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Purpose The aim of this study is to better characterize the clinical characteristics and outcomes of patients diagnosed with Immune checkpoint Inhibitor (ICI) pneumonitis and propose predictive models. Patients and methods Patients diagnosed with ICI pneumonitis at Mayo Clinic from 2014 to 2022 were studied. All cases were independently reviewed by our pulmonology specialist (A.E.) to confirm the appropriate diagnosis. The grading of pneumonitis was defined in accordance with ASCO guidelines (Schneider et al. in J Clin Oncol 39(36):4073–4126, 2021. https://doi.org/10.1200/JCO.21.01440 ). Predictive modeling was performed using gradient boosting machine learning technology, XGBoost (Chen in 1(4):1, 2015), to conduct binary classification and model reverse engineering using Shapley statistics (Lundberg and Lee in Adv Neural Inf Process Syst 30, 2017). Results One hundred and seventy patients with ICI pneumonitis were included (median age 67; IQR 59, 75). Median overall survival was 2.3 years (95% CI: 1.8, NR). A higher grade of ICI pneumonitis was associated with inferior survival (HR 5.85, 95% CI: 2.27, 15.09; p  < 0.001). Patients who were rechallenged with immunotherapy had significantly improved hazard of survival compared to patients not rechallenged (HR 0.37, 95% CI: 0.21, 0.68; p  = 0.001). Risk of death from ICI pneumonitis prior to starting immunotherapy was modeled with an area under the curve of the receiver operator characteristic (AUC-ROC) of 0.79 with the most contributory features including peripheral blood lymphocyte count, oxygen dependence, pulmonary function testing, and PD-L1 expression. Conclusion The presentation of ICI pneumonitis is highly variable, and outcomes are dependent on severity, but favor grade 2 disease when patients are rechallenged with immunotherapy. However, using commonly available clinical data, we can accurately identify patients at high risk of death from ICI pneumonitis. Further effort is needed to produce clinical models able to provide clinician decision support when evaluating patients with ICI toxicities and considering ICI rechallenge.

Invasive fungal infections (IFIs) remain an important cause of morbidity and mortality in patients with acute or chronic leukemia. Advances in the pharmacotherapy of fungal infections and a shift in the epidemiological characteristics of fungal pathogens toward fluconazole-resistant Candida species and saprophytic molds have placed a greater emphasis on selection of broader-spectrum agents for empirical therapy of IFIs in this high-risk population. Newer diagnostic modalities, such as the Aspergillus galactomannan test, the 1,3-β-d-glucan test, and polymerase chain reaction detection of fungal DNA, may facilitate the earlier diagnosis of IFIs, but their role in detecting breakthrough infection and their usefulness as a marker to withhold antifungal therapy in high-risk leukemia patients with IFI are less obvious, especially in patients who are receiving antifungal prophylaxis. Only 2 strategies have been shown in prospective studies to improve survival from mold infection in patients with acute myelogenous leukemia or myelodysplastic syndrome: (1) preemptive initiation of antifungal therapy at first sign of invasive aspergillosis on computed tomography (CT) scan and (2) antifungal prophylaxis with posaconazole. CT-guided treatment decisions are more complex in patients with advanced leukemia, however, because of concomitant infection or relapsing malignancy. Similarly, posaconazole is often not a viable prophylaxis or treatment option in patients with poor oral intake, gastrointestinal dysfunction, or possible drug interaction (eg, proton pump inhibitor prophylaxis in patients on high-dose glucocorticosteroids). As a result, the management of IFI in patients with leukemia demands an individualized treatment plan.

Ovarian cancer is the most lethal gynecologic malignancy. About 75% of ovarian cancer patients relapse and/or develop chemo‐resistant disease after initial response to standard‐of‐care treatment with platinum‐based therapies. HER2 amplifications and overexpression in ovarian cancer are reported to vary, and responses to HER2 inhibitors have been poor. Next generation sequencing technologies in conjunction with testing using patient‐derived xenografts (PDX) allow validation of personalized treatments. Using a whole‐genome mate‐pair next generation sequencing (MPseq) protocol, we identified several high grade serous ovarian cancers (HGS‐OC) with DNA alterations in genes encoding members of the ERBB2 pathway. The efficiency of anti‐HER2 therapy was tested in three different PDX lines with the identified alterations and high levels of HER2 protein expression. Treatment responses to pertuzumab or pertuzumab/trastuzumab were compared in each PDX line WITH standard carboplatin and paclitaxel combination treatment. In all three PDX models, HER2‐targeted therapy resulted in significant inhibition of tumor growth compared with untreated controls. However, the responses in each case were inferior to those to chemotherapy, even for chemo‐resistant lines. When chemotherapy and HER2‐targeted therapy were administered together, a significant regression of tumor was observed after 6 weeks of treatment compared with chemotherapy alone. Post‐treatment analysis of these tissues revealed that inhibition of the ERBB2 pathway occurred at the level of phosphorylation and expression of downstream targets. In conclusion, while targeting of presumably activated ERBB2 pathway alone in HGS‐OC results in a modest treatment benefit, a combination therapy including both chemotherapy drugs and HER2 inhibitors provides a far better response. Further studies are needed to address development of recurrence and sensitivity of recurrent disease to HER2‐targeted therapy. Most ovarian cancer patients relapse and develop chemo‐resistant disease. Here, we combined chemotherapy with genomically guided targeted therapy using patient‐derived xenograft (PDX) models. The PDX tumors faithfully recapitulate the DNA alterations of the original donor tumor. Targeting altered proteins of the ERBB pathway with HER2 monoclonal antibodies combined with chemotherapy resulted in greater inhibition of tumor growth than chemotherapy alone.

