Calculating the Tumor Nuclei Content for Comprehensive Cancer Panel Testing

Artificial Intelligence and Lung Pathology

This manuscript provides a comprehensive overview of the application of artificial intelligence (AI) in lung pathology, particularly in the diagnosis of lung cancer. It discusses various AI models designed to support pathologists and clinicians. AI models supporting pathologists are to standardize diagnosis, score PD-L1 status, supporting tumor cellularity count, and indicating explainability for pathologic judgements. Several models predict outcomes beyond pathologic diagnosis and predict clinical outcomes like patients' survival and molecular alterations. The manuscript emphasizes the potential of AI to enhance accuracy and efficiency in pathology, while also addressing the challenges and future directions for integrating AI into clinical practice.

The Current Achievements of Multi-Gene Panel Tests in Clinical Settings for Patients with Non-Small-Cell Lung Cancer

Some multi-gene panel tests have been implemented in clinical settings to guide targeted therapy in non-small-cell lung cancer (NSCLC) in Japan. The current performance of multi-gene panel tests under the condition that the Oncomine Dx Target Test (ODxTT) and Amoy Dx® Pan Lung Cancer PCR panel (AmoyDx-multi) are available remains relatively unknown. We retrospectively reviewed consecutive patients with NSCLC, whose FFPE samples were considered for genetic testing. We assessed the submission rates, the success rates, and the driver oncogene detection rates of multi-gene panel tests. A total of 225 patients were histologically newly diagnosed with NSCLC or diagnosed with a recurrence of NSCLC without a previous multi-gene panel test at our institution. Among the 225 patients, the FFPE samples of 212 patients (94.2%) were submitted for multi-gene panel testing, including 191 samples (84.9%) for the ODxTT and 21 samples (9.3%) for the AmoyDx-multi. Among the 212 samples submitted to multi-gene panel tests, the success rate was 99.5% (211/212). The detection rate of driver oncogene alterations for all histologies was 52.4% (111/212), and that for adenocarcinoma was 69.7% (106/152). A favorable submission rate and success rate of multi-gene panel tests were shown, along with a favorable detection rate in recent clinical settings.

Digital counting of tissue cells for molecular analysis: the QuANTUM pipeline

The estimation of tumor cellular fraction (TCF) is a crucial step in predictive molecular pathology, representing an entry adequacy criterion also in the next-generation sequencing (NGS) era. However, heterogeneity of quantification practices and inter-pathologist variability hamper the robustness of its evaluation, stressing the need for more reliable results. Here, 121 routine histological samples from non-small cell lung cancer (NSCLC) cases with complete NGS profiling were used to evaluate TCF interobserver variability among three different pathologists (pTCF), developing a computational tool (cTCF) and assessing its reliability vs ground truth (GT) tumor cellularity and potential impact on the final molecular results. Inter-pathologist reproducibility was fair to good, with overall Wk ranging between 0.46 and 0.83 (avg. 0.59). The obtained cTCF was comparable to the GT (p = 0.129, 0.502, and 0.130 for surgical, biopsies, and cell block, respectively) and demonstrated good reliability if elaborated by different pathologists (Wk = 0.9). Overall cTCF was lower as compared to pTCF (30 ± 10 vs 52 ± 19, p < 0.001), with more cases < 20% (17, 14%, p = 0.690), but none containing < 100 cells for the algorithm. Similarities were noted between tumor area estimation and pTCF (36 ± 29, p < 0.001), partly explaining variability in the human assessment of tumor cellularity. Finally, the cTCF allowed a reduction of the copy number variations (CNVs) called (27 vs 29, - 6.9%) with an increase of effective CNVs detection (13 vs 7, + 85.7%), some with potential clinical impact previously undetected with pTCF. An automated computational pipeline (Qupath Analysis of Nuclei from Tumor to Uniform Molecular tests, QuANTUM) has been created and is freely available as a QuPath extension. The computational method used in this study has the potential to improve efficacy and reliability of TCF estimation in NSCLC, with demonstrated impact on the final molecular results.

