PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “clinical genomics”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources
PubMed2006

Epidemiological studies in the information and genomics era: experience of the Clinical Genome of Cancer Project in São Paulo, Brazil.

Genomics is expanding the horizons of epidemiology, providing a new dimension for classical epidemiological studies and inspiring the development of large-scale multicenter studies with the statistical power necessary for the assessment of gene-gene and gene-environment interactions in cancer etiology and prognosis. This paper describes the methodology of the Clinical Genome of Cancer Project in São Paulo, Brazil (CGCP), which includes patients with nine types of tumors and controls. Three major epidemiological designs were used to reach specific objectives: cross-sectional studies to examine gene expression, case-control studies to evaluate etiological factors, and follow-up studies to analyze genetic profiles in prognosis. The clinical groups included patients' data in the electronic database through the Internet. Two approaches were used for data quality control: continuous data evaluation and data entry consistency. A total of 1749 cases and 1509 controls were entered into the CGCP database from the first trimester of 2002 to the end of 2004. Continuous evaluation showed that, for all tumors taken together, only 0.5% of the general form fields still included potential inconsistencies by the end of 2004. Regarding data entry consistency, the highest percentage of errors (11.8%) was observed for the follow-up form, followed by 6.7% for the clinical form, 4.0% for the general form, and only 1.1% for the pathology form. Good data quality is required for their transformation into useful information for clinical application and for preventive measures. The use of the Internet for communication among researchers and for data entry is perhaps the most innovative feature of the CGCP. The monitoring of patients' data guaranteed their quality.

Adult↗
PubMed2025

Efficacy of EGFR tyrosine kinase inhibitors in patients with non-small cell lung cancer with EGFR exon 19 insertions: clinical-genomic, preclinical analysis through LC-SCRUM-Asia (multi-institutional genomic screening registry).

BACKGROUND: EGFR exon 19 insertions (EGFRex19ins) are rare EGFR mutations. Their clinical-genomic characteristics and outcomes with EGFR-tyrosine kinase inhibitors (TKIs) remain uncertain. METHODS: We evaluated the clinical-genomic characteristics and outcomes of EGFR-TKIs for EGFRex19ins in the multi-institutional prospective lung cancer genomic screening project (LC-SCRUM-Asia). We also studied preclinical Ba/F3 models expressing EGFR-K745_E746insIPVAIK (Ba/F3-IPVAIK) to investigate their sensitivity to 1st-, 2nd-, 3rd-generation, and EGFR exon 20 insertion-active TKIs. RESULTS: In LC-SCRUM-Asia, 16,204 NSCLC patients were enrolled from March 2015 to December 2023. EGFRex19ins were detected in 13 samples (0.1 % of NSCLC). The median age was 72 years (range, 38-80); most patients were female (77 %), had adenocarcinoma (92 %), and were never-smokers (62 %). Twelve patients (93 %) had EGFR-K745_E746insIPVAIK, while one (7 %) had EGFR-K745_E746insVPVAIK. The most frequent co-mutation was TP53 (62 %); no patients had other driver alterations. Six patients (46 %) tested positive for EGFR exon 19 deletions with PCR-based Cobas EGFR test, likely due to cross-reactivity arising from sequence homology. Twelve patients received EGFR-TKIs; five (42 %) experienced partial response. In the preclinical study, Ba/F3-IPVAIK showed the highest sensitivity to 2nd-generation EGFR-TKIs compared to other EGFR-TKIs. Structural studies supported these consistent results. When broken down by EGFR-TKI generations, response rates for 1st-, 2nd-, and 3rd-generation TKIs were 50 % (1/2), 80 % (4/5), and 0 % (0/5), respectively. The median PFS for 1st-, 2nd-, and 3rd-generation TKIs were 8.7 (95 % CI, 7.4-NR), 14.7 (95 % CI, 8.0-NR), and 4.4 (95 % CI, 3.4-NR) months, respectively. CONCLUSION: Our preclinical, structural, and clinical findings indicate 2nd-generation EGFR-TKIs are more effective for EGFRex19ins compared to other TKIs.

Adult↗
PubMed2004

Organizational challenges in clinical genomic research.

Genome sequence data are enabling clinical genomic investigation, in which the characteristics of human patients are explored using comprehensive inventories of biomolecules. Successful investigators must navigate rapid technological change, collect and analyse large volumes of data, and engage systems of clinical care. Such projects will increasingly rely on fully integrated multidisciplinary teams, demanding new organizational models in academic biomedical research.