BackgroundThe efficacy of osimertinib in previously EGFR-TKI-treated NSCLC without identification of T790M mutational status remains unclear in real-world practice.Patients and methods417 patients had stage III–IV NSCLC harboring EGFR mutation and 154 out of 417 patients receiving osimertinib as ≥ second-line EGFR-TKI were identified. The time to treatment failure and risk of death were analyzed.ResultsHigher risk of death was found in EGFR-mutant patients with age ≥ 65 years, non-adenocarcinoma, no surgery or radiation, non-exon 19 deletion/exon 21 L858R, higher ECOG PS (2–4), PD-L1 expression ≥ 50%, and bone/liver/adrenal metastasis (all p < 0.05). Osimertinib as ≥ second-line TKI in patients with/without identification of T790M revealed lower risk of death compared to first-line first/second generation TKI without subsequent osimertinib (p = 0.0002; 0.0232, respectively). However, osimertinib-treated patients with T790M did not have superior survival than those without (p = 0.2803). A higher risk of treatment failure for osimertinib was found in males, patients with first-line TKI duration ≤ 12 months, BMI drop > 10%, and PD-L1 expression ≥ 50% (All p < 0.05). Nonetheless, osimertinib as ≥ second-line TKI in patients without identification of 790 M did not have higher risk of treatment failure than those with T790M (p = 0.1236).ConclusionsThis study demonstrates that osimertinib as second line or subsequent TKI in EGFR-TKI-treated patients without identification of T790M revealed lower risk of death compared to first-line first/second generation TKI without subsequent osimertinib, in real-world practice. Additionally, EGFR-mutant patients with PD-L1 expression ≥ 50% had a higher risk of treatment failure for osimertinib and worse overall survival than those with PD-L1 expression < 50%. These results suggest that osimertinib as second line or subsequent TKI may be a potential alternative option for the treatment of patients without identification of T790M and PD-L1 expression ≥ 50% is associated with a significantly poor outcome in patients receiving osimertinib.

BackgroundImmune checkpoint inhibitor therapy-related (ICI) pneumonitis poses a significant challenge in patients with cancer. There is paucity of data on patient characteristics and outcomes in this population.MethodsThis is a retrospective study of patients diagnosed with ICI pneumonitis at the Mayo Clinic from 2014 to 2022. A list of patients was compiled using Mayo Clinic’s informatics tool, Advanced Text Explorer, with keywords ‘pneumonitis’ and ‘immunotherapy’ (n=848). All cases were independently reviewed by our pulmonology specialist (A.E.) to confirm the appropriate diagnosis which yielded 170 patients. Excluded patients were those with alternative diagnoses. The grading of pneumonitis was defined in accordance with ASCO guidelines.1 Results170 patients with ICI pneumonitis were included (median age 67; range 25–87) and 48% were male (table 1). The severity of ICI pneumonitis was as follows: grade 1 (n=17, 10%), grade 2 (n=85, 50%), grade 3 (n=53, 31%), and grade 4 (n=15, 9%). The median time from initiation of immunotherapy to development of ICI pneumonitis was 4 months (interquartile range 2 - 9.5). 47 (28%) had another ICI toxicity. Median overall survival (OS) was 2.5 years (95%, CI: 1.8-NR). A higher grade of ICI pneumonitis was associated with inferior outcomes (HR 2.0, 95% CI 1.5–2.8, p<0.001), while PD-L1 expression, age at diagnosis of ICI pneumonitis, and smoking status were not associated with inferior outcomes (p > 0.05). 51 (30%) were rechallenged with immunotherapy after an initial episode of ICI pneumonitis. Among those rechallenged, 23 (45%) developed recurrent pneumonitis (78% grade 2, 22% grade 3–4). Patients rechallenged, had significantly improved outcomes compared to patients who were not rechallenged (HR 0.37, 95% CI 0.2 – 0.7, p=0.001). On subset analysis, we identified the majority of the benefit was from patients with grade 2 severity (figure 1). The median OS based on grade of ICI pneumonitis was 28 months (95% CI: 28-NR) for grade 1, 52 months (95% CI: 38-NR) for grade 2, 13 months (95% CI: 7.6-NR) for grade 3, and 4 months (95% CI: 2.2-NR) for grade 4.ConclusionsPatients with grade 1–2 ICI pneumonitis do significantly better than patients with grade 3–4 ICI pneumonitis. Rechallenge may result in a high frequency of recurrent pneumonitis (45%); however, patients who were rechallenged had significantly improved outcomes compared to patients who were not rechallenged. Further studies should be done to validate whether all patients with ≤ grade 2 pneumonitis should undergo a rechallenge.Ethics ApprovalThis study was approved by the Mayo Clinic IRB.ReferenceSchneider BJ, et. al. Management of Immune-Related Adverse Events in Patients Treated With Immune Checkpoint Inhibitor Therapy: ASCO Guideline Update. J Clin Oncol. 2021 Dec 20;39(36):4073–4126. doi: 10.1200/JCO.21.01440. Epub 2021 Nov 1. Erratum in: J Clin Oncol. 2022 Jan 20;40(3):315. PMID: 34724392.Abstract 1265 Table 1Patient CharacteristicsAbstract 1265 Figure 1Swimmers plot comparing grade 1–4 immune checkpoint inhibitor therapy-related pneumonitis with and without rechallenge of immunotherapy

