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AbstractBackgroundRecent therapeutic advances and screening technologies have improved survival among patients with lung cancer, who are now at high risk of developing second primary lung cancer (SPLC). Recently, an SPLC risk‐prediction model (called SPLC‐RAT) was developed and validated using data from population‐based epidemiological cohorts and clinical trials, but real‐world validation has been lacking. The predictive performance of SPLC‐RAT was evaluated in a hospital‐based cohort of lung cancer survivors.MethodsThe authors analyzed data from 8448 ever‐smoking patients diagnosed with initial primary lung cancer (IPLC) in 1997–2006 at Mayo Clinic, with each patient followed for SPLC through 2018. The predictive performance of SPLC‐RAT and further explored the potential of improving SPLC detection through risk model‐based surveillance using SPLC‐RAT versus existing clinical surveillance guidelines.ResultsOf 8448 IPLC patients, 483 (5.7%) developed SPLC over 26,470 person‐years. The application of SPLC‐RAT showed high discrimination area under the receiver operating characteristics curve: 0.81). When the cohort was stratified by a 10‐year risk threshold of ≥5.6% (i.e., 80th percentile from the SPLC‐RAT development cohort), the observed SPLC incidence was significantly elevated in the high‐risk versus low‐risk subgroup (13.1% vs. 1.1%, p < 1 × 10–6). The risk‐based surveillance through SPLC‐RAT (≥5.6% threshold) outperformed the National Comprehensive Cancer Network guidelines with higher sensitivity (86.4% vs. 79.4%) and specificity (38.9% vs. 30.4%) and required 20% fewer computed tomography follow‐ups needed to detect one SPLC (162 vs. 202).ConclusionIn a large, hospital‐based cohort, the authors validated the predictive performance of SPLC‐RAT in identifying high‐risk survivors of SPLC and showed its potential to improve SPLC detection through risk‐based surveillance.Plain Language Summary Lung cancer survivors have a high risk of developing second primary lung cancer (SPLC). However, no evidence‐based guidelines for SPLC surveillance are available for lung cancer survivors. Recently, an SPLC risk‐prediction model was developed and validated using data from population‐based epidemiological cohorts and clinical trials, but real‐world validation has been lacking. Using a large, real‐world cohort of lung cancer survivors, we showed the high predictive accuracy and risk‐stratification ability of the SPLC risk‐prediction model. Furthermore, we demonstrated the potential to enhance efficiency in detecting SPLC using risk model‐based surveillance strategies compared to the existing consensus‐based clinical guidelines, including the National Comprehensive Cancer Network.

Abstract Microglia-mediated neuroinflammation contributes to acute demyelination in neuromyelitis optica spectrum disorders (NMOSD). Soluble triggering receptor expressed on myeloid cells 2 (sTREM2) in the CSF has been associated with microglial activation in several neurodegenerative diseases. However, the basis for this immune-mediated attack and the pathophysiological role of sTREM2 in NMOSD remain to be elucidated. Here, we performed Mendelian randomization analysis and identified a genetic association between increased CSF sTREM2 and NMOSD risk. CSF sTREM2 was elevated in patients with NMOSD and was positively correlated with neural injury and other neuroinflammation markers. Single-cell RNA sequencing of human macrophage/microglia-like cells in CSF, a proxy for microglia, showed that increased CSF sTREM2 was positively associated with microglial dysfunction in patients with NMOSD. Furthermore, we demonstrated that sTREM2 is a reliable biomarker of microglial activation in a mouse model of NMOSD. Using unbiased transcriptomic and lipidomic screens, we identified that excessive activation, overwhelmed phagocytosis of myelin debris, suppressed lipid metabolism and enhanced glycolysis underlie sTREM2-mediated microglial dysfunction, possibly through the nuclear factor kappa B (NF-κB) signalling pathway. These molecular and cellular findings provide a mechanistic explanation for the genetic association between CSF sTREM2 and NMOSD risk and indicate that sTREM2 could be a potential biomarker of NMOSD progression and a therapeutic target for microglia-mediated neuroinflammation.

