Citations

Objective Glaucoma and cancer are debilitating diseases with increasing global prevalence and morbidity. However, current literature lacks a systematic consolidation of their relationships and interactions. This systematic review aims to (A) summarize the association between intraocular/non-ocular cancers and their treatments with the prevalence and etiology of glaucoma, (B) explore glaucoma as a risk factor for complications or poor prognosis for intraocular cancer, and (C) explore the management of glaucoma secondary to cancer therapies. Methods A systematic search was performed from inception to July 2025 across three databases with variants of ‘cancer’ and ‘glaucoma’ as search terms. Findings were narratively synthesized. Results Of 8,103 identified studies, 44 were included in this review. Eighteen studies reported increased glaucoma prevalence amongst intraocular and non-ocular cancer patients. Fifteen studies suggested increased risk of regional invasion, metastases, and high-risk histopathologies when intraocular cancers co-occurred with glaucoma. Corticosteroids in cancer therapy have been linked to intraocular pressure (IOP) elevation, while androgen deprivation therapy was associated with lowered glaucoma risk. Conclusion Given the relationship between glaucoma and intraocular/non-ocular cancers, strategies to monitor and manage glaucoma risk following cancer diagnosis and/or therapy may be considered. Glaucoma may be an early sign of complications in intraocular cancers.

ABSTRACT Background Isolated chromosome 5/5q losses (–5/5q) without TP53 mutations are associated with favorable outcomes in myeloid neoplasms (MN) with <5% blasts. However, the clinical implication of concurrent −5/5q and TP53 aberrations in MN with ≥5% blasts is poorly understood. Methods Patients with TP53 ‐mutated MN carrying ≥5% blasts assessing the prognostic impact of ‐5/5q on 24‐month overall survival (OS24) were examined. Results Of 587 patients, 515 (88%) exhibited −5/5q overwhelmingly in the context of a complex karyotype (98.3% vs. 61.1% complex karyotype without −5/5q; p < .0001) and multihit TP53 allelic state (88.3% vs. 56.9%; p < .0001). Proportions of patients with blasts ≥20% were comparable between groups with and without −5/5q; p = 0.26. Notably, patients with −5/5q exhibited significantly fewer coalterations; p < .0001. Looking at outcomes, presence of −5/5q was associated with shorter median 24‐month overall survival (7.8 months vs. 11.2 months; p Log‐rank = .012), an effect restricted to subgroups with blasts <20% ( p = .039; N = 163), absent −7/7q ( p = .007; N = 225), or WHO5‐defined single hit allelic state ( p = 0.030; N = 91). Importantly, −5/5q retained independent adverse prognostic significance regardless of TP53 allelic state in a multivariable model. Furthermore, among the subset of 75 (13%) patients undergoing allogeneic stem cell transplantation, −5/5q predicted significantly shorter median 5‐year posttransplant survival (16.2 months vs. median not reached; p Log‐rank = .009). Conclusions These findings emphasize the independent prognostic relevance of chromosome 5/5q losses underscoring the clinical relevance of cytogenetic testing for −5/5q even in this high‐risk cohort.

