC subtypes have been reported based on The Cancer Genome Atlas (TCGA). Here we report the mutational and immune landscapes of ACC obtained from a real-world patient dataset. Methods: DNA (592-gene or whole exome; N=215) and RNA sequencing (whole transcriptome; N=121) were performed for ACC specimens submitted to Caris Life Sciences (Phoenix, AZ). PD-L1+ expression was tested by IHC (SP142; ≥1%). Hierarchical agglomerative clustering (HAC) analysis was performed on a pre-defined set of immune genes. Specimens grouped into immune-high/intermediate (IH) and immune-low (IL) groups. Microenvironmental cell populations (MCP)-counter analysis was used to estimate immune cell infiltrates. Statistical significance was determined using chi-square/Fisher’s exact/Mann-Whitney U tests and adjusted for multiple comparisons (q&lt;0.05). Results: Overall, the most frequent mutations were in TP53 (37%), CTNNB1 (18.7%), ATRX (12.1%), NF1 (9.6%), and RB1 (8.75%), consistent with previous reports. Further, 6.4% of tumors were PD-L1+, 6.1% TMB-high (≥ 10 mut/MB), and 5.9% dMMR/MSI-H. 38.2% of tumors were biopsied from metastatic sites (M). Compared to M, primary (P) specimens had a higher prevalence of TP53 (43.4 vs 26.9%, p&lt;0.05) and TERT promoter mutations (11.1 vs 0%, p=0.08), and a lower prevalence of SMARCB1 (0 vs 3.7%, p=0.054) and BRCA2 (0 vs 3.8%, p=0.056) mutations. Interestingly, M lesions were enriched for HAVCR2 expression (1.3-fold, p&lt;0.05), as well as infiltration of monocytes (1.8-fold, q&lt;0.05) and endothelial cells (1.4-fold, q&lt;0.05). HAC based segregation of tumors based on immune activity was corroborated by a general enrichment of immune cell infiltrates in the IH tumors. IH tumors were enriched for common immunotherapy-related biomarkers (TMB-high, dMMR/MSI-H and PD-L1 positivity), along with a higher prevalence of TP53 and ATRX mutations, while CTNNB1 mutation and CDK4 copy number amplification were less common in IH tumors. Conclusions: Querying a large real-world ACC patient dataset, we find somatic alterations and a low prevalence of ICI-related biomarkers (&lt;10%), consistent with previous reports. Monocyte and endothelial cell infiltration in metastatic tumors suggests an immunosuppressive phenotype compared to primary tumors. Finally, identification of molecular alterations in tumors with distinct immune phenotypes may facilitate development of new therapeutic strategies in ACC. [Table: see text]

Early clinical outcome prediction based on the initial National Early Warning Score + Lactate (News+L) Score among adult emergency department patients

BackgroundThe National Early Warning Score + Lactate (NEWS+L) Score has been previously shown to outperform NEWS alone in prediction of mortality and need for critical care in a small adult...

A senescence-related signature for predicting the prognosis of breast cancer: A bioinformatics analysis.

Breast cancer is a heterogeneous disease with diverse prognosis and treatment outcomes. Current gene signatures for prognostic prediction are limited to specific subtypes of breast cancer. Cellular senescence is a state of irreversible cell cycle arrest that affects various physiological and pathological processes. This study aimed to develop and validate a senescence-related signature for predicting the prognosis of breast cancer patients. We retrieved 744 senescence-associated genes from the SeneQuest database and analyzed their expression profiles in 2 large datasets of breast cancer patients: The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC). We used univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression analysis to derive a 29-gene senescence-related risk signature. The risk signature was significantly associated with disease-specific survival (DSS), clinical characteristics, molecular subtypes, and immune checkpoint genes expressions in both datasets. The risk signature also stratified high-risk and low-risk patients within the same clinical stage and molecular subtype. The risk signature was an independent prognostic factor for breast cancer patients. The senescence-related signature may be a useful biomarker for predicting prognosis and immunotherapy response of breast cancer patients. The risk signature may also guide adjuvant chemotherapy decisions, especially in hormone receptor positive (HR+) and human epidermal growth factor receptor type 2 (HER2)- subtypes.

Exploring the Therapeutic Potential of Elastase Inhibition in Age-Related Macular Degeneration in Mouse and Human.

Abnormal turnover of the extracellular matrix (ECM) protein elastin has been linked to AMD pathology. Elastin is a critical component of Bruch's membrane (BrM), an ECM layer that separates the retinal pigment epithelium (RPE) from the underlying choriocapillaris. Reduced integrity of BrM's elastin layer corresponds to areas of choroidal neovascularization (CNV) in wet AMD. Serum levels of elastin-derived peptides and anti-elastin antibodies are significantly elevated in AMD patients along with the prevalence of polymorphisms of genes regulating elastin turnover. Despite these results indicating significant associations between abnormal elastin turnover and AMD, very little is known about its exact role in AMD pathogenesis. Here we report on results that suggest that elastase enzymes could play a direct role in the pathogenesis of AMD. We found significantly increased elastase activity in the retinas and RPE cells of AMD mouse models, and AMD patient-iPSC-derived RPE cells. A1AT, a protease inhibitor that inactivates elastase, reduced CNV lesion sizes in mouse models. A1AT completely inhibited elastase-induced VEGFA expression and secretion, and restored RPE monolayer integrity in ARPE-19 monolayers. A1AT also mitigated RPE thickening, an early AMD phenotype, in HTRA1 overexpressing mice, HTRA1 being a serine protease with elastase activity. Finally, in an exploratory study, examining archival records from large patient data sets, we identified an association between A1AT use, age and AMD risk. Our results suggest that repurposing A1AT may have therapeutic potential in modifying the progression to AMD.

The Effectiveness of Collaborative Care in Publicly Insured Populations.

The Centers for Medicare and Medicaid Services covers the cost of collaborative care for Medicare beneficiaries. However, only 24 states cover the costs of collaborative care in their Medicaid programs despite evidence indicating the cost-effectiveness of delivering behavioral health services in primary care. This study examines benchmark data from a behavioral health medical group embedded within primary care practices across the United States using a large dataset of patients treated in collaborative care. The study explores the effectiveness of collaborative care in reducing depression and anxiety symptoms by comparing Medicare, Medicaid, and privately insured populations, seeking to inform the importance of supporting advocacy for continued Medicaid fee adoption for collaborative care.