Pathologist Computer-Aided Diagnostic Scoring of Tumor Cell Fraction: A Swiss National Study

Tumor cell fraction (TCF) estimation is a common clinical task with well-established large interobserver variability. It thus provides an ideal test bed to evaluate potential impacts of employing a tumor cell fraction computer-aided diagnostic (TCFCAD) tool to support pathologists' evaluation. During a National Slide Seminar event, pathologists (n = 69) were asked to visually estimate TCF in 10 regions of interest (ROIs) from hematoxylin and eosin colorectal cancer images intentionally curated for diverse tissue compositions, cellularity, and stain intensities. Next, they re-evaluated the same ROIs while being provided a TCFCAD-created overlay highlighting predicted tumor vs nontumor cells, together with the corresponding TCF percentage. Participants also reported confidence levels in their assessments using a 5-tier scale, indicating no confidence to high confidence, respectively. The TCF ground truth (GT) was defined by manual cell-counting by experts. When assisted, interobserver variability significantly decreased, showing estimates converging to the GT. This improvement remained even when TCFCAD predictions deviated slightly from the GT. The standard deviation (SD) of the estimated TCF to the GT across ROIs was 9.9% vs 5.8% with TCFCAD (P < .0001). The intraclass correlation coefficient increased from 0.8 to 0.93 (95% CI, 0.65-0.93 vs 0.86-0.98), and pathologists stated feeling more confident when aided (3.67 ± 0.81 vs 4.17 ± 0.82 with the computer-aided diagnostic [CAD] tool). TCFCAD estimation support demonstrated improved scoring accuracy, interpathologist agreement, and scoring confidence. Interestingly, pathologists also expressed more willingness to use such a CAD tool at the end of the survey, highlighting the importance of training/education to increase adoption of CAD systems.

Suitability of respiratory endoscopy for sampling malignant thoracic tumors for comprehensive genomic profiling

Comprehensive genomic profiling (CGP) is implemented to detect actionable gene aberrations and design matched therapies. Although malignant thoracic tumors are commonly detected through respiratory endoscopy, it is questionable whether the small specimens obtained thereof are sufficient for CGP. Therefore, this study aimed to investigate the suitability of respiratory endoscopy for sampling primary and metastatic thoracic tumors for CGP. Patients whose specimens were collected through respiratory endoscopy and assessed by pathologists to determine their suitability for CGP at our institution between June 2019 and May 2022 were reviewed retrospectively. The suitability of each procedure as a sampling technique for CGP and, in the cases actually analyzed, the distribution of the detected gene aberration were assessed. In total, 122 patients were eligible for analysis; the median age was 61 (range, 29-86) years, and 71 (58.2%) patients were male. Primary intrathoracic tumors were found in 91 (74.6%) cases, including 84 (68.9%) primary lung cancers; the remaining thoracic metastases of extrathoracic origin included various types. The suitability rates of specimens obtained using conventional bronchoscopy with and without cryobiopsy, endobronchial ultrasound-guided transbronchial needle aspiration, and medical thoracoscopy were 82.8% (24/29), 70.4% (19/27), 72.9% (35/48), and 100% (18/18), respectively. Of the 96 cases judged suitable, 83 were subjected to CGP, and all but one were successfully analyzed. Finally, 47 (56.6%) patients had at least one actionable gene aberration and eight (9.6%) were treated with the corresponding targeted therapies. In conclusion, specimens obtained through respiratory endoscopy are suitable for CGP; medical thoracoscopy and cryobiopsy in conventional bronchoscopy are particularly useful.

Evaluation of appropriate conditions for Oncomine DxTT testing of FFPE specimens for driver gene alterations in non-small cell lung cancer

BACKGROUND

The Oncomine Dx Target Test Multi-CDx System (ODxTT) is a next-generation sequencing panel approved as a companion diagnostic for drugs targeted to corresponding gene alterations in non-small cell lung cancer. However, appropriate slide conditions for ODxTT have remained unclear.

METHODS

We focused on the production of the number of tumor cells on a formalin-fixed paraffin-embedded (FFPE) section and the number of prepared slides, designated the TS value, and determined a TS value of ≥4000 as a target slide condition for ODxTT. We evaluated the impact of this condition on ODxTT testing with tumor specimens found to have a TS of <4000 (n = 23) or a TS of ≥4000 (n = 142).

RESULTS

A positive correlation was apparent between the TS value and the concentrations of both DNA and RNA. Among the 142 samples with a TS of ≥4000, a sufficient concentration of DNA or RNA for ODxTT analysis was achieved in 100% and 98% samples, respectively. Among samples explored for driver gene alterations after determination of the target slide condition (TS ≥4000), most (84.9%) had a TS of ≥4000 and were submitted for ODxTT analysis.

