p53 Immunohistochemistry (IHC) is a reliable surrogate for determining TP53 mutation status in endometrial carcinomas (ECs). However, the correlation of p53 IHC patterns and TP53 mutation characteristics in mismatch repair deficiency (MMRd) and/or POLE-mutant ECs was not comprehensively investigated. In this study, we identified 4 p53 expression patterns in 40 MMRd and/or POLE-mutant ECs with TP53 mutations. Thirteen cases (33%) displayed a wild-type pattern. Nine cases (23%) showed atypical pattern, characterized by the presence of eye-catching clustered cells with strong nuclear staining or weak-to-moderate cytoplasmic staining, which were patchily distributed with blurred boundaries. Fourteen cases (35%) demonstrated subclonal pattern with distinct regions of wild-type and mutation-type staining, of which 3 cases were originally misdiagnosed as "mixed EC." Only 4 (10%) cases exhibited typical aberrant pattern. Tumors with wild-type and atypical patterns were predominantly associated with MMRd and POLE mutations, respectively. Among 52 TP53 mutations identified, 75% were missense and 25% were truncating, predominantly in DNA-binding domain. Gain-of-function missense mutations were more frequent in cases with subclonal patterns, whereas non-gain-of-function missense mutations predominated in wild-type or atypical patterns. Concurrent mutations were present in 25% of cases and were more common in aberrant or atypical patterns. Interestingly, 2 POLE wild-type cases with subclonal MMR expression showed p53 overexpression across the entire tumor, complicating molecular subtyping. These findings highlight the prevalence of atypical and subclonal p53 expression patterns in MMRd and/or POLE-mutant ECs with TP53 mutations, aiding in accurate IHC interpretation and thus more precise EC histological and molecular classification.
{"title":"Prevalence of Atypical and Subclonal p53 Immunohistochemistry Expression in Mismatch Repair Deficient and/or POLE-Mutant Endometrial Carcinomas with TP53 Mutation.","authors":"Jing Wang, Yumeng Cai, Jun Wang, Jiuyuan Fang, Junyi Pang, Hui Zhang, Junliang Lu, Zijuan Zhang, Huanwen Wu, Zhiyong Liang","doi":"10.1016/j.labinv.2025.104216","DOIUrl":"10.1016/j.labinv.2025.104216","url":null,"abstract":"<p><p>p53 Immunohistochemistry (IHC) is a reliable surrogate for determining TP53 mutation status in endometrial carcinomas (ECs). However, the correlation of p53 IHC patterns and TP53 mutation characteristics in mismatch repair deficiency (MMRd) and/or POLE-mutant ECs was not comprehensively investigated. In this study, we identified 4 p53 expression patterns in 40 MMRd and/or POLE-mutant ECs with TP53 mutations. Thirteen cases (33%) displayed a wild-type pattern. Nine cases (23%) showed atypical pattern, characterized by the presence of eye-catching clustered cells with strong nuclear staining or weak-to-moderate cytoplasmic staining, which were patchily distributed with blurred boundaries. Fourteen cases (35%) demonstrated subclonal pattern with distinct regions of wild-type and mutation-type staining, of which 3 cases were originally misdiagnosed as \"mixed EC.\" Only 4 (10%) cases exhibited typical aberrant pattern. Tumors with wild-type and atypical patterns were predominantly associated with MMRd and POLE mutations, respectively. Among 52 TP53 mutations identified, 75% were missense and 25% were truncating, predominantly in DNA-binding domain. Gain-of-function missense mutations were more frequent in cases with subclonal patterns, whereas non-gain-of-function missense mutations predominated in wild-type or atypical patterns. Concurrent mutations were present in 25% of cases and were more common in aberrant or atypical patterns. Interestingly, 2 POLE wild-type cases with subclonal MMR expression showed p53 overexpression across the entire tumor, complicating molecular subtyping. These findings highlight the prevalence of atypical and subclonal p53 expression patterns in MMRd and/or POLE-mutant ECs with TP53 mutations, aiding in accurate IHC interpretation and thus more precise EC histological and molecular classification.</p>","PeriodicalId":17930,"journal":{"name":"Laboratory Investigation","volume":" ","pages":"104216"},"PeriodicalIF":4.2,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144667953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01Epub Date: 2025-07-17DOI: 10.1016/j.labinv.2025.104213
Anne Tuomisto, Päivi Sirniö, Hanna Elomaa, Henna Karjalainen, Ville K Äijälä, Meeri Kastinen, Vilja V Tapiainen, Maarit Ahtiainen, Olli Helminen, Erkki-Ville Wirta, Jukka Rintala, Sanna Meriläinen, Juha Saarnio, Tero Rautio, Toni T Seppälä, Jan Böhm, Jukka-Pekka Mecklin, Markus J Mäkinen, Juha P Väyrynen
High immune cell infiltration is generally associated with better survival in colorectal cancer (CRC). Recently, a prognostic score called CD8IE-FOXP3IS, which integrates the densities of tumor intraepithelial CD8+ and intrastromal FOXP3+ cells, was introduced using multiplex immunofluorescence. In this study, we developed a triple chromogenic immunohistochemistry assay to evaluate the CD8IE-FOXP3IS score and assessed its prognostic value in comparison with the CD3-CD8 T-cell density score (based on the principles of the Immunoscore) and conventional prognostic parameters. Multiplex immunohistochemistry combined with machine learning-assisted image analysis was used to quantify CD8IE and FOXP3IS densities in 2 independent cohorts comprising 1724 CRC patients. Multivariable Cox regression models were used to evaluate the prognostic value of the CD8IE-FOXP3IS score. We found that a low CD8IE-FOXP3IS score was associated with higher disease stage, more frequent lymphovascular invasion, and mismatch repair proficient status. In addition, a low CD8IE-FOXP3IS score was associated with higher CRC-specific mortality independent of the CD3-CD8 T-cell density score and other tumor and patient characteristics (cohort 1: hazard ratio [HR] for low vs high CD8IE-FOXP3IS score, 3.08; 95% CI, 1.54-6.15; Ptrend = 6.0E-4; cohort 2: HR, 4.30; 95% CI, 2.58-7.17; Ptrend = 3.2E-9). These findings indicate that triple chromogenic immunohistochemistry combined with digital pathology is an applicable method for quantifying tumor intraepithelial CD8+ and stromal FOXP3+ cell densities, allowing for the determination of the CD8IE-FOXP3IS score. The CD8IE-FOXP3IS score shows a strong prognostic value, which appears superior to overall CD3+ and CD8+ T-cell density measurement.
