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The Journal of Molecular Diagnostics :... Mar 2019Although classic histomorphology is the cornerstone of bone tumor diagnostics, this field has rapidly evolved since the advancement of new molecular techniques. The... (Review)
Review
Although classic histomorphology is the cornerstone of bone tumor diagnostics, this field has rapidly evolved since the advancement of new molecular techniques. The identification of novel genetic alterations in bone tumors has led to more insight into the genetic background of these tumors, which has resulted in a more prominent role of molecular pathology in daily practice. Numerous studies have been conducted in the past few decades and illustrated that based on molecular alterations, bone tumors can be roughly classified as tumors with simple karyotypes and those with complex karyotypes. The first group can be subclassified as tumors that carry specific translocations, somatic gene mutations, or more or less specific amplifications. On the other hand, sarcomas with complex karyotypes usually lack specific alterations. Many techniques are available for the detection of recurrent genetic alterations, now also including IHC analysis, and this review focuses on assays routinely performed in molecular diagnostics. Subsequently, tumor classes with distinct genetic abnormalities are discussed and illustrated by more specific examples, and the usefulness of molecular pathology in routine diagnostics is highlighted.
Topics: Animals; Bone Neoplasms; Humans; Karyotyping; Mutation; Pathology, Molecular; Sarcoma; Translocation, Genetic
PubMed: 30572118
DOI: 10.1016/j.jmoldx.2018.11.002 -
Pathologie (Heidelberg, Germany) Aug 2022Odontogenic tumors (OTs) are rare, with an estimated incidence rate of less than 0.5 cases per 100,000 per year. The causes of OTs remain unclear. Nonetheless, the... (Review)
Review
BACKGROUND
Odontogenic tumors (OTs) are rare, with an estimated incidence rate of less than 0.5 cases per 100,000 per year. The causes of OTs remain unclear. Nonetheless, the majority of OTs seem to arise de novo, without an apparent causative factor. Although the etiopathogenesis of most OTs remains unclear, there have been some recent advances in understanding the genetic basis relating to specific histologies and clinical features. Molecular analyses performed by different techniques, including Sanger sequencing, next-generation sequencing, and allele-specific PCR, have uncovered mutations in genes related to the oncogenic MAPK/ERK signaling pathway. Genetic mutations in these pathway genes have been reported in epithelial and mixed OTs, in addition to odontogenic carcinomas and sarcomas. Notably, B‑RAF proto-oncogene serine/threonine kinase (BRAF) and KRAS proto-oncogene GTPase (KRAS) pathogenic mutations have been reported in a high proportion of ameloblastoma and ameloblastoma-related tumors and adenomatoid odontogenic tumors, respectively.
OBJECTIVE
To discuss how molecular profiling aids in diagnostic classification of odontogenic tumors.
CONCLUSION
Molecular profiling of odontogenic tumors helps to identify patients for neoadjuvant therapies and reduces postoperative morbidity.
Topics: Humans; Ameloblastoma; Odontogenic Tumors; Pathology, Molecular; Proto-Oncogene Proteins B-raf; Proto-Oncogene Proteins p21(ras)
PubMed: 36378285
DOI: 10.1007/s00292-022-01152-7 -
Annual Review of Genomics and Human... Aug 2022Molecular diagnostic tests enable rapid analysis of genomic and proteomic markers. These tests are subject to diverging premarket access and postmarket surveillance... (Review)
Review
Molecular diagnostic tests enable rapid analysis of genomic and proteomic markers. These tests are subject to diverging premarket access and postmarket surveillance requirements and mechanisms in the United States and the European Union. Each of these jurisdictions has its own challenges in keeping the regulations up to date with technological developments. A specific area of attention is that of laboratory-developed tests in the United States and health institution in-house-produced tests in the European Union, for which the United States and the European Union have markedly different regulatory approaches. Both jurisdictions have specific but differing requirements for the use of test samples and test-related data under their rules regarding the protection of (personal) health data, which can cause complexity when moving samples or sample-related data from one jurisdiction to the other.
Topics: European Union; Humans; Pathology, Molecular; Proteomics; United States; United States Food and Drug Administration
PubMed: 36044907
DOI: 10.1146/annurev-genom-121521-010416 -
EBioMedicine Nov 2021To reduce the high incidence and mortality of gastric cancer (GC), we aimed to develop deep learning-based models to assist in predicting the diagnosis and overall...