CONCLUSION

Our findings indicate that a TS of ≥4000 is a feasible and relevant criterion for ODxTT testing, and its adoption should help to improve the success rate of such testing in clinical practice.

Applied Molecular-Based Quality Control of Biobanked Samples for Multi-Omics Approach

Biobanks are vital for high-throughput translational research, but the rapid development of novel molecular techniques, especially in omics assays, poses challenges to traditional practices and recommendations. In our study, we used biospecimens from oncological patients in Polish clinics and collaborated with the Indivumed Group. For serum/plasma samples, we monitored hemolysis, controlled RNA extraction, assessed cDNA library quality and quantity, and verified NGS raw data. Tissue samples underwent pathologic evaluation to confirm histology and determine tumor content. Molecular quality control measures included evaluating the RNA integrity number, assessing cDNA library quality and quantity, and analyzing NGS raw data. Our study yielded the creation of distinct workflows for conducting preanalytical quality control of serum/plasma and fresh-frozen tissue samples. These workflows offer customization options to suit the capabilities of different biobanking entities. In order to ensure the appropriateness of biospecimens for advanced research applications, we introduced molecular-based quality control methods that align with the demands of high-throughput assays. The novelty of proposed workflows, rooted in innovative molecular techniques, lies in the integration of these QC methods into a comprehensive schema specifically designed for high-throughput research applications.

Fine-needle biopsy with 19G needle is effective in combination with endoscopic ultrasound-guided tissue acquisition for genomic profiling of unresectable pancreatic cancer

OBJECTIVES

Comprehensive genomic profiling (CGP) has been approved in Japan since June 2019, enabling mutation-specific therapy. Although tissue sampling via endoscopic ultrasound-guided tissue acquisition (EUS-TA) is standard in pancreatic cancer, reports on obtaining appropriate samples for CGP, especially for the OncoGuide NCC Oncopanel System (NOP) and FoundationOne CDx (FOne), are lacking. Therefore, we investigated the success rate and factors related to appropriate EUS-TA sampling for CGP analysis suitability in unresectable pancreatic ductal adenocarcinoma (UR-PDAC).

METHODS

Participants comprised 150 UR-PDAC patients who underwent EUS-TA and tumor sample evaluation for CGP analysis suitability between June 2019 and December 2021. The proportion of patients meeting the criteria was evaluated considering tumor size, puncture lesion, presence of metastasis, type and size of puncture needle, suction method, number of punctures, and puncture route.

RESULTS

In total, 39.2% (60/153) of samples met NOP analysis suitability criteria and 0% met FOne analysis suitability criteria. The suitability rate was significantly higher with 19G fine-needle biopsy (FNB) (56.0%; 42/75) than with 22G FNB (32.6%; 14/43) and 22G fine-needle aspiration (11.4%; 4/35). Nineteen-gauge needle (odds ratio [OR] 2.53; 95% confidence interval [CI] 1.15-5.57; P = 0.021) and FNB (OR 3.57; 95% CI 1.05-12.20; P = 0.041) were independent factors contributing to NOP analysis suitability. Among 30 patients who underwent actual NOP analysis, the analysis success rate was 100% (30/30).

CONCLUSION

In sample collection via EUS-TA, 19G and FNB needles contribute to NOP analysis suitability.

A collaborative workflow between pathologists and deep learning for the evaluation of tumour cellularity in lung adenocarcinoma

AIMS

The reporting of tumour cellularity in cancer samples has become a mandatory task for pathologists. However, the estimation of tumour cellularity is often inaccurate. Therefore, we propose a collaborative workflow between pathologists and artificial intelligence (AI) models to evaluate tumour cellularity in lung cancer samples and propose a protocol to apply it to routine practice.

METHODS AND RESULTS

We developed a quantitative model of lung adenocarcinoma that was validated and tested on 50 cases, and a collaborative workflow where pathologists could access the AI results and adjust their original tumour cellularity scores (adjusted-score) that we tested on 151 cases. The adjusted-score was validated by comparing them with a ground truth established by manual annotation of haematoxylin and eosin slides with reference to immunostains with thyroid transcription factor-1 and napsin A. For training, validation, testing the AI and testing the collaborative workflow, we used 40, 10, 50 and 151 whole slide images of lung adenocarcinoma, respectively. The sensitivity and specificity of tumour segmentation were 97 and 87%, respectively, and the accuracy of nuclei recognition was 99%. One pathologist's visually estimated scores were compared to the adjusted-score, and the pathologist's scores were altered in 87% of cases. Comparison with the ground truth revealed that the adjusted-score was more precise than the pathologists' scores (P < 0.05).

