Citations

ABSTRACT Lymphoma is one of the leading causes of cancer and cancer deaths and yet has not been amenable to population screening. The role of methylated DNA markers (MDMs) in the detection of lymphoma has not been extensively studied. We aimed to discover, validate, and test tissue–derived MDMs of lymphoma in archival plasma specimens. Reduced representation bisulfite sequencing (RRBS) was performed on a discovery set of frozen tissues. MDMs identified were converted to methylation–specific PCR assays and validated on independent formalin–fixed, paraffin‐embedded (FFPE) tissues. Target enrichment long–probe quantitative‐amplified signal (TELQAS) assays were developed and assayed in plasma–extracted, bisulfite‐converted DNA from independent treatment‐naïve lymphoma patients and healthy controls. Prediction of cancer status was modeled using random forest model with in silico cross‐validation. After discovery and validation in tissue, 16 TELQAS assays ( ZNF503 , VWA5B1 , HOXA9 , GABRG3 , ITGA5 , MAX.chr17.7190 , BNC1 , CDK20 , MAX.chr4.4069 , TPBG , DNAH14 , SYT6 , CACNG8 , FAM110B , ADRA1D , and NRN1 ) were selected for testing in plasma. These detected 78% (95% CI, 74%–82%) of lymphoma cases at 90% specificity. Excluding marginal zone and T‐cell lymphomas, sensitivity increased to 84% (80%–88%). MDMs in plasma show promise to detect lymphoma and are candidates for inclusion in multi‐cancer detection studies.

Abstract Background Sarcomatoid carcinomas (SC) are rare tumors with both epithelial and mesenchymal characteristics, linked to aggressive behavior and poor prognosis. Sarcomatoid carcinoma of unknown primary (SCUP) is an exceedingly rare subset with limited literature and no standardized management guidelines. This study aims to characterize the clinical presentations, treatment patterns, and genomic landscape of SCUP. Patients and Methods Data were retrospectively collected from the Mayo Clinic Rochester Cancer of Unknown Primary Registry. Patients included had biopsy-proven SC with no identifiable primary tumor despite comprehensive diagnostic evaluations. Baseline characteristics, immunohistochemistry (IHC) results, next-generation sequencing (NGS) data, and treatment outcomes were analyzed. Statistical analyses included descriptive statistics, Kaplan–Meier survival estimates, and Cox proportional hazards regression. Results Fifty-two SCUP patients were identified, with a median age of 60 years. Most patients presented with widely metastatic disease, particularly lytic bone lesions. Elevated alkaline phosphatase (ALP) was noted in nearly half of the patients. IHC showed high positivity for AE1/AE3 and OSCAR antibodies. Tumor NGS revealed 247 alterations, with TP53 being the most common mutation. Patients receiving definitive therapy had a median overall survival (OS) of 72 months, significantly longer than those receiving systemic therapy (14 months). Immunotherapy was a significant prognostic factor, reducing the risk of death by 90%. Conclusions This study provides essential insights into the clinical and genomic characteristics of SCUP, advocating for the integration of definitive therapy and immunotherapy in treatment protocols. Further prospective studies are needed to validate these findings and improve patient outcomes.

Background: Angiosarcomas are rare tumors that can be difficult to diagnose due to subtle changes in the vascular endothelium. When there is evidence to suggest malignancy, such as a pathologic fracture, further investigation is needed, and a high suspicion for angiosarcoma needs to be present so that appropriate immunohistochemical stains are utilized on biopsied tissue. In situations where such suspicion is high and prior biopsies have been negative, performance of splenectomy, can be both diagnostic and therapeutic when splenomegaly is present. Case Report: This is a case of a 52-year-old woman with splenomegaly, initially attributed to infection, in the setting of upper respiratory symptoms and thrombocytopenia. Three months later, however, she presented with back pain. Imaging showed lytic bone lesions with pathologic vertebral fracture and numerous liver lesions that were too small to characterize further. Initial biopsies of the liver and bone did not reveal a pathologic process. Several months later, still without a unifying diagnosis, she presented to our institution. MRI of the brain was done for neurologic concerns and showed pathologic enhancement in the calvarium. A PET scan showed diffuse avidity of the skeleton and spleen. After discussing the case with a hematologist, splenectomy was performed for both diagnostic and therapeutic purposes. Angiosarcoma was identified in the spleen and in a PET-directed bone biopsy. With a definitive diagnosis, she returned home and subsequently elected to pursue hospice care. Conclusion: When there is a high clinical suspicion for malignant angiosarcoma, a multidisciplinary approach is necessary to direct both tissue acquisition and necessary histochemical staining.

