In silico clinical studies for optimal COVID-19 vaccination schedules in patients with cancer.

This study introduces a tailored COVID-19 model for patients with cancer, incorporating viral variants and immune-response dynamics. The model aims to optimize vaccination strategies, contributing to personalized healthcare for vulnerable groups.

Mechanistic model for booster doses effectiveness in healthy, cancer, and immunosuppressed patients infected with SARS-CoV-2.

SARS-CoV-2 vaccines are effective at limiting disease severity, but effectiveness is lower among patients with cancer or immunosuppression. Effectiveness wanes with time and varies by vaccine type. Moreover, previously prescribed vaccines were based on the ancestral SARS-CoV-2 spike-protein that emerging variants may evade. Here, we describe a mechanistic mathematical model for vaccination-induced immunity. We validate it with available clinical data and use it to simulate the effectiveness of vaccines against viral variants with lower antigenicity, increased virulence, or enhanced cell binding for various vaccine platforms. The analysis includes the omicron variant as well as hypothetical future variants with even greater immune evasion of vaccine-induced antibodies and addresses the potential benefits of the new bivalent vaccines. We further account for concurrent cancer or underlying immunosuppression. The model confirms enhanced immunogenicity following booster vaccination in immunosuppressed patients but predicts ongoing booster requirements for these individuals to maintain protection. We further studied the impact of variants on immunosuppressed individuals as a function of the interval between multiple booster doses. Our model suggests possible strategies for future vaccinations and suggests tailored strategies for high-risk groups.

Utility of Noncancerous Chest CT Features for Predicting Overall Survival and Noncancer Death in Patients With Stage I Lung Cancer Treated With Stereotactic Body Radiotherapy.

BACKGROUND. Noncancerous imaging markers can be readily derived from pre-treatment diagnostic and radiotherapy planning chest CT examinations. OBJECTIVE. The purpose of this article was to explore the ability of noncancerous features on chest CT to predict overall survival (OS) and noncancer-related death in patients with stage I lung cancer treated with stereotactic body radiation therapy (SBRT). METHODS. This retrospective study included 282 patients (168 female, 114 male; median age, 75 years) with stage I lung cancer treated with SBRT between January 2009 and June 2017. Pretreatment chest CT was used to quantify coronary artery calcium (CAC) score, pulmonary artery (PA)-to-aorta ratio, emphysema, and body composition in terms of the cross-sectional area and attenuation of skeletal muscle and subcutaneous adipose tissue at the T5, T8, and T10 vertebral levels. Associations of clinical and imaging features with OS were quantified using a multivariable Cox proportional hazards (PH) model. Penalized multivariable Cox PH models to predict OS were constructed using clinical features only and using both clinical and imaging features. The models' discriminatory ability was assessed by constructing time-varying ROC curves and computing AUC at prespecified times. RESULTS. After a median OS of 60.8 months (95% CI, 55.8-68.0), 148 (52.5%) patients had died, including 83 (56.1%) with noncancer deaths. Higher CAC score (11-399: hazard ratio [HR], 1.83 [95% CI, 1.15-2.91], p = .01; ≥ 400: HR, 1.63 [95% CI, 1.01-2.63], p = .04), higher PA-to-aorta ratio (HR, 1.33 [95% CI, 1.16-1.52], p < .001, per 0.1-unit increase), and lower thoracic skeletal muscle index (HR, 0.88 [95% CI, 0.79-0.98], p = .02, per 10-cm2/m2 increase) were independently associated with shorter OS. Discriminatory ability for 5-year OS was greater for the model including clinical and imaging features than for the model including clinical features only (AUC, 0.75 [95% CI, 0.68-0.83] vs 0.61 [95% CI, 0.53-0.70]; p < .01). The model's most important clinical or imaging feature according to mean standardized regression coefficients was the PA-to-aorta ratio. CONCLUSION. In patients undergoing SBRT for stage I lung cancer, higher CAC score, higher PA-to-aorta ratio, and lower thoracic skeletal muscle index independently predicted worse OS. CLINICAL IMPACT. Noncancerous imaging features on chest CT performed before SBRT improve survival prediction compared with clinical features alone.