CONCLUSION

We proposed a collaborative workflow between AI and pathologists as a model to improve daily practice and enhance the prediction of tumour cellularity for genetic tests.

The Significance of External Quality Assessment Schemes for Molecular Testing in Clinical Laboratories

Simple Summary

Patients and clinicians often rely on the outcome of laboratory tests, but can we really trust these test results? Good quality management is key for laboratories to guarantee reliable test results. This review focusses on external quality assessment (EQA) schemes which are a tool for laboratories to examine and improve the quality of their testing routines. In this review, an overview of the role and importance of EQA schemes for clinical laboratories is given, and different types of EQA schemes and EQA providers available on the market are discussed, as well as recent developments in the EQA landscape.

Abstract

External quality assessment (EQA) schemes are a tool for clinical laboratories to evaluate and manage the quality of laboratory practice with the support of an independent party (i.e., an EQA provider). Depending on the context, there are different types of EQA schemes available, as well as various EQA providers, each with its own field of expertise. In this review, an overview of the general requirements for EQA schemes and EQA providers based on international guidelines is provided. The clinical and scientific value of these kinds of schemes for clinical laboratories, clinicians and patients are highlighted, in addition to the support EQA can provide to other types of laboratories, e.g., laboratories affiliated to biotech companies. Finally, recent developments and challenges in laboratory medicine and quality management, for example, the introduction of artificial intelligence in the laboratory and the shift to a more individual-approach instead of a laboratory-focused approach, are discussed. EQA schemes should represent current laboratory practice as much as possible, which poses the need for EQA providers to introduce latest laboratory innovations in their schemes and to apply up-to-date guidelines. By incorporating these state-of-the-art techniques, EQA aims to contribute to continuous learning.

Pathological criteria for multiplex gene-panel testing using next-generation sequencing in non-small cell lung cancer

BACKGROUND

Multiplex gene-panel tests have recently been developed, including the Oncomine Dx Target Test multi-CDx system (ODxTT), and are commonly used to determine the adaptation of molecular-targeting drugs in non-small cell lung cancer. However, in actual clinical settings, we obtain false results owing to the small biopsy samples. We aimed to optimize tissue preparation methods to improve the success rate.

PATIENTS AND METHODS

We investigated 88 biopsy samples. The area and nucleated cell count in the first cut section were quantified using a morphometric software. Pathological parameters, including "total tissue area" and "total nucleated cell count," were calculated by multiplying the total number of slides submitted to ODxTT. Optimal cutoff values to obtain the best success rate were also determined. Additionally, we morphometrically measured actual tumor cell proportions and attempted to determine the lower limit possible to detect mutations.

RESULTS

Optimal cutoff values for "total nucleated cell count" and "total tissue area" were 132,885 and 32.94 mm², respectively. The actual tumor cell proportions ranged from 4.6 to 97.7%. Even in cases with actual tumor cell proportions of less than 20% (ranging from 4.6 to 19.7%), there was no false negative.

CONCLUSION

Thus, we proposed the pathological criteria for accurate ODxTT. Our result suggested that tumor cell proportions of less than 20% (around 5%) could be applicable for ODxTT. We hope that our results will help pathologists to choose between the multi-plex test (ODxTT) or single-plex test in routine diagnostics.

Translational Modeling Identifies Synergy between Nanoparticle-Delivered miRNA-22 and Standard-of-Care Drugs in Triple-Negative Breast Cancer

Purpose

Downregulation of miRNA-22 in triple-negative breast cancer (TNBC) is associated with upregulation of eukaryotic elongation 2 factor kinase (eEF2K) protein, which regulates tumor growth, chemoresistance, and tumor immunosurveillance. Moreover, exogenous administration of miRNA-22, loaded in nanoparticles to prevent degradation and improve tumor delivery (termed miRNA-22 nanotherapy), to suppress eEF2K production has shown potential as an investigational therapeutic agent in vivo.

Methods

To evaluate the translational potential of miRNA-22 nanotherapy, we developed a multiscale mechanistic model, calibrated to published in vivo data and extrapolated to the human scale, to describe and quantify the pharmacokinetics and pharmacodynamics of miRNA-22 in virtual patient populations.

