Background: In this study, we evaluated the potential of DNA polymerase epsilon (POLE) and DNA polymerase delta 1 (POLD1) as prognostic biomarkers for immune checkpoint inhibitor (ICI) treatment in patients with advanced stage non‐small cell lung cancer (NSCLC).Methods: Disease stage, PD‐L1 positivity, histological subtypes, POLE/POLD1 mutation status, tumor mutation burden (TMB), and response to ICIs in NSCLC cases were derived from AACR GENIE dataset (n = 24 120), TCGA‐Pan Lung Cancer dataset (n = 1144), AACR GENIE BPC NSCLC v2.0‐public (n = 2004), and Memorial Sloan Kettering‐Integrated Mutation Profiling of Actionable Cancer Targets dataset (n = 350). The smoking history from TCGA and AACR GENIE datasets was grouped into current, former or never‐smokers.Results: POLE and POLD1 genetic alterations were identified in 5% and 2.6% of NSCLC patients, respectively. Current smokers had 9% and 4% of POLE/POLD1 mutations, respectively, versus 1.7% for both POLE and POLD1 mutations prevalence in never‐smokers. POLE/POLD1 mutations were associated with elevated mutation counts than those with wild‐type (median mutation counts 16 vs. 7, p < 0.0001), more advanced disease stages (stage I disease 15.19% vs. 29.42%), more prevalent squamous histology subtype (21.69% vs. 9.05%, p = 0.0427), and a higher percentage of PD‐L1 positivity (66.67% vs. 43.87%, p < 0.001). Treatment with ICIs improved survival in patients with both POLE/POLD1 mutated and those with TMB > 18 (p < 0.001).Conclusion: Current smokers have a five‐fold increased risk of having POLE mutations than never‐smokers. POLE/POLD1 mutation status and TMB > 18 can be a composite biomarker for selecting NSCLC patients with survival benefits to ICI treatment.

Identification of isocitrate dehydrogenase (IDH)-mutant glioma patients at high risk of early progression is critical for radiotherapy treatment planning. Currently tools to stratify risk of early progression are lacking. We sought to identify a combination of molecular markers that could be used to identify patients who may have a greater need for adjuvant radiation therapy machine learning technology. 507 WHO Grade 2 and 3 glioma cases from The Cancer Genome Atlas, and 1309 cases from AACR GENIE v13.0 datasets were studied for genetic disparities between IDH1-wildtype and IDH1-mutant cohorts, and between different age groups. Genetic features such as mutations and copy number variations (CNVs) correlated with IDH1 mutation status were selected as potential inputs to train artificial neural networks (ANNs) to predict IDH1 mutation status. Grade 2 and 3 glioma cases from the Memorial Sloan Kettering dataset (n = 404) and Grade 3 glioma cases with subtotal resection (STR) from Northwestern University (NU) (n = 21) were used to further evaluate the best performing ANN model as independent datasets. IDH1 mutation is associated with decreased CNVs of EGFR (21% vs. 3%), CDKN2A (20% vs. 6%), PTEN (14% vs. 1.7%), and increased percentage of mutations for TP53 (15% vs. 63%), and ATRX (10% vs. 54%), which were all statistically significant (p < 0.001). Age > 40 was unable to identify high-risk IDH1-mutant with early progression. A glioma early progression risk prediction (GlioPredictor) score generated from the best performing ANN model (6/6/6/6/2/1) with 6 inputs, including CNVs of EGFR, PTEN and CDKN2A, mutation status of TP53 and ATRX, patient’s age can predict IDH1 mutation status with over 90% accuracy. The GlioPredictor score identified a subgroup of high-risk IDH1-mutant in TCGA and NU datasets with early disease progression (p = 0.0019, 0.0238, respectively). The GlioPredictor that integrates age at diagnosis, CNVs of EGFR, CDKN2A, PTEN and mutation status of TP53, and ATRX can identify a small cohort of IDH-mutant with high risk of early progression. The current version of GlioPredictor mainly incorporated clinically often tested genetic biomarkers. Considering complexity of clinical and genetic features that correlate with glioma progression, future derivatives of GlioPredictor incorporating more inputs can be a potential supplement for adjuvant radiotherapy patient selection of IDH-mutant glioma patients.