Incidence of Radiation Therapy Among Patients Enrolled in a Multidisciplinary Pulmonary Nodule and Lung Cancer Screening Clinic.

Importance: The number of pulmonary nodules discovered incidentally or through screening programs has increased markedly. Multidisciplinary review and management are recommended, but the involvement of radiation oncologists in this context has not been defined. Objective: To assess the role of stereotactic body radiation therapy among patients enrolled in a lung cancer screening program. Design, Setting, and Participants: This prospective cohort study was performed at a pulmonary nodule and lung cancer screening clinic from October 1, 2012, to September 31, 2019. Referrals were based on chest computed tomography with Lung Imaging Reporting and Data System category 4 finding or an incidental nodule 6 mm or larger. A multidisciplinary team of practitioners from radiology, thoracic surgery, pulmonology, medical oncology, and radiation oncology reviewed all nodules and coordinated workup and treatment as indicated. Exposures: Patients referred to the pulmonary nodule and lung cancer screening clinic with an incidental or screen-detected pulmonary nodule. Main Outcomes and Measures: The primary outcome was the proportion of patients undergoing therapeutic intervention with radiation therapy, stratified by the route of detection of their pulmonary nodules (incidental vs screen detected). Secondary outcomes were 2-year local control and metastasis-free survival. Results: Among 1150 total patients (median [IQR] age, 66.5 [59.3-73.7] years; 665 [57.8%] female; 1024 [89.0%] non-Hispanic White; 841 [73.1%] current or former smokers), 234 (20.3%) presented with screen-detected nodules and 916 (79.7%) with incidental nodules. For patients with screen-detected nodules requiring treatment, 41 (17.5%) received treatment, with 31 (75.6%) undergoing surgery and 10 (24.4%) receiving radiation therapy. Patients treated with radiation therapy were older (median [IQR] age, 73.8 [67.1 to 82.1] vs 67.6 [61.0 to 72.9] years; P < .001) and more likely to have history of tobacco use (67 [95.7%] vs 128 [76.6%]; P = .001) than those treated with surgery. Fifty-eight patients treated with radiation therapy (82.9%) were considered high risk for biopsy, and treatment recommendations were based on a clinical diagnosis of lung cancer after multidisciplinary review. All screened patients who received radiation therapy had stage I disease and were treated with stereotactic body radiation therapy. For all patients receiving stereotactic body radiation therapy, 2-year local control was 96.3% (95% CI, 91.1%-100%) and metastasis-free survival was 94.2% (95% CI, 87.7%-100%). Conclusions and Relevance: In this unique prospective cohort, 1 in 4 patients with screen-detected pulmonary nodules requiring intervention were treated with stereotactic body radiation therapy. This finding highlights the role of radiation therapy in a lung cancer screening population and the importance of including radiation oncologists in the multidisciplinary management of pulmonary nodules.

Strategies to minimize heterogeneity and optimize clinical trials in Acute Respiratory Distress Syndrome (ARDS): Insights from mathematical modelling.

BACKGROUND: Mathematical modelling may aid in understanding the complex interactions between injury and immune response in critical illness. METHODS: We utilize a system biology model of COVID-19 to analyze the effect of altering baseline patient characteristics on the outcome of immunomodulatory therapies. We create example parameter sets meant to mimic diverse patient types. For each patient type, we define the optimal treatment, identify biologic programs responsible for clinical responses, and predict biomarkers of those programs. FINDINGS: Model states representing older and hyperinflamed patients respond better to immunomodulation than those representing obese and diabetic patients. The disparate clinical responses are driven by distinct biologic programs. Optimal treatment initiation time is determined by neutrophil recruitment, systemic cytokine expression, systemic microthrombosis and the renin-angiotensin system (RAS) in older patients, and by RAS, systemic microthrombosis and trans IL6 signalling for hyperinflamed patients. For older and hyperinflamed patients, IL6 modulating therapy is predicted to be optimal when initiated very early (<4th day of infection) and broad immunosuppression therapy (corticosteroids) is predicted to be optimally initiated later in the disease (7th - 9th day of infection). We show that markers of biologic programs identified by the model correspond to clinically identified markers of disease severity. INTERPRETATION: We demonstrate that modelling of COVID-19 pathobiology can suggest biomarkers that predict optimal response to a given immunomodulatory treatment. Mathematical modelling thus constitutes a novel adjunct to predictive enrichment and may aid in the reduction of heterogeneity in critical care trials. FUNDING: C.V. received a Marie Sklodowska Curie Actions Individual Fellowship (MSCA-IF-GF-2020-101028945). R.K.J.'s research is supported by R01-CA208205, and U01-CA 224348, R35-CA197743 and grants from the National Foundation for Cancer Research, Jane's Trust Foundation, Advanced Medical Research Foundation and Harvard Ludwig Cancer Center. No funder had a role in production or approval of this manuscript.