Results

Our analysis revealed the dose-response relationship, suggested optimal treatment frequency for miRNA-22 nanotherapy, and highlighted key determinants of therapy response, from which combination with immune checkpoint inhibitors was identified as a candidate strategy for improving treatment outcomes. More importantly, drug synergy was identified between miRNA-22 and standard-of-care drugs against TNBC, providing a basis for rational therapeutic combinations for improved response

Conclusions

The present study highlights the translational potential of miRNA-22 nanotherapy for TNBC in combination with standard-of-care drugs. 

Supplementary Information

The online version contains supplementary material available at 10.1007/s11095-022-03176-3.

Comparison of sampling methods for next generation sequencing for patients with lung cancer

Introduction

Success of next generation sequencing (NGS) analysis is becoming indispensable in the treatment of advanced lung cancer. However, the advantages and disadvantages of each sampling method in the NGS analysis have not yet been clarified.

Methods

We compared the success rates of NGS analysis, and DNA and RNA yields for transbronchial biopsy (TBB), endobronchial ultrasound‐guided transbronchial needle aspiration (EBUS‐TBNA), computed tomography (CT)‐guided biopsy, fluid sample, and surgical biopsy for NGS analysis in patients through the lung cancer genomic screening project for individualized medicine (LC‐SCRUM)‐Asia, a nationwide NGS screening project. In case, sufficient samples could not be collected by TBB and EBUS‐TBNA, re‐biopsy (genome re‐biopsy) was performed.

Results

A total of 223 patients were enrolled and success rates of NGS analysis were not different between samples obtained through TBB, EBUS‐TBNA, and CT‐guided biopsy; however, success rates for fluid samples and surgical biopsy samples were significantly higher than those of other methods. The risk of genome re‐biopsy was higher with TBB for centrally located lesions. CT‐guided biopsy yielded more samples but had a lower success rate for analysis of RNA‐based NGS than TBB.

Conclusions

TBB is the mainstay of sampling methods, but for centrally located lesions, EBUS‐TBNA may be a better strategy. For CT‐guided biopsy, the success rate of RNA‐based NGS analysis is low. Fluid samples are expected to yield successful results as surgical biopsy samples, but the latter are better for sample preservation. Determining the optimal method for genome biopsy for each case is important.

Obtaining spatially resolved tumor purity maps using deep multiple instance learning in a pan-cancer study

Tumor purity is the percentage of cancer cells within a tissue section. Pathologists estimate tumor purity to select samples for genomic analysis by manually reading hematoxylin-eosin (H&E)-stained slides, which is tedious, time consuming, and prone to inter-observer variability. Besides, pathologists' estimates do not correlate well with genomic tumor purity values, which are inferred from genomic data and accepted as accurate for downstream analysis. We developed a deep multiple instance learning model predicting tumor purity from H&E-stained digital histopathology slides. Our model successfully predicted tumor purity in eight The Cancer Genome Atlas (TCGA) cohorts and a local Singapore cohort. The predictions were highly consistent with genomic tumor purity values. Thus, our model can be utilized to select samples for genomic analysis, which will help reduce pathologists' workload and decrease inter-observer variability. Furthermore, our model provided tumor purity maps showing the spatial variation within sections. They can help better understand the tumor microenvironment.

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MIL model successfully predicts a sample's tumor purity from histopathology slides

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MIL model learns to spatially resolve tumor purity from sample-level labels

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Tumor purity varies spatially within a sample

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Pathologists’ region selection is vital for correct percentage tumor nuclei estimation

Given some big data and coarse-level labels, extracting fine-level information is a demanding yet rewarding challenge in data science. This study develops a machine learning model utilizing big data and exploiting coarse-level labels to reveal fine-level details within the data. Although it can be applied to different data science tasks with enormous data and coarse labels, we applied it to a computational histopathology task with gigapixel histopathology slides and sample-level labels. Specifically, the model revealed spatial resolution of tumor purity within histopathology slides using only sample-level genomic tumor purity values during training. This can also be extended to other omics features, providing precious information about cancer biology and promising personalized, precision medicine. Such studies are of great clinical importance in discovering imaging biomarkers and better understanding the tumor microenvironment.