Glioblastoma (GBM) continues to be one of the most lethal malignancies and is almost always fatal. In this review article, the role of radiation therapy, systemic therapy, as well as the molecular basis of classifying GBM is described. Technological advances in the treatment of GBM are outlined as well as the diagnostic imaging characteristics of this tumor. In addition, factors that affect prognosis such as differentiating progression from treatment effect is discussed. The role of MRI guided radiation therapy and how this technology may provide a mechanism to improve the care of patients with this disease are described.

Hepatocellular carcinoma (HCC) is the most common liver tumor, with a continually rising incidence. The curative treatment for HCC is surgical resection or liver transplantation; however, only a small portion of patients are eligible due to local tumor burden or underlying liver dysfunction. Most HCC patients receive nonsurgical liver-directed therapies (LDTs), including thermal ablation, transarterial chemoembolization (TACE), transarterial radioembolization (TARE), and external beam radiation therapy (EBRT). Stereotactic ablative body radiation (SABR) is a specific type of EBRT that can precisely deliver a high dose of radiation to ablate tumor cells using a small number of treatments (or fractions, typically 5 or less). With onboard MRI imaging, MRI-guided SABR can improve therapeutic dose while minimizing normal tissue exposure. In the current review, we discuss different LDTs and compare them with EBRT, specifically SABR. The emerging MRI-guided adaptive radiation therapy has been reviewed, highlighting its advantages and potential role in HCC management.

Objectives: Stereotactic Body Radiotherapy (SBRT) and Yttrium-90 (Y90) are among the ablative therapies used as treatment options for localized hepatocellular carcinoma (HCC). To date, direct comparisons of the 2 modalities’ outcomes and costs are lacking. This study aimed to analyze demographic, treatment, and cost information for patients with HCC treated with SBRT and Y90. Methods: Patients with HCC treated with SBRT or Y90 radioembolization between January 2018 and January 2020 at one institution were retrospectively reviewed. Demographic and treatment data were compared utilizing χ² tests. Kaplan-Meier curves and log-rank tests were applied to compare overall survival and progression-free survival in different treatment groups. Cox proportional hazard models were applied to analyze the unadjusted and adjusted survival differences. Ten SBRT and 10 Y90 patients were randomly selected for Medicare cost analysis. Results: Sixty-three patients received Y90, and 21 received SBRT. On univariable and multivariable analysis, there was no significant difference in overall survival or progression-free survival between the Y90 and SBRT cohorts. SBRT patients had higher American Joint Committee on Cancer staging (P=0.039), greater tumor size (4.07 vs. 2.96 cm, P=0.013), and greater rates of prior liver-directed therapy (71.4% SBRT vs. 12.7% Y90, P<0.001). The average cost for SBRT was $15,148, and Y90 was $41,360. Conclusions: SBRT and Y90 are effective therapies in the treatment of HCC, specifically having similar overall survival and progression-free survival. Y90 was found to have a significantly higher cost than SBRT. This study demonstrates the need for prospective studies to assess these modalities in treating HCC.

Pancreas cancer has a poor prognosis despite aggressive treatment and is the fourth leading cause of cancer death in the United States. At diagnosis, most patients have either metastatic or locally advanced disease. In this article, we review the evolution of treatments in locally advanced pancreas cancer (LAPC) and discuss the various radiation therapy fractionation schemes. Furthermore, we examine the data supporting dose escalation and the delivery of ablative biologically effective doses in the setting of LAPC. Finally, we review the role of MRI-guided radiation therapy in escalating dose while sparing organs at risk in the era of stereotactic magnetic resonance-guided adaptive radiation therapy.