Abstract Background The authors previously developed an artificial intelligence (AI) to assist cytologists in the evaluation of digital whole‐slide images (WSIs) generated from bile duct brushing specimens. The aim of this trial was to assess the efficiency and accuracy of cytologists using a novel application with this AI tool. Methods Consecutive bile duct brushing WSIs from indeterminate strictures were obtained. A multidisciplinary panel reviewed all relevant information and provided a central interpretation for each WSI as being “positive,” “negative,” or “indeterminate.” The WSIs were then uploaded to the AI application. The AI scored each WSI as positive or negative for malignancy (i.e., computer‐aided diagnosis [CADx]). For each WSI, the AI prioritized cytologic tiles by the likelihood that malignant material was present in the tile. Via the AI, blinded cytologists reviewed all WSIs and provided interpretations (i.e., computer‐aided detection [CADe]). The diagnostic accuracies of the WSI evaluation via CADx, CADe, and the original clinical cytologic interpretation (official cytologic interpretation [OCI]) were compared. Results Of the 84 WSIs, 15 were positive, 42 were negative, and 27 were indeterminate after central review. The WSIs generated on average 141,950 tiles each. Cytologists using the AI evaluated 10.5 tiles per WSI before making an interpretation. Additionally, cytologists required an average of 84.1 s of total WSI evaluation. WSI interpretation accuracies for CADx (0.754; 95% CI, 0.622–0.859), CADe (0.807; 95% CI, 0.750–0.856), and OCI (0.807; 95% CI, 0.671–0.900) were similar. Conclusions This trial demonstrates that an AI application allows cytologists to perform a triaged review of WSIs while maintaining accuracy.

Abstract Objectives To describe mismatch repair (MMR) and microsatellite instability (MSI) testing practices in laboratories using the College of American Pathologists (CAP) MSI/MMR proficiency testing programs prior to the 2022 publication of the MSI/MMR practice guidelines copublished by CAP and the Association of Molecular Pathology (AMP). Methods Data from supplemental questionnaires provided with the 2020-B MSI/MMR programs to 542 laboratories across different practice settings were reviewed. Questionnaires contained 21 questions regarding the type of testing performed, specimen/tumor types used for testing, and clinical practices for checkpoint blockade therapy. Results Domestic laboratories test for MSI/MMR more often than international laboratories (P = .04) and academic hospitals/medical centers test more frequently than nonhospital sites/clinics (P = .03). The most commonly used testing modality is immunohistochemistry, followed by polymerase chain reaction, then next-generation sequencing. Most laboratories (72.6%; 347/478) reported awareness of the use of immune checkpoint inhibitor therapy for patients with high MSI or MMR-deficient results. Conclusions The results demonstrate the state of MMR and MSI testing in laboratories prior to the publication of the CAP/AMP best practice guidelines, highlighting differences between various laboratory types. The findings indicate the importance of consensus guidelines and provide a baseline for comparison after their implementation.

Aims. To assess the utility of C4d immunohistochemistry for esophageal pemphigus vulgaris. Methods and results. We searched for patients with a history of esophageal pemphigus vulgaris who had esophageal biopsies for routine hematoxylin and eosin (H&E) staining. A total of 8 biopsies from 7 patients were available. We also identified 18 non-pemphigus esophageal biopsies for controls. C4d immunohistochemistry was performed on each biopsy. Five of 6 (83%) biopsies with classic pemphigus vulgaris histologic findings were positive for intercellular staining at the basal layer. The negative biopsy was in a patient that had recently received high-dose corticosteroid treatment for a flare. Two biopsies with atypical histologic features for pemphigus vulgaris had negative C4d staining but positive direct immunofluorescence (DIF) studies. Various nonspecific C4d staining patterns were observed in the controls, but none showed the intercellular staining pattern that was observed in pemphigus vulgaris. Conclusions. Suprabasal clefting with acantholysis and “tombstone effect” are described histologic features of pemphigus vulgaris on H&E. However, procedural artifact may mimic these findings. Currently, the gold standard for pemphigus vulgaris is DIF, which is not always available because it cannot routinely be performed on formalin-fixed paraffin embedded tissue. Our study shows that C4d immunohistochemistry may be a useful adjunct in evaluating esophageal pemphigus vulgaris.

Abstract Aberrant activation of GLI transcription factors has been implicated in the pathogenesis of different tumor types including pancreatic ductal adenocarcinoma. However, the mechanistic link with established drivers of this disease remains in part elusive. In this study, using a new genetically engineered mouse model overexpressing constitutively active mouse form of GLI2 and a combination of genome-wide assays, we provide evidence of a novel mechanism underlying the interplay between KRAS, a major driver of pancreatic ductal adenocarcinoma development, and GLI2 to control oncogenic gene expression. These mice, also expressing KrasG12D, show significantly reduced median survival rate and accelerated tumorigenesis compared with the KrasG12D only expressing mice. Analysis of the mechanism using RNA sequencing demonstrate higher levels of GLI2 targets, particularly tumor growth–promoting genes, including Ccnd1, N-Myc, and Bcl2, in KrasG12D mutant cells. Furthermore, chromatin immunoprecipitation sequencing studies showed that in these cells KrasG12D increases the levels of trimethylation of lysine 4 of the histone 3 (H3K4me3) at the promoter of GLI2 targets without affecting significantly the levels of other major active chromatin marks. Importantly, Gli2 knockdown reduces H3K4me3 enrichment and gene expression induced by mutant Kras. In summary, we demonstrate that Gli2 plays a significant role in pancreatic carcinogenesis by acting as a downstream effector of KrasG12D to control gene expression.