A Multiscale Model to Identify Limiting Factors in Nanoparticle-Based miRNA Delivery for Tumor Inhibition. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021;2021:4230-4233. [PMID: 34892157 PMCID: PMC8712117 DOI: 10.1109/embc46164.2021.9630862]

MicroRNA-based gene therapy for cancer treatment via nanoparticles (NPs) requires navigation of multiple physical and physiological barriers in order to efficiently deliver the miRNAs to the cancer cell cytoplasm. We here present a mathematical model to investigate the variability associated with tumor, NP, and miRNA characteristics, and identify the limiting factors in miRNA delivery to tumors. Through global parameter analysis, the miRNA release rate from NPs and NP degradability were found to have the most significant impact on cytosolic accumulation of miRNAs. These NP properties can be fine-tuned in order to optimize the delivery system for enhancing the efficacy of miRNA-based therapy.Clinical Relevance-Understanding the effect of nanoparticle, tumor, and miRNA characteristics in governing the efficacy of miRNA-based cancer therapy will support its clinical translation.

Multiplex gene-panel testing for lung cancer patients

The year 2019 was considered to be the first year of cancer genome medicine in Japan, with three gene-panel tests using next-generation sequencing (NGS) techniques being introduced into clinical practice. Among the three tests, the Oncomine CDx Target test was approved under the category of regular molecular testing for lung cancer, which meant that this test could be used to select patients for molecularly targeted drugs. Conversely, the other two tests, NCC OncoPanel and FoundationOne CDx, were assigned to be used under the National Cancer Genome Medicine Network, and implementation was restricted to patients for whom standard treatment was completed or expected to be completed. These NGS tests can detect a series of genetic alterations in individual tumors, which further promotes the development of therapeutic agents and elucidates molecular pathways. The NGS tests require appropriate tissue size and tumor cell content, which can be accessed only by pathologists. In this report, we review the current reimbursement schema in our national healthcare policy and the requirements of the specimens for NGS testing based on the recently published 'Guidance of Gene-panel Testing Using Next-Generation Sequencers for Lung Cancer', by the Japanese Society of Lung Cancer.

Evaluation of the efficacy and safety of a new flex-rigid pleuroscope

Objective

New flex‐rigid pleuroscope enables observations with a maximum angle of curvature of 180^°, allowing visualization of the area near the insertion site of the pleuroscope. And, it improved the image quality and channel inner diameter. The aim of this study was to evaluate the clinical effectiveness and safety of a new flex‐rigid pleuroscope.

Methods

A retrospective analysis of patients who were examined with a new flex‐rigid pleuroscope under local anesthesia at our institution was conducted.

Pleuroscopy was performed in 33 patients with undiagnosed exudative pleural effusions from December 2016 to March 2019.

Results

A total of 33 patients (10 women, 23 men); their median age 74 years (range 24‐90) were investigated. Pleuroscopy showed that 18 had malignant pleural disease (54%), and 15 had benign pleural diseases (46%). The top three most frequent causes of pleural disease were pleural metastases of lung carcinoma (30.3%), pyothorax (15.1%), and malignant pleural mesothelioma (12.1%). In 32 cases (97%), observation at the introducer insertion site was possible. It was not possible in one case due to hard adhesions. The diagnostic rate was 100%, and the complication rate was 6.1%. There were no major complications, and minor complications included mild pain (one case) and minor bleeding (one case) that was stanched spontaneously.

Conclusions

The new flex‐rigid pleuroscope is effective and safe for diagnosing pleural effusions. The improved bending angle is likely to minimize the blind area. The new pleuroscopy fiberscope may improve the diagnostic rate.

Pleural cryobiopsy is useful for comprehensive cancer genetic panel testing

An 83-year-old woman presented with dyspnoea. Her chest X-ray showed a right-sided pleural effusion. Flex-rigid pleuroscopy was performed and showed a mass in the anterior portion. The mass was biopsied with conventional biopsy forceps, but the mass was solid, and sufficient tissues could not be obtained. Therefore, the mass was biopsied with a cryoprobe. The tip of the probe was attached to the mass, and it was cooled with carbon dioxide once for 5 sec and then for 7 sec in the same place. The tissue size obtained was 2 mm by conventional biopsy forceps, and 5 mm at 5 sec and 12 mm at 7 sec by cryobiopsy. Histological analysis of the conventional biopsy forceps specimen showed cancer cells in the glandular cavity, but it was not sufficient tissue for comprehensive cancer genetic panel (CGP) testing. The cryobiopsy specimens showed cancer cells and sufficient tissue for comprehensive CGP testing.