Heterogeneous immunogenicity of SARS-CoV-2 vaccines in cancer patients receiving radiotherapy.

The immunogenicity of SARS-CoV-2 vaccines in cancer patients receiving radiotherapy is unknown. This prospective cohort study demonstrates that anti-SARS-CoV-2 spike antibody and neutralization titers are reduced in a subset of thoracic radiotherapy patients, possibly due to immunosuppressive conditions. Antibody testing may be useful to identify candidates for additional vaccine doses.

Automated clinical target volume delineation using deep 3D neural networks in radiation therapy of Non-small Cell Lung Cancer.

BACKGROUND AND PURPOSE: Clinical targeted volume (CTV) delineation accounting for the patient-specific microscopic tumor spread can be a difficult step in defining the treatment volume. We developed an intelligent and automated CTV delineation system for locally advanced non-small cell lung carcinoma (NSCLC) to cover the microscopic tumor spread while avoiding organs-at-risk (OAR). MATERIALS AND METHODS: A 3D UNet with a customized loss function was used, which takes both the patients' respiration-correlated ("4D") CT scan and the physician contoured internal gross target volume (iGTV) as inputs, and outputs the CTV delineation. Among the 84 identified patients, 60 were randomly selected to train the network, and the remaining as testing. The model performance was evaluated and compared with cropped expansions using the shape similarities to the physicians' contours (the ground-truth) and the avoidance of critical OARs. RESULTS: On the testing datasets, all model-predicted CTV contours followed closely to the ground truth, and were acceptable by physicians. The average dice score was 0.86. Our model-generated contours demonstrated better agreement with the ground-truth than the cropped 5 mm/8 mm expansion method (median of median surface distance of 1.0 mm vs 1.9 mm/2.0 mm), with a small overlap volume with OARs (0.4 cm3 for the esophagus and 1.2 cm3 for the heart). CONCLUSIONS: The CTVs generated by our CTV delineation system agree with the physician's contours. This approach demonstrates the capability of intelligent volumetric expansions with the potential to be used in clinical practice.

Results and Molecular Correlates from a Pilot Study of Neoadjuvant Induction FOLFIRINOX Followed by Chemoradiation and Surgery for Gastroesophageal Adenocarcinomas.

PURPOSE: We performed a NCI-sponsored, prospective study of neoadjuvant FOLFIRINOX followed by chemoradiation with carboplatin/paclitaxel followed by surgery in patients with locally advanced gastric or gastroesophageal cancer. PATIENTS AND METHODS: The primary objective was to determine completion rate of neoadjuvant FOLFIRINOX × 8 followed by chemoradiation. Secondary endpoints were toxicity and pathologic complete response (pCR) rate. Exploratory analysis was performed of circulating tumor DNA (ctDNA) to treatment response. RESULTS: From October 2017 to June 2018, 25 patients were enrolled. All patients started FOLFIRINOX, 92% completed all eight planned cycles, and 88% completed chemoradiation. Twenty (80%) patients underwent surgical resection, and 7 had a pCR (35% in resected cohort, 28% intention to treat). Tumor-specific mutations were identified in 21 (84%) patients, of whom 4 and 17 patients had undetectable and detectable ctDNA at baseline, respectively. Presence of detectable post-chemoradiation ctDNA (P = 0.004) and/or postoperative ctDNA (P = 0.045) were associated with disease recurrence. CONCLUSIONS: Here we show neoadjuvant FOLFIRINOX followed by chemoradiation for locally advanced gastroesophageal cancer is feasible and yields a high rate of pCR. ctDNA appears to be a promising predictor of postoperative recurrence.See related commentary by Catenacci, p. 6281.