{"title":"Integrating Tumor Intraepithelial CD8<sup>+</sup> and Stromal FOXP3<sup>+</sup> T-Cell Densities as an Enhanced Immune Prognostic Index in Colorectal Cancer.","authors":"Anne Tuomisto, Päivi Sirniö, Hanna Elomaa, Henna Karjalainen, Ville K Äijälä, Meeri Kastinen, Vilja V Tapiainen, Maarit Ahtiainen, Olli Helminen, Erkki-Ville Wirta, Jukka Rintala, Sanna Meriläinen, Juha Saarnio, Tero Rautio, Toni T Seppälä, Jan Böhm, Jukka-Pekka Mecklin, Markus J Mäkinen, Juha P Väyrynen","doi":"10.1016/j.labinv.2025.104213","DOIUrl":"10.1016/j.labinv.2025.104213","url":null,"abstract":"<p><p>High immune cell infiltration is generally associated with better survival in colorectal cancer (CRC). Recently, a prognostic score called CD8<sup>IE</sup>-FOXP3<sup>IS</sup>, which integrates the densities of tumor intraepithelial CD8<sup>+</sup> and intrastromal FOXP3<sup>+</sup> cells, was introduced using multiplex immunofluorescence. In this study, we developed a triple chromogenic immunohistochemistry assay to evaluate the CD8<sup>IE</sup>-FOXP3<sup>IS</sup> score and assessed its prognostic value in comparison with the CD3-CD8 T-cell density score (based on the principles of the Immunoscore) and conventional prognostic parameters. Multiplex immunohistochemistry combined with machine learning-assisted image analysis was used to quantify CD8<sup>IE</sup> and FOXP3<sup>IS</sup> densities in 2 independent cohorts comprising 1724 CRC patients. Multivariable Cox regression models were used to evaluate the prognostic value of the CD8<sup>IE</sup>-FOXP3<sup>IS</sup> score. We found that a low CD8<sup>IE</sup>-FOXP3<sup>IS</sup> score was associated with higher disease stage, more frequent lymphovascular invasion, and mismatch repair proficient status. In addition, a low CD8<sup>IE</sup>-FOXP3<sup>IS</sup> score was associated with higher CRC-specific mortality independent of the CD3-CD8 T-cell density score and other tumor and patient characteristics (cohort 1: hazard ratio [HR] for low vs high CD8<sup>IE</sup>-FOXP3<sup>IS</sup> score, 3.08; 95% CI, 1.54-6.15; P<sub>trend</sub> = 6.0E-4; cohort 2: HR, 4.30; 95% CI, 2.58-7.17; P<sub>trend</sub> = 3.2E-9). These findings indicate that triple chromogenic immunohistochemistry combined with digital pathology is an applicable method for quantifying tumor intraepithelial CD8<sup>+</sup> and stromal FOXP3<sup>+</sup> cell densities, allowing for the determination of the CD8<sup>IE</sup>-FOXP3<sup>IS</sup> score. The CD8<sup>IE</sup>-FOXP3<sup>IS</sup> score shows a strong prognostic value, which appears superior to overall CD3<sup>+</sup> and CD8<sup>+</sup> T-cell density measurement.</p>","PeriodicalId":17930,"journal":{"name":"Laboratory Investigation","volume":" ","pages":"104213"},"PeriodicalIF":4.2,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144667952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-31DOI: 10.1016/j.labinv.2025.104257
Yu-Wen Huang , Ying-Ju Kuo , Ming-Chi Chen , Jackson Rodrigues , Tsung-Lun Lee , Chia-Fan Chang , Yen-Bin Hsu , Pen-Yuan Chu , Shyh-Kuan Tai , Guan-Yu Zhuo , Muh-Hwa Yang
Worst pattern of invasion-5 (WPOI-5) in oral cavity squamous cell carcinoma (OCSCC) is associated with aggressive disease behavior and worse prognosis. This study integrated clinical data analysis with multimodal nonlinear optical (MNLO) microscopy to investigate the prognostic implications and tumor microenvironment (TME) characteristics of WPOI-5 in OCSCC. Clinical data from 263 OCSCC patients were analyzed for overall survival and relapse-free survival (RFS). E-cadherin and N-cadherin expression levels were investigated in the epithelium at the tumor invasion front and within WPOI-5 regions. MNLO microscopy, combining second harmonic generation (SHG), third harmonic generation, and 2-photon fluorescence, was used to visualize and quantify structural changes in the TME associated with WPOI-5. Polarization-resolved SHG was used to investigate collagen cross-linking and remodeling. WPOI-5 was significantly associated with unfavorable overall survival and RFS in the univariate analysis and remained an independent predictor of poor RFS in multivariate analysis. Compared with the tumor invasion front, WPOI-5 exhibited reduced E-cadherin and enhanced N-cadherin expression, a hallmark of epithelial-to-mesenchymal transition, suggesting enhanced invasiveness and metastatic potential because of reduced intercellular adhesions. MNLO imaging revealed distinct TME structural organization between WPOI-5(+) and WPOI-5(−) samples, including differences in collagen fiber structure, orientation, and epithelial-to-mesenchymal transition–associated features at the tumor invasion front. Polarization-resolved SHG imaging further demonstrated increased collagen cross-linking and remodeling, as well as the perpendicular alignment of collagen fibers to the tumor boundary in WPOI-5(+) samples. This integrated approach provides preliminary evidence for the prognostic significance of WPOI-5 and offers proof-of-concept mechanistic insights into its role in OCSCC progression, offering a basis for future validation studies toward improved risk stratification and potential therapeutic targeting.
