Laboratory Investigation最新文献

New therapies are being developed for breast cancer, and in this process, some “old” biomarkers are reutilized and given a new purpose. It is not always recognized that by changing a biomarker’s intended use, a new biomarker assay is created. The Ki-67 biomarker is typically assessed by immunohistochemistry (IHC) to provide a proliferative index in breast cancer. Canadian laboratories assessed the analytical performance and diagnostic accuracy of their Ki-67 IHC laboratory-developed tests (LDTs) of relevance for the LDTs’ clinical utility.

Canadian clinical IHC laboratories enrolled in the Canadian Biomarker Quality Assurance Pilot Run for Ki-67 in breast cancer by invitation. The Dako Ki-67 IHC pharmDx assay was employed as a study reference assay. The Dako central laboratory was the reference laboratory. Participants received unstained slides of breast cancer tissue microarrays with 32 cases and performed their in-house Ki-67 assays. The results were assessed using QuPath, an open-source software application for bioimage analysis. Positive percent agreement (PPA, sensitivity) and negative percent agreement (NPA, specificity) were calculated against the Dako Ki-67 IHC pharmDx assay for 5%, 10%, 20%, and 30% cutoffs.

Overall, PPA and NPA varied depending on the selected cutoff; participants were more successful with 5% and 10%, than with 20% and 30% cutoffs. Only 4 of 16 laboratories had robust IHC protocols with acceptable PPA for all cutoffs. The lowest PPA for the 5% cutoff was 85%, for 10% was 63%, for 20% was 14%, and for 30% was 13%. The lowest NPA for the 5% cutoff was 50%, for 10% was 33%, for 20% was 50%, and for 30% was 57%.

Despite many years of international efforts to standardize IHC testing for Ki-67 in breast cancer, our results indicate that Canadian clinical LDTs have a wide analytical sensitivity range and poor agreement for 20% and 30% cutoffs. The poor agreement was not due to the readout but rather due to IHC protocol conditions. International Ki-67 in Breast Cancer Working Group (IKWG) recommendations related to Ki-67 IHC standardization cannot take full effect without reliable fit-for-purpose reference materials that are required for the initial assay calibration, assay performance monitoring, and proficiency testing.

Intrahepatic cholangiocarcinoma (ICC) is a lethal cancer with poor survival especially when it spreads. The histopathology of its rare intraductal papillary neoplasm of the bile duct type (IPNB) characteristically shows cancer cells originating within the confined bile duct space. These cells eventually invade and infiltrate the nearby liver tissues, making it a good model to study the mechanism of local invasion, which is the earliest step of metastasis. To discover potential suppressor genes of local invasion in ICC, we analyzed the somatic mutation profiles and performed clonal evolution analyses of the 11 pairs of macrodissected locally invasive IPNB tissues (LI-IPNB) and IPNB tissues without local invasion from the same patients. We identified a protein-truncating variant in an E3 ubiquitin ligase, RNF213 (c.6967C>T; p.Gln2323X; chr17: 78,319,102 [hg19], exon 29), as the most common protein-truncating variant event in LI-IPNB samples (4/11 patients). Knockdown of RNF213 in HuCCT1 and YSCCC cells showed increased migration and invasion, and reduced vasculogenic mimicry but maintained normal proliferation. Transcriptomic analysis of the RNF213-knockdown vs control cells was then performed in the HuCCT1, YSCCC, and KKU-100 cells. Gene ontology enrichment analysis of the common differentially expressed genes revealed significantly altered cytokine and oxidoreductase-oxidizing metal ion activities, as confirmed by Western blotting. Gene Set Enrichment Analysis identified the most enriched pathways being oxidative phosphorylation, fatty acid metabolism, reactive oxygen species, adipogenesis, and angiogenesis. In sum, loss-of-function mutation of RNF213 is a common genetic alteration in LI-IPNB tissues. RNF213 knockdown leads to increased migration and invasion of ICC cells, potentially through malfunctions of the pathways related to inflammation and energy metabolisms.