Academies and Institutes↗
PubMed2002

An integrative model for in-silico clinical-genomics discovery science.

Human Genome discovery research has set the pace for Post-Genomic Discovery Research. While post-genomic fields focused at the molecular level are intensively pursued, little effort is being deployed in the later stages of molecular medicine discovery research, such as clinical-genomics. The objective of this study is to demonstrate the relevance and significance of integrating mainstream clinical informatics decision support systems to current bioinformatics genomic discovery science. This paper is a feasibility study of an original model enabling novel "in-silico" clinical-genomic discovery science and that demonstrates its feasibility. This model is designed to mediate queries among clinical and genomic knowledge bases with relevant bioinformatic analytic tools (e.g. gene clustering). Briefly, trait-disease-gene relationships were successfully illustrated using QMR, OMIM, SNOMED-RT, GeneCluster and TreeView. The analyses were visualized as two-dimensional dendrograms of clinical observations clustered around genes. To our knowledge, this is the first study using knowledge bases of clinical decision support systems for genomic discovery. Although this study is a proof of principle, it provides a framework for the development of clinical decision-support-system driven, high-throughput clinical-genomic technologies which could potentially unveil significant high-level functions of genes.

Artificial Intelligence↗
PubMed2026

TargetQC: A targeted quality control framework for clinical genomic testing.

Reliable genetic testing depends on accurate assessment of sequencing quality in clinically relevant genomic regions that directly influence variant interpretation. We developed TargetQC, a flexible quality control framework that supports user-defined gene sets, coverage thresholds, and variant sets for evaluating sequencing performance across exome sequencing (ES) and genome sequencing (GS) platforms. TargetQC assesses exon and gene coverage, identifies regions meeting predefined coverage thresholds, evaluates variant detection accuracy, and measures sequencing quality at pathogenic variant sites. We applied TargetQC to the reference sample NA12878 and 665 clinical samples across five ES platforms and one GS platform. ES-VendorB and ES-VendorE achieved the most complete coverage of OMIM coding regions in NA12878, whereas ES-VendorD and ES-VendorE showed the highest coverage compliance in clinical samples. ES-VendorB and GS demonstrated the highest variant detection accuracy. TargetQC provides a practical framework for benchmarking sequencing performance and informing platform selection in clinical genomics.

exome sequencing↗
PubMed2026

Examining gaps in institutional policies for clinical genomic data sharing: A cross-jurisdictional study.

The sharing of data generated by clinical genetic and genomic testing without explicit consent is important for timely diagnosis and treatment. While many jurisdictions permit the sharing of identifiable data for direct clinical care, institutional policies vary in how clearly they specify key elements, including when sharing is permitted, what data are covered, and what safeguards apply. Greater clarity around these elements may support responsible data sharing while balancing timely care with transparency and appropriate protections. We conducted a mixed-methods content analysis of data-sharing and privacy policies from 33 clinical genomic institutions across 17 countries and regions. Using a predefined analytical framework, we assessed how policies document key governance elements relevant to sharing without explicit consent. Two independent reviewers extracted information about clinical contexts, data types, justifications, and protections. Although 70% of institutions described circumstances permitting data sharing without explicit consent, most policies did not clearly define the scope or governance of such sharing. Policies also rarely distinguished clinical from research or secondary use and inconsistently specified privacy and security safeguards. While sharing was commonly justified for clinical care (78.3%) or testing services (43.5%), data recipient roles and onward-sharing expectations were often left undefined. This uneven documentation could make it difficult for clinical teams and institutional decision-makers to identify and justify decisions about what is permitted and under what conditions. A guidance framework specifying core governance elements and corresponding protections could help institutions communicate their governance choices more clearly and support comparable baseline practices for responsible data sharing.

Information Dissemination↗
PubMed2004

Post-genomic applications of tissue microarrays: basic research, prognostic oncology, clinical genomics and drug discovery.

Tissue microarrays (TMAs) are an ordered array of tissue cores on a glass slide. They permit immunohistochemical analysis of numerous tissue sections under identical experimental conditions. The arrays can contain samples of every organ in the human body, or a wide variety of common tumors and obscure clinical cases alongside normal controls. The arrays can also contain pellets of cultured tumor cell lines. These arrays may be used like any histological section for immunohistochemistry and in situ hybridization to detect protein and gene expression. This new technology will allow investigators to analyze numerous biomarkers over essentially identical samples, develop novel prognostic markers and validate potential drug targets. The ability to combine TMA technology with DNA microarrays and proteomics makes it a very attractive tool for analysis of gene expression in clinically stratified tumor specimens and relate expression of each particular protein with clinical outcome. Public domain software allows researchers to examine digital images of individual histological specimens from TMAs, evaluate and score them and store the quantitative data in a relational database. TMA technology may be specifically applied to the profiling of proteins of interest in other pathophysiological conditions such as congestive heart failure, renal disease, hypertension, diabetes, cystic fibrosis and neurodegenerative disorders. This review is intended to summarize the strengths and weaknesses of TMA technology which will have an increasingly important role in the laboratories of the post-genomic era.

