Citations

Purpose To characterize the prevalence and incidence of in‐game hand and wrist injuries in the National Basketball Association (NBA), to determine the factors associated with an equal or greater player efficiency rating (PER), and to determine the factors associated with an equal or greater true shooting percentage (TS%) 2 years after a hand and wrist injury using a large‐scale national database of NBA players. Methods Injury data from seasons 2015‐2016 to 2020‐2021, with exclusion of the 2019‐2020 because of abbreviated play due to the coronavirus disease 2019, were extracted from a public online database, Pro Sports Transactions. Injury characteristics and NBA player demographic information were assessed using descriptive statistics. Poisson logistic regression analyses were performed to identify risk factors associated with equal or increased PER and TS% 2years after injury. Results There were 214 reported hand and wrist injuries, and of these injuries, 173 (81%) were classified as structural. The most common injury types were a strain or sprain (0.63 per 1,000 game exposures), followed by fractures (0.37 per 1,000 game exposures). Older age (relative risk [RR] 0.89; 95% confidence interval [CI] 0.84‐0.95) and more years played in the NBA were modestly associated with relative risk of having a decreased PER at 2 years after injury. Increased weight (RR 1.02; 95% CI 1‐1.05) and increased body mass index (RR 1.14; 95% CI 1.01‐1.29) were also modestly associated with having a decreased PER and TS%, respectively at 2 years after injury. Conclusions Strains/sprains and fractures are the most common hand and wrist injuries sustained by NBA players. Regardless of dominant or nondominant hand and wrist injuries, NBA players are likely to return to baseline overall player efficiency based on PER and TS% within 2 years of injury. Clinical Relevance Our study characterizes hand and wrist injuries of NBA players and provides an understanding for these injuries on player performance at 2 years.

Abstract Although incarcerated adults are at elevated risk of dying from cancer, little is known about cancer screening in carceral settings. This study compared stage-specific incidence of screen-detectable cancers among incarcerated and recently released people with the general population, as a reflection of screening practices. We calculated the age- and sex-standardized incidence ratios (SIR) for early- and late-stage cancers for incarcerated and recently released adults compared to the general Connecticut population between 2005 and 2016. Our sample included 143 cancer cases among those incarcerated, 406 among those recently released, and 201 360 in the general population. The SIR for early-stage screen-detectable cancers was lower among incarcerated (SIR = 0.28, 95% CI = 0.17 to 0.43) and recently released (SIR = 0.69, 95% CI = 0.51 to 0.88) individuals than the general population. Incidence of late-stage screen-detectable cancer was lower during incarceration (SIR = 0.51, 95% CI = 0.27 to 0.88) but not after release (SIR = 1.32, 95% CI = 0.93 to 1.82). Findings suggest that underscreening and underdetection of cancer may occur in carceral settings.

Abstract Accurate biomarkers for predicting COVID‐19 severity have remained an unmet need due to an incomplete understanding of virus pathogenesis and heterogeneity among patients. Cellular senescence and its pro‐inflammatory phenotype are suggested to be a consequence of SARS‐CoV‐2 infection and potentially drive infection‐dependent pathological sequelae. Senescence‐associated markers in infected individuals have been identified primarily in the lower respiratory tract, while little is known about their presence in more easily accessible bio‐specimens. Here, we measured the abundance of senescence‐associated signatures in whole blood, plasma and peripheral blood mononuclear cells (PBMCs) of COVID‐19 patients and patients without an infection. Bulk transcriptomic and targeted proteomic assays revealed that the level of senescence‐associated markers, including the senescence‐associated secretory phenotype (SASP), is predictive of SARS‐CoV‐2 infection. Single‐cell RNA‐sequencing data demonstrated that a senescence signature is particularly enriched in monocytes of COVID‐19 patients, partially correlating with disease severity. Our findings suggest that monocytes are prematurely induced to senescence by SARS‐CoV‐2 infection, might contribute to exacerbating a SASP‐like inflammatory response and can serve as markers and predictors for COVID‐19 and its sequelae.

Patients with advanced cancers who either do not experience initial response to or progress while on immune checkpoint inhibitors (ICIs) receive salvage radiotherapy to reduce tumor burden and tumor-related symptoms. Occasionally, some patients experience substantial global tumor regression with a rebound of cytotoxic CD8 + T cells. We have termed the rebound of cytotoxic CD8 + T cells in response to salvage therapy as T cell resilience and examined the underlying mechanisms of resilience. Resilient T cells are enriched for CX3CR1 + CD8 + T cells with low mitochondrial membrane potential, accumulate less reactive oxygen species (ROS), and express more malic enzyme 1 (ME1). ME1 overexpression enhanced the cytotoxicity and expansion of effector CD8 + T cells partially via the type I interferon pathway. ME1 also increased mitochondrial respiration while maintaining the redox state balance. ME1 increased the cytotoxicity of peripheral lymphocytes from patients with advanced cancers. Thus, preserved resilient T cells in patients rebound after salvage therapy and ME1 enhances their resiliency.