Abstract Background Standardizing beam modeling in the treatment planning system is challenging due to machine‐specific configuration variations. Because of the proton therapy system (PTS) complexity and continuous development, there is no vendor's representative (“golden”) beam data like in LINACs at this stage. Purpose The primary goal of this study is to create a PTS‐specific repository of source model parameters and beam commissioning data for scanning proton therapy treatment planning systems and establish a set of reference values with associated bands of variations for this data. Methods We conducted a survey of 31 PTSs at 27 proton therapy centers to gather beam commissioning source model parameters used in their treatment planning system, ensuring a diverse selection of PTSs from major vendors: Hitachi, IBA, Varian, and Mevion. For each proton therapy center, we collected (i) beam meterset calibration in protons per MU, (ii) in‐air spot size at isocenter in terms of standard deviation in x‐ (crossline, σ x ) and y‐ (inline, σ y ) directions, (iii) in‐air angular spread at isocenter in x‐direction (θ x ) and y‐direction (θ y ) and (iv) distal falloff. For each PTS, we plotted each parameter as a function of nominal energy and performed polynomial regression analysis with optimal model selection based on Akaike Information Criterion. We calculated intraclass correlation coefficients (ICC) to quantify inter‐PTS variability and generated uncertainty bands representing standard deviations across PTSs for each parameter. Additionally, we computed percentage deviations of each individual PTS from the overall multi‐vendor mean to identify systematic vendor‐specific patterns and outliers across the 31 total PTSs analyzed. Results Multi‐vendor beam parameter analysis across 31 PTSs revealed systematic vendor‐specific patterns in inter‐PTS consistency and energy dependencies. Beam meterset calibration demonstrated excellent inter‐PTS consistency across most vendors (ICC: Varian ProBeam ≈ 0, IBA Proteus ONE = 0.006, Mevion S250i with HYPERSCAN = 0.015), with IBA Proteus PLUS systems showing moderate variation (ICC = 0.156 for the dedicated nozzle, ICC = 0.248, for the universal nozzle). Spot size and angular spread variability were highly vendor‐dependent, ranging from excellent consistency in IBA Proteus ONE to substantial variation in IBA Proteus PLUS with the universal nozzle (angular spread ICC = 0.566). Distal falloff maintained excellent consistency across all vendors (ICC < 0.023), indicating reliable energy spread characteristics. Uncertainty band analysis revealed characteristic energy‐dependent patterns, with most systems showing larger uncertainties at lower energies for spot size and angular spread, while IBA Proteus PLUS with the universal nozzle exhibited the largest uncertainty bands overall. Percentage deviation analysis demonstrated vendor‐specific clustering patterns, with some systems showing systematic positive or negative deviations from the multi‐vendor mean. Conclusions The reference data provided in this work will help to cross‐check the beam model during treatment planning system commissioning. Furthermore, this information is useful for Monte Carlo applications and research, where beam characteristics are required to set up phase space parameters, thereby avoiding the need to model the entire PTS. Finally, the results of this study will have indispensable educational value by providing valuable insights into the characteristics and capabilities of different PTSs.

We investigated the prognostic impact of blast counts, TP53 allelic state determinants (number of hits, del(17p), variant allele frequency, complex karyotype),and a novel karyotypic clonal cell fraction (≤50% clonal cells vs >50% clonal cells (termed ‘CK50’)) in 495 individuals with TP53- mutated ( TP53 MUT ) myeloid neoplasms. Outcome examined was 24-month survival (OS24). The cohort (median age 71) included 29% (144/495) myelodysplastic syndromes (MDS)/MDS-acute myeloid leukaemia (AML) (1%–19% blasts) and 71% (351/495) AML (≥20% blasts), with 18% (81/460) having low CK50. Overall, 83% received front-line hypomethylating agents. Higher blast counts (<20% vs ≥20%) were marginally associated with CK50 (p=0.08). In the OS24 analysis, blast count showed a marginal association with OS24 (HR 1.3 (95% CI 1.0 to 1.6); p=0.07), while CK50 predicted significantly inferior outcomes (HR=1.7 (95% CI 1.2 to 2.3); p=0.002). In a multivariable model including all TP53 allelic state determinants, only CK50 and complex karyotype remained relevant for predicting adverse outcomes.

Abstract Purpose: Recent advances have seen the development of targeted therapeutics against the receptor tyrosine kinase (RTK)/RAS/MAPK pathway, which, when aberrantly activated, drives the malignant transformation of many cancer indications. However, the efficacy of inhibitors targeting single molecules is dampened by pathway feedback activation and acquired drug resistance. We seek to evaluate the application of JAB-3312 (sitneprotafib), a potent inhibitor of SHP2, in RTK/RAS/MAPK pathway–targeted combination therapies. Furthermore, SHP2 plays a vital role in PD-1–mediated immunosuppression. The rational combination of JAB-3312 with PD-1 blocking therapies is also explored. Experimental Design: Biochemical and cellular assays were applied to evaluate the potency of JAB-3312 in SHP2 inhibition. Tumor cell lines and cell line– and patient-derived xenografts were used to test different combinations of JAB-3312 with KRASG12C, MEK, EGFR, and PD-1 inhibitors. Results: JAB-3312 produced potent in vitro inhibition of SHP2 activity and downstream ERK phosphorylation, with IC50 values of 1.44 nmol/L and 0.68 to 4.84 nmol/L, respectively. When used in combination, JAB-3312 significantly increased the antitumor activity of the KRASG12C inhibitor glecirasib in naïve and resistant models. The combination of JAB-3312 with MEK inhibitors significantly delayed RTK signaling reactivation and enhanced tumor growth inhibition in KRAS-mutated cancer models. The JAB-3312–osimertinib combination exhibited great efficacy in osimertinib-resistant non–small cell lung cancer models. Additionally, JAB-3312 enhanced the efficacy of PD-1 blockade therapies by promoting an antitumor microenvironment. Representative cases of patients who responded to the combination therapies from two ongoing clinical trials (NCT05288205 and NCT04720976) were reported. Conclusions: JAB-3312 in combination with RTK/RAS/MAPK or PD-1 blockade therapies is a promising strategy that warrants further clinical investigation.

