Eosinophilia is typically secondary, that is, reactive, in nature and is associated with a wide variety of neoplastic and non‐neoplastic disorders. Clonal eosinophilia is also seen in a wide variety of hematopoietic neoplasms, and sub‐classification can be diagnostically challenging. A proper evaluation of persistent eosinophilia involves correlation of clinical history, laboratory data, cellular morphology, and ancillary testing. Knowledge of appropriate ancillary testing is necessary for a timely diagnosis. We present a review of the literature regarding eosinophilia, including the 2016 World Health Organization (WHO) update of WHO‐defined eosinophilic disorders. We also present a review of eosinophilia in a case‐based format including guidelines for evaluation of both routine and challenging cases. The purpose of this guideline is not to provide an in‐depth discussion of each diagnosis, but rather a practical method that all pathologists can utilize to investigate eosinophilia.

Ferroptosis has emerged as a cytotoxic T lymphocyte (CTL)-induced tumor cell death pathway. The regulation of tumor cell sensitivity to ferroptosis is incompletely understood. Here, we report that interferon regulatory factor 8 (IRF8) functions as a regulator of tumor cell intrinsic ferroptosis. Genome-wide gene expression profiling identified the ferroptosis pathway as an IRF8-regulated pathway in tumor cells. IRF8.KO tumor cells acquire resistance to intrinsic ferroptosis induction and IRF8-deficient tumor cells also exhibit decreased ferroptosis in response to tumor-specific CTLs. Irf8 deletion increased p53 expression in tumor cells and knocking out p53 in IRF8.KO tumor cells restored tumor cell sensitivity to intrinsic ferroptosis induction. Furthermore, IRF8.KO tumor cells grew significantly faster than WT tumor cells in immune-competent mice. To restore IRF8 expression in tumor cells, we designed and synthesized codon usage-optimized IRF8-encoding DNA to generate IRF8-encoding plasmid NTC9385R-mIRF8. Restoring IRF8 expression via a lipid nanoparticle-encapsulated NTC9385R-mIRF8 plasmid therapy suppressed established tumor growth in vivo. In human cancer patients, nivolumab responders have a significantly higher IRF8 expression level in their tumor cells as compared to the non-responders. Our data determine that IRF8 represses p53 expression to maintain tumor cell sensitivity to intrinsic ferroptosis.

A hallmark of human colorectal cancer is lost expression of FAS, the death receptor for FASL of cytotoxic T lymphocytes (CTLs). However, it is unknown whether restoring FAS expression alone is sufficient to suppress csolorectal-cancer development. The FAS promoter is hypermethylated and inversely correlated with FAS mRNA level in human colorectal carcinomas. Analysis of single-cell RNA-Seq datasets revealed that FAS is highly expressed in epithelial cells and immune cells but down-regulated in colon-tumor cells in human colorectal-cancer patients. Codon usage-optimized mouse and human FAS cDNA was designed, synthesized, and encapsulated into cationic lipid to formulate nanoparticle DOTAP-Chol-mFAS and DOTAP-Chol-hFAS, respectively. Overexpression of codon usage-optimized FAS in metastatic mouse colon-tumor cells enabled FASL-induced elimination of FAS⁺ tumor cells in vitro, suppressed colon tumor growth, and increased the survival of tumor-bearing mice in vivo. Overexpression of codon-optimized FAS-induced FAS receptor auto-oligomerization and tumor cell auto-apoptosis in metastatic human colon-tumor cells. DOTAP-Chol-hFAS therapy is also sufficient to suppress metastatic human colon tumor xenograft growth in athymic mice. DOTAP-Chol-mFAS therapy exhibited no significant liver toxicity. Our data determined that tumor-selective delivery of FAS DNA nanoparticles is sufficient for suppression of human colon tumor growth in vivo.

Publicly available gene expression datasets were analyzed to develop a chromophobe and oncocytoma related gene signature (COGS) to distinguish chRCC from RO. The datasets GSE11151, GSE19982, GSE2109, GSE8271 and GSE11024 were combined into a discovery dataset. The transcriptomic differences were identified with unsupervised learning in the discovery dataset (97.8% accuracy) with density based UMAP (DBU). The top 30 genes were identified by univariate gene expression analysis and ROC analysis, to create a gene signature called COGS. COGS, combined with DBU, was able to differentiate chRCC from RO in the discovery dataset with an accuracy of 97.8%. The classification accuracy of COGS was validated in an independent meta-dataset consisting of TCGA-KICH and GSE12090, where COGS could differentiate chRCC from RO with 100% accuracy. The differentially expressed genes were involved in carbohydrate metabolism, transcriptomic regulation by TP53, beta-catenin-dependent Wnt signaling, and cytokine (IL-4 and IL-13) signaling highly active in cancer cells. Using multiple datasets and machine learning, we constructed and validated COGS as a tool that can differentiate chRCC from RO and complement histology in routine clinical practice to distinguish these two tumors.

The standard-of-care (SOC) for genomic testing of myeloid cancers primarily relies on karyotyping/fluorescent in situ hybridization (FISH) (cytogenetic analysis) and targeted gene panels (usually ≤54 genes) that harbor hotspot pathogenic variants (molecular genetic analysis). Despite this combinatorial approach, ~50% of myeloid cancer genomes remain cytogenetically normal, and the limited sequencing variant profiles obtained from targeted panels are unable to resolve the molecular etiology of many myeloid tumors. In this study, we evaluated the performance and clinical utility of combinatorial use of optical genome mapping (OGM) and a 523-gene next-generation sequencing (NGS) panel for comprehensive genomic profiling of 30 myeloid tumors and compared it to SOC cytogenetic methods (karyotyping and FISH) and a 54-gene NGS panel. OGM and the 523-gene NGS panel had an analytical concordance of 100% with karyotyping, FISH, and the 54-gene panel, respectively. Importantly, the IPSS-R cytogenetic risk group changed from very good/good to very poor in 22% of MDS (2/9) cases based on comprehensive profiling (karyotyping, FISH, and 54-gene panel vs. OGM and 523-gene panel), while additionally identifying six compound heterozygous events of potential clinical relevance in six cases (6/30, 20%). This cost-effective approach of using OGM and a 523-gene NGS panel for comprehensive genomic profiling of myeloid cancers demonstrated increased yield of actionable targets that can potentially result in improved clinical outcomes.