Genomic Predictors Associated With Exceptional Response to Systemic Therapy in Advanced Pancreatic Cancer.

INTRODUCTION: Exceptional response to therapy is rare in patients with advanced pancreatic cancer. This study explored potential genomic differences between typical and exceptional responses that could confer more favorable biology. METHODS: We included exceptional responders and controls with advanced pancreatic cancer from Cleveland Clinic from April 2013 to August 2017. Exceptional responders were defined as patients with an overall survival of more than 18 months for metastatic disease and more than 24 months for locally advanced disease. Clinical data were obtained, and next-generation sequencing was performed. Statistical analyses comparing the 2 groups were performed using descriptive statistics, the Kaplan-Meier method, and the log-rank test. RESULTS: The study comprised 4 exceptional responders and 6 controls. Both groups were well balanced in age, sex, race, and treatment regimens. Exceptional responders had significantly fewer nonsynonymous mutations than controls (2.25 vs 5.17; P = .014). A mutation count of less than 3 was associated with significantly better progression-free survival (17.2 vs 2.3 months; P = .002) and overall survival (29.4 vs 4.6 months; P = .013). Tumor mutational burden did not differ between exceptional responders and controls (4.88 vs 5.70 mut/Mb; P = .39). CONCLUSION: A lower number of nonsynonymous mutations may correlate with exceptional outcomes in patients with pancreatic cancer. These findings should encourage future studies into genomic signatures of exceptional response.

Utility of an Artificial Intelligence Enabled Electrocardiogram for Risk Assessment in Liver Transplant Candidates.

BACKGROUND: Post-operative cardiac complications occur infrequently but contribute to mortality after liver transplantation (LT). Artificial intelligence-based algorithms based on electrocardiogram (AI-ECG) are attractive for use during pre-operative evaluation to screen for risk of post-operative cardiac complications, but their use for this purpose is unknown. AIMS: The aim of this study was to evaluate the performance of an AI-ECG algorithm in predicting cardiac factors such as asymptomatic left ventricular systolic dysfunction or potential for developing post-operative atrial fibrillation (AF) in cohorts of patients with end-stage liver disease either undergoing evaluation for transplant or receiving a liver transplant. METHODS: A retrospective study was performed in two consecutive adult cohorts of patients who were either evaluated for LT or underwent LT at a single center between 2017 and 2019. ECG were analyzed using an AI-ECG trained to recognize patterns from a standard 12-lead ECG which could identify the presence of left ventricular systolic dysfunction (LVEF < 50%) or subsequent atrial fibrillation. RESULTS: The performance of AI-ECG in patients undergoing LT evaluation is similar to that in a general population but was lower in the presence of prolonged QTc. AI-ECG analysis on ECG in sinus rhythm had an AUROC of 0.69 for prediction of de novo post-transplant AF. Although post-transplant cardiac dysfunction occurred in only 2.3% of patients in the study cohorts, AI-ECG had an AUROC of 0.69 for prediction of subsequent low left ventricular ejection fraction. CONCLUSIONS: A positive screen for low EF or AF on AI-ECG can alert to risk of post-operative cardiac dysfunction or predict new onset atrial fibrillation after LT. The use of an AI-ECG can be a useful adjunct in persons undergoing transplant evaluation that can be readily implemented in clinical practice.

Machine learning analysis of volatolomic profiles in breath can identify non-invasive biomarkers of liver disease: A pilot study.

Disease-related effects on hepatic metabolism can alter the composition of chemicals in the circulation and subsequently in breath. The presence of disease related alterations in exhaled volatile organic compounds could therefore provide a basis for non-invasive biomarkers of hepatic disease. This study examined the feasibility of using global volatolomic profiles from breath analysis in combination with supervised machine learning to develop signature pattern-based biomarkers for cirrhosis. Breath samples were analyzed using thermal desorption-gas chromatography-field asymmetric ion mobility spectroscopy to generate breathomic profiles. A standardized collection protocol and analysis pipeline was used to collect samples from 35 persons with cirrhosis, 4 with non-cirrhotic portal hypertension, and 11 healthy participants. Molecular features of interest were identified to determine their ability to classify cirrhosis or portal hypertension. A molecular feature score was derived that increased with the stage of cirrhosis and had an AUC of 0.78 for detection. Chromatographic breath profiles were utilized to generate machine learning-based classifiers. Algorithmic models could discriminate presence or stage of cirrhosis with a sensitivity of 88-92% and specificity of 75%. These results demonstrate the feasibility of volatolomic profiling to classify clinical phenotypes using global breath output. These studies will pave the way for the development of non-invasive biomarkers of liver disease based on volatolomic signatures found in breath.

Increased Incidence of Venous Thromboembolism with Cancer Immunotherapy.

BACKGROUND: Cancer immunotherapy is associated with several immune-related adverse events, but the relationship between immunotherapy and venous thromboembolism has not been thoroughly studied. METHODS: We conducted a retrospective cohort study of 1,686 patients who received immunotherapy for a variety of malignancies to determine the incidence of venous thromboembolism and the impact of venous thromboembolism on survival. To examine the potential role of inflammation in venous thromboembolism, we also profiled immune cells and plasma cytokines in blood samples obtained prior to initiation of immunotherapy in a sub-cohort of patients treated on clinical trials who subsequently did (N = 15), or did not (N = 10) develop venous thromboembolism. FINDINGS: Venous thromboembolism occurred while on immunotherapy in 404/1686 patients (24%) and was associated with decreased overall survival [HR=1.22 (95% CI 1.06-1.41), p<0.008]. Patients that developed venous thromboembolism had significantly higher pretreatment levels of myeloid-derived suppressor cells (5.382 ± 0.873 vs. 3.341 ± 0.3402, mean ± SEM; p=0.0045), interleukin 8 (221.2 ± 37.53 vs. 111.6 ± 25.36, mean ± SEM; p=0.016), and soluble vascular cell adhesion protein 1 (1210 ± 120.6 vs. 895.5 ± 53.34, mean ± SEM; p=0.0385). CONCLUSIONS: These findings demonstrate that venous thromboembolism is an underappreciated and important immune-related adverse event associated with cancer immunotherapy, and may implicate an interleukin 8 and myeloid-derived suppressor cell-driven pathway in pathogenesis.

