Cheville, John C.

This cohort study examines the oncological, neurological, and serological profiles of adult male patients with testicular germ cell tumors and paraneoplastic neurologic syndromes.

Abstract Purpose: Germ cell tumors (GCTs) pose significant diagnostic challenges due to the limited sensitivity and specificity of current tumor markers. Hereby we utilize phage immunoprecipitation sequencing (PhIP-Seq) technique to develop a unique immunosignature panel (iSIGN) with high sensitivity and specificity to improve the diagnosis and differentiation of GCTs. Patients and Methods: Serum samples from patients with confirmed gonadal or extragonadal GCTs and controls were collected from Mayo Clinic repositories. Controls included benign testicular lesions, autoimmune diseases, neurodegenerative disorders, and other cancers. Samples were randomized into development and validation cohorts. PhIP-Seq identified antigen-autoantibody interactions, and enrichment scores were calculated to develop a biomarker panel distinguishing GCT from non-GCT cases. A second biomarker panel was developed to predict seminoma from nonseminoma cases. Results: A total of 427 serum samples were analyzed, including 150 from GCT patients and 277 controls. For our primary model to distinguish GCT cases (GCT-iSIGN), 24 peptides from 16 antigens were identified based on significant differential autoantibody binding enrichment in GCT patients (p < 0.05), ≥2 peptides per antigen, and enrichment scores ≥ 2.5-fold. GCT-iSIGN was highly sensitive (93%) and specific (99%) for identifying GCT cases from controls with an area under curve (AUC) of 0.93 and 9% Unknown Case Rate (UCR). The secondary panel (Sem-iSIGN) included 17 peptides corresponding to 5 unique proteins with high specificity (93%), moderate sensitivity (65%) and AUC of 0.77 to distinguish seminoma from nonseminoma GCT cases. Conclusion: This study demonstrates the potential use of PhIP-Seq to identify unique immunosignature panels that can serve as reliable biomarkers for GCT. These panels address the limitations of traditional markers and other proteomic techniques. This immunosignature model represents a cost-effective, stable, and scalable approach to enhancing GCT diagnosis and management. Citation Format: M Bakri Hammami, Andrew Knight, Haidara Kherbek, Brian Costello, Silvana De Lorenzo, Bradley C. Leibovich, John C. Cheville, Yong Guo, Jessica Sagen, Janet E. Olson, Alicia Algeciras-Schimnich, Sean J. Pittock, John R. Mills, Surendra Dasari, Divyanshu Dubey. iSIGN panel identifies germ cell tumors via whole-proteome phage immunoprecipitation sequencing [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Mechanisms of Cancer Immunity and Cancer-related Autoimmunity; 2025 Sep 24-27; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(9 Suppl):Abstract nr B027.

Aims Schistosomiasis remains endemic in various parts of the world, and insights into pathogen immunobiology are mainly based on experimental models, while studies on human tissues are limited. Methods We explored the role of immune checkpoint pathway by evaluating the immunohistochemical expression of programmed death-ligand 1 (PD-L1) in a retrospective cohort of patients with bilharzial cystitis. Inflammation severity by conventional histology and staining intensity by immunohistochemistry were assigned three-tier scores (0/1+/2+), and a cut-off for staining percentage was set at 5%. Results 38 biopsies from 31 patients were considered adequate for evaluation, and positive staining was detected in 80.6% of patients (34 biopsies). High expressors (22.6%) showed strong positive membranous staining (score 2+) with high staining density (more than 5% of inflammatory cells). Low expressors (58.1%) showed mild/moderate staining (score 1+) predominantly in less than 5% of the cells (91.6%) or expressed restricted cytoplasmic staining (6/31). All high expressors showed severe inflammation (score 2+) (p<0.001), and viable ova were only observed in these cases. Calcified ova were associated with mild/moderate inflammation or absent/minimal inflammation, correlating with low expressors or non-expressors (19.4%), respectively. Conclusion Schistosomal granuloma exhibits upregulated PD-L1 expression proportional to inflammation severity and pathogen viability, highlighting a critical immune checkpoint engagement in disease pathology.

