Multiplex imaging reveals spatially resolved DNA-damage response neighborhoods in TP53-mutated myelodysplastic neoplasms.

While increased DNA damage is a well-described feature of myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML), it is unclear whether all lineages and all regions of the marrow are homogeneously affected. In this study, we performed immunohistochemistry on formalin-fixed, paraffin-embedded whole-section bone marrow biopsies using a well-established antibody to detect pH2A.X (phosphorylated histone variant H2A.X) that recognizes DNA double-strand breaks. Focusing on TP53-mutated and complex karyotype MDS/AML, we find a greater pH2A.X+ DNA damage burden compared to TP53 wild-type neoplastic cases and non-neoplastic controls. To understand how double-strand breaks vary between lineages and spatially in TP53-mutated specimens, we applied a low-multiplex immunofluorescence staining and spatial analysis protocol to visualize pH2A.X+ cells with p53 protein staining and lineage markers. pH2A.X marked predominantly mid- to late-stage erythroids, whereas early erythroids and CD34+ blasts were relatively spared. In a prototypical example, these pH2A.X+ erythroids were organized locally as distinct colonies, and each colony displayed pH2A.X+ puncta at a synchronous level. This highly coordinated immunophenotypic expression was also seen for p53 protein staining and among presumed early myeloid colonies. Neighborhood clustering analysis showed distinct marrow regions differentially enriched in pH2A.X+/p53+ erythroid or myeloid colonies, indicating spatial heterogeneity of DNA-damage response and p53 protein expression. The lineage and architectural context within which DNA damage phenotype and oncogenic protein are expressed is relevant to current therapeutic developments that leverage macrophage phagocytosis to remove leukemic cells in part due to irreparable DNA damage. © 2024 The Pathological Society of Great Britain and Ireland.

HER2/ERBB2 copy number analysis by targeted next-generation sequencing in breast cancer.

OBJECTIVES: A combination of immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) is the current standard of care for HER2 evaluation in breast cancer. Here, we investigate the potential clinical utility of next-generation sequencing (NGS)-derived HER2/ERBB2 copy number (CN) data for predicting HER2 status as defined by American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) guidelines. METHODS: In total, 294 locally recurrent and metastatic breast cancers previously tested by targeted hybrid capture-based NGS and by HER2 IHC/FISH were included. Analyses focused on the ERBB2 median log2 ratios and start-end genomic coordinates from NGS, average HER2 CN and HER2/CEP17 ratios from FISH, and the HER2 IHC scores. We also determined a more stringent log2 ratio cutoff to predict HER2-positive status with 100% specificity. RESULTS: Sixty-four (22%) cases were HER2 positive and 230 (78%) were HER2 negative by ASCO/CAP guidelines. The ERBB2 median log2 ratios from NGS strongly correlated with HER2 status by IHC/FISH (area under receiver operator characteristic curve = 0.951). ERBB2 log2 ratio more than 1.7 was 100% specific for HER2-positive results by IHC/FISH. Start and end genomic coordinates for regions of gain near ERBB2 by NGS also predicted HER2 status. CONCLUSIONS: Copy number data from our NGS panel strongly correlate with HER2 status. Using a stringent cutoff, ERBB2 log2 ratio accurately predicts HER2 positivity with high specificity. The NGS CN assessment may have utility in determining HER2 status in certain clinical settings.

Long-standing laryngeal rhinoscleroma with rare Mikulicz cells.

Rhinoscleroma is an infectious granulomatous disease. It is important to identify pathognomonic Mikulicz cells on microscopy, as these can be rare and the chronic inflammatory infiltrate can appear otherwise nonspecific on biopsies.

Distinguishing Gastric/Esophageal Adenocarcinoma from Pancreatic Adenocarcinoma Using Methylation-Based Droplet Digital PCR.

The goal of this study was to develop a methylation-based droplet digital PCR to separate 2 cancer classes that do not have sensitive and specific immunohistochemical stains: gastric/esophageal and pancreatic adenocarcinomas. The assay used methylation-independent primers and methylation-dependent probes to assess a single differentially methylated CpG site; analyses of array data from The Cancer Genome Atlas network showed that high methylation at the cg06118999 probe supports the presence of cells originating from the stomach or esophagus (eg, as in gastric metastasis), whereas low methylation suggests that these cells are rare to absent (eg, pancreatic metastasis). On validation using formalin-fixed paraffin-embedded primary and metastatic samples from our institution, methylation-based droplet digital PCR targeting the corresponding CpG dinucleotide generated evaluable data for 60 of the 62 samples (97%) and correctly classified 50 of the 60 evaluable cases (83.3%), mostly adenocarcinomas from the stomach or pancreas. This ddPCR was created to be easy-to-interpret, rapid, inexpensive, and compatible with existing platforms at many clinical laboratories. We suggest that similarly accessible PCRs could be developed for other differentials in pathology that do not have sensitive and specific immunohistochemical stains.