Animals↗
PubMed2024

Deep-Learning Model for Tumor-Type Prediction Using Targeted Clinical Genomic Sequencing Data.

UNLABELLED: Tumor type guides clinical treatment decisions in cancer, but histology-based diagnosis remains challenging. Genomic alterations are highly diagnostic of tumor type, and tumor-type classifiers trained on genomic features have been explored, but the most accurate methods are not clinically feasible, relying on features derived from whole-genome sequencing (WGS), or predicting across limited cancer types. We use genomic features from a data set of 39,787 solid tumors sequenced using a clinically targeted cancer gene panel to develop Genome-Derived-Diagnosis Ensemble (GDD-ENS): a hyperparameter ensemble for classifying tumor type using deep neural networks. GDD-ENS achieves 93% accuracy for high-confidence predictions across 38 cancer types, rivaling the performance of WGS-based methods. GDD-ENS can also guide diagnoses of rare type and cancers of unknown primary and incorporate patient-specific clinical information for improved predictions. Overall, integrating GDD-ENS into prospective clinical sequencing workflows could provide clinically relevant tumor-type predictions to guide treatment decisions in real time. SIGNIFICANCE: We describe a highly accurate tumor-type prediction model, designed specifically for clinical implementation. Our model relies only on widely used cancer gene panel sequencing data, predicts across 38 distinct cancer types, and supports integration of patient-specific nongenomic information for enhanced decision support in challenging diagnostic situations. See related commentary by Garg, p. 906. This article is featured in Selected Articles from This Issue, p. 897.

Humans↗
PubMed2026

Assessing the readiness of Oxford Nanopore sequencing for clinical genomics applications.

Long-read sequencing (LRS) technologies, namely, Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio), have emerged as promising solutions to overcome the limitations of short-read sequencing (SRS). Nevertheless, the still higher sequencing error rates compared with SRS, need for customized pipelines, rapidly updating software, and incipient scalability continue to present challenges for adopting ONT in standard clinical practice. Here we assess the performance of ONT (R9 and R10 chemistries) in comparison to Illumina and MGI across 17 well-characterized reference samples with 11 clinical variants representing nine different genetic diseases. To enable this, we have implemented a production-ready pipeline including SNV, indel, STR, SV, and CNV detection, alongside reporting key summary metrics to ensure high-quality data at the production sequencing level. Our results show high accuracy of ONT across SNVs (F-score 0.978-0.983) and SVs (F-score = 0.75) but still weaknesses across indels (F-score 0.659-0.758). However, we highlight that ONT accurately detected all four pathogenic indels as well as the performance improvement in exons and with the newer R10 chemistry. We further demonstrated the importance of long reads to detect clinically impactful variants such as a FMR1 pathogenic expansion, often misclassified by SRS as being in the premutation range. Our multiplatform analysis and Sanger validation uncovered a 1 bp error in the Coriell annotation for a cystic fibrosis-causing indel in GM07829. This work underscores the growing readiness of ONT for clinical applications, highlighting both its advancements and its potential for broader adoption in clinical genomics and large-scale operations.

Humans↗
PubMed2025

An Integrated Clinical Genomic and Transcriptomic Subgrouping of Central Chondrosarcoma.

