Citations

686 Background: Immune checkpoint inhibitors (ICI) have been used to treat advanced muscle invasive and/or metastatic bladder cancer. However, ICIs are only effective in 30-40% of cases. In light of potentially significant IRAE’s, tools to predict individual patient level benefits are desirable. AI technology offers the opportunity to apply computational methods to predict outcomes from readily available digitized pathology slides. We investigated the utility of an AI platform integrating computational biomarkers based on morphological characterization of digitized H&E slide whole images (WSI) to predict response to ICI. Methods: We analyzed H&E-stained whole slide images (WSI) of bladder tumor tissue collected from transurethral resection of bladder tumor (TURBT) from 116 patients with advanced or metastatic bladder cancer at a single institution between 2015-2020. Adjacent multiplex IHC stained specimens were analyzed myeloid and lymphoid marker panels. 20 patients from the overall cohort treated with ICI were designated ‘responders’ (complete response, partial response, stable disease) and 20 patients were identified as non-responders (progressive disease) based on ICI best clinical/radiographic response. WSIs were divided into small non-overlapping image patches. These image tiles were processed into multiple AI encoder models to extract morphological features. The tile morphological features, represented by high dimensional vectors, were combined by an aggregation model to represent the whole slide morphology and then used to classify the patients into responders vs non-responders to immunotherapy. Area-under-the-receiver operating characteristic (AUC) was used to measure the performance of response prediction. Results: Our method shows AUC of 0.708 at classification of the patients (n=40) into responder and non-responder groups. With a cutoff that identifies the top 50% patients (n=20) of high probability of responding to immunotherapy predicted by our models, 75% of them are responders. In the bottom 50% patients (n=20) of the low scores, 75% of them are non-responders. . Multiplex IHC (myeloid and lymphoid panel) was performed using adjacent sections and were characterized yielding deeper mechanistic insight into the inflammatory populations driving predictive morphologic patterns. Conclusions: By applying innovative AI morphological analysis on patient WSIs, we generated a computational biomarker that shows promising ability to predict patient response to immunotherapy in bladder cancer. This approach merits future prospective validation and additional patient level analysis in broader cohorts. [Table: see text]

654 Background: MSI and TMB correlate with ICI efficacy. We assessed the association between TMB and MSI with outcomes in pts with aUC treated with anti-PD1/L1 in a ‘real-world’ cohort. We hypothesize that pts with high TMB and MSI-high (H) have better outcomes with ICI. Methods: In this retrospective study we included pts from 13 sites treated with ICI for aUC. We calculated overall response rate (ORR), median overall and progression-free survival (mOS, mPFS) using KM method from ICI start. TMB and MSI were assessed by NGS. TMB was analyzed as dichotomous (≥10 vs <10 mut/Mb) and continuous variable. The analysis was stratified by therapy line (1L/upfront, 2+L). Multivariable models were adjusted by Khaki factors for 1L/upfront and Bellmunt factors for 2+L. We separately analyzed pts on maintenance avelumab (mAV). MSI is reported with descriptive statistics only. Results: 342 pts were treated with ICI 1L/upfront or 2+L (69% pure UC, median age at ICI start 69, 77% men, 90% White, 16% upper tract primary, 12% liver metastases [mets], 78% ECOG PS 0-1). Median f/u from ICI start was 34 months (mo). ORR was 36% (95%CI 26-46%) in pts with TMB≥10 vs 30% (95%CI 23-36%) with TMB<10 (OR=1.4 [95%CI 0.8-2.5] p=0.3). ORR was 75% (6/8) in pts with MSI-H and 30% (60/200) with MSI stable (MSI-S). mPFS was similar between TMB≥10 and <10 groups (6 vs 4 mo; HR=0.88 [95%CI 0.61-1.26] p=0.48) and between MSI-H and MSI-S (5 mo). mOS was numerically longer (not significant) in pts with TMB≥10 vs TMB<10: 25 vs 21 mo; (HR=0.7 [95%CI 0.50-1.09] p=0.12) and with MSI-H and MSI-S (NR and 20 mo). A significant association was found between TMB (continuous variable) and OS (HR=0.97 [95%CI 0.95-0.99] p=0.01). TMB analyses by therapy line are shown in Table. In the 1L/upfront setting (N=144), ORR 71% (5/7) vs 33% (45/135), mPFS 5 and 4 mo, mOS NR and 22 mo for MSI-H and MSI-S, respectively. Pts on mAV (n=77) were 77% men, 92% White, 16% upper primary, 13% liver mets, 84% ECOG PS 0-1 with median f/u 15 mo from avelumab start; mOS was NR for MSI-H and 24 mo for MSI-S; mPFS was 4 mo for both groups. Of 3 pts on mAV with MSI-H: 1 CR, 2 SD; of 58 pts with MSI-S: 4CR, 4PR, 24 SD, 21 PD, 5 unknown. Conclusions: MSI-H had numerically higher ORR and higher TMB was associated with longer OS with ICI, but further validation is needed. Limitations: retrospective design, small sample size for MSI-H cases, lack of randomization and central scan review, selection/confounding. [Table: see text]

