Molecular testing on serous effusion: An update

Pericardial effusion cytology: malignancy rates, patterns of metastasis, comparison with pericardial window, and genomic correlates

INTRODUCTION

Cytologic evaluation of pericardial fluid is essential for diagnosing malignant pericardial effusions secondary to metastatic disease and for guiding appropriate clinical management; however, large cohort and up-to-date studies on malignancy rates and distribution of primary tumor sites is lacking.

MATERIALS AND METHODS

A retrospective analysis of pericardial fluid specimens from 2 large academic medical centers over a 10-year period was conducted. Clinical and specimen characteristics were correlated with cytologic diagnoses, and compared with surgical pathology pericardial specimens when available. In addition, genomic testing results were examined in a subset of malignant cases.

RESULTS

A total of 1667 pericardial fluid specimens were evaluated, with 15.3% diagnosed as malignant. Lung cancer (50.6%) was by far the most common primary tumor causing malignant pericardial effusions, followed by breast (13.0%), hematolymphoid (12.6%), and gastrointestinal (6.1%) cancers. A subset of patients with paired cytology and surgical pathology pericardial specimens showed concordance in 84.2% of cases, with discordant cases more frequently presenting with a positive cytology but negative surgical pathology result. Genomic analysis of a subset of malignant pericardial effusions revealed the most frequently mutated genes to be TP53, KRAS, CDKN2A/B, and PIK3CA, with a larger proportion of high tumor mutational burden (≥10 muts/Mb) in pericardial fluid samples compared to primary or metastatic sites.

CONCLUSIONS

While lung cancer is the most frequent cause of a cytology-confirmed malignant pericardial effusion, familiarity with relative frequencies of metastases from other sites can be particularly helpful, especially in the diagnostic work-up of an occult malignant pericardial effusion.

Minimally Invasive, Maximally Effective: The Power of Precision Cytoanalysis on Effusion Samples-A Comprehensive Exploration from Traditional Methods to Innovative Approaches

Precision medicine translates through molecular assays and in minimally invasive diagnosis, evident in analyses of effusions that serve therapeutic and diagnostic purposes. This cost-effective and low-risk approach provides advantages, playing a pivotal role in late-stage oncology and frequently standing as the primary resource for cancer diagnosis and treatment pathways. This article outlines the workflow for managing serous fluid and explores how cytology effusion analysis extends beyond immunocytological diagnosis. Combined with current molecular tests it showcases the potential to be a skillful tool in precision cytopathology.

Advances in Molecular and Genetic Technologies and the Problems Related to Their Application in Personalized Medicine

Advances in the global personalized medicine market are directly related to innovations and developments in molecular and genetic technologies. This review focuses on the key trends in the development of these technologies in the healthcare sector. The existing global developments having an impact on the evolution of the personalized medicine market are reviewed. Efficient measures to support the development of molecular and genetic technologies are proposed.

Comprehensive Genomic Studies on the Cell Blocks of Pancreatic Cancer

Pancreatic cancer is one of the deadliest malignancies, characterized by late-stage diagnosis and limited treatment options. Comprehensive genomic profiling plays an important role in understanding the molecular mechanisms underlying the disease and identifying potential therapeutic targets. Cell blocks (CBs), derived from EUS-FNA, have become valuable resources for diagnosis and genomic analysis. We examine the molecular profile of pancreatic ductal adenocarcinoma (PDAC) using specimens obtained from CB EUS-FNA, across a large gene panel, within the framework of next-generation sequencing (NGS). Our findings revealed that over half (55%) of PDAC CB cases provided adequate nucleic acid for next-generation sequencing, with tumor cell percentages averaging above 30%. Despite challenges such as low DNA quantification and degraded DNA, sequencing reads showed satisfactory quality control statistics, demonstrating the detection of genomic alterations. Most cases (84.6%) harbored at least one gene variant, including clinically significant gene mutation variants such as KRAS, TP53, and CDKN2A. Even at minimal concentrations, as long as the extracted DNA is of high quality, performing comprehensive molecular profiling on PDAC samples from cell blocks has remained feasible. This strategy has yielded valuable information about the diagnosis, genetic landscape, and potential therapeutic targets, aligning closely with a precision cytopathology approach.

Using a deep learning neural network for the identification of malignant cells in effusion cytology material

AIM

To evaluate the application of an artificial neural network in the detection of malignant cells in effusion samples.