Central conventional chondrosarcoma, a malignant cartilage-producing bone tumor, is the second most common bone sarcoma. Chondrosarcomas are histologically graded, which is so far the best predictor of survival. Early mutations in isocitrate dehydrogenase 1 (IDH1) and IDH2 genes are frequent, leading to the production of the oncometabolite D-2-hydroxyglutarate, which affects DNA methylation, resulting in a preferred chondrogenic differentiation over osteogenic differentiation of mesenchymal stem cells, which are currently considered the precursor cells of chondrosarcoma. DNA methylation profiling has previously revealed distinct profiles between IDH-mutant and IDH-wild-type chondrosarcomas, but the presence of further DNA methylation subgroups indicates that classification based solely on IDH status is too simplistic. In this study, we aim to identify biological subgroups in a total of 116 chondrosarcomas by integrating clinical data, IDH mutation status, gene expression, and genome-wide loss of heterozygosity (LOH). Clinical associations were observed between several factors, including sex and histological grade, as well as tumor site and IDH mutation status. RNA sequencing and genome-wide LOH confirmed the distinction between IDH-wild-type and IDH-mutant chondrosarcomas, where the number of chromosome arms affected by LOH was significantly higher in IDH-wild-type tumors than in IDH-mutant tumors. However, no clear subgroups emerged within each IDH group. Further clustering on RNA expression of differentiation markers identified subgroups characterized by chondrogenic, osteogenic, resting chondrocyte, or dedifferentiated profiles. These different subgroups showed a specific clinical presentation and suggest different precursor cells. Instead of a simple dichotomy between IDH-mutant and IDH-wild-type, our integrated approach highlights interconnected clinical, genomic, and transcriptomic patterns that offer a more nuanced view of chondrosarcoma biology and might potentially guide treatment stratification.

Humans↗
PubMed2005

The Genome Health Clinic and Genome Health Nutrigenomics concepts: diagnosis and nutritional treatment of genome and epigenome damage on an individual basis.

The evidence of a direct link between increased genome/epigenome damage and elevated risk for adverse health outcomes during the various stages of life, such as infertility, foetal development and cancer is becoming increasingly stronger. The latter is briefly reviewed against a background of evidence indicating that genome and epigenome damage biomarkers, in the absence of overt exposure of genotoxins, are themselves sensitive indicators of deficiency in micronutrients required as cofactors or as components of DNA repair enzymes, for maintenance methylation of CpG sequences and prevention of DNA oxidation and/or uracil incorporation into DNA. The latter is illustrated with cross-sectional and dietary intervention data obtained using the micronucleus assay and other efficient biomarkers for diagnosing genome and/or epigenome instability. The concept of recommended dietary allowances for genome stability and how this could be achieved is discussed. The 'Genome Health Nutrigenomics' concept is also introduced to define and focus attention on the specialized research area of how diet impacts on genome stability and how genotype determines nutritional requirements for genome health maintenance. The review concludes with a vision for a paradigm shift in disease prevention strategy based on the diagnosis and nutritional treatment of genome/epigenome damage on an individual basis, i.e. The Genome Health Clinic.

Concept Formation↗
PubMed2006

Clinical genomics data standards for pharmacogenetics and pharmacogenomics.

This special report concerns a talk on data standards given at a workshop entitled 'An International Perspective on Pharmacogenetics: The Intersections between Innovation, Regulation and Health Delivery', which was held by the Organization for Economic Co-operation and Development (OECD) on October 17-19, 2005, in Rome, Italy. The worlds of healthcare and life sciences (HCLS) are extremely fragmented in terms of their underlying information technology, making it difficult to semantically exchange information between disparate entities. While we have reached the point where functional interoperability is ubiquitous, we are still far from achieving true semantic interoperability where a receiving system can use incoming data as though it was created internally. The critical enablers of semantic interoperability are information standards dedicated to HCLS data, spanning all the way from biological research data to clinical research and clinical trials, and finally to healthcare clinical data. The challenge lies in integrating various data standards based on predetermined goals, thereby improving the quality of care provided to patients.

Clinical Medicine↗
PubMed1999

Functional genomics: clinical effect and the evolving role of the surgeon.

The genetic and molecular revolution that has occurred over the last 2 decades has dramatically increased our understanding of basic disease processes and will undoubtedly lead to improved detection methods and treatment. This will occur at an even more rapid rate after the completion of the Human Genome Project in the next 2 to 3 years. While these remarkable technological advances offer great hopes for novel therapeutic modalities, complicated medical, ethical, and legal issues will need to be addressed. This article briefly describes the advances that have occurred and their future ramifications for the field of surgery. Most assuredly, we will all be affected by these changes. Surgeons have the opportunity to be active participants and real leaders in the research and complex decisions regarding the optimal treatment of patients. However, formal training in these techniques and their potential applications will be required. Surgeons, as well as all physicians, must rise to the occasion or, otherwise, we will be relegated to a bystander status with clinical and moral decisions being made by nonclinicians.

Ethics, Medical↗
PubMed1999

Mutations of the mitochondrial genome: clinical overview and possible pathophysiology of cell damage.