BackgroundImmune checkpoint inhibitor therapy-related (ICI) pneumonitis is a potential serious complication for patients with cancer. We have previously shown that modeling can be used to predict the risk of death from ICI pneumonitis.1 Further predictive modeling to risk stratify patients with ICI pneumonitis is needed.MethodsA database of cancer patients diagnosed with ICI pneumonitis seen at Mayo Clinic from 2014–2022 was utilized for exploratory data analysis. Within this cohort, we isolated clinical variables from before ICI pneumonitis diagnoses to determine if we could model the propensity for developing low grade (1–2) versus high grade (3–4) pneumonitis at the time of immunotherapy initiation. Those clinical variables included age, sex, weight, common laboratory values, immunotherapy treatment, cancer type, and baseline pulmonary function tests (PFTs). We used a gradient boosting machine learning technology, Xgboost2 to conduct binary classification. Given the relatively small cohort size for AI analysis (n = 170), modeling was conducted with 1,000-fold bootstrapping to minimize dependence on data arrangement and k-fold cross validation to minimize model overfitting. Model reverse engineering was done with Shapley statistics3 to determine which features had the largest contribution. Once identified, only those highly weighted features were used for logistic regression analysis providing more reproducible predictions by decreasing model variance.Results170 patients with ICI pneumonitis were included (median age 67; range 25–87). The severity of ICI pneumonitis was as follows: grade 1 (n=16, 9%), grade 2 (n=86, 51%), grade 3 (n=57, 34%), and grade 4 (n=11, 6%). 47 patients (28%) had another ICI toxicity. Median overall survival was 2.5 years (95%, CI: 1.8-NR). A higher grade of ICI pneumonitis was associated with inferior survival (HR 2.0, 95% CI 1.5–2.8, p<0.001). Our approach resulted in a low versus high grade pneumonitis binary classification model with an area under the curve of the receiver operator characteristic of 0.74 (figure 1). The features most predictive of whether a patient would develop high grade pneumonitis were baseline DLCO obtained from PFTs, hemoglobin concentration, monocyte count, total white blood cell count, and immunotherapy choice.ConclusionsWe demonstrate that commonly available clinical data can be used to risk stratify patients to low versus high grade ICI pneumonitis. Further effort is needed to produce clinical models able to provide clinician decision support when evaluating patients with ICI toxicities. Investigation is underway which uses a large cancer data set to independently validate this model and to predict who will develop immunotherapy toxicities.ReferencesHazim A, et al. Utilizing predictive modeling to identify patients at high risk of death from immune checkpoint inhibitor therapy-related pneumonitis. Journal of Clinical Oncology. 2023;41(16_suppl):1552–1552.Chen T, He T, Benesty M, Khotilovich V, Tang Y, Cho H, Chen K, Mitchell R, Cano I, Zhou T. Xgboost: extreme gradient boosting. R package version 0.4–2 , 2015;1(4):1–4.Lundberg SM, Lee SI. A unified approach to interpreting model predictions. Advances in neural information processing systems , 2017; 30 .Ethics ApprovalThis study was approved by the Mayo Clinic IRB.Abstract 1266 Figure 1Area under the curve of the receiver operator characteristic (AUC-ROC) from modeling propensity of low grade versus high grade immune checkpoint inhibitor therapy-related pneumonitis