MATERIALS AND METHODS

In this retrospective study, we selected 90 cases of effusion cytology samples over 2 years. There were 52 cases of metastatic adenocarcinoma and 38 benign effusion samples. In each case, an average of five microphotographs from the representative areas were taken at 40× magnification from Papanicolaou-stained samples. A total of 492 images were obtained from these 90 cases. We applied a deep convolutional neural network (DCNN) model to identify malignant cells in the cytology images of effusion cytology smears. The training was performed for 15 epochs. The model consisted of 783 layers with 188 convolution-max pool layers in between.

RESULTS

In the test set, the DCNN model correctly identified 54 of 56 images of benign samples and 49 out of 56 images of malignant samples. It showed 88% sensitivity, 96% specificity and 96% positive predictive value in the screening of malignant cases in effusion. The area under the receiver operating curve was 0.92.

CONCLUSION

DCNN is a unique technology that can detect malignant cells from cytological images. The model works rapidly and there is no bias in cell selection or feature extraction. The present DCNN model is promising and can have a significant impact on the diagnosis of malignancy in cytology.

Molecular testing opportunities on cytology effusion specimens: the pre-analytic effects of various body fluid cytology preparation methods on RNA extraction quality and targeted sequencing

INTRODUCTION

RNA sequencing (RNAseq) analysis is emerging as a clinical research or diagnostic approach for cytologic samples, but there is need for formal comparison of different sample preparation methods in the cytology laboratory to identify which pre-analytic methods could provide alternatives to formalin-fixed paraffin-embedded (FFPE) sections.

MATERIALS AND METHODS

We prepared 13 malignant effusions (metastatic estrogen receptor-positive breast cancer) in the cytology laboratory using 6 routine cytologic methods: FFPE cell block, Carnoy's solution, 95% ethanol (EtOH), air-dried and Diff-Quik, ThinPrep, and SurePath preparations. Measurements of RNA quality, expression of 2 multigene expression signatures, molecular subtype, and 4 common activating mutation sites in each preparation were compared with fresh frozen (FF) cell pellet in RNA preservative using distribution of fragment length and concordance correlation coefficient (CCC).

RESULTS

The fraction of RNA fragments measuring 200 bases or more (DV200) were 24% higher from cytospins fixed in Carnoy's solution or 95% EtOH than DV200 from FFPE cell blocks. SurePath samples failed RNAseq quality control. There was high concordance of gene expression measurements with FF samples using cytospins fixed in Carnoy's solution, 95% EtOH, Diff-Quik (CCC = 0.829, 0.812, 0.760, respectively), or ThinPrep (CCC = 0.736), but lower using FFPE cell block (CCC = 0.564). The proportion of mutant transcripts was concordant between FF and any cytologic preparation methods.

CONCLUSIONS

Cytospin preparations fixed with Carnoy's or 95% ETOH then Papanicolaou stained produced RNAseq results that were equivalent to FF samples and superior to FFPE cell block sections.

Decoding the primary tumor origin in carcinomatous serous effusions by immunocytochemistry

INTRODUCTION

Malignant effusions are commonly encountered in day-to-day cytology practice. Determining the primary site of malignancy in carcinomatous effusions is a Herculean task. Cytology coupled with immunocytochemistry is often found helpful in this context.

MATERIALS AND METHODS

This study was undertaken to evaluate diagnostic utility of immunocytochemistry (ICC) on the sections from cell blocks (CBs) to detect the primary site of origin in metastatic carcinomatous effusions. To determine the origin of the primary tumor, TTF1 (lung), PAX-8 (ovary), CDX2 (colo-rectal), GATA3 (breast), and CK19 (pancreaticobiliary) were employed depending on the clinical and radiological findings, and serum tumor markers.

RESULTS

A total of 13,459 serous effusion samples were received for cytological evaluation from January 2017 to December 2021 of which 2708 (20.1%) were carcinomatous effusions. Out of these, 1044 (38.5%), 1611 (59.5%), and 53 (2.0%) were from pleural, peritoneal and pericardial cavities, respectively. Of these, majority were adenocarcinoma. ICC was done in 309 (11.4%) cases. Ovary was the most common primary site in 179 (57.9%) cases, followed by lung (75, 24.3%), pancreaticobiliary (12, 3.9%), colo-rectal (8, 2.6%), breast (6, 1.9%), prostate (2, 0.6%) and kidney (1, 0.3). Lung was the commonest primary site in pleural (67/113, 59.3%) and pericardial (6/8, 75%) effusions. Ovary (168/188, 89.4%) was the most common primary responsible for carcinomatous effusions in the peritoneal cavity. However, in 17 (5.5%) cases, the exact primary site could not be established.

CONCLUSIONS

Judicious and methodical use of ICC on CB helps identify the primary site of the tumor in most carcinomatous effusions. This is of immense help to the treating clinician in directing appropriate therapy.