Abstract BACKGROUND Few methods exist via which to assess treatment response with high fidelity in gliomas. Cell-free DNA (cfDNA) is of growing interest as a liquid biomarker in plasma and CSF and has been used in other cancer types to optimize therapeutic regimens for individual patients. While CSF has previously been used as a source of cfDNA for gliomas, it remains unknown how cfDNA abundance and sequencing change throughout treatment and inevitable recurrence. To that end, we leveraged our growing biobank of longitudinal CSF specimens, acquired via CSF access devices, to determine the potential utility of CSF cfDNA as a monitoring tool for treatment response in patients with gliomas. MATERIAL AND METHODS Longitudinal CSF specimens were acquired via Ommaya reservoirs (NCT04692337) or ventriculoperitoneal shunts (NCT04692324) in patients with brain tumors, including gliomas. cfDNA was extracted from 1-5 mL of CSF based on available sample volumes and quantified via Qubit. Next-Generation sequencing (PredicineCARE) or low-pass whole genome sequencing (LPWGS) was performed by Predicine, Inc based on the amount of cfDNA available. RESULTS CSF acquired prior to versus after resection demonstrated an increase in quantified cfDNA (2.97x, range: 1.58-5.26x), consistent with the impact of increased parenchymal disruption and closer contact with CSF. Thereafter, CSF cfDNA continued to decrease throughout chemoradiation and adjuvant treatment and increased at recurrence, including in patients co-enrolled in immunotherapy trials for IL-7 agonists and pembrolizumab. Interestingly, copy number burden (CNB) increased by the time of recurrence in three patients with known disease progression, and continued to decrease throughout immunotherapy treatment in one patient despite concerns of pseudoprogression. In one patient with a hypermutated glioblastoma, CSF cfDNA revealed over 59 genomic alterations, including MAP2K1, KIT, and PDGFRA, and over 100 more variants of unknown significance, each of which had been detected in sequencing of the tissue acquired at resection and subsequently decreased with chemoradiation. In another patient with a known progressing EGFR-amplified GBM, over 200 new variants were identified by the patient’s final sample and EGFR copy number increased from 2 to over 30. CONCLUSION Analysis of cfDNA over a patient’s disease course, including resection and treatment with standard-of-care and experimental therapies, may be of use for disease monitoring and treatment response. Further work is needed to evaluate these findings in a larger cohort of patients and to determine the sensitivity of changes in mutations, CNB, and cfDNA quantity for glioma disease burden.

Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson’s disease (PD) and Alzheimer’s disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1 *04 subtypes best accounted for the association, strongest with HLA-DRB1 *04:04 and HLA-DRB1 *04:07, and intermediary with HLA-DRB1 *04:01 and HLA-DRB1 *04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1 *04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1 *04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues.

AbstractINTRODUCTIONDown syndrome (DS) is a genetic cause of early‐onset Alzheimer's disease (AD). The National Institute on Aging–Alzheimer's Association AT(N) Research Framework is a staging model for AD biomarkers but has not been assessed in DS.METHODData are from the Alzheimer's Biomarker Consortium–Down Syndrome. Positron emission tomography (PET) amyloid beta (Aβ; 15 mCi of [11C]Pittsburgh compound B) and tau (10 mCi of [18F]AV‐1451) were used to classify amyloid (A) –/+ and tau (T) +/–. Hippocampal volume classified neurodegeneration (N) –/+. The modified Cued Recall Test assessed episodic memory.RESULTSAnalyses included 162 adults with DS (aged M = 38.84 years, standard deviation = 8.41). Overall, 69.8% of participants were classified as A–/T–/(N)–, 11.1% were A+/T–/(N)–, 5.6% were A+/T+/(N)–, and 9.3% were A+/T+/(N)+. Participants deemed cognitively stable were most likely to be A–T–(N)– and A+T–(N)–. Tau PET (T+) most closely aligning with memory impairment and AD clinical status.DISCUSSIONFindings add to understanding of AT(N) biomarker profiles in DS.Highlights Overall, 69.8% of adults with Down syndrome (DS) aged 25 to 61 years were classified as amyloid (A)–/tau (T)–/neurodegeneration (N)–, 11.1% were A+/T–/(N)–, 5.6% were A+/T+/(N)–, and 9.3% were A+/T+/(N)+. The AT(N) profiles were associated with clinical Alzheimer's disease (AD) status and with memory performance, with the presence of T+ aligned with AD clinical symptomology. Findings inform models for predicting the transition to the prodromal stage of AD in DS.