Comparing machine learning algorithms for predicting ICU admission and mortality in COVID-19.

As predicting the trajectory of COVID-19 is challenging, machine learning models could assist physicians in identifying high-risk individuals. This study compares the performance of 18 machine learning algorithms for predicting ICU admission and mortality among COVID-19 patients. Using COVID-19 patient data from the Mass General Brigham (MGB) Healthcare database, we developed and internally validated models using patients presenting to the Emergency Department (ED) between March-April 2020 (n = 3597) and further validated them using temporally distinct individuals who presented to the ED between May-August 2020 (n = 1711). We show that ensemble-based models perform better than other model types at predicting both 5-day ICU admission and 28-day mortality from COVID-19. CRP, LDH, and O2 saturation were important for ICU admission models whereas eGFR <60 ml/min/1.73 m2, and neutrophil and lymphocyte percentages were the most important variables for predicting mortality. Implementing such models could help in clinical decision-making for future infectious disease outbreaks including COVID-19.

Assessment of a Contralateral Esophagus-Sparing Technique in Locally Advanced Lung Cancer Treated With High-Dose Chemoradiation: A Phase 1 Nonrandomized Clinical Trial.

IMPORTANCE: Severe acute esophagitis occurs in up to 20% of patients with locally advanced lung cancer treated with chemoradiation therapy to at least 60 Gy once daily and represents a dose-limiting toxic event associated with poor outcomes. OBJECTIVE: To assess whether formalized sparing of the contralateral esophagus (CE) is associated with reduced risk of severe acute esophagitis. DESIGN, SETTING, AND PARTICIPANTS: This single-center phase 1 nonrandomized clinical trial assessing an empirical CE-sparing technique enrolled patients from July 2015 to January 2019. In total, 27 patients with locally advanced non-small cell lung carcinoma (with or without solitary brain metastasis) or limited-stage small cell lung carcinoma with gross tumor within 1 cm of the esophagus were eligible. INTERVENTIONS: Intensity-modulated radiation therapy to 70 Gy at 2 Gy/fraction concurrent with standard chemotherapy with or without adjuvant durvalumab. The esophageal wall contralateral to gross tumor was contoured as an avoidance structure to guide a steep dose falloff gradient. Target coverage was prioritized over CE sparing, and 99% of internal and planning target volumes had to be covered by 70 Gy and at least 63 Gy, respectively. MAIN OUTCOMES AND MEASURES: The primary end point was the rate of at least grade 3 acute esophagitis as assessed by Common Terminology Criteria for Adverse Events, version 4. RESULTS: Of 27 patients enrolled, 25 completed chemoradiation therapy. Nineteen patients had non-small cell lung carcinoma, and 6 had small cell lung carcinoma. The median age at diagnosis was 67 years (range, 51-81 years), and 15 patients (60%) were men. Thirteen patients (52%) had stage IIIA cancer, 10 (40%) had stage IIIB cancer, and 2 (8%) had stage IV cancer. The median CE maximum dose was 66 Gy (range, 44-71 Gy); the median volume of CE receiving at least 55 Gy was 1.4 cm3 (range, 0-5.3 cm3), and the median volume of CE receiving at least 45 Gy was 2.7 cm3 (range, 0-9.2 cm3). The median combined percentage of lung receiving at least 20 Gy was 25% (range, 11%-37%). The median follow-up was 33.3 months (range, 11.1-52.2 months). Among the 20 patients who had treatment breaks of 0 to 3 days and were thus evaluable for the primary end point, the rate of at least grade 3 esophagitis was 0%. Other toxic events observed among all 25 patients included 7 (28%) with grade 2 esophagitis, 3 (12%) with at least grade 2 pneumonitis (including 1 with grade 5), and 2 (8%) with at least grade 3 cardiac toxic event (including 1 with grade 5). There was no isolated local tumor failure. The 2-year progression-free survival rate was 57% (95% CI, 33%-75%), and the 2-year overall survival rate was 67% (95% CI, 45%-82%). CONCLUSIONS AND RELEVANCE: This phase 1 nonrandomized clinical trial found that the CE-sparing technique was associated with reduced risk of esophagitis among patients treated uniformly with chemoradiation therapy (to 70 Gy), with no grade 3 or higher esophagitis despite tumor within 1 cm of the esophagus. This technique may be translated into clinical practice. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02394548.