Mitochondria possess their own DNA and transcription and translation machinery for the synthesis of 13 protein subunits for the oxidative phosphorylation system, two rRNAs and 22 tRNAs. In 1988 the first human neurodegenerative diseases associated with mutations in the mitochondrial genome were described. The most recent biochemical and genetic research suggests that mitochondrial disorders are best categorized as: (i) primary mutations of the mitochondrial DNA, either sporadic or maternally inherited; (ii) nuclear mutations that result in alterations in mitochondrial DNA or intergenomic signalling defects; or (iii) Mendelian defects that affect the respiratory chain in the absence of mitochondrial DNA mutations. There is still little information about the pathophysiology of these different disorders. In order to obtain some insight into the cellular mechanisms of neurodegeneration, we examined cultured fibroblasts from patients with the MELAS (mitochondrial encephalopathy, lactic acidosis and stroke-like episodes) syndrome, which is most frequently caused by a mutation in the mitochondrial tRNA for leucine. We found that their basal level of ionized calcium was elevated and that they could not normally sequester calcium influxes induced by depolarization. In addition, they were unable to maintain normal mitochondrial membrane potentials, as determined using a voltage-sensitive fluorescent indicator. Despite these physiological perturbations, the MELAS fibroblasts had normal concentrations of ATP. If neurons in MELAS patients have similar physiological abnormalities, their functional properties and long-term viability may be compromised.

DNA, Mitochondrial↗
PubMed2006

Hereditary spastic paraplegia: clinical genomics and pharmacogenetic perspectives.

Hereditary spastic paraplegias (HSPs) are a group of single-gene disorders characterised by degeneration of the corticospinal tract axons, leading to bilateral, symmetrical, slowly-progressive spastic paraparesis, predominantly of the lower extremities. So far, ~ 30 different chromosomal HSP loci have been identified by genetic linkage analysis. Defects in intracellular trafficking and transport in myelination and abnormalities of mitochondrial proteins have been involved in HSP pathogenesis. At present, treatment of the HSPs is primarily directed symptomatically toward reducing muscle spasticity. Yet, recent progresses in the identification of HSP mutations are providing formidable tools to pharmacogenetic approaches of drug discovery, validation and prediction of individual response.

Baclofen↗
PubMed2026

Integrating clinical and genomic features to predict response to neoadjuvant therapy in microsatellite-stable rectal cancer.

BACKGROUND: Neoadjuvant therapy (NAT) has shifted rectal cancer management toward organ preservation. However, achieving a complete response (CR) for "watch-and-wait" strategies is hindered by high response heterogeneity. Although immunotherapy-combined NAT has expanded the candidate pools, the predictive significance of molecular alterations remains unclear. OBJECTIVES: This study aimed to evaluate clinical and genomic profiles of rectal cancer patients undergoing NAT to identify response predictors and to develop a nomogram for estimating CR probability. DESIGN: Retrospective, single-center cohort study. METHODS: This study included 437 patients with rectal adenocarcinoma at Fudan University Shanghai Cancer Center between December 2019 and March 2023. Patients underwent paired tumor and germline genomic sequencing (887-gene panel) before NAT. Logistic and Cox regression analyses were performed to identify clinical and genetic risk factors associated with tumor response and long-term survival. RESULTS: Of the 437 patients, 96.6% had microsatellite-stable (MSS) tumors. In the MSS locally advanced rectal cancer cohort (N = 307), the CR rate was 35.5%. Multivariate analysis identified immunotherapy-combined NAT (iTNT) (OR 4.41, 95% CI: 2.42-8.27), SYNE1 mutation (OR 2.12, 95% CI: 1.06-4.26), negative mesorectal fascia (MRF) status (OR 0.34, 95% CI: 0.17-0.66), and lower tumor location (OR 0.48, 95% CI: 0.27-0.84) as independent predictors of CR. KRAS mutation was the sole independent predictor of reduced disease-free survival (DFS; HR 1.93, 95% CI: (1.11-3.36), p = 0.020). KRAS G12D subtype was associated with the worst 2-year distant metastasis-free survival (71.3%) and exhibited a distinct predilection for lung metastasis. The clinical-genomic nomogram yielded strong discrimination (AUC = 0.705) and calibration, with favorable DCA net benefit. CONCLUSION: Clinical and genomic features jointly determine outcomes in MSS rectal cancer. SYNE1 mutation serves as a novel biomarker for CR, while KRAS mutations, especially the G12D subtype, identify patients at high risk for systemic relapse. The clinical-genomic nomogram facilitates individualized selection for organ-preservation strategies.

biomarker↗