The glycans form a unique complex on the surface of cancer cells and play a pivotal role in tumor progression, impacting proliferation, invasion, and metastasis. TRA-1-60 is a glycan that was identified as a critical marker for the establishment of fully reprogrammed inducible pluripotent stem cells. Its expression has been detected in multiple cancer tissues, including embryonal carcinoma, prostate cancer, and pancreatic cancer, but the biological and pathological characterization of TRA-1-60-expressing tumor cells remains unclear within various types of malignancies. Here, we report the biological characteristics of TRA-1-60-expressing gastric cancer cells, especially those with its cell surface expression, and the therapeutic significance of targeting TRA-1-60. The cells with cell membrane expression of TRA-1-60 were mainly observed in the invasive area of patient gastric cancer tissues and correlated with advanced stages of the disease based on histopathological and clinicopathological analyses. In vitro analysis using a scirrhous gastric adenocarcinoma line, HSC-58, which highly expresses TRA-1-60 on its plasma membrane, revealed increased stress-resistant mechanisms, supported by the upregulation of glutathione synthetase and NCF-1 (p47phox) via lipid–ROS regulatory pathways, as detected by RNA-seq analysis followed by oxidative stress gene profiling. Our in vivo therapeutic study using the TRA-1-60-targeting antibody–drug conjugate, namely, Bstrongomab-conjugated monomethyl auristatin E, showed robust efficacy in a mouse model of peritoneal carcinomatosis induced by intraperitoneal xenograft of HSC-58, by markedly reducing massive tumor ascites. Thus, targeting the specific cell surface glycan, TRA-1-60, shows a significant therapeutic impact in advanced-stage gastric cancers.

Immunohistochemistry (IHC) is used to guide treatment decisions in multiple cancer types. For treatment with checkpoint inhibitors, programmed death ligand 1 (PD-L1) IHC is used as a companion diagnostic. However, the scoring of PD-L1 is complicated by its expression in cancer and immune cells. Separation of cancer and noncancer regions is needed to calculate tumor proportion scores (TPS) of PD-L1, which is based on the percentage of PD-L1-positive cancer cells. Evaluation of PD-L1 expression requires highly experienced pathologists and is often challenging and time-consuming. Here, we used a multi-institutional cohort of 77 lung cancer cases stained centrally with the PD-L1 22C3 clone. We developed a 4-step pipeline for measuring TPS that includes the coregistration of hematoxylin and eosin, PD-L1, and negative control (NC) digital slides for exclusion of necrosis, segmentation of cancer regions, and quantification of PD-L1+ cells. As cancer segmentation is a challenging step for TPS generation, we trained DeepLab V3 in the Visiopharm software package to outline cancer regions in PD-L1 and NC images and evaluated the model performance by mean intersection over union (mIoU) against manual outlines. Only 14 cases were required to accomplish a mIoU of 0.82 for cancer segmentation in hematoxylin-stained NC cases. For PD-L1-stained slides, a model trained on PD-L1 tiles augmented by registered NC tiles achieved a mIoU of 0.79. In segmented cancer regions from whole slide images, the digital TPS achieved an accuracy of 75% against the manual TPS scores from the pathology report. Major reasons for algorithmic inaccuracies include the inclusion of immune cells in cancer outlines and poor nuclear segmentation of cancer cells. Our transparent and stepwise approach and performance metrics can be applied to any IHC assay to provide pathologists with important insights on when to apply and how to evaluate commercial automated IHC scoring systems.

Epstein–Barr virus–associated gastric carcinoma (EBVaGC) is characterized by prominent tumor-infiltrating lymphocytes (TILs) and has a favorable prognosis. Tertiary lymphoid structures (TLS), characterized by ectopic aggregated lymphocytes with high-endothelial venules (HEV), are associated with favorable outcomes in various solid tumors. We hypothesized that EBVaGC, characterized by intense TILs, may be closely associated with TLS or HEV. To test this hypothesis, we digitally analyzed the TLS, HEV, and TILs in 73 surgically resected advanced EBVaGCs. For HEV, dual MECA-79 and CD31 dual immunohistochemistry were performed, and the ectopic expression of MECA-79 in tumor cells was measured. In 73 patients with EBVaGC, a high-TLS ratio was found in 29 (39.7%) cases, high-tumor-associated HEV density in 44 (60.3%) cases, and high-CD8⁺ TIL density in 38 (52.1%) cases. Ectopic tumor expression of MECA-79 was observed in 36 patients (49.3%) cases. A low-TLS ratio and tumor-associated HEV density were significantly associated with lymph node metastasis (P =.005 and.042, respectively). Ectopic MECA-79 expression was significantly associated with lymph node metastasis (P =.003). Patients with a low-TLS ratio (P =.038), low-HEV density (P =.042), and ectopic tumor MECA-79 expression (P =.032) had significantly worse prognoses. In conclusion, TLS ratio and HEV density affect the survival of patients with EBVaGC and may be related to the immune response that interrupts lymph node metastasis.