Vascular Normalization to Improve Treatment of COVID-19: Lessons from Treatment of Cancer.

The dramatic impact of the COVID-19 pandemic has resulted in an "all hands on deck" approach to find new therapies to improve outcomes in this disease. In addition to causing significant respiratory pathology, infection with SARS-CoV-2 (like infection with other respiratory viruses) directly or indirectly results in abnormal vasculature, which may contribute to hypoxemia. These vascular effects cause significant morbidity and may contribute to mortality from the disease. Given that abnormal vasculature and poor oxygenation are also hallmarks of solid tumors, lessons from the treatment of cancer may help identify drugs that can be repurposed to treat COVID-19. Although the mechanisms that result in vascular abnormalities in COVID-19 are not fully understood, it is possible that there is dysregulation of many of the same angiogenic and thrombotic pathways as seen in patients with cancer. Many anticancer therapeutics, including androgen deprivation therapy (ADT) and immune checkpoint blockers (ICB), result in vascular normalization in addition to their direct effects on tumor cells. Therefore, these therapies, which have been extensively explored in clinical trials of patients with cancer, may have beneficial effects on the vasculature of patients with COVID-19. Furthermore, these drugs may have additional effects on the disease course, as some ADTs may impact viral entry, and ICBs may accelerate T-cell-mediated viral clearance. These insights from the treatment of cancer may be leveraged to abrogate the vascular pathologies found in COVID-19 and other forms of hypoxemic respiratory failure.

In silico dynamics of COVID-19 phenotypes for optimizing clinical management.

Understanding the underlying mechanisms of COVID-19 progression and the impact of various pharmaceutical interventions is crucial for the clinical management of the disease. We developed a comprehensive mathematical framework based on the known mechanisms of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, incorporating the renin-angiotensin system and ACE2, which the virus exploits for cellular entry, key elements of the innate and adaptive immune responses, the role of inflammatory cytokines, and the coagulation cascade for thrombus formation. The model predicts the evolution of viral load, immune cells, cytokines, thrombosis, and oxygen saturation based on patient baseline condition and the presence of comorbidities. Model predictions were validated with clinical data from healthy people and COVID-19 patients, and the results were used to gain insight into identified risk factors of disease progression including older age; comorbidities such as obesity, diabetes, and hypertension; and dysregulated immune response. We then simulated treatment with various drug classes to identify optimal therapeutic protocols. We found that the outcome of any treatment depends on the sustained response rate of activated CD8+ T cells and sufficient control of the innate immune response. Furthermore, the best treatment-or combination of treatments-depends on the preinfection health status of the patient. Our mathematical framework provides important insight into SARS-CoV-2 pathogenesis and could be used as the basis for personalized, optimal management of COVID-19.

Low Rates of Chest Wall Toxicity When Individualizing the Planning Target Volume Margin in Patients With Early Stage Lung Cancer Treated With Stereotactic Body Radiation Therapy.