212 Background: Patients with prostate cancer with liver metastases are known to have a worse prognosis. In this study, we evaluated ctDNA in mCRPC (metastatic castration-resistant prostate cancer) patients with and without liver metastases. Methods: A retrospective chart review identified mCRPC patients with liver metastases at Tulane Cancer Center and Huntsman Cancer Institute. Liver metastases were confirmed via molecular or conventional imaging. All patients had ctDNA assessed with a multi-gene cancer panel via the Guardant 360 assay. Alterations with <0.1% allelic fraction, synonymous alterations, and variants of unknown significance were excluded from analyses. Statistical analyses were performed using Fisher’s Exact and Wilcoxon Rank Sum Tests. Correction for multiple testing was not performed, hence these alterations may be subject to a type 1 error. Results: 53 mCRPC patients with liver metastases and 144 mCRPC patients without liver metastases were included in the study. We found seven genes that are more likely to be pathologically altered in ctDNA in mCRPC patients with liver metastases (See Tables 1-3): AR (OR=2.38, 95% CI: [1.25, 4.52], p=0.01), BRAF (OR=2.74, 95% CI:[1.05, 7.18], p=0.05), BRCA2 (OR=5.33, 95% CI:[1.49, 19.02], p=0.01), CDK6 (OR=4.09, 95% CI:[1.35, 12.42], p=0.01), EGFR (OR=3.12, 95% CI:[1.22, 7.99], p=0.02), FGFR1 (OR=5.69, 95% CI:[1.81, 17.86], p-value=0.003), MYC (OR=4.55, 95% CI:[1.63, 12.68], p=0.004), and PIK3CA (OR=4.34, 95% CI:[1.87, 10.06], p=0.01). Additionally, mCRPC patients with liver metastases are more likely to have copy number alterations (CNA) (p= 0.01) compared to mCRPC patients without liver involvement. There were no other significant differences in the remaining 70 genes interrogated. Germline pathogenic alterations did not vary between the two groups. Conclusions: In mCRPC patients with liver metastases, these exploratory analyses suggest ctDNA testing is more likely to detect pathologic alterations in AR, BRAF, BRCA2, CDK6, EGFR, FGFR1, MYC, and PIK3CA. Additionally, mCRPC patients were more likely to have copy number alterations (CNA). Limitations of the Guardant 360 assays are notable in this setting given the incomplete ascertainment of gene deletions and the incomplete number of prostate-relevant genes assessed. [Table: see text]

PURPOSE Patients with biochemically recurrent prostate cancer (BRPC) after radical prostatectomy and a short PSA doubling time are at risk for distant metastases. Apalutamide, an androgen receptor antagonist, and abiraterone acetate plus prednisone (AAP) prolong survival in the metastatic setting. We evaluated whether intensification of androgen-deprivation therapy (ADT) improves outcomes in BRPC. PATIENTS AND METHODS PRESTO is a randomized phase III, open-label trial in patients with BRPC and PSA doubling time ≤9 months (ClinicalTrials.gov identifier: NCT03009981 ). Patients were randomly assigned 1:1:1 to receive a finite 52-week treatment course with ADT control, ADT + apalutamide, or ADT + apalutamide + AAP. The primary end point was PSA progression-free survival (PSA-PFS), defined as serum PSA >0.2 ng/mL after treatment completion. RESULTS Five hundred three patients were enrolled. The median PSA was 1.8 ng/mL (IQR, 1.0-3.6). At the first planned interim analysis, both experimental arms significantly prolonged PSA-PFS compared with the control arm (median, 24.9 months for ADT + apalutamide v 20.3 months for ADT; hazard ratio [HR], 0.52 [95% CI, 0.35 to 0.77]; P = .00047; median, 26.0 months for ADT + apalutamide + AAP v 20.0 months for ADT; HR, 0.48 [95% CI, 0.32 to 0.71]; P = .00008). Median time to testosterone recovery did not differ across treatment arms. The most common grade ≥3 adverse event was hypertension (7.5%, 7.4%, and 18% in ADT, ADT + apalutamide, and ADT + apalutamide + AAP arms, respectively). CONCLUSION Intensified AR blockade for a finite duration prolongs PSA-PFS with a manageable safety profile, without adversely affecting time to testosterone recovery. The addition of apalutamide to ADT should be considered in patients with high-risk BRPC.