{"title":"Deciphering the Worst Pattern of Invasion in Oral Cancer: Integrative Clinical, Pathological, and Multimodal Nonlinear Optical Imaging Insights","authors":"Yu-Wen Huang , Ying-Ju Kuo , Ming-Chi Chen , Jackson Rodrigues , Tsung-Lun Lee , Chia-Fan Chang , Yen-Bin Hsu , Pen-Yuan Chu , Shyh-Kuan Tai , Guan-Yu Zhuo , Muh-Hwa Yang","doi":"10.1016/j.labinv.2025.104257","DOIUrl":"10.1016/j.labinv.2025.104257","url":null,"abstract":"<div><div>Worst pattern of invasion-5 (WPOI-5) in oral cavity squamous cell carcinoma (OCSCC) is associated with aggressive disease behavior and worse prognosis. This study integrated clinical data analysis with multimodal nonlinear optical (MNLO) microscopy to investigate the prognostic implications and tumor microenvironment (TME) characteristics of WPOI-5 in OCSCC. Clinical data from 263 OCSCC patients were analyzed for overall survival and relapse-free survival (RFS). E-cadherin and N-cadherin expression levels were investigated in the epithelium at the tumor invasion front and within WPOI-5 regions. MNLO microscopy, combining second harmonic generation (SHG), third harmonic generation, and 2-photon fluorescence, was used to visualize and quantify structural changes in the TME associated with WPOI-5. Polarization-resolved SHG was used to investigate collagen cross-linking and remodeling. WPOI-5 was significantly associated with unfavorable overall survival and RFS in the univariate analysis and remained an independent predictor of poor RFS in multivariate analysis. Compared with the tumor invasion front, WPOI-5 exhibited reduced E-cadherin and enhanced N-cadherin expression, a hallmark of epithelial-to-mesenchymal transition, suggesting enhanced invasiveness and metastatic potential because of reduced intercellular adhesions. MNLO imaging revealed distinct TME structural organization between WPOI-5(+) and WPOI-5(−) samples, including differences in collagen fiber structure, orientation, and epithelial-to-mesenchymal transition–associated features at the tumor invasion front. Polarization-resolved SHG imaging further demonstrated increased collagen cross-linking and remodeling, as well as the perpendicular alignment of collagen fibers to the tumor boundary in WPOI-5(+) samples. This integrated approach provides preliminary evidence for the prognostic significance of WPOI-5 and offers proof-of-concept mechanistic insights into its role in OCSCC progression, offering a basis for future validation studies toward improved risk stratification and potential therapeutic targeting.</div></div>","PeriodicalId":17930,"journal":{"name":"Laboratory Investigation","volume":"106 1","pages":"Article 104257"},"PeriodicalIF":4.2,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145431792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-31DOI: 10.1016/j.labinv.2025.104256
Pengfei Zhang , Xiaohua Tang , Francis Atim Akanyibah , Suping Du , Fei Mao
Spatiotemporal proteomics, as a vital component of spatiotemporal omics, possesses the capability to conduct large-scale screening and analysis of protein molecules across different spatial and temporal dimensions under various physiological or pathological conditions. This enables a precise and visualizable landscape of molecular distribution and expression changes. This technology is progressively becoming the most cutting-edge and effective tool in research on various diseases, including inflammatory bowel disease (IBD) and its associated colorectal cancer (CRC). Digital spatial profilers, imaging mass spectrometry, and imaging mass cytology have become widely adopted spatiotemporal proteomics technologies in IBD and CRC research due to their advantages of high-throughput, high-specificity, and single-cell resolution. In IBD research, these techniques not only help analyze the changes in protein distribution within intrinsic muscle layer cells, intestinal epithelial cells, and immune cells but also help examine the distribution and expression differences within the gut microbiota. In CRC research, spatiotemporal proteomics primarily focuses on molecular dynamic changes occurring across different stages of CRC (initiation, progression, and metastasis), including cellular distribution and differential expression of relevant molecules within the peritumoral region and alterations in the distribution of protein molecules across cellular compartments. Moreover, the translational applications of spatiotemporal proteomics warrant equal attention. These extend beyond screening traditional molecular therapeutic targets to encompass the development of precision therapies and adjunctive treatments (hyperbaric oxygen therapy, kinesitherapy, and controlled location and timing of medication). This review summarized the strengths and limitations of spatiotemporal proteomics technologies widely applied in IBD and CRC; described the spatial and temporal landscapes revealed by these techniques, elucidating their applications in diagnosis, treatment, and prognosis; and finally outlined the feasible directions for future optimization and advancement of spatiotemporal proteomics.
{"title":"Spatiotemporal Proteomics: Unveiling Evolving Molecular Landscapes in Inflammatory Bowel Disease and Associated Colorectal Cancer","authors":"Pengfei Zhang , Xiaohua Tang , Francis Atim Akanyibah , Suping Du , Fei Mao","doi":"10.1016/j.labinv.2025.104256","DOIUrl":"10.1016/j.labinv.2025.104256","url":null,"abstract":"<div><div>Spatiotemporal proteomics, as a vital component of spatiotemporal omics, possesses the capability to conduct large-scale screening and analysis of protein molecules across different spatial and temporal dimensions under various physiological or pathological conditions. This enables a precise and visualizable landscape of molecular distribution and expression changes. This technology is progressively becoming the most cutting-edge and effective tool in research on various diseases, including inflammatory bowel disease (IBD) and its associated colorectal cancer (CRC). Digital spatial profilers, imaging mass spectrometry, and imaging mass cytology have become widely adopted spatiotemporal proteomics technologies in IBD and CRC research due to their advantages of high-throughput, high-specificity, and single-cell resolution. In IBD research, these techniques not only help analyze the changes in protein distribution within intrinsic muscle layer cells, intestinal epithelial cells, and immune cells but also help examine the distribution and expression differences within the gut microbiota. In CRC research, spatiotemporal proteomics primarily focuses on molecular dynamic changes occurring across different stages of CRC (initiation, progression, and metastasis), including cellular distribution and differential expression of relevant molecules within the peritumoral region and alterations in the distribution of protein molecules across cellular compartments. Moreover, the translational applications of spatiotemporal proteomics warrant equal attention. These extend beyond screening traditional molecular therapeutic targets to encompass the development of precision therapies and adjunctive treatments (hyperbaric oxygen therapy, kinesitherapy, and controlled location and timing of medication). This review summarized the strengths and limitations of spatiotemporal proteomics technologies widely applied in IBD and CRC; described the spatial and temporal landscapes revealed by these techniques, elucidating their applications in diagnosis, treatment, and prognosis; and finally outlined the feasible directions for future optimization and advancement of spatiotemporal proteomics.</div></div>","PeriodicalId":17930,"journal":{"name":"Laboratory Investigation","volume":"106 1","pages":"Article 104256"},"PeriodicalIF":4.2,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145431722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-29DOI: 10.1016/j.labinv.2025.104254