PURPOSE: Chest wall (CW) toxicity is a potentially debilitating complication of stereotactic body radiation therapy for non-small cell lung cancer, occurring in 10% to 40% of patients. Smaller tumor-to-CW distance has been identified as a risk factor for CW toxicity. We report our experience with individualizing the planning target volume (PTV) along the CW in an effort to reduce the volume of this organ at risk receiving 30 Gy to 50 Gy. METHODS AND MATERIALS: We performed an institutional review board-approved retrospective analysis of patients with stage I (T1-2aN0M0) non-small cell lung cancer who received stereotactic body radiation therapy between June 2009 and July 2016. Four-dimensional computed tomography was used for treatment planning. A uniform 5-mm expansion of the internal target volume was generated for the PTV. Areas of overlap with the CW were removed from the PTV. Treatment was delivered with cone beam computed tomography guidance. CW toxicity was assessed per the Common Terminology Criteria for Adverse Events, version 5. Descriptive statistics were used to analyze outcomes. RESULTS: The median follow-up time was 36.8 months. A total of 260 tumors were treated in 225 patients. 225 tumors in 203 patients were peripheral. The internal target volumes for 143 tumors (63.6%) were located within 5 mm of the CW. The median total dose was 48 Gy (range, 42-60 Gy) in 4 fractions (range, 3-5 fractions). The overall rate of grade 1 to 2 CW toxicity was 2.2%, and 2.8% for tumors located within 5 mm of the CW. There were no grade 3/4 cases and no increase in local recurrences with the use of a truncated PTV with a 3-year local control of 92.1% (95% confidence interval, 87.4%-96.8%). CONCLUSIONS: Truncation of the PTV margin along the CW resulted in a marked reduction of CW toxicity for tumors in close proximity to the CW, with only a 2.8% rate of grade 1 to 2 CW toxicity. Despite PTV reduction, there was no appreciable increase in local failures. A multi-institutional validation of this technique is needed before general incorporation into clinical practice.

In silico dynamics of COVID-19 phenotypes for optimizing clinical management.

Understanding the underlying mechanisms of COVID-19 progression and the impact of various pharmaceutical interventions is crucial for the clinical management of the disease. We developed a comprehensive mathematical framework based on the known mechanisms of the SARS-CoV-2 virus infection, incorporating the renin-angiotensin system and ACE2, which the virus exploits for cellular entry, key elements of the innate and adaptive immune responses, the role of inflammatory cytokines and the coagulation cascade for thrombus formation. The model predicts the evolution of viral load, immune cells, cytokines, thrombosis, and oxygen saturation based on patient baseline condition and the presence of co-morbidities. Model predictions were validated with clinical data from healthy people and COVID-19 patients, and the results were used to gain insight into identified risk factors of disease progression including older age, co-morbidities such as obesity, diabetes, and hypertension, and dysregulated immune response 1,2 . We then simulated treatment with various drug classes to identify optimal therapeutic protocols. We found that the outcome of any treatment depends on the sustained response rate of activated CD8 + T cells and sufficient control of the innate immune response. Furthermore, the best treatment -or combination of treatments - depends on the pre-infection health status of the patient. Our mathematical framework provides important insight into SARS-CoV-2 pathogenesis and could be used as the basis for personalized, optimal management of COVID-19.

Differential inflammatory response dynamics in normal lung following stereotactic body radiation therapy with protons versus photons.

BACKGROUND AND PURPOSE: To compare time-dependent changes in lung parenchyma of early-stage non-small cell lung carcinoma (NSCLC) patients after stereotactic body radiation therapy with protons (SBPT) or photons (SBRT). MATERIALS AND METHOD: We retrospectively identified NSCLC patients treated with SBPT and matched each one with a SBRT patient by patient, tumor, and treatment characteristics. Lung parenchyma on serial post-treatment chest computer tomography (CT) scans was deformably registered with the treatment plan to analyze lung density changes as function of dose, quantified by Houndsfield Unit (HU)/Gy. A thoracic radiologist also evaluated the CTs using an established grading system. RESULTS: We matched 23 SBPT/SBRT pairs, including 5 patients treated with both modalities (internally matched cohort). Normal lung response following SBPT significantly increased in the early time period (CTs acquired <6 months, median 3 months) post-treatment, and then did not change significantly in the later time period (CTs acquired 6-14 months, median 9 months). For SBRT, the normal lung response was similar to SBPT in the early time period, but then increased significantly from the early to the late time period (p = 0.007). These differences were most pronounced in sensitive (response >6 HU/Gy) patients and in the internally matched cohort. However, there was no significant difference in the maximum observed response in the entire cohort over all time periods, median 3.4 [IQR, 1.0-5.4] HU/Gy (SBPT) versus 2.5 [1.6-5.2] HU/Gy (SBRT). Qualitative radiological evaluation was highly correlated with the quantitative analysis (p < 0.0001). CONCLUSION: While there was no significant difference in maximum response after SBPT versus SBRT, dose-defined lung inflammation occurred earlier after proton irradiation. Further investigation is warranted into the mechanisms of inflammation and therapeutic consequences after proton versus photon irradiation.