Pelvicalyceal invasion (PCI) is a relatively novel pT3a staging parameter for renal cell carcinoma (RCC) nephrectomies. While interobserver reproducibility staging studies of sinus/vascular invasion in RCC exist, a similar evaluation for PCI has not been performed. Moreover, in our experience, there is also diagnostic variability in how pathologists interpret PCI. Herein, we explore interobserver reproducibility among genitourinary (GU) pathologists. Twenty hematoxylin and eosin-stained digitized slides from RCCs (all grossly approaching the renal pelvis) were distributed to 31 GU pathologists to classify each as PCI or not PCI based on their respective clinical practices; slides with concomitant sinus/fat/vascular invasion were excluded. Slides were then evaluated for the following 4 morphologic features: tumor abutting renal pelvis, tumor pushing/indenting into the renal pelvis, polypoid configuration of tumor into the renal pelvis, and tumor eroding through renal pelvic urothelium. Interobserver reproducibility was assessed, and the morphologic features were correlated with PCI. Relationships between pathologists’ interpretations, morphologic features, and PCI were evaluated using hierarchical clustering. Although the diagnosis of PCI was relatively uniform with a majority agreement (>67%) reached in 16/20 slides, overall interobserver reproducibility was only moderate (kappa=0.601). While all 4 morphologic features were sensitive for PCI, polypoid configuration of the tumor into the renal pelvis and the tumor eroding through the renal pelvic urothelium were most specific (90%, 100%, respectively). Although we show general consensus among genitourinary pathologists on PCI assessment, clarifying the diagnostic guidelines with specific criteria should be included in pathologic staging systems.

Aims Testicular sex cord‐stromal tumours (TSCSTs) are relatively rare, accounting for ~5% of all testicular neoplasms. They were historically classified into Leydig cell tumour, Sertoli cell tumour, granulosa cell tumour, and unclassified sex cord‐stromal tumour. More recently, classification was expanded to incorporate additional histologic types, including some associated with inherited cancer predisposition syndromes. However, the classification of TSCSTs still relies entirely on morphology, with some tumour types being defined based on their resemblance to ovarian counterparts. In recent years, molecular studies have identified drivers and genomic alterations associated with aggressive behaviour and progression; however, these findings have not yet impacted classification and management. Methods and results Under sponsorship of the International Society of Urological Pathology (ISUP) and the Genitourinary Pathology Society (GUPS), a group of genitourinary pathologists was assembled in 2023 with the aim of assessing how to use these new data to improve the classification and management of TSCSTs. Conclusions This paper summarizes the recommendations derived from the consensus activities and the first meeting of the te sticular s ex cord‐ s tromal t umour (TESST) group (held at Johns Hopkins Hospital, Baltimore, USA, 3/23/2024).

Abstract Objectives We aimed to assess the expression of biomarkers of response to antibody-drug conjugates (TROP2 and nectin-4) and immune microenvironment (NKG7, PD-L1, and B7-H3) in penile squamous cell carcinoma (pSCC). Methods Our archive was queried for patients who had a penectomy for pSCC between 2000 and 2022. Primary tumors were immunostained for B7-H3 and NKG7, while metastatic specimens were immunostained for TROP2 and nectin-4. Expression of PD-L1, TROP2, and nectin-4 in primary tumors was previously characterized. H-scores (0-300) were used to quantify expression. Associations between biomarkers, tumor-infiltrating lymphocytes (TILs), and clinicopathologic and outcome parameters were evaluated. Results For both TROP2 and nectin-4, H-scores within the lymph node metastases were higher compared to those within the primary tumors (mean, 264.5 vs 244.8, P = .0003; mean, 170.6 vs 146.7, P = .05, respectively; 33 paired specimens). For B7-H3 (n = 107), 32.7% of the primary tumors had an H-score of more than 0. In 34.8% of the cases, NKG7 expression was observed in 25% to 50% of the TILs. A significant association was noted between TIL density, B7-H3, NKG7, and PD-L1 expression. Conclusions Therapeutic strategies targeting TROP2 and nectin-4 hold promise for patients with advanced pSCC. The potential of PD-L1, B7-H3, and NKG7 for predicting response to immunomodulatory treatment warrants further research.