Baptiste Hamelin , Salome Hosch , Claudio Neidhöfer , Marie-Thérèse Ruf , Jasmin D. Haslbauer , Christopher M. Field , Pascal Schläpfer , Massimiliano Manzo , Andreas Neumayr , Esther Kuenzli , Maria Mancuso , Melanie Sachs , Nadine Mensah , Regula Bernhard , Barbara Klaus-Wirthner , Maura Concu , Ronny Nienhold , Richard Kuehl , Veronika Baettig , Maja Weisser-Rohacek , Kirsten D. Mertz
Pathogen detection in formalin-fixed paraffin-embedded (FFPE) tissue remains challenging. We implemented metagenomic next-generation sequencing (mNGS) in our clinical diagnostic workflow to evaluate its feasibility, diagnostic yield, and pathogen spectrum in routine infectious pathology cases. Between November 2021 and April 2025, we analyzed 623 FFPE tissue samples using a low-depth mNGS workflow on the Thermo Fisher Ion Torrent platform with a CLC Genomics Workbench (Qiagen) bioinformatics pipeline. Our assay was designed to detect DNA pathogens. When possible, results were validated by orthogonal methods, including species-specific PCRs, 16S/internal transcribed spacer PCR, and immunohistochemistry on tissue sections. Among 623 samples analyzed, at least 1 potentially pathogenic and plausible microorganism was identified in 229 samples (36.8%), whereas 334 (53.6%) were negative and 60 (9.6%) were uninterpretable due to quality control failures or suspected contamination. Of the 229 positive samples, 145 (63.3%) involved bacteria, 37 (16.2%) viruses, 28 (12.2%) fungi, and 9 (3.9%) parasites; mixed infections with >1 pathogen were detected in 10 (4.4%) samples. The most frequently identified bacterial family was Mycobacteriaceae (n = 27), including Mycobacterium xenopi (n = 8), which is not routinely covered by syndromic multiplex PCR panels. Notable viral and fungal detections included a novel human circovirus and Coccidioides posadasii. Despite variable sample quality and DNA input, mNGS yielded reliable results in a wide range of tissue types. mNGS is a feasible, valuable addition to routine infectious pathology diagnostics, particularly in complex or inconclusive cases. The assay improved the diagnostic yield compared with conventional PCR, expanded the range of detectable pathogens, and proved robust even in low-quality FFPE samples. These results support broader adoption of mNGS in tissue-based pathogen diagnostics.
福尔马林固定石蜡包埋(FFPE)组织中的病原体检测仍然具有挑战性。我们在临床诊断工作流程中实施了新一代宏基因组测序(mNGS),以评估其在常规感染病理病例中的可行性、诊断率和病原体谱。在2021年11月至2025年4月期间,我们使用Thermo Fisher Ion Torrent平台上的低深度mNGS工作流程和CLC Genomics Workbench生物信息学管道分析了623个FFPE组织样本。我们的试验设计用于检测DNA病原体。在可能的情况下,通过正交方法验证结果,包括物种特异性PCR, 16S/ITS PCR和组织切片的免疫组织化学。在分析的623份样品中,229份(36.8%)样品中至少鉴定出一种潜在致病性和似是而非的微生物,334份(53.6%)样品为阴性,60份(9.6%)样品由于质量控制失败或疑似污染而无法解释。229份阳性标本中,细菌145份(63.3%),病毒37份(16.2%),真菌28份(12.2%),寄生虫9份(3.9%);在10份(4.4%)样本中检出一种以上病原菌的混合感染。最常发现的细菌家族是分枝杆菌科(n=27),包括xenopi分枝杆菌(n=8),该分支杆菌通常未被综合征多重PCR检测覆盖。值得注意的病毒和真菌检测包括一种新的人类圆环病毒和波萨达球螨。尽管样品质量和DNA输入不同,但mNGS在广泛的组织类型中产生了可靠的结果。宏基因组NGS是常规感染病理学诊断的一种可行的、有价值的补充,特别是在复杂或不确定的病例中。与传统PCR相比,该方法提高了诊断率,扩大了可检测病原体的范围,并且即使在低质量的FFPE样品中也证明了其可靠性。这些结果支持在基于组织的病原体诊断中更广泛地采用mNGS。
{"title":"Unbiased DNA Pathogen Detection in Tissues: Real-World Experience With Metagenomic Sequencing in Pathology","authors":"Baptiste Hamelin , Salome Hosch , Claudio Neidhöfer , Marie-Thérèse Ruf , Jasmin D. Haslbauer , Christopher M. Field , Pascal Schläpfer , Massimiliano Manzo , Andreas Neumayr , Esther Kuenzli , Maria Mancuso , Melanie Sachs , Nadine Mensah , Regula Bernhard , Barbara Klaus-Wirthner , Maura Concu , Ronny Nienhold , Richard Kuehl , Veronika Baettig , Maja Weisser-Rohacek , Kirsten D. Mertz","doi":"10.1016/j.labinv.2025.104254","DOIUrl":"10.1016/j.labinv.2025.104254","url":null,"abstract":"<div><div>Pathogen detection in formalin-fixed paraffin-embedded (FFPE) tissue remains challenging. We implemented metagenomic next-generation sequencing (mNGS) in our clinical diagnostic workflow to evaluate its feasibility, diagnostic yield, and pathogen spectrum in routine infectious pathology cases. Between November 2021 and April 2025, we analyzed 623 FFPE tissue samples using a low-depth mNGS workflow on the Thermo Fisher Ion Torrent platform with a CLC Genomics Workbench (Qiagen) bioinformatics pipeline. Our assay was designed to detect DNA pathogens. When possible, results were validated by orthogonal methods, including species-specific PCRs, <em>16S</em>/internal transcribed spacer PCR, and immunohistochemistry on tissue sections. Among 623 samples analyzed, at least 1 potentially pathogenic and plausible microorganism was identified in 229 samples (36.8%), whereas 334 (53.6%) were negative and 60 (9.6%) were uninterpretable due to quality control failures or suspected contamination. Of the 229 positive samples, 145 (63.3%) involved bacteria, 37 (16.2%) viruses, 28 (12.2%) fungi, and 9 (3.9%) parasites; mixed infections with >1 pathogen were detected in 10 (4.4%) samples. The most frequently identified bacterial family was Mycobacteriaceae (n = 27), including <em>Mycobacterium xenopi</em> (n = 8), which is not routinely covered by syndromic multiplex PCR panels. Notable viral and fungal detections included a novel human circovirus and <em>Coccidioides posadasii</em>. Despite variable sample quality and DNA input, mNGS yielded reliable results in a wide range of tissue types. mNGS is a feasible, valuable addition to routine infectious pathology diagnostics, particularly in complex or inconclusive cases. The assay improved the diagnostic yield compared with conventional PCR, expanded the range of detectable pathogens, and proved robust even in low-quality FFPE samples. These results support broader adoption of mNGS in tissue-based pathogen diagnostics.</div></div>","PeriodicalId":17930,"journal":{"name":"Laboratory Investigation","volume":"106 1","pages":"Article 104254"},"PeriodicalIF":4.2,"publicationDate":"2025-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145409520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-15DOI: 10.1016/j.labinv.2025.104253
Fei Deng , Yongfeng Zhang , Lanjing Zhang