Optical tissue clearing and three-dimensional (3D) immunofluorescence (IF) microscopy is transforming imaging of the complex tumor microenvironment (TME). However, current 3D IF microscopy has restricted multiplexity; only 3 or 4 cellular and noncellular TME components can be localized in cleared tumor tissue. Here we report a light-emitting diode (LED) photobleaching method and its application for 3D multiplexed optical mapping of the TME. We built a high-power LED light irradiation device and temperature-controlled chamber for completely bleaching fluorescent signals throughout optically cleared tumor tissues without compromise of tissue and protein antigen integrity. With newly developed tissue mounting and selected region-tracking methods, we established a cyclic workflow involving IF staining, tissue clearing, 3D confocal microscopy, and LED photobleaching. By registering microscope channel images generated through 3 work cycles, we produced 8-plex image data from individual 400 μm-thick tumor macrosections that visualize various vascular, immune, and cancer cells in the same TME at tissue-wide and cellular levels in 3D. Our method was also validated for quantitative 3D spatial analysis of cellular remodeling in the TME after immunotherapy. These results demonstrate that our LED photobleaching system and its workflow offer a novel approach to increase the multiplexing power of 3D IF microscopy for studying tumor heterogeneity and response to therapy.

Tissue gene expression studies are impacted by biological and technical sources of variation, which can be broadly classified into wanted and unwanted variation. The latter, if not addressed, results in misleading biological conclusions. Methods have been proposed to reduce unwanted variation, such as normalization and batch correction. A more accurate understanding of all causes of variation could significantly improve the ability of these methods to remove unwanted variation while retaining variation corresponding to the biological question of interest. We used 17,282 samples from 49 human tissues in the Genotype-Tissue Expression data set (v8) to investigate patterns and causes of expression variation. Transcript expression was transformed to z-scores, and only the most variable 2% of transcripts were evaluated and clustered based on coexpression patterns. Clustered gene sets were assigned to different biological or technical causes based on histologic appearances and metadata elements. We identified 522 variable transcript clusters (median: 11 per tissue) among the samples. Of these, 63% were confidently explained, 16% were likely explained, 7% were low confidence explanations, and 14% had no clear cause. Histologic analysis annotated 46 clusters. Other common causes of variability included sex, sequencing contamination, immunoglobulin diversity, and compositional tissue differences. Less common biological causes included death interval (Hardy score), disease status, and age. Technical causes included blood draw timing and harvesting differences. Many of the causes of variation in bulk tissue expression were identifiable in the Tabula Sapiens data set of single-cell expression. This is among the largest explorations of the underlying sources of tissue expression variation. It uncovered expected and unexpected causes of variable gene expression and demonstrated the utility of matched histologic specimens. It further demonstrated the value of acquiring meaningful tissue harvesting metadata elements to use for improved normalization, batch correction, and analysis of both bulk and single-cell RNA-seq data.