BackgroundImmunotherapy has shown promise in treating patients with metastatic NSCLC, but response rates vary. This study aims to investigate the relationship between PD-L1 CNV and response to immunotherapy in patients with NSCLC.MethodsWe conducted a retrospective analysis of patients who received immunotherapy, and were identified to have information on CNV status for PD-L1 through the MayoComplete Solid Tumor Panel (MCSTP) Next Generation Sequencing (NGS) assay. Response to therapy was evaluated using evidence of radiographic progression, date of death or date of last follow-up. Progression-free survival (PFS) and Overall survival (OS) were defined as time interval between data of initiation of immunotherapy to date of radiographic progression and date of death respectively.Results98 patients were included in the study, most of whom had received immunotherapy as a first-line treatment (77%). The median age was 70.5 years (range: 39–88), and 64% were male. The most common histology was adenocarcinoma (68%), followed by squamous cell carcinoma (16%) and others (16%). We found that PD-L1 CNV was altered in 54% of patients with either heterozygous deletion (34%) or copy number gain (20%). We observed higher median PD-L1% in patients with PD-L1 CNV copy number gain compared to normal/deletions (80% vs 5%,p=0.0172) (table 1).In terms of smoking status, 94% of patients had a history of smoking (84% former smokers, 10% current smokers and 6% never smokers). Most patients had stage IV disease at treatment initiation (68%), and the ECOG performance status was mostly 0 or 1 (78%). The median PFS and OS for the cohort was 5.4 and 23.8 months respectively (table 1). We observed improved response to immunotherapy with higher PDL1 IHC% as has been reported previously. However, we did not find any significant differences in median PFS by presence (7.5 [normal] vs 5.0 months [altered], p=0.28) and type (7.5 [normal] vs 5.5 [deletion] vs 4.4 months [gain], p=0.56) of PD-L1 CNV alteration. Similarly, there were no significant differences in OS by presence (23.8 [normal] vs 26.6 [altered] months, p=0.38) and type (23.7 [normal] vs 26.6 [deletion] vs not reached [gain] months, p=0.51) of PD-L1 CNV alteration (figure 1).ConclusionsOur study did not find any significant difference in median PFS and OS between patients with normal PD-L1 CNV and those with altered PD-L1 CNV, including different types of PD-L1 CNV alterations. Our study suggests that PD-L1 CNV status may not be a reliable predictive biomarker for response to immunotherapy in patients with advanced NSCLC.Abstract 534 Table 1Abstract 534 Figure 1Overall survival (days)

γH2AX is a protein biomarker for double-stranded DNA breakage; its expression was studied in cervical squamous intraepithelial lesions and carcinomas. Immunostaining for phospho-γH2AX was performed in sections from histologically confirmed cervical SIL and carcinomas, as well as from normal cervices used as controls. In total, 275 cases were included in the study: 112 low grade SIL (LGSIL), 99 high grade SIL (HGSIL), 24 squamous cell carcinoma (SCC), 12 adenocarcinoma and 28 cervical specimens with no essential lesions. Correlation of histological grading, high risk vs. low risk HPV virus presence, activated vs. non-activated status (by high risk HPV mRNA expression) and γH2AX expression in both basal and surface segments of the squamous epithelium was performed. Gradual increase of both basal and surface γH2AX expression was noted up from normal cervices to LGSIL harboring a low risk HPV type, to LGSIL harboring a high risk virus at a non-activated state (p<0.05). Thereafter, both basal and surface γH2AX expression dropped in LGSIL harboring a high risk virus at an activated state and in HGSIL. γH2AX could serve as a potential biomarker discriminating between LGSIL and HGSIL, as well as between LGSIL harboring high risk HPV at an activated state.

Adagrasib produced responses in 43% of previously treated patients with non–small-cell lung cancer containing a KRAS G12C mutation, with median overall survival of 12.6 months. Regressions of stable brain metastases were noted in one third of evaluable patients. Gastrointestinal toxic effects dominated the adverse events, but fewer than 7% of patients stopped therapy.

Targeted therapies have changed the treatment landscape of non-small-cell lung cancer and led to improved patient survival across all stages of lung cancer. Newer advances in common and novel oncogenic drivers continue to occur at vigorous speed, making it challenging to stay up to date with the rapidly evolving field. In this article, we review the emerging perspectives in the treatment of actionable targets in lung cancer. We focus on the development of newer KRAS-directed therapies, particularly on non-G12C mutations, pan-RAS inhibitors, and RAS-GTP inhibitors. We also describe the current standard of care for EGFR- and ALK-altered NSCLC and dive into the novel treatments expected to be in the clinic soon. A similar approach is taken toward MET, HER2, RET, ROS1, and FGFR alterations as emerging targets in non-small-cell lung cancer. Finally, we conclude this review with the current body of evidence for targeting TROP-2 as a novel target, potentially of importance in post-targeted therapy scenarios.