There are often performance differences between intra-data set and cross-data set tests in machine learning (ML) modeling. However, reducing these differences may reduce ML performance. It is thus a challenging dilemma for developing models that excel in intra-data set testing and are generalizable to cross-data set testing. Therefore, we aimed to understand and improve the performance and generalizability of ML in intra-data set and cross-data set testing. We evaluated 4200 ML models of classifying lung adenocarcinoma deaths using The Cancer Genome Atlas (n = 286) and Oncogenomic-Singapore (n = 167) data sets and 1680 models of classifying glioblastoma deaths using The Cancer Genome Atlas (n = 151) and Clinical Proteomic Tumor Analysis Consortium (n = 97) data sets. After examining performance distributions of these ML models, we applied a dual analytical framework, including statistical analyses and SHapley Additive exPlanations–based meta-analysis, to quantify factors’ importance and trace model success back to design principles. We also developed a framework to identify the best generalizable model. Strikingly, the Jarque-Bera test revealed significant deviations of model performances from normality in both cancer types and testing contexts. Simple linear models with sparse feature sets consistently dominated in lung adenocarcinoma experiments, whereas nonlinear models dominated in glioblastoma ones, suggesting that the best modeling strategy appears to be cancer type/disease dependent. Importantly, both robust analysis of variance and Kruskal-Wallis tests consistently identified differentially expressed genes as one of the most influential factors in both cancer types. The proposed multicriteria framework successfully identified the model that achieved both the best cross-data set performance and similar intra-data set performance. In summary, ML performance distributions significantly deviated from normality, which motivates using both robust parametric and nonparametric statistical tests. We quantified and provided possible exploitability on the factors associated with cross-data set performances and generalizability of ML models in 2 cancer types. A multicriteria framework was developed and validated to identify the models that are accurate and consistently robust across data sets.
{"title":"Toward the Best Generalizable Performance of Machine Learning in Modeling Omic and Clinical Data","authors":"Fei Deng , Yongfeng Zhang , Lanjing Zhang","doi":"10.1016/j.labinv.2025.104253","DOIUrl":"10.1016/j.labinv.2025.104253","url":null,"abstract":"<div><div>There are often performance differences between intra-data set and cross-data set tests in machine learning (ML) modeling. However, reducing these differences may reduce ML performance. It is thus a challenging dilemma for developing models that excel in intra-data set testing and are generalizable to cross-data set testing. Therefore, we aimed to understand and improve the performance and generalizability of ML in intra-data set and cross-data set testing. We evaluated 4200 ML models of classifying lung adenocarcinoma deaths using The Cancer Genome Atlas (n = 286) and Oncogenomic-Singapore (n = 167) data sets and 1680 models of classifying glioblastoma deaths using The Cancer Genome Atlas (n = 151) and Clinical Proteomic Tumor Analysis Consortium (n = 97) data sets. After examining performance distributions of these ML models, we applied a dual analytical framework, including statistical analyses and SHapley Additive exPlanations–based meta-analysis, to quantify factors’ importance and trace model success back to design principles. We also developed a framework to identify the best generalizable model. Strikingly, the Jarque-Bera test revealed significant deviations of model performances from normality in both cancer types and testing contexts. Simple linear models with sparse feature sets consistently dominated in lung adenocarcinoma experiments, whereas nonlinear models dominated in glioblastoma ones, suggesting that the best modeling strategy appears to be cancer type/disease dependent. Importantly, both robust analysis of variance and Kruskal-Wallis tests consistently identified differentially expressed genes as one of the most influential factors in both cancer types. The proposed multicriteria framework successfully identified the model that achieved both the best cross-data set performance and similar intra-data set performance. In summary, ML performance distributions significantly deviated from normality, which motivates using both robust parametric and nonparametric statistical tests. We quantified and provided possible exploitability on the factors associated with cross-data set performances and generalizability of ML models in 2 cancer types. A multicriteria framework was developed and validated to identify the models that are accurate and consistently robust across data sets.</div></div>","PeriodicalId":17930,"journal":{"name":"Laboratory Investigation","volume":"105 12","pages":"Article 104253"},"PeriodicalIF":4.2,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145313163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-13DOI: 10.1016/j.labinv.2025.104251
Marika Valentino , Vittorio Bianco , Gioacchino D’Ambrosio , Marco Paulli , Giovanni Smaldone , Valentina Brancato , Lisa Miccio , Marco Salvatore , Marcello Gambacorta , Pietro Ferraro
Histology remains a cornerstone in diagnosis and prognosis of renal diseases. Histopathological analysis of kidney tissue is crucial for understanding renal pathophysiology. The availability of multiple stained sections is essential for conducting comprehensive histopathological analysis and achieving accurate diagnosis. Fourier ptychographic microscopy (FPM) has emerged as a promising microscopy technique. The ability to provide high-resolution, quantitative phase-contrast images over a wide area, particularly in a stain-free mode, makes FPM highly appealing to experts in histopathology. As renal pathologies are characterized by subtle morphologic changes encoded in tissue slides, phase maps obtained using FPM are well suited for providing detailed, high-contrast images of tissue structures. FPM provides a quantitative imaging tool that can be descriptive of the sample and/or expressive of the disease. Here, we explored FPM capability to image pathological kidney tissue, enabling pathologists to select regions of interest within the intricate architecture of renal tissue and zoom in to observe minute submicron structures, ranging from overall tissue organization and glomeruli distribution to individual basal membranes. Membranous glomerulonephritis (MG) was focused on because of its high dependence on histologic examination. We extracted descriptive features able to discriminate between healthy kidney tissues and those affected by MG. Moreover, FPM phase-contrast images allowed observing in detail the glomerular basal membranes and measuring the differences in lateral thickness with respect to healthy specimens. This is because of better glomerular membranes contrast in FPM images with respect to the hematoxylin-and-eosin–stained images. Our study shows the broad potential of FPM in characterizing hallmarks of MG disease even in stain-free tissue slides.
