Oncologist最新文献

Immune checkpoint inhibitors (ICIs) have advanced the treatment of metastatic melanoma. However, some patients develop ICI-associated toxicities like hepatitis (ie, immune-mediated hepatitis; IMH). Although these toxicities usually resolve with steroids, steroid-refractory events may occur, which may be a major source of morbidity and mortality without obviously defined treatment algorithms. Herein, we present 2 patients with metastatic melanoma who had IMH that was steroid-refractory and only partially mycophenolate-responsive, but fully resolved with budesonide. The case suggests that budesonide is a potential option to treat IMH that is refractory to standard treatments, but further investigation in a larger series is needed to identify the most optimal setting for budesonide use.

Background: The prognosis for patients with pancreatic ductal adenocarcinoma (PDAC) is poor. Secondary brain metastasis (Br-M) occurs in less than 1% of patients. Clinical characteristics and molecular alterations have not been characterized in this rare patients' subset.

Materials and methods: The Foundry software platform was used to retrospectively query electronic health records for patients with Br-M secondary to PDAC from 2005 to 2023; clinical, molecular, and overall survival (OS) data were analyzed.

Results: Br-M was diagnosed in 44 patients with PDAC. Median follow-up was 78 months; median OS from initial PDAC diagnosis was 47 months. Median duration from PDAC diagnosis to Br-M detection was 24 months; median OS from Br-M diagnosis was 3 months. At Br-M diagnosis, 82% (n = 36) of patients had elevated CA19-9. Lung was the most common preexisting metastatic location (71%) with Br-M, followed by liver (66%). Br-M were most frequently observed in the frontal lobe (34%, n = 15), cerebellar region (23%, n = 10), and leptomeninges (18%, n = 8). KRAS mutations were detected in 94.1% (n = 16) of patients who had molecular data available (n = 17) with KRASG12V being the most frequent subtype 47% (n = 8); KRASG12D in 29% (n = 5); KRASG12R in 18% (n = 3). Patients who underwent Br-M surgical resection (n = 5) had median OS of 8.6 months, while median OS following stereotactic radiosurgery only (n = 11) or whole-brain radiation only (n = 20) was 3.3 and 2.8 months, respectively.

Conclusion: Br-M is a late PDAC complication, resulting in an extremely poor prognosis especially in leptomeningeal disease. KRAS was mutated in 94.1% of the patients and the KRASG12V subtype was prevalent.

Background: Immune checkpoint inhibitors (ICI) have revolutionized cancer treatment but can trigger immune-related encephalitis. We report one of the largest case series of patients with immune-related encephalitis and review of the literature.

Methods: Retrospective series of patients with immune-related encephalitis and literature review.

Results: Fourteen patients with cancer treated with ICI (50% combination therapy) developed immune-related encephalitis. Diagnostic testing revealed cerebral spinal fluid (CSF) lymphocytic pleocytosis (85%) and elevated protein (69%), abnormal brain magnetic resonance imaging(MRI) (33%) or brain FDG-PET (25%), electroencephalogram (EEG) abnormalities (30%), and autoantibodies (31%). Encephalitis treatment included: corticosteroids (86%), intravenous immunoglobulin (IVIg) (36%), plasmapheresis (7%), and rituximab (29%). There were no deaths and 12 patients had significant recovery, although long-term complications were observed. All patients discontinued ICI. Longitudinal follow-up demonstrated anti-cancer response to ICI at 3 months (85%) and 6 months post-ICI initiation (77%). A literature review identified 132 patients with immune-related encephalitis. Most were treated with PD-1 inhibitors (18% combination). Common abnormalities included elevated CSF protein (84%) or pleocytosis (77%), abnormal brain MRI (65%), or autoantibodies (47%). Nearly all were treated with corticosteroids, many required additional therapy with IVIg (26%) or rituximab (12%). Most patients had clinical improvement (81%) but a minority (10%) had a clinical relapse after completing corticosteroid taper. ICIs were resumed in 7 patients (5%), with relapse in 3.

Conclusions and relevance: Immune-related encephalitis is treatable and improves with corticosteroids in most cases but may require additional immunosuppression. Re-emergence of encephalitis is rare and does not typically result in adverse outcomes, and this should be considered in neurological immune-related adverse event management guidelines.

