Cheville, John C.

Pathology remains a labor-intensive discipline, relying on workflows rooted in practices established over a century ago. Despite incremental technological advancements, the diagnostic process—from tissue preparation to interpretation—still heavily depends on thinly sliced tissue sections stained and examined under brightfield microscopy by skilled pathologists. Difficult cases often necessitate iterative staining or complex immunohistochemistry (IHC) analyses. However, the recent emergence of machine learning (ML) presents an opportunity to revolutionize traditional diagnostic workflows. One promising advancement is Digital Chemical Pathology (DCP), a paradigm that combines modern ML algorithms with infrared (IR) imaging to streamline pathology and enhance diagnostic accuracy. Infrared wavelengths inherently align with molecular vibrational frequencies, providing intrinsic contrast based on the chemical composition of samples. Mid-IR spectroscopic microscopes leverage this principle to spatially resolve molecular distributions at the pixel level, creating "chemical fingerprints" that ML algorithms can correlate with cellular identities and disease states. Recent advancements, particularly the development of broadly tunable quantum cascade lasers (QCLs), have enabled faster IR imaging, paving the way for clinical applications of IR spectroscopic microscopes. In this research, we demonstrate the potential of DCP using frozen tissue samples. Our approach focuses on two core tasks: (1) virtual staining, translating IR images into realistic, stained images interpretable by pathologists, and (2) tissue segmentation, enabling the automated detection of cancer and the distinction between normal and cancerous tissues. Furthermore, we incorporate statistical safety algorithms to generate uncertainty maps, ensuring the reliability of predictions. Our findings highlight that the integration of IR imaging and ML can facilitate automated diagnostics, providing pathologists with powerful tools for enhanced healthcare delivery. By leveraging DCP, we aim to modernize pathology workflows, reduce diagnostic turnaround times, and improve patient outcomes through precise and efficient analysis. Citation Format: Kianoush Falahkheirkhah, Kevin Yeh, Ji-Hun Oh, Yen-Ting Liu, Ruo-Jing Ho, Ishaan Sharma, Matthew Confer, Andres Orr, Mykolas Tamonis, John Cheville, Rohit Bhargava. Transforming cancer diagnosis with digital chemical pathology [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 2470.

Abstract Background The mechanisms underlying metastatic latency in renal cell carcinoma (RCC) remain poorly understood. Methods This study evaluated 2 large independent cohorts for differences in tumor biology between patients who developed metastases early (≤1 year after nephrectomy) and those with late onset (>3 years). Results In the discovery cohort (n = 161), late metastatic RCC was associated with clear cell histology (88.9% vs 78.7%), lower pathological stage (pT1-2; 40.3% vs 18.0%), and favorable histopathological features including low grade (40.0% vs 2.3%), less sarcomatoid (5.6% vs 21.8%), and reduced necrosis (37.7% vs 78.3%; all P < .02). Late metastatic RCC tumors exhibited increased angiogenesis (63.5% vs 19.4%) and reduced inflammation (78.8% vs 50.0%; all P < .02) profiles. Genomic driver analyses revealed comparable rates of PBRM1 and SETD2 loss in late and early metastatic RCC, while BAP1 loss was significantly less common in late metastatic RCC (7.5% vs 27.1%; P < .02). In multivariable models, BAP1/PBRM1/SETD2 status and tumor necrosis emerged as key discriminators of late metastatic RCCs. These findings were confirmed in the second cohort (n = 307). Late metastatic RCC was enriched for fatty acid oxidation and angiogenesis pathways, supporting a less aggressive phenotype. This was further evidenced by a lower engraftment rate in murine models (0% vs 36.5%; P < .001) and significantly longer overall survival from the time of metastasis (median survival doubled, P < .001). Interestingly, late metastatic RCC shared genomic and phenotypic features with RCC that metastasizes to the pancreas, suggesting a common underlying biology influencing both metastatic latency and pancreatic tropism. Conclusions Overall, these findings advocate for recognition of late metastatic RCC because of its distinct biology and improved prognosis.

Abstract Purpose: Monitoring disease progression in patients with high-grade gliomas (HGG) is challenging due to treatment-related changes in imaging and the requirement for neurosurgical intervention to obtain diagnostic tissue. DNA junctions in HGG often amplify oncogenes, making these DNA fragments potentially more abundant in blood than monoallelic mutations. In this study, we piloted a cell-free DNA approach for disease detection in the plasma of patients with HGG by leveraging patient-specific DNA junctions associated with oncogene amplifications. Experimental Design: Whole-genome sequencing of grade 3 or 4 isocitrate dehydrogenase–mutant or wild-type astrocytomas was utilized to identify amplified junctions. Individualized qPCR assays were developed using patient-specific primers designed for the amplified junction. ctDNA levels containing these junctions were measured in patient plasma samples. Results: Unique amplified junctions were evaluated by individualized semi-qPCR assays in presurgical plasma of 18 patients, 15 with tumor-associated focal amplifications and three without tumor-associated focal amplifications. high copy-number junctions were robustly detected in the plasma of 14 of 15 (93.3%) patients with amplified junctions and none of the controls. Changes in junction abundance correlated with disease trajectory in serial plasma samples from five patients, including increased abundance of amplified junctions preceding radiographic disease progression. Conclusions: In patients with grade 3 or 4 astrocytomas who had tumor-associated amplifications, patient-specific amplified junctions were successfully detected in assayed plasma from most patients. Longitudinal analysis of plasma samples correlated with disease trajectory, including cytoreduction and progression.