Abstract Radioresistance of melanoma brain metastases limits the clinical utility of conventionally fractionated brain radiation in this disease, and strategies to improve radiation response could have significant clinical impact. The catalytic subunit of DNA-dependent protein kinase (DNA-PKcs) is critical for repair of radiation-induced DNA damage, and inhibitors of this kinase can have potent effects on radiation sensitivity. In this study, the radiosensitizing effects of the DNA-PKcs inhibitor peposertib were evaluated in patient-derived xenografts of melanoma brain metastases (M12, M15, M27). In clonogenic survival assays, peposertib augmented radiation-induced killing of M12 cells at concentrations ≥100 nmol/L, and a minimum of 16 hours exposure allowed maximal sensitization. This information was integrated with pharmacokinetic modeling to define an optimal dosing regimen for peposertib of 125 mpk dosed just prior to and 7 hours after irradiation. Using this drug dosing regimen in combination with 2.5 Gy × 5 fractions of radiation, significant prolongation in median survival was observed in M12-eGFP (104%; P = 0.0015) and M15 (50%; P = 0.03), while more limited effects were seen in M27 (16%, P = 0.04). These data support the concept of developing peposertib as a radiosensitizer for brain metastases and provide a paradigm for integrating in vitro and pharmacokinetic data to define an optimal radiosensitizing regimen for potent DNA repair inhibitors.

AbstractRecent studies have reported the involvement of peripheral nervous system (PNS) in association with MOG‐IgG, including isolated neuropathies. In this retrospective study we characterized the PNS involvement in MOG antibody associated disease (MOGAD). Six out of 215 MOGAD patients had PNS involvement (all polyradiculopathy) that occurred concurrently with a CNS demyelinating episode. We also demonstrated MOG expression in healthy human controls' proximal nerve root. Nine patients with true‐positive MOG‐IgG1 had PNS involvement temporally unrelated to a CNS demyelinating event. All these patients had an alternate etiology of PNS involvement. Isolated peripheral neuropathy is not a feature of MOGAD, but inflammatory nerve root involvement can occur concurrently with CNS demyelinating events.

Abstract Recent advances in the field of immuno‐oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high‐throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi‐marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Background Distal medium vessel occlusions (DMVOs) and minor strokes represent emerging frontiers in mechanical thrombectomy (MT). Although several randomized clinical trials (RCTs) are underway, the design characteristics of these trials and the specific questions they aim to address have not been extensively explored. This current study sought to investigate the design and data elements reported in active prospective DMVO and minor stroke studies. Methods The ClinicalTrials.gov database was searched for ongoing prospective studies assessing the role of MT in patients with DMVOs or minor strokes. The Nested Knowledge AutoLit platform was utilized to categorize reported outcomes and inclusion/exclusion criteria. Frequencies of reported data elements were extracted from study protocols. Results A total of 10 (8 DMVO and 2 minor stroke) studies enrolling 3520 patients were included. All DMVO studies employ different criteria regarding target occlusion locations. Five DMVO studies use stent retrievers as the first-line thrombectomy technique (62.5%, 5/8), while three studies allow any MT techniques, generally at the operator’s discretion. Four DMVO studies permit intravenous thrombolysis (IVT) utilization in both intervention and control arms (50%, 4/8). The DISTALS trial excludes patients receiving IVT, while the DUSK trial and Tigertriever registry only enroll patients who are ineligible for IVT or for whom IVT failed to achieve reperfusion. DMVO studies exhibit notable heterogeneity in symptom onset duration thresholds for inclusion (<6 hours: 2 studies; <12 hours: 2 studies; <24 hours: 3 studies). Minor stroke trials employ similar inclusion criteria and outcome measures except for symptom duration thresholds for inclusion (8 hours for ENDOLOW and 23 hours for MOSTE). Conclusions There is considerable heterogeneity among active DMVO trials regarding potential target DMVO locations and time thresholds for inclusion based on the last known well time. Furthermore, our review indicates that the utility of aspiration thrombectomy in DMVOs and the advantages of MT without IVT over IVT alone will remain largely unexplored even after completion of active DMVO trials.

To evaluate deep learning-based calcium segmentation and quantification on ECG-gated cardiac CT scans compared with manual evaluation. Automated calcium quantification was performed using a neural network based on mask regions with convolutional neural networks (R-CNNs) for multi-organ segmentation. Manual evaluation of calcium was carried out using proprietary software. This is a retrospective study of archived data. This study used 40 patients to train the segmentation model and 110 patients were used for the validation of the algorithm. The Pearson correlation coefficient between the reference actual and the computed predictive scores shows high level of correlation (0.84; P < .001) and high limits of agreement (±1.96 SD; −2000, 2000) in Bland–Altman plot analysis. The proposed method correctly classifies the risk group in 75.2% and classifies the subjects in the same group. In total, 81% of the predictive scores lie in the same categories and only seven patients out of 110 were more than one category off. For the presence/absence of coronary artery calcifications, the deep learning model achieved a sensitivity of 90% and a specificity of 94%. Fully automated model shows good correlation compared with reference standards. Automating process reduces evaluation time and optimizes clinical calcium scoring without additional resources.