We present a 54-year-old White male with a diagnosis of stage IV pancreatic neuroendocrine carcinoma. Next-generation sequencing of the tumor/blood identified a complex tumor genome, which included a rearranged during transfection (RET) gene fusion. The patient initially received cytotoxic chemotherapy with a significant radiographic response. After 4 cycles of chemotherapy, the patient was transitioned to a clinical trial using selpercatinib, a RET inhibitor, as maintenance therapy. Unfortunately, our patient developed progression of disease at the first treatment monitoring scan. Our patient suffered primary resistance to RET-targeted therapy. Proposed mechanisms of resistance include intrinsic resistance of the nuclear receptor co-activator 4-RET fusion to RET inhibition, the RET fusion representing a passenger alteration to another tumorigenic driver pathway and/or decreased efficacy of RET inhibition after platinum-based chemotherapy. Our patient's clinical course highlights the fact that "actionable" genomic alterations do not always equate to patient benefit.

Background: Patients with metastatic renal cell carcinoma (mRCC) experience emotional distress and limited supportive care access. This study assesses a mindfulness app's feasibility, acceptability, and preliminary efficacy in improving emotional symptoms, trait mindfulness, and overall quality of life for patients with mRCC on immunotherapy.

Methods: This multinational study recruited patients with mRCC undergoing immunotherapy from Brazil and the United States. Participants were required to engage in mindfulness app-based activities for 20-30 min daily, at least 4 days per week, over a 4-week period. Assessments were conducted at weeks 0, 2, 4, and 12 to evaluate emotional symptoms (PROMIS-Anxiety and Depression, Fear of Cancer Recurrence-7), fatigue (Brief Fatigue Inventory), trait mindfulness (Mindfulness Attention Awareness Scale), and quality of life (Functional Assessment of Chronic Illness Therapy-General). Self-reported data were used to assess adherence. Linear mixed-effects models were used to evaluate changes over time for the measured outcomes.

Results: Among 50 patients with mRCC, the feasibility of this intervention was demonstrated; 96% of patients were assessed at week 4, with high adherence rates reported by 75% of patients. Participants expressed positive feedback on the smartphone-based approach. Significant improvements were observed in emotional symptoms, fatigue, and quality of life scores from baseline to post-intervention (P = .001 for each), suggesting the positive impact of this intervention.

Conclusion: Our findings provide encouraging evidence for the feasibility and acceptability of a mindfulness app-based intervention among patients with mRCC. This intervention may offer a viable and accessible means of providing psychosocial support to patients with mRCC.

Background: Peritoneal metastasis (PM) after the rupture of hepatocellular carcinoma (HCC) is a critical issue that negatively affects patient prognosis. Machine learning models have shown great potential in predicting clinical outcomes; however, the optimal model for this specific problem remains unclear.

Methods: Clinical data were collected and analyzed from 522 patients with ruptured HCC who underwent surgery at 7 different medical centers. Patients were assigned to the training, validation, and test groups in a random manner, with a distribution ratio of 7:1.5:1.5. Overall, 78 (14.9%) patients experienced postoperative PM. Five different types of models, including logistic regression, support vector machines, classification trees, random forests, and deep learning (DL) models, were trained using these data and evaluated based on their receiver operating characteristic curve and area under the curve (AUC) values and F1 scores.

Results: The DL models achieved the highest AUC values (10-fold training cohort: 0.943, validation set: 0.928, and test set: 0.892) and F1 scores (10-fold training set: 0.917, validation cohort: 0.908, and test set:0.899) The results of the analysis indicate that tumor size, timing of hepatectomy, alpha-fetoprotein levels, and microvascular invasion are the most important predictive factors closely associated with the incidence of postoperative PM.

Conclusion: The DL model outperformed all other machine learning models in predicting postoperative PM after the rupture of HCC based on clinical data. This model provides valuable information for clinicians to formulate individualized treatment plans that can improve patient outcomes.

The prognosis of patients with glioblastoma (GBM) remains poor despite current treatments. Targeted therapy in GBM has been the subject of intense investigation but has not been successful in clinical trials. The reasons for the failure of targeted therapy in GBM are multifold and include a lack of patient selection in trials, the failure to identify driver mutations, and poor blood-brain barrier penetration of investigational drugs. Here, we describe a case of a durable complete response in a newly diagnosed patient with GBM with leptomeningeal dissemination and PTPRZ1-MET fusion who was treated with tepotinib, a brain-penetrant MET inhibitor. This case of successful targeted therapy in a patient with GBM demonstrates that early molecular testing, identification of driver molecular alterations, and treatment with brain-penetrant small molecule inhibitors have the potential to change the outcome in select patients with GBM.