Abstract Addressing the limited responsiveness to immune checkpoint blockade (ICB) in human cancers remains a critical challenge. Efforts over the past two decades have primarily focused on enhancing CD8 T cell function and preventing their exhaustion. However, less attention has been given to understanding the molecular mechanisms that contribute to the immunosuppressive tumor microenvironment (TME), which impedes CD8 T cell infiltration and fosters ICB resistance. The TME in ICB-resistant tumors is characterized by Transforming Growth Factor beta (TGF-β) cytokine signaling, leading to a fibrotic extracellular matrix (ECM) and the accumulation of immunosuppressive fibroblasts and myeloid cells. These features hinder CD8 T cell penetration, thereby promoting immune escape. The immune checkpoint molecule B7-H3, overexpressed in ICB-resistant cancers, has been linked to impaired CD8 T cell infiltration and poor prognosis. However, the molecular mechanisms governing B7-H3 function remain poorly understood. We investigated the relationship between B7-H3 gene expression and ICB response using transcriptomic data from two randomized phase 3 trials (IMvigor010 and IMvigor210). Bulk RNAseq data, tissue staining, and spectral flow cytometry were used to characterize the TME composition of B7-H3 high and low tumors. Multi-omic profiling of tumor cell lines with manipulated B7-H3 expression was performed to identify downstream targets of B7-H3. Syngeneic mouse tumor models were used to assess the impact of B7-H3 on tumor growth and antitumor immunity. High B7-H3 expression was associated with shorter overall survival in both IMvigor010 (HR=0.48, 95% CI: 0.33-0.70, p<0.0001) and IMvigor210 trials (HR=0.68, 95% CI: 0.51-0.92, p=0.01). In ICB-refractory cancers, B7-H3 expression correlated with high levels of fibroblasts, collagen deposits, and M2 macrophages. Gene set enrichment analysis revealed a positive association between B7-H3 and TGF-β signaling. Genetic deletion of B7-H3 in tumor cells reduced the surface expression of MMP14, a metalloprotease that activates TGF-β. Pan-cancer analysis identified MMP14 as the gene most correlated with B7-H3 (Pearson r=0.69, p<0.0001). TGF-β activation was reduced by 70% in B7-H3 knockout cells compared to wild-type. Loss of B7-H3 led to MMP14 accumulation in lysosomes, resulting in its degradation. We generated a B7-H3 inhibitor, 5D10, which promotes MMP14 degradation and inhibits TGF-β activation. In humanized B7-H3 mouse models, 5D10 significantly reduced TGF-β activation, enhancing CD8 T cell infiltration and impairing tumor growth. Our research identifies B7-H3 as a driver of immune exclusion and ICB resistance. We describe a novel, receptor-independent mechanism where B7-H3 promotes TGF-β activation via stabilization of MMP14. Targeting B7-H3 represents a strategy to modulate the TME, transforming immune-excluded tumors into immune-inflamed states that may respond better to ICB. Citation Format: Fabrice Lucien, Roxane Lavoie, Jack Korleski, Yohan Kim, Bharath Wootla, Liguo Wang, Ava Farrell, Kelly Harper, Martine Charbonneau, Claire Dubois, Igor Frank, Sounak Gupta, John Cheville, Jacob Orme, Stephen Boorjian, Parash Shah, Eugene Kwon, Sean Park, Haidong Dong. The immune checkpoint molecule B7-H3 is a driver of tumor immune exclusion by mediating TGF-β activation [abstract]. In: Proceedings of the AACR IO Conference: Discovery and Innovation in Cancer Immunology: Revolutionizing Treatment through Immunotherapy; 2025 Feb 23-26; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(2 Suppl):Abstract nr B034.