In clinical practice, programmed death ligand 1 (PD-L1) detection is prone to nonspecific staining due to the complex cellular composition of pleural effusion smears. In this study, diaminobenzidine (DAB) and 3-amino-9-ethylcarbazole (AEC) immunohistochemistry double staining was performed to investigate PD-L1 expression in tumor cells from malignant pleural effusion (MPE). MPE was considered as a metastasis in non–small cell lung cancer patients; thus, the heterogeneity between metastatic and primary lung cancer was revealed as well. Ninety paired specimens of MPE cell blocks and matched primary lung cancer tissues from non–small cell lung cancer patients were subjected to PD-L1 and thyroid transcription factor-1(TTF-1)/p63 immunohistochemistry double staining. Two experienced pathologists independently evaluated PD-L1 expression using 3 cutoffs (1%, 10%, and 50%). PD-L1 expression in MPE was strongly correlated with that in matched primary lung cancer tissues (R = 0.813; P < .001). Using a 4-tier scale (cutoffs: 1%, 10%, and 50%), the concordance was 71.1% (Cohen’s κ = .534). Using a 2-tier scale, the concordance was 75.6% (1%, Cohen’s κ = 0.53), 78.9% (10%, Cohen’s κ = 0.574), and 95.6% (50%, Cohen’s κ = 0.754). The rates of PD-L1 positivity in MPE (56.7%) were higher than that in lung tissues (32.2%). All 27 discordant cases had higher scores in MPE. The double-staining method provided superior identification of PD-L1-positive tumor cells on a background with nonspecific staining. In conclusion, PD-L1 expression was moderately concordant between metastatic MPE cell blocks and matched primary lung carcinoma tissues, with variability related to tumor heterogeneity. MPE should be considered to detect PD-L1 when histological specimens are unattainable, especially when PD-L1 expression is >50%. PD-L1 positivity rates were higher in MPE. Double staining can improve PD-L1 detection by reducing false-negative/positive results.

Precision medicine aims to provide personalized care based on individual patient characteristics, rather than guideline-directed therapies for groups of diseases or patient demographics. Images—both radiology- and pathology-derived—are a major source of information on presence, type, and status of disease. Exploring the mathematical relationship of pixels in medical imaging (“radiomics”) and cellular-scale structures in digital pathology slides (“pathomics”) offers powerful tools for extracting both qualitative and, increasingly, quantitative data. These analytical approaches, however, may be significantly enhanced by applying additional methods arising from fields of mathematics such as differential geometry and algebraic topology that remain underexplored in this context. Geometry’s strength lies in its ability to provide precise local measurements, such as curvature, that can be crucial for identifying abnormalities at multiple spatial levels. These measurements can augment the quantitative features extracted in conventional radiomics, leading to more nuanced diagnostics. By contrast, topology serves as a robust shape descriptor, capturing essential features such as connected components and holes. The field of topological data analysis was initially founded to explore the shape of data, with functional network connectivity in the brain being a prominent example. Increasingly, its tools are now being used to explore organizational patterns of physical structures in medical images and digitized pathology slides. By leveraging tools from both differential geometry and algebraic topology, researchers and clinicians may be able to obtain a more comprehensive, multi-layered understanding of medical images and contribute to precision medicine’s armamentarium.

High-grade serous ovarian cancer (HGSOC) remains the most lethal female cancer by far. Herein, clinical HGSOC samples had higher N⁶-methyladenosine (m⁶A) modification than normal ovarian tissue, and its dysregulation had been reported to drive aberrant transcription and translation programs. However, Kringle-containing transmembrane protein 2 (KREMEN2) and its m⁶A modification have not been fully elucidated in HGSOC. In this study, the data from the high-throughput messenger RNA (mRNA) sequencing of clinical samples were processed using the weighted correlation network analysis and functional enrichment analysis. Results revealed that KREMEN2 was a driver gene in the tumorigenesis of HGSOC and a potential target of m⁶A demethylase fat-mass and obesity-associated protein (FTO). KREMEN2 and FTO levels were upregulated and downregulated, respectively, and correlation analysis showed a significant negative correlation in HGSOC samples. Importantly, upregulated KREMEN2 was remarkably associated with lymph node metastasis, distant metastasis, peritoneal metastasis, and high International Federation of Gynecology and Obstetrics stage (Ⅲ/Ⅳ), independent of the age of patients. KREMEN2 promoted the growth of HGSOC in vitro and in vivo, which was dependent on FTO. The methylated RNA immunoprecipitation qPCR and RNA immunoprecipitation assays were performed to verify the m⁶A level and sites of KREMEN2. FTO overexpression significantly decreased m⁶A modification in the 3′ and 5′ untranslated regions of KREMEN2 mRNA and downregulated its expression. In addition, we found that FTO-mediated m⁶A modification of KREMEN2 mRNA was recognized and stabilized by the m⁶A reader IGF2BP1 rather than by IGF2BP2 or IGF2BP3. This study highlights the m⁶A modification of KREMEN2 and extends the importance of RNA epigenetics in HGSOC.