Introduction: Locally advanced non-small cell lung cancer (NSCLC) is highly resistant to chemoradiotherapy, and many cancer patients experience chronic stress. Studies that suggest stimulation of β-adrenergic receptors (β-AR) promotes tumor invasion and therapy resistance. We investigated whether β-AR inhibition with beta-blockers acts as a chemotherapy and radiation sensitizer in vitro and in patients treated with chemoradiation for locally advanced NSCLC. Methods: We investigated the effects of the non-selective beta-blocker propranolol on two human lung adenocarcinoma cell lines (PC9, A549) treated with radiation or cisplatin. We retrospectively evaluated 77 patients with Stage IIIA NSCLC who received induction chemoradiation followed by surgery. Pathological and imaging response, metastatic rate, and survival were analyzed using SPSS v22.0 and PrismGraphpad6. Results: Propranolol combined with radiation or cisplatin decreased clonogenic survival of PC9 and A549 cells in vitro (p < 0.05). Furthermore, propranolol decreased expression of phospho-protein kinase A (p-PKA), a β-adrenergic pathway downstream activation target, in both cell lines compared to irradiation or cisplatin alone (p < 0.05). In patients treated for Stage IIIA NSCLC, 16 took beta-blockers, and 61 did not. Beta-blockade is associated with a trend to improved overall survival (OS) at 1 year (81.3% vs 57.4%, p = 0.08) and distant metastasis-free survival (DMFS) (2.6 years vs. 1.3 years, p = 0.16). Although beta-blocker use was associated with decreased distant metastases (risk ratio (RR) 0.19; p = 0.03), it did not affect primary tumor pathological response (p = 0.40) or imaging response (p = 0.36). Conclusions: β-AR blockade enhanced radiation and cisplatin sensitivity of human lung cancer cells in vitro. Use of beta-blockers is associated with decreased distant metastases and potentially improved OS and DMFS. Additional studies are warranted to evaluate the role of beta-blockers as a chemoradiation sensitizer in locally advanced NSCLC.

All node positive vulvar cancer patients should benefit from and thus should receive adjuvant radiation, including those with one positive node.

BackgroundImmune checkpoint inhibitors (ICIs) are important new therapeutic options for the treatment of malignancy. Existing data on the relative safety of ICI treatment in patients with pre-existing autoimmune disease (AID) are limited.MethodsIn this retrospective study utilizing an oncology medical claims database, we determined the rates of treatment with immunosuppressive agents and hospitalization within 180 days of treatment with ICIs (pembrolizumab, nivolumab, and ipilimumab) in patients both with and without AID. Patients had diagnoses of either malignant melanoma or lung cancer. Immunosuppressive agents evaluated included oral prednisone and intravenous methylprednisolone.Results124 cancer patients with AID and 1896 cancer patients without AID met inclusion criteria for oral prednisone analysis, while 284 patients with AID and 3230 patients without AID met inclusion criteria for all other analyzes. Following treatment with PD-1 inhibitors, rates of treatment with both oral prednisone and intravenous methylprednisolone within 180 days of ICI treatment were significantly increased in the AID group relative to the control group (oral prednisone: 16.7% treatment in AID vs 8.3% in non-AID, p=0.0048; intravenous methylprednisolone: 8.4% treatment in AID vs 3.7% in non-AID, p=0.0012). Rates of hospitalization were significantly increased in melanoma patients with AID relative to melanoma patients without AID following treatment with PD-1 inhibitors (24.1% in AID vs 5.8% in non-AID, p<0.0001).ConclusionCancer patients with AID have higher rates of hospitalization and treatment with immunosuppressive agents following treatment with ICI therapy compared with patients with no AID. This suggests that patients with AID may have increased toxicity risk while being treated with checkpoint inhibitor therapy. Further prospective clinical trials are needed to determine safety.

BackgroundTreatment with immune checkpoint inhibitors (ICIs) has been associated with an increased rate of cardiac events. There are limited data on the risk factors that predict cardiac events in patients treated with ICIs. Therefore, we created a machine learning (ML) model to predict cardiac events in this at-risk population.MethodsWe leveraged the CancerLinQ database curated by the American Society of Clinical Oncology and applied an XGBoosted decision tree to predict cardiac events in patients taking programmed death receptor-1 (PD-1) or programmed death ligand-1 (PD-L1) therapy. All curated data from patients with non-small cell lung cancer, melanoma, and renal cell carcinoma, and who were prescribed PD-1/PD-L1 therapy between 2013 and 2019, were used for training, feature interpretation, and model performance evaluation. A total of 356 potential risk factors were included in the model, including elements of patient medical history, social history, vital signs, common laboratory tests, oncological history, medication history and PD-1/PD-L1-specific factors like PD-L1 tumor expression.ResultsOur study population consisted of 4960 patients treated with PD-1/PD-L1 therapy, of whom 418 had a cardiac event. The following were key predictors of cardiac events: increased age, corticosteroids, laboratory abnormalities and medications suggestive of a history of heart disease, the extremes of weight, a lower baseline or on-treatment percentage of lymphocytes, and a higher percentage of neutrophils. The final model predicted cardiac events with an area under the curve–receiver operating characteristic of 0.65 (95% CI 0.58 to 0.75). Using our model, we divided patients into low-risk and high-risk subgroups. At 100 days, the cumulative incidence of cardiac events was 3.3% in the low-risk group and 6.1% in the high-risk group (p<0.001).ConclusionsML can be used to predict cardiac events in patients taking PD-1/PD-L1 therapy. Cardiac risk was driven by immunological factors (eg, percentage of lymphocytes), oncological factors (eg, low weight), and a cardiac history.

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