BACKGROUND
To reduce the high incidence and mortality of gastric cancer (GC), we aimed to develop deep learning-based models to assist in predicting the diagnosis and overall survival (OS) of GC patients using pathological images.
METHODS
2333 hematoxylin and eosin-stained pathological pictures of 1037 GC patients were collected from two cohorts to develop our algorithms, Renmin Hospital of Wuhan University (RHWU) and the Cancer Genome Atlas (TCGA). Additionally, we gained 175 digital pictures of 91 GC patients from National Human Genetic Resources Sharing Service Platform (NHGRP), served as the independent external validation set. Two models were developed using artificial intelligence (AI), one named GastroMIL for diagnosing GC, and the other named MIL-GC for predicting outcome of GC.
FINDINGS
The discriminatory power of GastroMIL achieved accuracy 0.920 in the external validation set, superior to that of the junior pathologist and comparable to that of expert pathologists. In the prognostic model, C-indices for survival prediction of internal and external validation sets were 0.671 and 0.657, respectively. Moreover, the risk score output by MIL-GC in the external validation set was proved to be a strong predictor of OS both in the univariate (HR = 2.414, P < 0.0001) and multivariable (HR = 1.803, P = 0.043) analyses. The predicting process is available at an online website (https://baigao.github.io/Pathologic-Prognostic-Analysis/).
INTERPRETATION
Our study developed AI models and contributed to predicting precise diagnosis and prognosis of GC patients, which will offer assistance to choose appropriate treatment to improve the survival status of GC patients.
FUNDING
Not applicable.
Topics: Algorithms; Area Under Curve; Biomarkers, Tumor; Deep Learning; Female; Humans; Image Processing, Computer-Assisted; Immunohistochemistry; Male; Neoplasm Grading; Neoplasm Staging; Pathology, Molecular; ROC Curve; Retrospective Studies; Stomach Neoplasms
PubMed: 34678610
DOI: 10.1016/j.ebiom.2021.103631 -
American Journal of Transplantation :... Apr 2022
Topics: Allografts; Bronchiolitis Obliterans; Graft Rejection; Humans; Lung; Lung Transplantation; Pathology, Molecular
PubMed: 34910363
DOI: 10.1111/ajt.16925 -
International Journal of Molecular... Mar 2023Molecular pathology, diagnostics and therapeutics are three closely related topics of critical importance in medical research and clinical practice [...].
Molecular pathology, diagnostics and therapeutics are three closely related topics of critical importance in medical research and clinical practice [...].
Topics: Pathology, Molecular
PubMed: 36902493
DOI: 10.3390/ijms24055063 -
Archives of Pathology & Laboratory... Aug 2022Next-generation sequencing studies are increasingly used in the evaluation of suspected chronic myeloid neoplasms (CMNs), but there is wide variability among...
CONTEXT.—
Next-generation sequencing studies are increasingly used in the evaluation of suspected chronic myeloid neoplasms (CMNs), but there is wide variability among laboratories in the genes analyzed for this purpose. Recently, the Association for Molecular Pathology CMN working group recommended a core 34-gene set as a minimum target list for evaluation of CMNs. This list was recommended based on literature review, and its diagnostic yield in clinical practice is unknown.
OBJECTIVE.—
To determine the diagnostic yield of the core 34 genes and assess the potential impact of including selected additional genes.
DESIGN.—
We retrospectively reviewed 185 patients with known or suspected CMNs tested using a 62-gene next-generation sequencing panel that included all 34 core genes.
RESULTS.—
The Association for Molecular Pathology's core 34 genes had a diagnostic yield of 158 of 185 (85.4%) to detect at least 1 variant with strong/potential clinical significance and 107 of 185 (57.8%) to detect at least 2 such variants. The 62-gene panel had a diagnostic yield of 160 of 185 (86.5%) and 112 of 185 (60.5%), respectively. Variants of unknown significance were identified in 49 of 185 (26.5%) using the core 34 genes versus 76 of 185 (41.1%) using the 62-gene panel.
CONCLUSIONS.—
This study demonstrates that the Association for Molecular Pathology-recommended core 34-gene set has a high diagnostic yield in CMNs. Inclusion of selected additional genes slightly increases the rate of abnormal results, while also increasing the detection of variants of unknown significance. We recommend inclusion of CUX1, DDX41, ETNK1, RIT1, and SUZ12 in addition to the Association for Molecular Pathology's 34-gene core set for routine evaluation of CMNs.