Abstract Accurate response assessment in patients with high-grade gliomas (HGGs) is complicated by post-treatment radiographic changes that are equivocal for treatment effect versus progression. Plasma-based liquid biopsy assays for circulating tumor DNA (ctDNA) have had limited sensitivity to date, due in part to the presence of the blood-brain barrier that limits the diffusion of tumor-derived analytes out of the central nervous system. To address this challenge, we developed a ctDNA plasma-based assay to detect individualized tumor-derived amplified junctions in patients with HGGs. These junctions occur due to large-scale chromosomal rearrangements, such as those associated with epidermal growth factor receptor (EGFR) or cyclin-dependent kinase 4 (CDK4) amplification. To identify these amplified junctions, whole genome sequencing was performed on resected tissue. Primers were designed to flank junction breakpoints and were then utilized on each patient’s plasma samples to detect the amplified junction via qPCR. Tumor-specific amplified junctions were robustly detected in plasma from 14/14 (100%) patients with IDH-mutant or wild-type grade 4 astrocytomas whose tumor genomes demonstrated amplification-related junctions, located at chromosomes 7, 11, or 12. In comparison, ctDNA could not be detected in three control cases that did not have an amplification or did not have high copy number junctions. Importantly, serial plasma samples obtained prior to and at disease recurrence in 4 patients demonstrated an increasing abundance of amplified junctions that accurately correlated with disease progression in 4/4 patients (100%). In two of these patients, increasing abundance of amplified junctions preceded radiographic changes compatible with disease progression by approximately 2 or 4 months, respectively. In conclusion, tumor-specific amplified junctions could reliably be detected in plasma from patients with IDH-mutant or wild-type grade 4 astrocytomas and correlated with changes in disease burden. Further work is currently ongoing to evaluate these promising results in a larger cohort of patients with serial plasma samples.

AbstractBackgroundNeoadjuvant platinum‐based chemotherapy offers a modest survival advantage in muscle‐invasive bladder cancer (MIBC) for patients with pathologic response. B7‐H3 (CD276), an immune checkpoint overexpressed in various cancers, including urothelial‐cell carcinoma (UCC), has been associated with chemoresistance and poor oncologic outcomes. We aimed to explore if B7H3 expression on bladder biopsy samples was a predictive biomarker for pathologic response to neoadjuvant platinum‐based chemotherapy.MethodsThis was a retrospective cohort study among MIBC patients receiving neoadjuvant platinum‐based chemotherapy followed by radical cystectomy. All patients underwent routine preoperative biopsy of their tumour. Immunohistochemistry was used to evaluate B7‐H3 expression from pre‐operative specimens. The primary outcome of interest was pathologic complete response (pCR). Statistical analysis included Mann–Whitney U test, Fisher's exact test, Kaplan–Meier method, and Cox regression for survival analysis.ResultsAmong 87 patients analysed, high B7‐H3 expression was found in 44.8% (n = 39) of patients. The median follow‐up periods were similar between the high and low B7‐H3 groups (high expression; 4.29 years [SD 3.04], low expression 3.94 years [SD 3.04], p = 0.60). Only 20.5% of patients with high B7‐H3 expression achieved pCR, compared to 41.7% in the low expression group (p = 0.04). Cox regression showed no significant differences in recurrence‐free or cancer‐specific survival between the high and low B7‐H3 expression groups (p > 0.05).ConclusionHigh B7‐H3 expression is associated with a reduced likelihood of achieving pCR in MIBC patients undergoing neoadjuvant chemotherapy. This suggests B7‐H3's potential as a predictive biomarker for chemotherapy response. Further research is needed to explore the role of B7‐H3 on platinum‐based chemotherapy response in urothelial cancer.

Introduction: Non-invasive assays are needed to better discriminate patients with prostate cancer (PCa) to avoid over-treatment of indolent disease. We analyzed 14 methylated DNA markers (MDMs) from urine samples of patients with biopsy-proven PCa relative to healthy controls and further studied discrimination of clinically significant PCa (csPCa) from healthy controls and Gleason 6 cancers. Methods: To evaluate the panel, urine from 24 healthy male volunteers with no clinical suspicion for PCa and 24 men with biopsy-confirmed disease across all Gleason scores was collected. Blinded to clinical status, DNA from the supernatant was analyzed for methylation signal within specific DNA sequences across 14 genes (HES5, ZNF655, ITPRIPL1, MAX.chr3.6187, SLCO3A1, CHST11, SERPINB9, WNT3A, KCNB2, GAS6, AKR1B1, MAX.chr3.8028, GRASP, ST6GALNAC2) by target enrichment long-probe quantitative-amplified signal assays. Results: Utilizing an overall specificity cut-off of 100% for discriminating normal controls from PCa cases across the MDM panel resulted in 71% sensitivity (95% CI: 49–87%) for PCa detection (4/7 Gleason 6, 8/12 Gleason 7, 5/5 Gleason 8+) and 76% (50–92%) for csPCa (Gleason ≥ 7). At 100% specificity for controls and Gleason 6 patients combined, MDM panel sensitivity was 59% (33–81%) for csPCa (5/12 Gleason 7, 5/5 Gleason 8+). Conclusions: MDMs assayed in urine offer high sensitivity and specificity for detection of clinically significant prostate cancer. Prospective evaluation is necessary to estimate discrimination of patients as first-line screening and as an adjunct to prostate-specific antigen (PSA) testing.