{"title":"Stain-Free Characterization of Membranous Glomerulonephritis via Fourier Ptychographic Microscopy","authors":"Marika Valentino , Vittorio Bianco , Gioacchino D’Ambrosio , Marco Paulli , Giovanni Smaldone , Valentina Brancato , Lisa Miccio , Marco Salvatore , Marcello Gambacorta , Pietro Ferraro","doi":"10.1016/j.labinv.2025.104251","DOIUrl":"10.1016/j.labinv.2025.104251","url":null,"abstract":"<div><div>Histology remains a cornerstone in diagnosis and prognosis of renal diseases. Histopathological analysis of kidney tissue is crucial for understanding renal pathophysiology. The availability of multiple stained sections is essential for conducting comprehensive histopathological analysis and achieving accurate diagnosis. Fourier ptychographic microscopy (FPM) has emerged as a promising microscopy technique. The ability to provide high-resolution, quantitative phase-contrast images over a wide area, particularly in a stain-free mode, makes FPM highly appealing to experts in histopathology. As renal pathologies are characterized by subtle morphologic changes encoded in tissue slides, phase maps obtained using FPM are well suited for providing detailed, high-contrast images of tissue structures. FPM provides a quantitative imaging tool that can be descriptive of the sample and/or expressive of the disease. Here, we explored FPM capability to image pathological kidney tissue, enabling pathologists to select regions of interest within the intricate architecture of renal tissue and zoom in to observe minute submicron structures, ranging from overall tissue organization and glomeruli distribution to individual basal membranes. Membranous glomerulonephritis (MG) was focused on because of its high dependence on histologic examination. We extracted descriptive features able to discriminate between healthy kidney tissues and those affected by MG. Moreover, FPM phase-contrast images allowed observing in detail the glomerular basal membranes and measuring the differences in lateral thickness with respect to healthy specimens. This is because of better glomerular membranes contrast in FPM images with respect to the hematoxylin-and-eosin–stained images. Our study shows the broad potential of FPM in characterizing hallmarks of MG disease even in stain-free tissue slides.</div></div>","PeriodicalId":17930,"journal":{"name":"Laboratory Investigation","volume":"105 12","pages":"Article 104251"},"PeriodicalIF":4.2,"publicationDate":"2025-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145301574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-13DOI: 10.1016/j.labinv.2025.104252
Haohua Teng , Yueyuxiao Yang , Chan Xiang , Jikai Zhao , Zhanxian Shang , Qian Zhu , Lianying Guo , Qiushun He , Meng Yang , Yuchen Han
Lymphoepithelial carcinoma (LEC) can occur in various organs, such as the lung, nasopharynx, and thymus. We investigated the spatial characteristics of the tumor immune microenvironment (TIME) among primary pulmonary LECs (pLECs), pulmonary metastatic nasopharyngeal carcinomas (pmNPCs), and thymic LECs (tLECs). In this retrospective study, a total of 160 surgically resected LEC cases, comprising 116 pLECs, 26 tLECs, and 18 pmNPCs, were included. The TIME features, based on hematoxylin and eosin (H&E)-stained whole-slide images (WSIs) and multiplexed immunofluorescence staining images, were obtained and their association with patient prognosis was analyzed. We developed a semisupervized model for automated tumor segmentation based on H&E WSIs. The performance of the model was robust, with a mean accuracy rate of 0.847 on the testing set. Subsequent TIME analysis revealed different spatial distribution patterns of lymphocytes on H&E WSIs among pLECs, tLECs, and pmNPCs. Lymphocyte count and distribution were prognostically relevant in pLECs, with an increasing trend of lymphocytes from the peripheral normal lung area to the tumor core in patients with a good prognosis. Further TIME analysis based on multiplexed immunofluorescence images uncovered that spatial arrangement and spatial interaction pattern characteristics were dependent on specific tumor types and cell subtypes. Our semisupervized learning model offers an automated and reproducible method for tumor segmentation for the TIME of rare LECs. Our analysis revealed different TIME patterns that distinguish among pLEC, tLEC, and pmNPC and demonstrates that the spatial arrangement and positional interaction patterns of PDL1+ tumor cells and FOXP3+ regulatory T cells could stratify prognosis in patients with pLEC.