Deep Learning Accurately Quantifies Plasma Cell Percentages on CD138-Stained Bone Marrow Samples.

The diagnosis of plasma cell neoplasms requires accurate, and ideally precise, percentages. This plasma cell percentage is often determined by visual estimation of CD138-stained bone marrow biopsies and clot sections. While not necessarily inaccurate, estimates are by definition imprecise. For this study, we hypothesized that deep learning can be used to improve precision. We trained a semantic segmentation-based convolutional neural network (CNN) using annotations of CD138+ and CD138- cells provided by one pathologist on small image patches of bone marrow and validated the CNN on an independent test set of image patches using annotations from two pathologists and a non-deep learning commercial software. On validation, we found that the intraclass correlation coefficients for plasma cell percentages between the CNN and pathologist #1, a non-deep learning commercial software and pathologist #1, and pathologists #1 and #2 were 0.975, 0.892, and 0.994, respectively. The overall results show that CNN labels were almost as accurate as pathologist labels at a cell-by-cell level. Once satisfied with performance, we scaled-up the CNN to evaluate whole slide images (WSIs), and deployed the system as a workflow friendly web application to measure plasma cell percentages using snapshots taken from microscope cameras.

Geographic Variability of Nodular Lymphocyte-Predominant Hodgkin Lymphoma.

OBJECTIVES: Nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) differs from classic Hodgkin lymphoma (CHL) in terms of clinicopathologic features, including Epstein-Barr virus (EBV) association. CHL geographic variability is well known, with higher frequencies of mixed-cellularity subtype and EBV positivity in low/middle-income countries (LMICs), but there are few well-characterized series of NLPHL from LMICs. METHODS: We detail clinicopathologic findings of 21 NLPHL cases received in consultation from Kenya and summarize reports of NLPHL with EBV testing published since 2000. RESULTS: Median age of consultation cases was 36 years, and male/female ratio was 3.2. All cases involved peripheral lymph nodes and showed at least some B-cell-rich nodular immunoarchitecture, with prominent extranodular lymphocyte-predominant (LP) cells and T-cell-rich variant patterns most commonly seen. LP cells expressed pan-B-cell markers, including strong OCT2; lacked CD30 and CD15 expression in most cases; and were in a background of expanded/disrupted follicular dendritic cell meshworks and increased T-follicular helper cells. LP cells were EBV negative in 18 cases. Historical cases showed a low rate of EBV positivity with no significant difference between LMICs and high-income countries. CONCLUSIONS: Unlike CHL, NLPHL shows few geographic differences in terms of clinicopathologic features and EBV association. These findings have implications for diagnosis, prognostication, and treatment of patients with NLPHL in LMICs.

DNA Methylation-Based Classification of Small B-Cell Lymphomas: A Proof-of-Principle Study.

Although most small B-cell lymphomas (SBCLs) can be diagnosed using routine methods, challenges exist. For example, marginal zone lymphomas (MZLs) can be difficult to rule-in, in large part because no widely-used, sensitive, and specific biomarker is available for the marginal zone cell of origin. In this study, it was hypothesized that DNA methylation array profiling can assist with the classification of SBCLs, including MZLs. Extramedullary SBCLs, including challenging cases, were reviewed internally for pathology consensus and profiled. By combining the resulting array data set with data sets from other groups, a set of 26 informative probes was selected and used to train machine learning models to classify 4 common SBCLs: chronic lymphocytic leukemia/small lymphocytic lymphoma, follicular lymphoma, mantle cell lymphoma, and MZL. Prediction probability cutoff was used to separate classifiable from unclassifiable cases, and show that the trained model was able to classify 95% of independent test cases (n = 264/279). The concordance between model predictions and pathology diagnoses was 99.6% (n = 262/263) among classifiable test cases. One validation reference test case was reclassified based on model prediction. The model was also used to predict the diagnoses of two challenging SBCLs. Although the differential examined and data on difficult cases are limited, these results support accurate methylation-based classification of SBCLs. Furthermore, high specificities of predictions suggest that methylation signatures can be used to rule-in MZLs.