ASCO Guidelines provide recommendations with comprehensive review and analyses of the relevant literature for each recommendation, following the guideline development process as outlined in the ASCO Guidelines Methodology Manual . ASCO Guidelines follow the ASCO Conflict of Interest Policy for Clinical Practice Guidelines . Clinical Practice Guidelines and other guidance (“Guidance”) provided by ASCO is not a comprehensive or definitive guide to treatment options. It is intended for voluntary use by clinicians and should be used in conjunction with independent professional judgment. Guidance may not be applicable to all patients, interventions, diseases or stages of diseases. Guidance is based on review and analysis of relevant literature, and is not intended as a statement of the standard of care. ASCO does not endorse third-party drugs, devices, services, or therapies and assumes no responsibility for any harm arising from or related to the use of this information. See complete disclaimer in Appendix 1 and 2 (online only) for more . PURPOSE To provide evidence-based recommendations for patients with metastatic castration-resistant prostate cancer (mCRPC). METHODS An Expert Panel including patient representation completed a systematic review of the evidence and made recommendations. RESULTS Depending upon prior treatment received, androgen receptor pathway inhibitors (ARPIs: enzalutamide, abiraterone with prednisone), poly(ADP-ribose) polymerase inhibitors (PARPi), chemotherapeutic agents (docetaxel, cabazitaxel), radiopharmaceuticals (radium 223, 177 Lu-prostate-specific membrane antigen [PSMA]-617), and sipuleucel-T have demonstrated an overall survival (OS) benefit for patients with mCRPC. For patients with BRCA1 / 2 alterations who did not receive prior ARPI, the combination of PARPi and ARPI (talazoparib + enzalutamide, olaparib and/or niraparib + abiraterone) has shown clinical benefit. For patients with BRCA1 / 2 alterations who received prior ARPI or ARPI followed by docetaxel, olaparib showed OS benefit. In select patients with microsatellite instability-high/mismatch repair-deficient, pembrolizumab showed clinical efficacy. RECOMMENDATIONS Prior systemic therapy for castration-sensitive prostate cancer will determine subsequent therapy used for mCRPC. Continue androgen-deprivation therapy for patients with mCRPC indefinitely. Early adoption of somatic genetic testing and palliative care is recommended. Patients with mCRPC and bony metastases should receive a bone-protective agent. The panel recommends the combination of ARPI with PARPi in patients with BRCA1 / 2 alterations who did not receive prior ARPI. For patients who received prior ARPI, the panel recommends docetaxel chemotherapy. The panel recommends 177 Lu-PSMA-617 or cabazitaxel chemotherapy for patients who receive prior ARPI and docetaxel chemotherapy. For patients with BRCA1 / 2 alterations who received prior ARPI, the panel recommends PARPi monotherapy. Radium 223 is recommended for patients with symptomatic bone–only disease. Evidence for optimal sequencing for mCRPC regimens is lacking. Additional information is available at www.asco.org/genitourinary-cancer-guidelines .

Introduction: TP53 mutations are found in 18% of adult patients (pts) with acute lymphoblastic leukemias (ALL), and portends poor prognosis (Saygin, Blood Cancer Discov 2024). TP53 mutations are often associated with low hypodiploidy and Li Fraumeni syndrome (germline) in children. However, we and others have shown that TP53-mutant (TP53-m) ALL arises from pre-existing TP53-m clonal hematopoiesis in adults as opposed to germline origin. The impact of co-occurring mutations, TP53 allelic frequency (AF) and different types of treatment on outcomes of TP53-m ALL are not fully characterized. We set out to investigate the clinical and molecular predictors of outcomes in adults with TP53-mutant ALL. Methods: We retrospectively studied 107 patients with TP53-m ALL treated at seven different academic centers in North America. Genetic profiling of pre-treatment bone marrow samples was performed with a comprehensive panel covering 147 myeloid and lymphoid genes. We also performed RNA-sequencing to identify fusions that define ALL subtypes. Single nucleotide polymorphism (SNP) array was used to define low hypodiploidy. Results: The median age at diagnosis was 59 years (range, 10-80), 42% were female, 70% White. 89% of pts had B-ALL while 11% had T-lineage ALL. 24% of pts were classified to have therapy-related ALL based on their history of exposure to genotoxic therapy for another cancer. 45% of pts had hypodiploid karyotype, 79% of whom were low-hypodiploid. 7% had hyperdiploid karyotype and 5% had BCR::ABL1. 11 pts had two different TP53 variants. 90% of TP53 variants involved the DNA binding domain. Most frequently observed co-occurring mutations involved CDKN2A (20%), NOTCH1 (12%) and RB1 (10%) genes. 71% of pts were treated with standard cytotoxic chemotherapy, while the remaining pts received newer antibody-based therapies (i.e., inotuzumab, blinatumomab) or venetoclax in first-line setting. 11% of pts received allogeneic hematopoietic cell transplant (HCT) in first complete remission (CR1) while 3% received HCT after relapse (CR2 or CR3). When patients with vs without low hypodiploidy were compared, we did not observe a significant difference in overall survival (OS) as outcomes were poor in both groups (median, 17 vs 19 months, p= 0.89). However, pts who had TP53 AF &gt;0.5 had significantly worse OS when compared to pts with TP53 VAF &lt;0.5 (13 vs 25 months, p= 0.03). Conclusions: TP53-m ALL is a very high-risk disease subtype and its dismal outcome is independent from presence of co-existing low hypodiploidy. Loss of heterozygosity, characterized by TP53 AF &gt;0.5 is associated with even worse survival. New therapies are urgently needed to improve outcomes in this subset.