{"title":"Artificial Intelligence–Powered Spatial Analysis of the Tumor Microenvironment in Pulmonary Lymphoepithelial Carcinoma","authors":"Haohua Teng , Yueyuxiao Yang , Chan Xiang , Jikai Zhao , Zhanxian Shang , Qian Zhu , Lianying Guo , Qiushun He , Meng Yang , Yuchen Han","doi":"10.1016/j.labinv.2025.104252","DOIUrl":"10.1016/j.labinv.2025.104252","url":null,"abstract":"<div><div>Lymphoepithelial carcinoma (LEC) can occur in various organs, such as the lung, nasopharynx, and thymus. We investigated the spatial characteristics of the tumor immune microenvironment (TIME) among primary pulmonary LECs (pLECs), pulmonary metastatic nasopharyngeal carcinomas (pmNPCs), and thymic LECs (tLECs). In this retrospective study, a total of 160 surgically resected LEC cases, comprising 116 pLECs, 26 tLECs, and 18 pmNPCs, were included. The TIME features, based on hematoxylin and eosin (H&E)-stained whole-slide images (WSIs) and multiplexed immunofluorescence staining images, were obtained and their association with patient prognosis was analyzed. We developed a semisupervized model for automated tumor segmentation based on H&E WSIs. The performance of the model was robust, with a mean accuracy rate of 0.847 on the testing set. Subsequent TIME analysis revealed different spatial distribution patterns of lymphocytes on H&E WSIs among pLECs, tLECs, and pmNPCs. Lymphocyte count and distribution were prognostically relevant in pLECs, with an increasing trend of lymphocytes from the peripheral normal lung area to the tumor core in patients with a good prognosis. Further TIME analysis based on multiplexed immunofluorescence images uncovered that spatial arrangement and spatial interaction pattern characteristics were dependent on specific tumor types and cell subtypes. Our semisupervized learning model offers an automated and reproducible method for tumor segmentation for the TIME of rare LECs. Our analysis revealed different TIME patterns that distinguish among pLEC, tLEC, and pmNPC and demonstrates that the spatial arrangement and positional interaction patterns of PDL1<sup>+</sup> tumor cells and FOXP3<sup>+</sup> regulatory T cells could stratify prognosis in patients with pLEC.</div></div>","PeriodicalId":17930,"journal":{"name":"Laboratory Investigation","volume":"105 12","pages":"Article 104252"},"PeriodicalIF":4.2,"publicationDate":"2025-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145301614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-11DOI: 10.1016/j.labinv.2025.104250
Ana Mantrana , María Teresa Sánchez-Montero , Carmen Navarrete-Sirvent , Nerea Herrera-Casanova , Rafael Mena-Osuna , Aurora Rivas-Crespo , Alejandra Díaz-Chacón , Virginia Ávila-Oca , Marta Toledano-Fonseca , María Victoria García-Ortíz , Rafael González-Fernández , María Auxiliadora Gómez-España , Carlos Villar , Francisco Javier Medina-Fernández , Enrique Aranda , Silvia Guil-Luna , Antonio Rodríguez-Ariza
S-nitrosoglutathione reductase (GSNOR) is increasingly recognized as a tumor suppressor, and we have recently reported that its deficiency drives an aggressive and immune-evasive phenotype in colorectal cancer (CRC). However, the mechanisms linking GSNOR loss to immune escape remain incompletely understood. In this study, we uncover a previously unrecognized connection between metabolic reprogramming and immune escape in GSNOR-deficient CRC and identify a therapeutic vulnerability that can be exploited to restore immune responsiveness. A comprehensive analysis of 137 clinical CRC samples revealed that GSNOR-deficient tumors exhibit high-grade tumor budding, an established marker of poor prognosis, and reduced CD4+ and CD8+ T-cell infiltration, consistent with an immunosuppressive tumor microenvironment. Integrating transcriptomic, immunohistochemical, and single–cell RNA-sequencing data, we demonstrate that GSNOR-deficient tumors undergo a striking metabolic reprogramming toward glycolytic dependence, with elevated lactate production contributing to T-cell exclusion. Based on these findings, we show that pharmacologic glycolysis inhibition with 2-deoxyglucose reverses immune resistance in GSNOR-knockout models, enhancing CD8+ T-cell infiltration and sensitizing tumors to anti–PD-1 therapy both in vitro and in vivo. Notably, this is the first demonstration that metabolic intervention can restore immune sensitivity in GSNOR-deficient CRC. Our results identify GSNOR expression as a predictive biomarker for metabolic-immune combinatorial strategies and support the clinical translation of 2-deoxyglucose plus anti–PD-1 as a precision immunotherapy approach for this high-risk CRC phenotype.
s -亚硝基谷胱甘肽还原酶(GSNOR)越来越被认为是一种肿瘤抑制因子,我们最近报道了它的缺乏导致结直肠癌(CRC)的侵袭性和免疫逃避表型。然而,将GSNOR丢失与免疫逃逸联系起来的机制仍然不完全清楚。在这项研究中,我们揭示了gsnorr缺陷CRC中代谢重编程和免疫逃逸之间先前未被认识到的联系,并确定了一种可用于恢复免疫反应性的治疗脆弱性。对137例临床CRC样本的综合分析显示,gsnorr缺陷肿瘤表现为高级别肿瘤出芽,这是一种预后不良的标志,CD4+和CD8+ t细胞浸润减少,与免疫抑制肿瘤微环境一致。综合转录组学、免疫组织化学和单细胞RNA-seq数据,我们证明了gsnorr缺陷肿瘤经历了惊人的代谢重编程,导致糖酵解依赖,乳酸产量升高导致t细胞排斥。基于这些发现,我们发现2-脱氧葡萄糖(2-DG)的药理学糖酵解抑制逆转了gsnoro - ko模型的免疫抵抗,增强了CD8+ t细胞的浸润,并使肿瘤对抗pd -1治疗增敏。值得注意的是,这是首次证明代谢干预可以恢复gsnorr缺陷CRC的免疫敏感性。我们的研究结果确定GSNOR表达作为代谢-免疫组合策略的预测性生物标志物,并支持2-DG加抗pd -1的临床翻译作为这种高风险CRC表型的精确免疫治疗方法。
{"title":"Glycolysis Inhibition Restores Immune Sensitivity in GSNOR–Deficient Colorectal Cancer","authors":"Ana Mantrana , María Teresa Sánchez-Montero , Carmen Navarrete-Sirvent , Nerea Herrera-Casanova , Rafael Mena-Osuna , Aurora Rivas-Crespo , Alejandra Díaz-Chacón , Virginia Ávila-Oca , Marta Toledano-Fonseca , María Victoria García-Ortíz , Rafael González-Fernández , María Auxiliadora Gómez-España , Carlos Villar , Francisco Javier Medina-Fernández , Enrique Aranda , Silvia Guil-Luna , Antonio Rodríguez-Ariza","doi":"10.1016/j.labinv.2025.104250","DOIUrl":"10.1016/j.labinv.2025.104250","url":null,"abstract":"<div><div>S-nitrosoglutathione reductase (GSNOR) is increasingly recognized as a tumor suppressor, and we have recently reported that its deficiency drives an aggressive and immune-evasive phenotype in colorectal cancer (CRC). However, the mechanisms linking GSNOR loss to immune escape remain incompletely understood. In this study, we uncover a previously unrecognized connection between metabolic reprogramming and immune escape in GSNOR-deficient CRC and identify a therapeutic vulnerability that can be exploited to restore immune responsiveness. A comprehensive analysis of 137 clinical CRC samples