Genomic Characterization of de novo Metastatic Breast Cancer.

PURPOSE: In contrast to recurrence after initial diagnosis of stage I-III breast cancer [recurrent metastatic breast cancer (rMBC)], de novo metastatic breast cancer (dnMBC) represents a unique setting to elucidate metastatic drivers in the absence of treatment selection. We present the genomic landscape of dnMBC and association with overall survival (OS). EXPERIMENTAL DESIGN: Targeted DNA sequencing (OncoPanel) was prospectively performed on either primary or metastatic tumors from 926 patients (212 dnMBC and 714 rMBC). Single-nucleotide variants, copy-number variations, and tumor mutational burden (TMB) in treatment-naïve dnMBC primary tumors were compared with primary tumors in patients who ultimately developed rMBC, and correlated with OS across all dnMBC. RESULTS: When comparing primary tumors by subtype, MYB amplification was enriched in triple-negative dnMBC versus rMBC (21.1% vs. 0%, P = 0.0005, q = 0.111). Mutations in KMTD2, SETD2, and PIK3CA were more prevalent, and TP53 and BRCA1 less prevalent, in primary HR+/HER2- tumors of dnMBC versus rMBC, though not significant after multiple comparison adjustment. Alterations associated with shorter OS in dnMBC included TP53 (wild-type: 79.7 months; altered: 44.2 months; P = 0.008, q = 0.107), MYC (79.7 vs. 23.3 months; P = 0.0003, q = 0.011), and cell-cycle (122.7 vs. 54.9 months; P = 0.034, q = 0.245) pathway genes. High TMB correlated with better OS in triple-negative dnMBC (P = 0.041). CONCLUSIONS: Genomic differences between treatment-naïve dnMBC and primary tumors of patients who developed rMBC may provide insight into mechanisms underlying metastatic potential and differential therapeutic sensitivity in dnMBC. Alterations associated with poor OS in dnMBC highlight the need for novel approaches to overcome potential intrinsic resistance to current treatments.

Minimalist approaches to cancer tissue-of-origin classification by DNA methylation.

Classification of cancers by tissue-of-origin is fundamental to diagnostic pathology. While the combination of clinical data, tissue histology, and immunohistochemistry is usually sufficient, there remains a small but not insignificant proportion of difficult-to-classify cases. These challenging cases provide justification for ancillary molecular testing, including high-throughput DNA methylation array profiling, which promises cell-of-origin information and compatibility with formalin-fixed specimens. While diagnostically powerful, methylation profiling platforms are costly and technically challenging to implement, particularly for less well-resourced laboratories. To address this, we simulated the performance of "minimalist" methylation-based tests for cancer classification using publicly-available and internal institutional profiling data. These analyses showed that small and focused sets of the most informative CpG biomarkers from the arrays are sufficient for accurate diagnoses. As an illustrative example, one classifier, using information from just 53 out of about 450,000 available CpG probes, achieved an accuracy of 94.5% on 2575 fresh primary validation cases across 28 cancer types from The Cancer Genome Atlas Network. By training minimalist classifiers on formalin-fixed primary and metastatic cases, generally high accuracies were also achieved on additional datasets. These results support the potential of minimalist methylation testing, possibly via quantitative PCR and targeted next-generation sequencing platforms, in cancer classification.

Emerging patterns in clonal haematopoiesis.

Clonal haematopoiesis (CH) is defined by the presence of acquired mutations and/or cytogenetic abnormalities in haematopoietic cells. By definition, these premalignant clones do not meet criteria for haematopoietic neoplasms listed in the Revised Fourth Edition of the WHO classification. CH is fairly common in elderly individuals and is associated with higher risks for haematological cancers, in particular myelodysplastic syndrome and acute myeloid leukaemia (AML), as well as cardiovascular events. Similar small clones have also been detected during follow-up in patients with AML in morphological remission, in individuals with aplastic anaemia, and in pre-chemotherapy blood samples from patients with other types of cancers. In each of these contexts, the presence of mutations carries different clinical implications, and sometimes demonstrates unique genetic profiles. Emerging research suggests that the number and identity of mutations, the size of the mutant clones and various other factors, including age, immune status and history of exogenous drugs/toxins, are important for disease biology and progression. This review focuses specifically on the subset of CH with gene mutations detected by sequencing, and includes discussions of nomenclature and molecular technologies that detect and quantify gene mutations.