Abstract Recent studies have described the tumor microenvironment and the key transcription factors in untreated small cell lung cancer (SCLC), but less is known about the salient features in recurrent SCLC (rSCLC). This information could provide valuable insight about the effectiveness of second and later line therapies. In this study, we compared transcriptome profiles (by RNA-seq) of rSCLC against untreated primaries (pSCLC). rSCLC samples (n=23) were obtained from frozen biopsies in patients enrolled in our MC1923 (NCT04607954) phase 2 clinical trial whose disease progressed after chemoimmunotherapy. The pSCLC group (n=73) included publicly available data from fresh frozen primary tumors after surgical resections. Normalized expression data were used in immune deconvolution and gene set enrichment analysis (GSEA) in molecular signature database. Additional GSEA included gene sets describing ASCL1 (A), NEUROD1 (N), ASCL1 and NEUROD1 (AN), and POU2F3 (P) transcription factor activities which are used for subtyping of SCLC. Immune deconvolutions by multiple software algorithms suggested depletion of immune infiltrates in rSCLC compared with pSCLC including dendritic cells, B cells, CD8+ T cells, and M1 macrophages. Furthermore, we found decreased chemotaxis and increased apoptosis of dendritic cells, reduced TNF signaling, and reduced lymphocyte co-stimulation in rSCLC by GSEA. Additionally, in comparisons with pSCLC, rSCLC tumors had significantly lower enrichment scores for POU2F3 activity, representing the SCLC-P subtype (p &lt; 0.007). Importantly, the SCLC-P was recently reported to be more immune inflamed than the other A, N, and AN subtypes. Altogether, our analyses provide strong evidence that the tumor microenvironment of rSCLC is significantly more immunosuppressed and with reduced immune cell infiltrates compared to pSCLC. Developing therapeutic strategies aimed at “warming” the tumor microenvironment and enhancing anti-tumor immune activity in ongoing multimodal therapies of recurrent SCLC will likely provide significant benefits to patients. Citation Format: Farhad Kosari, Mohamed Ali, Sarah H. Johnson, Alex Adjei, Julian R. Molina, Aaron S. Mansfield, Anastasios Dimou, Kaushal Parikh, Mohamed Shanshal, Katherine E. Smith, Ailsa G. Luce, Anna J. Schwecke, Janet Lensing, Ying-Chun Lo, John C. Cheville, George Vasmatzis, Konstantinos Leventakos. Small cell lung cancer (SCLC) at recurrence has a “colder” tumor microenvironment than primary SCLC according to gene expression profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6614.

Abstract Histopathology has been a cornerstone of biomedical tissue assessment for decades, involving a labor-intensive and multi-step process that includes biopsy, gross examination, sampling, and subsequent tissue processing into snap-frozen or formalin-fixed paraffin-embedded (FFPE) blocks. These blocks are then sectioned, stained, and examined microscopically to diagnose and grade tissues. Despite its effectiveness, the traditional workflow is time-consuming, resource-intensive, and reliant on chemical dyes and expert interpretation. Recently, innovative chemical imaging techniques, such as Stimulated Raman Scattering (SRS) microscopy, have begun to redefine this field by enabling direct measurement of the molecular composition of tissues, thereby bypassing conventional tissue processing and staining protocols. This study demonstrates the integration of SRS microscopy into pathology workflows to rapidly acquire high-resolution chemical data from minimally processed fresh-frozen tissues. Unlike traditional methods that rely on thin-sectioned slides, this approach collects data from intact thick tissues using "optical sectioning, " enabling the generation of three-dimensional datasets across multiple planes. These chemical images are processed through a generative adversarial network (GAN) pipeline to produce virtual hematoxylin and eosin (H&E) images that are visually and diagnostically comparable to traditionally stained specimens. Furthermore, the generative model is extended to simulate the morphology and staining patterns of FFPE-processed tissues, offering a versatile tool for creating archival-quality images. This method significantly enhances diagnostic capabilities by preserving lipids and small molecules that are often lost during conventional processing. Within minutes, it generates high-quality stained images that demonstrated high inter-pathologist agreement in tissue grading, proving diagnostically reliable for clinical use. We evaluate our approach through a comprehensive survey of pathologists, assessing its diagnostic utility and reliability. Our results demonstrate that the generated images are comparable in quality to real histological images, showing no discernible inferiority in diagnostic utility. In prostate pathology, the integration of SRS microscopy and AI significantly streamlines traditional workflows, reducing complexity and processing time while preserving diagnostic precision. Citation Format: Kianoush Falahkheirkhah, Sudipta Mukherjee, John Cheville, Rohit Bhargava. Enhancing pathology workflows with chemical imaging and AI-driven generative models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2469.