Topics: High-Throughput Nucleotide Sequencing; Humans; Mutation; Myeloproliferative Disorders; Pathology, Molecular; Retrospective Studies
PubMed: 34784413
DOI: 10.5858/arpa.2021-0124-OA -
Pathobiology : Journal of... 2019The updated 2016 WHO classification of hematopoietic tumors has a new category: "myeloid neoplasms with germline predisposition." These entities are rare, but are also... (Review)
Review
The updated 2016 WHO classification of hematopoietic tumors has a new category: "myeloid neoplasms with germline predisposition." These entities are rare, but are also currently underdiagnosed and underreported. Recognition is critical for appropriate clinical evaluation and therapy, with potential implications for the patient's entire family. The WHO includes 3 categories of myeloid neoplasms with germline predisposition: neoplasms without preexisting conditions, neoplasms with a history of thrombocytopenia, and neoplasms with other organ dysfunction. Specialized molecular testing is frequently necessary to make the diagnosis, as the presence of one of the implicated mutations is not sufficient for diagnosis and should be confirmed with germline DNA evaluation. Many families have unique mutations that are not detected by targeted sequencing panels. Periodic bone marrow (BM) examinations are recommended to assess patients' baseline morphology and rule out evidence of disease progression. Thus, accurate diagnosis requires a careful recording of clinical history, a BM morphology evaluation, and advanced molecular testing.
Topics: Bone Marrow Examination; Genetic Predisposition to Disease; Genotype; Germ-Line Mutation; Humans; Mutation; Myeloproliferative Disorders; Pathology, Molecular
PubMed: 30048985
DOI: 10.1159/000490311 -
The American Journal of Pathology Jul 2019The past decade has witnessed exponential growth in the generation of high-throughput human data across almost all known dimensions of biological systems. The discipline... (Review)
Review
The past decade has witnessed exponential growth in the generation of high-throughput human data across almost all known dimensions of biological systems. The discipline of network medicine has rapidly evolved in parallel, providing an unbiased, comprehensive biological framework through which to interrogate and integrate systematically these large-scale, multi-omic data to enhance our understanding of disease mechanisms and to design drugs that reflect a deep knowledge of molecular pathobiology. In this review, we discuss the key principles of network medicine and the human disease network and explore the latest applications of network medicine in this multi-omic era. We also highlight the current conceptual and technological challenges, which serve as exciting opportunities by which to improve and expand the network-based applications beyond the artificial boundaries of the current state of human pathobiology.
Topics: Humans; Pathology, Clinical; Pathology, Molecular
PubMed: 31014954
DOI: 10.1016/j.ajpath.2019.03.009 -
Cells Sep 2022Pancreatic ductal adenocarcinoma (PDAC) has an extremely poor prognosis due to the lack of methods or biomarkers for early diagnosis and its resistance to conventional... (Review)
Review
Pancreatic ductal adenocarcinoma (PDAC) has an extremely poor prognosis due to the lack of methods or biomarkers for early diagnosis and its resistance to conventional treatment modalities, targeted therapies, and immunotherapies. PDACs are a heterogenous group of malignant epithelial neoplasms with various histomorphological patterns and complex, heterogenous genetic/molecular landscapes. The newly proposed molecular classifications of PDAC based on extensive genomic, transcriptomic, proteomic and epigenetic data have provided significant insights into the molecular heterogeneity and aggressive biology of this deadly disease. Recent studies characterizing the tumor microenvironment (TME) have shed light on the dynamic interplays between the tumor cells and the immunosuppressive TME of PDAC, which is essential to disease progression, as well as its resistance to chemotherapy, newly developed targeted therapy and immunotherapy. There is a critical need for the development of predictive markers that can be clinically utilized to select effective personalized therapies for PDAC patients. In this review, we provide an overview of the histological and molecular heterogeneity and subtypes of PDAC, as well as its precursor lesions, immunosuppressive TME, and currently available predictive molecular markers for patients.
Topics: Biomarkers; Carcinoma, Pancreatic Ductal; Humans; Pancreatic Neoplasms; Pathology, Molecular; Proteomics; Tumor Microenvironment
PubMed: 36231030
DOI: 10.3390/cells11193068