Abstract Sequencing efforts have identified key oncogenic drivers and transcriptomic subtypes of high-grade gliomas (HGGs), but this knowledge has not resulted in individualized therapy or improved patient outcomes. Here, we used a functional genomics approach combining integrated genomic/transcriptomic analyses with patient-derived 3D micro-cancers (mCancers) to rapidly identify individualized therapeutic vulnerabilities and determine predictive response biomarkers. 30 primary/recurrent HGGs, including 20 glioblastomas, 5 astrocytomas, and 5 oligodendrogliomas, were included for drug testing. mCancers recapitulated the structural and molecular alterations, cellularity, and heterogeneity, of parental patient tumors. A total of 119 single-agent drugs and 183 drug combinations were tested, while a pre-selected drug panel comprising 25 glioma-relevant treatment strategies was tested across all cases. In general, mCancer efficacy corresponded well to historical responses to previously tested agents (EGFR, HDAC inhibitors, etc.). Combined, strong efficacy (i.e. >70% growth inhibition at Cmax) of single treatments targeting deregulated receptor tyrosine kinase (RTK), p53/apoptosis, cell cycle, DNA damage repair, IDH, or telomere maintainance pathways, was observed in 14 out of 30 cases. Surprisingly, transcriptional signatures, but not specific genetic alterations, were found to stratify drug responses. For example, mCancers enriched for the most aggressive mesenchymal (MES) and glycolytic/plurimetabolic (GPM) transcriptional subtypes exhibited stronger response to the BET inhibitor JQ1 (and other clinical BET inhibitors) and the DNA-PKcs/mTOR dual inhibitor CC-115. This therapeutic vulnerability was associated with enrichment of YAP/TAZ signaling, and the glioblastoma stem cell G-STEM signature. Notably, individual combination strategies were effective across tumors, with strong responses ranging from 38% to 77% of all tumors tested. Overall, this study underscores the value of functional genomics in identifying novel vulnerabilities of HGGs and associated response biomarkers. It also highlights the need for further clinical validation of several novel therapies and especially drug combination strategies with strong efficacy in the ex vivo setting.

Abstract OBJECTIVE We sought to define the mechanisms by which purines regulate DNA repair and therapy response. METHODS Phosphoproteomics was used to identify GTP-dependent (de)phosphorylation events after radiation (RT) and antibodies generated against novel sites. Animal models of glioblastoma (GBM) and normal tissues were used to assess DNA repair and treatment responses in vivo. RESULTS Pharmacogenomic inhibition of GTP (but not ATP) synthesis sensitized GBM cells to RT by inhibiting the activity of non-homologous end joining, but not homologous recombination. We found a GTP-dependent RT-induced dephosphorylation event on Abl interactor 1 (Abi-1) serine 323 (S323) using phosphoproteomics. We generated a new antibody for p-Abi-1 (S323), validated its specificity, and confirmed that RT causes a GTP-dependent dephosphorylation of Abi-1 (S323). Knockout of Abi-1 slowed RT-induced double-strand break (DSB) repair, and this was rescued by re-expression of dephosphomimetic Abi-1 (S323A) but not phosphomimetic Abi-1 (S323D). Abi-1 canonically binds to G protein Rac1. Expression of constitutively active Rac1 promoted but dominant negative Rac1 blocked the dephosphorylation of Abi-1 (S323) and DSB repair. Knock-down or inhibition of protein phosphatase 5 reversed the GTP- and Rac1-mediated dephosphorylation of Abi-1 and DSB repair. In GBM PDX samples, p-Abi-1 (S323) levels negatively correlated with Rac1 activity and predicted favorable efficacy of genotoxic treatments. In orthotopic GBM mouse models, inhibiting Rac1 enhanced RT responses and suppressed Abi-1 (S323) dephosphorylation. Abi-1 knockout enhanced efficacy of genotoxic treatments and could be rescued by Abi-1 S323A (but not Abi-1 S323D) re-expression. This regulation is generalizable beyond brain cancer, as GTP supplementation promoted DNA repair and p-Abi1 (S323) dephosphorylation in non-malignant cells and protected mice from RT-mediated gastrointestinal injury and bleomycin-induced pulmonary fibrosis. CONCLUSION The GTP-Rac1-PP5-Abi-1 signaling axis links metabolism and DNA repair. Disrupting this pathway can overcome GBM resistance to genotoxic therapy while augmenting it can mitigate genotoxic injury of normal tissues.