SummaryTo assess the relevance of co‐occurring somatic mutations in TP53‐mutated myeloid neoplasms with ≥10% blasts, we pooled 325 individuals from 10 centres. We focused on comparing three published somatic co‐alteration signatures comprising (1) nine MDS‐related genes (‘ICC‐MDSR’), (2) ICC‐MDSR + additional secondary mutations‐related genes (‘Tazi signature’) and (3) EPI6 (comprising six genes). Outcomes examined were 24‐month overall survival (OS24) and front‐line complete response (CR1). The median age was 69 years with 77% receiving front‐line hypomethylating agents (HMA). All three signatures ICC‐MDSR (p = 0.009), Tazi signature (p = 0.001) and EPI6 (p = 0.025) predicted inferior CR1. In the low‐intensity (HMA) subgroup, only Tazi signature (p = 0.026) predicted inferior CR1. In OS24 analysis of the HMA‐treated subgroup (N = 200), only Tazi signature was adverse (hazard ratio, HR = 1.6 [1.1–2.2]; p = 0.011). However, a forward stepwise multivariable age‐adjusted Cox model including all three signatures picked EPI6 as the sole significant adverse predictor in the entire cohort (p = 0.0001) as well as within the HMA‐treated subgroup (p = 0.0071). These data confirm the value of testing co‐occurring somatic alterations even within a high‐grade TP53‐mutated myeloid neoplasm cohort.

AbstractObjectivesAlthough hemispheric surgeries are among the most effective procedures for drug‐resistant epilepsy (DRE) in the pediatric population, there is a large variability in seizure outcomes at the group level. A recently developed HOPS score provides individualized estimation of likelihood of seizure freedom to complement clinical judgement. The objective of this study was to develop a freely accessible online calculator that accurately predicts the probability of seizure freedom for any patient at 1‐, 2‐, and 5‐years post‐hemispherectomy.MethodsRetrospective data of all pediatric patients with DRE and seizure outcome data from the original Hemispherectomy Outcome Prediction Scale (HOPS) study were included. The primary outcome of interest was time‐to‐seizure recurrence. A multivariate Cox proportional‐hazards regression model was developed to predict the likelihood of post‐hemispheric surgery seizure freedom at three time points (1‐, 2‐ and 5‐ years) based on a combination of variables identified by clinical judgment and inferential statistics predictive of the primary outcome. The final model from this study was encoded in a publicly accessible online calculator on the International Network for Epilepsy Surgery and Treatment (iNEST) website (https://hops‐calculator.com/).ResultsThe selected variables for inclusion in the final model included the five original HOPS variables (age at seizure onset, etiologic substrate, seizure semiology, prior non‐hemispheric resective surgery, and contralateral fluorodeoxyglucose–positron emission tomography [FDG‐PET] hypometabolism) and three additional variables (age at surgery, history of infantile spasms, and magnetic resonance imaging [MRI] lesion). Predictors of shorter time‐to‐seizure recurrence included younger age at seizure onset, prior resective surgery, generalized seizure semiology, FDG‐PET hypometabolism contralateral to the side of surgery, contralateral MRI lesion, non‐lesional MRI, non‐stroke etiologies, and a history of infantile spasms. The area under the curve (AUC) of the final model was 73.0%.SignificanceOnline calculators are useful, cost‐free tools that can assist physicians in risk estimation and inform joint decision‐making processes with patients and families, potentially leading to greater satisfaction. Although the HOPS data was validated in the original analysis, the authors encourage external validation of this new calculator.