Impact of Next-generation Sequencing on Interobserver Agreement and Diagnosis of Spitzoid Neoplasms

The American Journal of Surgical Pathology, Tempus-acknowledged — Atypical Spitzoid melanocytic tumors are diagnostically challenging. Many studies have suggested various genomic markers to improve classification and prognostication. We aimed to assess whether next-generation sequencing studies using the Tempus xO assay assessing mutations in 1711 cancer-related genes and performing whole transcriptome mRNA sequencing for structural alterations … Continued

Systematic Review and Meta-Analysis of L-Methylfolate Augmentation in Depressive Disorders

Pharmacopsychiatry, Tempus-authored — Objectives  Partial response to pharmacotherapy is common in major depressive disorder (MDD) and many patients require alternative pharmacotherapy or augmentation, including adjunctive L-methylfolate. Given that L-methylfolate augmentation is rarely included in major clinical practice guidelines, we sought to systematically review evidence for L-methylfolate augmentation in adults with MDD and to examine its … Continued

Fibroblasts As Paracrine Targets of the Oncometabolite D-2-HG in the IDH1-Mutant Cholangiocarcinoma Tumor Microenvironment

SITC Annual Meeting 2021, Tempus-authored — Background Cholangiocarcinoma (CCA) is an aggressive malignancy of the biliary tract that carries an unfavorable prognosis. Recurrent, hotspot mutations in the IDH1 gene are found in 10–20% of CCAs and can be targeted with mutant IDH1 inhibitors, though objective responses leading to a reduction in tumor size are rare.1 2 Mutant … Continued

BASECAMP-1: An Observational Study to Identify Relapsed Solid Tumor Patients With Human Leukocyte Antigen (HLA) Loss of Heterozygosity (LOH) and Leukapheresis for Future CAR T-Cell Therapy

SITC Annual Meeting 2021, Tempus-authored — Background Solid tumors comprise >90% of cancers. Metastatic colorectal cancer, non-small cell lung cancer, and pancreatic cancer are among the leading causes of cancer-related mortality (5-year overall survival: 14%, 6%, and 3%, respectively).1Chimeric antigen receptor (CAR) T-cell therapy demonstrated clinical outcomes in hematologic malignancies.2 3 However, translating engineered T-cell therapies to … Continued

Characterization of Tumor-Infiltrating T-Cell Repertoire in Human Cancers

SITC Annual Meeting 2021, Tempus-authored — Background TCR and BCR repertoire profiling is a promising technique that can provide a clinically useful window into the complex interactions between tumor cells and infiltrating lymphocytes. Despite recent advances in repertoire sequencing methods, the characterization of tumor-infiltrating T-cell repertoires has been limited to small sample sizes due to technical … Continued

Applying Machine Vision to Empower Preclinical Development of Cell Engager and Adoptive Cell Therapeutics in Patient-Derived Organoid Models of Solid Tumors

SITC Annual Meeting 2021, Tempus-authored — Background Cell engager and adoptive cell therapeutics have emerged as efficacious and durable treatments in patients with B-cell malignancies. Though many analogous strategies are under development in solid tumors, none have received approval. Preclinical development of these therapies requires cell labeling of immortalized cell lines and/or primary expanded T cells … Continued

Rapid Detection of Somatic Variants in Human Leukocyte Antigen Class 1 Genes From Solid Tumor Samples

SITC Annual Meeting 2021, Tempus-authored — Background Human Leukocyte Antigens (HLA) class 1 proteins are important for recognizing tumor specific mutations (neoantigens) and presenting them to CD8+ T-cells. Somatic mutations in HLA genes can potentially reduce the set of neoantigens available for presentation to T-cells, providing a possible immune escape mechanism for tumors. The presence of … Continued

Rechommend: An Ecg-Based Machine-Learning Approach for Identifying Patients at High-Risk of Undiagnosed Structural Heart Disease Detectable by Echocardiography

AHA Scientific Sessions 2021, Tempus-authored — Introduction: Timely diagnosis of structural heart disease improves patient outcomes, yet millions remain undiagnosed. ECG-based prediction models can help identify high-risk patients for targeted screening, but existing individual disease models often have low positive predictive values (PPV) and limited clinical utility. Hypothesis: An ECG-based composite model can predict one of multiple, … Continued

An ECG-Based Machine Learning Model for Predicting New Onset Atrial Fibrillation is Superior to Age and Clinical Variables in Selecting a Population at High Stroke Risk

AHA Scientific Sessions 2021, Tempus-authored — Background: Several large trials have employed age or clinical features to select patients for atrial fibrillation (AF) screening to reduce strokes. We hypothesized that a deep neural network (DNN) model risk prediction based on ECG would be superior to age and clinical variables at selecting a population at high risk … Continued

Prediction of Drug-Induced QTc Prolongation With an ECG Based Machine Learning Model

AHA Scientific Sessions 2021, Tempus-authored — Introduction: Initiation of QTc-prolonging medications may lead to the rare but potentially catastrophic event, torsades de pointes (TDP). At present, no adequate, generalizable tools exist to predict drug-induced long QTc (LQT); machine learning from ECG data is a promising approach. Hypothesis: Prediction of drug-induced LQT using an ECG-based machine learning model … Continued