3520 Background: In patients with metastatic colorectal cancer (CRC) and deficient DNA mismatch repair (dMMR), we previously found transcriptomic signatures reflecting stromal compartment composition and proliferative capacity that can predict the efficacy of immune checkpoint blockade (ICB). To identify proteomic markers of response and/or resistance to ICB, we performed spatially resolved proteomic analysis of the tumor microenvironment. Methods: Patients with surgically resected, primary dMMR metastatic CRCs received pembrolizumab (Mayo Clinic, N=30). In FFPE tissues, Digital Spatial Profiling of 71 proteins was performed using panels covering immune cells, immune activation, cell death, PI3/AKT signaling, MAPK signaling, and pan-tumor markers (GeoMx nCounter). In ten regions of interest/slide (~600 µm2) at the tumor invasive margin, protein expression was determined in four cellular compartments: epithelium (panCK+), immune cells (CD45+; leucocyte common antigen), stroma (panCK-), and nonimmune stroma (panCK-/CD45-). After normalization, protein abundance per compartment was analyzed by response (RECIST 1.1) [OmicVerse Python]. Differentially expressed proteins (binary) were examined by progression-free survival (PFS) using multivariable Cox regression with covariate adjustment (Lifelines Python). Results: Pre-treatment panels including 71 proteins were analyzed by treatment response and PFS after PD-1 inhibition. Proteins found to be significantly associated with response (p< 0.01) and PFS are described. Across all compartments, responders showed upregulation of NK cells and T cell subsets (CD3+, CD4+, CD8+), and ICOS; strongest association was found for CD4+: HRadj: 0.16; 95%CI: 0.08-0.31; p< 0.001. Nonresponders showed higher phospho-JNK (HRadj: 2.09; 95%CI: 1.28-3.42; p=0.003) and SMA. In the epithelial compartment, upregulation of the Treg marker CD25 and reduced caspase-9 were observed in responders. Among responders, the stromal compartment was highly enriched in HLA-DR, dendritic cells (CD11c), PD-L1, immune activation markers (CD40, CD44, CD80, CD27), CD95/Fas, and GZMB. In the stromal compartment, downregulation of BCL6 and phospho-GSK3B was observed in responders. The immune compartment of responders showed increased beta2-microglobulin and Ki-67, while the non-immune stromal compartment showed increase in the macrophage marker CD68. Importantly, proteins found to be upregulated in responders were significantly and independently associated with longer PFS whereas the opposite was true for nonresponders. Conclusions: In metastatic dMMR CRCs, spatially defined protein markers were significantly associated with anti-PD-1 response, and independently associated with patient PFS (strongest predictive utility for CD4 in immune stroma and phospho-JNK in epithelium).

Abstract Deep learning may detect biologically important signals embedded in tumor morphologic features that confer distinct prognoses. Tumor morphologic features were quantified to enhance patient risk stratification within DNA mismatch repair (MMR) groups using deep learning. Using a quantitative segmentation algorithm (QuantCRC) that identifies 15 distinct morphologic features, we analyzed 402 resected stage III colon carcinomas [191 deficient (d)-MMR; 189 proficient (p)-MMR] from participants in a phase III trial of FOLFOX-based adjuvant chemotherapy. Results were validated in an independent cohort (176 d-MMR; 1,094 p-MMR). Association of morphologic features with clinicopathologic variables, MMR, KRAS, BRAFV600E, and time-to-recurrence (TTR) was determined. Multivariable Cox proportional hazards models were developed to predict TTR. Tumor morphologic features differed significantly by MMR status. Cancers with p-MMR had more immature desmoplastic stroma. Tumors with d-MMR had increased inflammatory stroma, epithelial tumor-infiltrating lymphocytes (TIL), high-grade histology, mucin, and signet ring cells. Stromal subtype did not differ by BRAFV600E or KRAS status. In p-MMR tumors, multivariable analysis identified tumor-stroma ratio (TSR) as the strongest feature associated with TTR [HRadj 2.02; 95% confidence interval (CI), 1.14–3.57; P = 0.018; 3-year recurrence: 40.2% vs. 20.4%; Q1 vs. Q2–4]. Among d-MMR tumors, extent of inflammatory stroma (continuous HRadj 0.98; 95% CI, 0.96–0.99; P = 0.028; 3-year recurrence: 13.3% vs. 33.4%, Q4 vs. Q1) and N stage were the most robust prognostically. Association of TSR with TTR was independently validated. In conclusion, QuantCRC can quantify morphologic differences within MMR groups in routine tumor sections to determine their relative contributions to patient prognosis, and may elucidate relevant pathophysiologic mechanisms driving prognosis. Significance: A deep learning algorithm can quantify tumor morphologic features that may reflect underlying mechanisms driving prognosis within MMR groups. TSR was the most robust morphologic feature associated with TTR in p-MMR colon cancers. Extent of inflammatory stroma and N stage were the strongest prognostic features in d-MMR tumors. TIL density was not independently prognostic in either MMR group.