Role of Epidermal Growth Factor Receptor (EGFR) Inhibitors and Radiation in the Management of Brain Metastases from EGFR Mutant Lung Cancers.

The growth of genotype-directed targeted therapies, such as inhibitors of the epidermal growth factor receptor (EGFR), has revolutionized treatment for some patients with oncogene-addicted lung cancer. However, as systemic control for these patients has improved, brain metastases remain an important source of morbidity and mortality. Traditional treatment for brain metastases has been radiotherapy, either whole-brain radiation or stereotactic radiosurgery. The growing availability of drugs that can cross the blood-brain barrier and have activity in the central nervous system (CNS) has led to many studies investigating whether targeted therapy can be used in combination with or in lieu of radiation. In this review, we summarize the key literature about the incidence and nature of EGFR-mutant brain metastases (EGFR BMs), the data about the activity of EGFR inhibitors in the CNS, and whether they can be used as front-line therapy for brain metastases. Although initial use of tyrosine kinase inhibitors for EGFR BMs can often be an effective treatment strategy, multidisciplinary evaluation is critical, and prospective studies are needed to clarify which patients may benefit from early radiotherapy. IMPLICATIONS FOR PRACTICE: Management of brain metastases in epidermal growth factor receptor (EGFR) mutant lung cancer is a common clinical problem. The question of whether to start initial therapy with an EGFR inhibitor or radiotherapy (either whole-brain radiotherapy or stereotactic radiosurgery) is controversial. The development of novel EGFR inhibitors with enhanced central nervous system (CNS) penetration is an important advance in the treatment of CNS disease. Multidisciplinary evaluation and evaluation of extracranial disease status are critical to choosing the best treatment option for each patient.

Noncanonical agonist PPARγ ligands modulate the response to DNA damage and sensitize cancer cells to cytotoxic chemotherapy.

The peroxisome-proliferator receptor-γ (PPARγ) is expressed in multiple cancer types. Recently, our group has shown that PPARγ is phosphorylated on serine 273 (S273), which selectively modulates the transcriptional program controlled by this protein. PPARγ ligands, including thiazolidinediones (TZDs), block S273 phosphorylation. This activity is chemically separable from the canonical activation of the receptor by agonist ligands and, importantly, these noncanonical agonist ligands do not cause some of the known side effects of TZDs. Here, we show that phosphorylation of S273 of PPARγ occurs in cancer cells on exposure to DNA damaging agents. Blocking this phosphorylation genetically or pharmacologically increases accumulation of DNA damage, resulting in apoptotic cell death. A genetic signature of PPARγ phosphorylation is associated with worse outcomes in response to chemotherapy in human patients. Noncanonical agonist ligands sensitize lung cancer xenografts and genetically induced lung tumors to carboplatin therapy. Moreover, inhibition of this phosphorylation results in deregulation of p53 signaling, and biochemical studies show that PPARγ physically interacts with p53 in a manner dependent on S273 phosphorylation. These data implicate a role for PPARγ in modifying the p53 response to cytotoxic therapy, which can be modulated for therapeutic gain using these compounds.

Adipsin is an adipokine that improves ß cell function in diabetes.

A hallmark of type 2 diabetes mellitus (T2DM) is the development of pancreatic ß cell failure, which results in insulinopenia and hyperglycemia. We show that the adipokine adipsin has a beneficial role in maintaining ß cell function. Animals genetically lacking adipsin have glucose intolerance due to insulinopenia; isolated islets from these mice have reduced glucose-stimulated insulin secretion. Replenishment of adipsin to diabetic mice treated hyperglycemia by boosting insulin secretion. We identify C3a, a peptide generated by adipsin, as a potent insulin secretagogue and show that the C3a receptor is required for these beneficial effects of adipsin. C3a acts on islets by augmenting ATP levels, respiration, and cytosolic free Ca(2+). Finally, we demonstrate that T2DM patients with ß cell failure are deficient in adipsin. These findings indicate that the adipsin/C3a pathway connects adipocyte function to ß cell physiology, and manipulation of this molecular switch may serve as a therapy in T2DM.