NK-Cell Enteropathy and Similar Indolent Lymphoproliferative Disorders: A Case Series With Literature Review.

Objectives: We report four new cases of natural killer-cell enteropathy (NKCE) and similar lymphoproliferative disorders (LPDs), as well as review the literature concerning indolent natural killer (NK)-cell LPDs of the gastrointestinal tract. Methods: Pathologic and clinical data were obtained from institutional/referral records. Results: Patient 1 (45-year-old man) had anemia; a small intestinal lesion was endoscopically biopsied. Patient 2 (65-year-old woman) had biliary colic, treated with cholecystectomy. Patient 3 (62-year-old man) had a small colonic polyp, biopsied on routine colonoscopy. Patient 4 (68-year-old man) had presumed Crohn disease; multiple biopsies were performed over more than 10 years. Diagnostic specimens showed atypical infiltrates of Epstein-Barr virus-negative lymphocytes with immunophenotypes suggestive of NK cells. In all cases, there was distortion of glandular architecture but no marked intraepithelial lymphocytosis or necrosis. The patients did not receive therapy for lymphoma and were well on follow-up. Conclusions: These cases support the indolent nature of NKCE and similar LPDs, and they indicate that involvement outside the alimentary canal may occur.

MGMT promoter methylation status testing to guide therapy for glioblastoma: refining the approach based on emerging evidence and current challenges.

Glioblastoma (GBM) is the most common primary malignant brain tumor, with a universally poor prognosis. The emergence of molecular biomarkers has had a significant impact on histological typing and diagnosis, as well as predicting patient survival and response to treatment. The methylation status of the O6-methylguanine-DNA methyl-transferase (MGMT) gene promoter is one such molecular biomarker. Despite the strong evidence supporting the role of MGMT methylation status in prognostication, its routine implementation in clinical practice has been challenging. The methods and optimal cutoff definitions for MGMT status determination remain controversial. Variation in detection methods between laboratories presents a major challenge for consensus. Moreover, consideration of other clinical and genetic/epigenetic factors must also be incorporated into treatment decision making. In this review, we distill the available evidence to summarize our position on the optimal use of available assays, and propose strategies for resolving cases with equivocal methylation status and a framework for incorporating this important assay into research and clinical practice.

Trio-R: a script for assessing maternity and paternity in trio studies performed on Agilent chromosomal microarrays.

BACKGROUND: Trio studies, which involve the testing of samples from a proband and both parents, are often used by clinical laboratories to help with the classification of genetic variants, including copy number variants. In order for the results of the trio study to be valid, the mother and father must be the true biological parents of the proband. As such, non-paternity and sample mix-ups are potential sources of error. To address these potential issues, we developed a computer script to accurately assess maternity and paternity using single nucleotide polymorphism (SNP) data generated by Agilent chromosomal microarrays, a platform-of-choice for clinical copy number testing. RESULTS: We assessed the performance of the script on 10 putative trios tested at our laboratory, and found that the numbers and proportions of discordant SNPs were useful for determining parental relationships. The results of the assessment also confirmed maternity and paternity in the 10 trios tested, and by doing so essentially excluded pre-analytical sample switching in these 30 samples. CONCLUSIONS: Computational analysis of SNP data can be implemented as a quality control measure for trio testing performed on Agilent microarrays.

Computationally-Guided Development of a Stromal Inflammation Histologic Biomarker in Lung Squamous Cell Carcinoma.

The goal of this study is to use computational pathology to help guide the development of human-based prognostic H&E biomarker(s) suitable for research and potential clinical use in lung squamous cell carcinoma (SCC). We started with high-throughput computational image analysis with tissue microarrays (TMAs) to screen for histologic features associated with patient overall survival, and found that features related to stromal inflammation were the most strongly prognostic. Based on this, we developed an H&E stromal inflammation (SI) score. The prognostic value of the SI score was validated by two blinded human observers on two large cohorts from a single institution. The SI score was found to be reproducible on TMAs (Spearman rho = 0.88 between the two observers), and highly prognostic (e.g. hazard ratio = 0.32; 95% confidence interval: 0.19-0.54; p-value = 2.5 × 10-5 in multivariate analyses), particularly in comparison to established histologic biomarkers. Guided by downstream molecular/biomarker correlation studies starting with TCGA cases, we investigated the hypothesis that epithelial PD-L1 expression modified the prognostic value of SI. Our research demonstrates that computational pathology can be an efficient hypothesis generator for human pathology research, and support the histologic evaluation of SI as a prognostic biomarker in lung SCCs.