revealed that GSNOR-deficient tumors exhibit high-grade tumor budding, an established marker of poor prognosis, and reduced CD4<sup>+</sup> and CD8<sup>+</sup> T-cell infiltration, consistent with an immunosuppressive tumor microenvironment. Integrating transcriptomic, immunohistochemical, and single–cell RNA-sequencing data, we demonstrate that GSNOR-deficient tumors undergo a striking metabolic reprogramming toward glycolytic dependence, with elevated lactate production contributing to T-cell exclusion. Based on these findings, we show that pharmacologic glycolysis inhibition with 2-deoxyglucose reverses immune resistance in GSNOR-knockout models, enhancing CD8<sup>+</sup> T-cell infiltration and sensitizing tumors to anti–PD-1 therapy both in vitro and in vivo. Notably, this is the first demonstration that metabolic intervention can restore immune sensitivity in GSNOR-deficient CRC. Our results identify GSNOR expression as a predictive biomarker for metabolic-immune combinatorial strategies and support the clinical translation of 2-deoxyglucose plus anti–PD-1 as a precision immunotherapy approach for this high-risk CRC phenotype.</div></div>","PeriodicalId":17930,"journal":{"name":"Laboratory Investigation","volume":"105 12","pages":"Article 104250"},"PeriodicalIF":4.2,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145286480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Twenty percent and 45.4% of high-grade ovarian carcinomas (OC) and endometrial carcinomas (EC) exhibit CCNE1 amplification (CCNE1-amp), respectively, which is related to poor prognosis, but could serve as predictive biomarker for response to innovative targeted therapies. However, there is no consensus regarding how to evaluate the CCNE1 status (at the DNA, RNA, and/or protein level). Therefore, we conducted a systematic review of CCNE1 status testing in tubo-ovarian neoplasms and EC, comparing their performance for clinical purposes and highlighting the test’s interpretation criteria (CRD420250651291). Among the 734 records initially found on PubMed and Google Scholar, 48 reports were finally included. Molecular analyses and immunohistochemistry (IHC) were reported on 9774 tubo-ovarian neoplasms and 750 EC, and 6966 tubo-ovarian neoplasms and 856 EC, respectively. The most frequently morphological used method to detect CCNE1-amp was fluorescent in situ hybridization (13/16 studies, 81.3%), with quite consensual criteria to defined amplification (ie, CCNE1/chromosome 19 ratio ≥2, and/or >8/≥8 copies of CCNE1 per nucleus, and/or ≥4 CCNE1 copies in ≥40% of cells). The proportion of tubo-ovarian neoplasms with CCNE1 immunohistochemical overexpression varied from 13.5% to 96%, and 14.6% to 86.1% in EC. The sensitivity and specificity of CCNE1 IHC to detect/exclude CCNE1-amp varied from 54.5% to 100% and 59.3% to 90.1%, respectively. Given the reported data, CCNE1 overexpression should be considered either when an H-score is ≥100 or when the staining is >60% with >5% of cells strongly stained. Both CCNE1-amp and CCNE1 overexpressions were associated with poor prognosis and with response to Wee1 and CDK2 inhibitors in high-grade serous OC (overall response rate up to 53%, objective response rate of 32%-40%). In contrast, CCNE1 messenger RNA overexpression had no prognostic value. Thus, both CCNE1-amp detection by fluorescent in situ hybridization and CCNE1 protein levels quantification using IHC represent today the most validated tools to determine the CCNE1 status in OC/EC.
{"title":"Assessing the Status of Cyclin E1 (CCNE1) From Gene to Protein Level in Ovarian and Endometrial Carcinomas: A Systematic Review","authors":"Alexis Trecourt , Catherine Genestie , Alexander Valent , Mojgan Devouassoux-Shisheboran , Etienne Rouleau , Elisa Yaniz-Galende , Audrey Leformal , Valeria Naim , Alexandra Leary","doi":"10.1016/j.labinv.2025.104249","DOIUrl":"10.1016/j.labinv.2025.104249","url":null,"abstract":"<div><div>Twenty percent and 45.4% of high-grade ovarian carcinomas (OC) and endometrial carcinomas (EC) exhibit <em>CCNE1</em> amplification (<em>CCNE1</em>-amp), respectively, which is related to poor prognosis, but could serve as predictive biomarker for response to innovative targeted therapies. However, there is no consensus regarding how to evaluate the CCNE1 status (at the DNA, RNA, and/or protein level). Therefore, we conducted a systematic review of CCNE1 status testing in tubo-ovarian neoplasms and EC, comparing their performance for clinical purposes and highlighting the test’s interpretation criteria (CRD420250651291). Among the 734 records initially found on PubMed and Google Scholar, 48 reports were finally included. Molecular analyses and immunohistochemistry (IHC) were reported on 9774 tubo-ovarian neoplasms and 750 EC, and 6966 tubo-ovarian neoplasms and 856 EC, respectively. The most frequently morphological used method to detect <em>CCNE1</em>-amp was fluorescent in situ hybridization (13/16 studies, 81.3%), with quite consensual criteria to defined amplification (ie, <em>CCNE1</em>/chromosome 19 ratio ≥2, and/or >8/≥8 copies of <em>CCNE1</em> per nucleus, and/or ≥4 <em>CCNE1</em> copies in ≥40% of cells). The proportion of tubo-ovarian neoplasms with CCNE1 immunohistochemical overexpression varied from 13.5% to 96%, and 14.6% to 86.1% in EC. The sensitivity and specificity of CCNE1 IHC to detect/exclude <em>CCNE1</em>-amp varied from 54.5% to 100% and 59.3% to 90.1%, respectively. Given the reported data, CCNE1 overexpression should be considered either when an H-score is ≥100 or when the staining is >60% with >5% of cells strongly stained. Both <em>CCNE1</em>-amp and CCNE1 overexpressions were associated with poor prognosis and with response to Wee1 and CDK2 inhibitors in high-grade serous OC (overall response rate up to 53%, objective response rate of 32%-40%). In contrast, <em>CCNE1</em> messenger RNA overexpression had no prognostic value. Thus, both <em>CCNE1</em>-amp detection by fluorescent in situ hybridization and CCNE1 protein levels quantification using IHC represent today the most validated tools to determine the CCNE1 status in OC/EC.</div></div>","PeriodicalId":17930,"journal":{"name":"Laboratory Investigation","volume":"105 12","pages":"Article 104249"},"PeriodicalIF":4.2,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145280579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}