Abstract BACKGROUND Treatment of high-grade glioma (HGG) remains a challenge. Several groups have developed ex vivo drug sensitivity assays to evaluate susceptibility of the tumor tissue to specific chemotherapeutics. This tool, in addition to molecular analysis of tumors might provide another layer of confidence in choosing treatments for patients with high-grade gliomas. METHODS 3D PredictTM platform (Kiyatec, Greenville, SC, USA) was tested at three academic medical centers in the United States. Twelve patients with newly diagnosed and recurrent HGGs were included. Tumor spheroids created ex vivo were exposed to twelve pre-selected drugs. Responses were reported as: no response, moderate response and response. We analyzed: demographics, histopathology, stage of disease, success rate and results of the ex vivo assay and clinical implications. RESULTS Majority of patients were women (67%). Median age was 58.5. Histology: GBM-83%, HGGs-17%. Eighty three percent of the samples represented recurrent disease. Sixty percent represented first recurrence while the remaining 40% represented 2nd or 3rd recurrence. Eight out of 12 tissue samples (67%) were successfully tested ex vivo. In six cases (75%), the information was used for immediate clinical decision making. In 2 cases, the decision was deferred until the next progression of the disease. The drugs chosen for treatment based on assay results included: olaparib (the assay was positive for response to rucaparib), temozolomide, lomustine, carboplatin and irinotecan. CONCLUSIONS This platform is easy to use in a standard clinical setting, the success rate for creating viable spheroids for drug sensitivity testing is high and the information obtained can be useful in clinical practice. Addition of other agents to the assay, correlation with molecular testing of the tumor tissue and attempt to assess response to drug combinations should be considered in further development of this technology. Prospective clinical trial is needed to validate this approach for routine clinical use.

AbstractAnti‐CD19 chimeric antigen receptor T‐cell therapy (CART) has revolutionized the outcomes of relapsed and/or refractory B‐cell non‐Hodgkin lymphoma. However, CART is still limited by its availability, toxicity, and response durability. Not all patients make it to the CART infusion phase due to disease progression. Among those who receive CART, a significant number of patients experience life‐threatening cytokine release syndrome toxicity, and less than half maintain a durable response with the majority relapsing in pre‐existing sites of disease present pre‐CART. Radiation therapy stands as a promising peri‐CART and salvage treatment that can improve the outcomes of these patients. Evidence suggests that bridging radiotherapy prior to CART controls the disease during the manufacturing period, augments response rates and local control, cytoreduces/debulks the disease and decreases the severity of cytokine release syndrome, and may prolong disease‐free intervals and survival especially in patients with bulky disease. Consolidative radiotherapy for residual post‐CART disease alters the pattern of relapse and improves local recurrence‐free and progression‐free survivals. Salvage radiotherapy for relapsed post‐CART disease has favorable survival outcomes when delivered comprehensively for patients with limited relapsed disease and palliates symptoms for patients with diffuse relapsed disease. The biology of the disease during the peri‐CART period is poorly understood, and further studies investigating the optimal timing and dosing of radiation therapy (RT) are needed. In this review, we tackle the most significant challenges of CART, review and propose how RT can help mitigate these challenges, and provide The Mayo Clinic experts' approach on incorporating RT with CART.

Abstract Background Atrial functional mitral regurgitation (AFMR) is an increasingly recognized cause of functional MR thought to result from left atrial enlargement and myopathy in the setting of preserved left ventricular geometry and function. AFMR mostly occurs in patients with atrial fibrillation (AF) and/or heart failure with preserved ejection fraction. Purpose We investigated whether the use of an artificial intelligence-based electrocardiogram (AI-ECG) can identify patients with new-onset AF and sinus rhythm (SR) who are at highest risk of developing AFMR. Methods Adults with a new diagnosis of AF between 2010 and 2021 who had a transthoracic echocardiogram (TTE) within 1 month after AF diagnosis were identified. Similarly, adults in SR who never had AF diagnosis and had a TTE during the same period were identified. Exclusion criteria from both groups included >mild MR at baseline, primary mitral valve disease, cardiomyopathy, ≥moderate aortic valve disease, current or previous low ejection fraction, enlarged left ventricle, cardiac devices, previous cardiac surgeries, and the absence of follow-up TTE ≥6 months from baseline. Only patients who had ECG within 10 days of the TTE were included. When multiple ECGs were available, the closest was considered. A previously trained AI-ECG algorithm to detect the probability of AF was utilized. Incident AFMR was defined as >mild functional MR in the absence of >mild left ventricle enlargement or dysfunction. Diastolic dysfunction was defined according to ASE/EACVI guidelines. Results Overall, 1,570 patients with new-onset AF (median age 67 years; 34% females) and 16,802 patients in SR (median age 59 years; 46% females) were included. The median AI ECG probability for AF was 43% (IQR 26%-59%) in the new-onset AF group and 2% (0.5%-7%) in the SR group, Figure 1. Incident AFMR occurred in 152 patients in the AF group over median 3.06 (IQR 1.5-5.2) years of follow-up and in 482 patients in the SR group over median 3.0 (1.5-5.6) years of follow-up. The probability of silent AF by the AI-ECG was associated with incident AFMR in the new-onset AF group [hazard ratio 1.19 (95% CI 1.11-1.28) per 10%, p <.001] and the SR group [hazard ratio 1.19 (95% CI 1.12-1.25) per 10%, p <.001]. The AI ECG-derived AF probability remained as an independent risk factor for AFMR in multivariable analysis in both AF and SR, Table 1. Conclusion The AI ECG for AF might be able to reflect the degree of left atrial myopathy and thus the risk of incident AFMR in patients with AF and SR.Distribution of AI ECG probability of AFMultivariable risk factors for AFMR