Abstract Artificial intelligence has been introduced to clinical practice, especially radiology and radiation oncology, from image segmentation, diagnosis, treatment planning and prognosis. It is not only crucial to have an accurate artificial intelligence model, but also to understand the internal logic and gain the trust of the experts. This review is intended to provide some insights into core concepts of the interpretability, the state-of-the-art methods for understanding the machine learning models, the evaluation of these methods, identifying some challenges and limits of them, and gives some examples of medical applications.

PURPOSE The COVID-19 pandemic has profoundly affected cancer care worldwide, including radiation therapy (RT) for breast cancer (BC), because of risk-based resource allocation. We report the evolution of international breast RT practices during the beginning of the pandemic, focusing on differences in treatment recommendations between countries. MATERIALS AND METHODS Between July and November 2020, a 58-question survey was distributed to radiation oncologists (ROs) through international professional societies. Changes in RT decision making during the first surge of the pandemic were evaluated across six hypothetical scenarios, including the management of ductal carcinoma in situ (DCIS), early-stage, locally advanced, and metastatic BC. The significance of changes in responses before and during the pandemic was examined using chi-square and McNemar-Bowker tests. RESULTS One thousand one hundred three ROs from 54 countries completed the survey. Incomplete responses (254) were excluded from the analysis. Most respondents were from the United States (285), Japan (117), Italy (63), Canada (58), and Brazil (56). Twenty-one percent (230) of respondents reported treating at least one patient with BC who was COVID-19–positive. Approximately 60% of respondents reported no change in treatment recommendation during the pandemic, except for patients with metastatic disease, for which 57.7% (636/1,103; P < .0005) changed their palliative practice. Among respondents who noted a change in their recommendation during the first surge of the pandemic, omitting, delaying, and adopting short-course RT were the most frequent changes, with most transitioning to moderate hypofractionation for DCIS and early-stage BC. CONCLUSION Early in the COVID-19 pandemic, significant changes in global RT practice patterns for BC were introduced. The impact of published results from the FAST FORWARD trial supporting ultrahypofractionation likely confounded the interpretation of the pandemic's independent influence on RT delivery.

Histone‐lysine N‐methyltransferase SETD2 (SETD2), the sole histone methyltransferase that catalyzes trimethylation of lysine 36 on histone H3 (H3K36me3), is often mutated in clear cell renal cell carcinoma (ccRCC). SETD2 mutation and/or loss of H3K36me3 is linked to metastasis and poor outcome in ccRCC patients. Epithelial‐to‐mesenchymal transition (EMT) is a major pathway that drives invasion and metastasis in various cancer types. Here, using novel kidney epithelial cell lines isogenic for SETD2, we discovered that SETD2 inactivation drives EMT and promotes migration, invasion, and stemness in a transforming growth factor‐beta‐independent manner. This newly identified EMT program is triggered in part through secreted factors, including cytokines and growth factors, and through transcriptional reprogramming. RNA‐seq and assay for transposase‐accessible chromatin sequencing uncovered key transcription factors upregulated upon SETD2 loss, including SOX2, POU2F2 (OCT2), and PRRX1, that could individually drive EMT and stemness phenotypes in SETD2 wild‐type (WT) cells. Public expression data from SETD2 WT/mutant ccRCC support the EMT transcriptional signatures derived from cell line models. In summary, our studies reveal that SETD2 is a key regulator of EMT phenotypes through cell‐intrinsic and cell‐extrinsic mechanisms that help explain the association between SETD2 loss and ccRCC metastasis.

The EGFR-RAS-ERK pathway is one of the most important signaling cascades in cell survival, growth, and proliferation. Aberrant activation of this pathway is a common mechanism in various cancers. Here, we report that CDK2 is a novel regulator of the ERK pathway via USP37 deubiquitinase (DUB). Mechanistically, CDK2 phosphorylates USP37, which is required for USP37 DUB activity. Further, USP37 deubiquitinates and stabilizes ERK1/2, thereby enhancing cancer cell proliferation. Thus, CDK2 is able to promote cell proliferation by activating USP37 and, in turn, stabilizing ERK1/2. Importantly, combined CDK1/2 and EGFR inhibitors have a synergetic anticancer effect through the downregulation of ERK1/2 stability and activity. Indeed, our patient-derived xenograft (PDX) results suggest that targeting both ERK1/2 stability and activity kills cancer cells more efficiently even at lower doses of these two inhibitors, which may reduce their associated side effects and indicate a potential new combination strategy for cancer therapy.