Risk of thromboembolism in patients with ALK- and EGFR-mutant lung cancer: A cohort study.

INTRODUCTION: Thromboembolism (TE) is common in patients with non-small cell lung cancer (NSCLC) and is associated with worse outcomes. Recent advances in the understanding of NSCLC have led to the identification of molecular subtypes such as anaplastic lymphocyte kinase (ALK) and epidermal growth factor receptor (EGFR) mutations. The association of these subtypes with risk of TE has not been fully explored. METHODS: We conducted a retrospective cohort study of consecutive NSCLC patients seen at the Cleveland Clinic from July 2002 through July 2017 for whom molecular classification and follow-up were available. TE events included deep vein thrombosis (DVT), pulmonary embolism (PE), visceral vein thrombosis (VVT), and arterial events. TE-free survival and overall survival rates for each of the molecular subtypes (wild-type, ALK-mutant, and EGFR-mutant) were estimated by the Kaplan-Meier method. Cox proportional hazard regression analysis was used to identify factors associated with the endpoints TE and overall survival. TE was analyzed as a conditional, time-dependent covariate to assess its impact with respect to overall survival. RESULTS: The study population consisted of 461 patients. Approximately half were females (n = 263, 57%) and 58% (n = 270) were older than 65 years. TE occurred in 98 of 461 patients (21.3%) during a median follow-up of 33.1 months. The highest cumulative rates of TE were observed in patients with ALK-mutant NSCLC (N = 20/46, 43.5%) followed by patients with EGFR-mutant cancers (N = 35/165, 21.2%) and wild-type cancers (N = 43/250, 17.2%) P < .05. Cumulative incidence of TE at 6 months of follow-up was 15.7% (95% confidence interval [CI]: 5.0%-26.4%) for ALK-mutant cancers, 8.8% (95% CI: 4.4%-13.2%) for EGFR-mutant cancers, and 9.2% (95% CI: 5.4%-12.9%) for wild-type cancers. Patients who experienced TE had worse overall survival (all patients: hazard ratio = 2.8 95% CI 2.1-3.6, P < .001). CONCLUSIONS: Patients with ALK-mutant advanced lung adenocarcinoma have the highest rate of TE. TE is associated with worse survival across molecular subtypes. These findings should be taken into consideration in decision-making regarding thromboprophylaxis.

Dose-adjusted enoxaparin thromboprophylaxis in hospitalized cancer patients: a randomized, double-blinded multicenter phase 2 trial.

Hospitalized patients with cancer are at an increased risk of developing venous thromboembolism (VTE). The recommendation for routine pharmacologic thromboprophylaxis in hospitalized patients with cancer to prevent VTE is based on extrapolation of results from noncancer cohorts. There are limited data to support the efficacy and safety of fixed-dose low-molecular-weight heparin (LMWH) regimens in high-risk hospitalized patients with cancer. We conducted a randomized, double-blinded, phase 2 trial in hospitalized patients with active cancer at high risk of developing VTE based on Padua risk score. Patients were randomly assigned to fixed-dose enoxaparin (40 mg daily) vs weight-adjusted enoxaparin (1 mg/kg daily) during hospitalization. The primary objectives were to evaluate the safety of dose-adjusted enoxaparin and evaluate the incidence of VTE with fixed-dose enoxaparin. Blinded clinical assessments were performed at day 14, and patients randomly assigned to fixed-dose enoxaparin subsequently underwent a bilateral lower extremity ultrasound. A total of 50 patients were enrolled and randomized. The median weight of patients enrolled in weight-adjusted enoxaparin arm was 76 kg (range, 60.9-124.5 kg). There were no major hemorrhages or symptomatic VTE in either arm. At time of completion of the blinded clinical assessment, there was only 1 incidentally identified pulmonary embolus that occurred in the weight-adjusted arm. In the group randomly assigned to fixed-dose enoxaparin who subsequently underwent surveillance ultrasound, the cumulative incidence of DVT was 22% (90% binomial confidence interval, 0%-51.3%). This phase 2 trial confirms a high incidence of asymptomatic VTE among high-risk hospitalized patients with cancer and that weight-adjusted LMWH thromboprophylaxis is feasible and well-tolerated. This trial was registered at www.clinicaltrials.gov as #NCT02706249.

Risk of Thrombosis in Cancer: Clinical Factors and Role of Primary Prophylaxis.

Cancer and its treatments are commonly complicated by venous thromboembolism (VTE), but there is a substantial variation in risk between individual cancer patients. The risk of VTE in cancer patients is influenced by multiple risk factors including primary site of cancer, stage, comorbidities, use of specific antineoplastic agents. Several biomarkers have been associated with subsequent VTE including D-dimer and tissue factor, although no single risk factor or biomarker accurately is predictive of VTE on its own. The risk of VTE is best predicted by a validated risk assessment score. Cancer patients at risk of VTE benefit from thromboprophylaxis, supported by evidence in the setting of hospitalization for acute medical illness and surgery, and emerging data from two large randomized trials in the outpatient setting. This chapter focuses on approaches to identifying risk of VTE and approaches to reducing this risk with appropriate thromboprophylaxis.