Morphoproteomic Characterization of Lung Squamous Cell Carcinoma Fragmentation, a Histological Marker of Increased Tumor Invasiveness.

Accurate stratification of tumors is imperative for adequate cancer management. In addition to staging, morphologic subtyping allows stratification of patients into additional prognostic groups. In this study, we used an image-based computational method on pan-cytokeratin IHC stainings to quantify tumor fragmentation (TF), a measure of tumor invasiveness of lung squamous cell carcinoma (LSCC). In two independent clinical cohorts from tissue microarrays (TMA: n = 208 patients) and whole sections (WS: n = 99 patients), TF was associated with poor prognosis and increased risk of blood vessel infiltration. A third cohort from The Cancer Genome Atlas (TCGA: n = 335 patients) confirmed the poor prognostic value of TF using a similar human-based score on hematoxylin-eosin staining. Integration of RNA-seq data from TCGA and LC-MS/MS proteomics from WS revealed an upregulation of extracellular matrix remodeling and focal adhesion processes in tumors with high TF, supporting their increased invasive potential. This proposed histologic parameter is an independent and unfavorable prognostic marker that could be established as a new grading parameter for LSCC. Cancer Res; 77(10); 2585-93. ©2017 AACR.

KIF13B-NRG1 Gene Fusion and KRAS Amplification in a Case of Natural Progression of Lung Cancer.

An 85-year-old woman with a history of several primary lung cancers presented with liver metastases. The primary lung cancers were all managed surgically and the patient did not receive adjuvant or neoadjuvant therapy prior to presenting with metastases. Comparison of molecular testing results from the most recent primary and the liver metastases demonstrated ( a) a clonal relationship between the 2 cancers and ( 2) the presence of a KIF13B-NRG1 fusion and KRAS amplification unique to the metastases. When integrated, the molecular surgical pathology findings in this case illustrate the extent of "oncogenic drive" in preterminal lung cancer.

Proceedings of the third international molecular pathological epidemiology (MPE) meeting.

Molecular pathological epidemiology (MPE) is a transdisciplinary and relatively new scientific discipline that integrates theory, methods, and resources from epidemiology, pathology, biostatistics, bioinformatics, and computational biology. The underlying objective of MPE research is to better understand the etiology and progression of complex and heterogeneous human diseases with the goal of informing prevention and treatment efforts in population health and clinical medicine. Although MPE research has been commonly applied to investigating breast, lung, and colorectal cancers, its methodology can be used to study most diseases. Recent successes in MPE studies include: (1) the development of new statistical methods to address etiologic heterogeneity; (2) the enhancement of causal inference; (3) the identification of previously unknown exposure-subtype disease associations; and (4) better understanding of the role of lifestyle/behavioral factors on modifying prognosis according to disease subtype. Central challenges to MPE include the relative lack of transdisciplinary experts, educational programs, and forums to discuss issues related to the advancement of the field. To address these challenges, highlight recent successes in the field, and identify new opportunities, a series of MPE meetings have been held at the Dana-Farber Cancer Institute in Boston, MA. Herein, we share the proceedings of the Third International MPE Meeting, held in May 2016 and attended by 150 scientists from 17 countries. Special topics included integration of MPE with immunology and health disparity research. This meeting series will continue to provide an impetus to foster further transdisciplinary integration of divergent scientific fields.

Molecular testing for JAK2, MPL, and CALR in myeloproliferative neoplasms.

Polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF) are myeloproliferative neoplasms characterized by recurrent somatic mutations in JAK2, CALR, and MPL. This short review addresses (1) the spectrum of mutations seen in PV, ET, and PMF, (2) the emerging genotype-phenotype correlations, (3) the current role of molecular testing in disease classification and management, and (4) several important considerations for selecting an appropriate molecular test. In our view, sequential testing algorithms and simultaneous assessment of multiple mutations by next-generation sequencing are both valid approaches to testing. Am. J. Hematol. 91:1277-1280, 2016. © 2016 Wiley Periodicals, Inc.