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Results for “molecular profiling”

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PubMed2026

Plasma proteomic profiling of septic shock and acute pancreatitis identifies shared signatures and disease-specific pathways.

Septic shock represents the most severe form of infection-driven systemic inflammation, whereas acute pancreatitis induces a sterile inflammatory response. Although clinically similar, their molecular profiles may reveal distinct mechanisms underlying infectious and non-infectious inflammation. We performed plasma proteomic profiling using LC-MS/MS in patients with septic shock (n = 13), acute pancreatitis (n = 8), and healthy controls (n = 8). Among 663 quantified proteins, 231 were differentially expressed in septic shock versus controls, 83 in pancreatitis versus controls, and 29 in septic shock versus pancreatitis. Septic shock was characterized by higher plasma concentrations of MARCKS, HSP90AA1, PSAP, CD163, and GANAB, whereas pancreatitis showed higher levels of CPA1, APOC4, APOC3, BPGM, and APOC2. Cluster analysis demonstrated separation between groups, with overlapping proteomic patterns in sepsis and pancreatitis. Gene Ontology and KEGG analyses revealed shared inflammatory signatures, including upregulation of acute-phase responses and downregulation of coagulation pathways. However, septic shock exhibited more extensive proteomic alterations, with distinct activation of PI3K-Akt signaling and suppression of lipid metabolism. In conclusion, septic shock and pancreatitis share common inflammatory pathways, while proteomic differences highlight divergent regulation of coagulation, lipid metabolism, and anti-inflammatory signaling, offering potential biomarkers to distinguish infectious from sterile systemic inflammation.

Shock, Septic↗

PubMed2006

Protein analysis in human cerebrospinal fluid: Physiological aspects, current progress and future challenges.

The introduction of lumbar puncture into clinical medicine over 100 years ago marks the beginning of the study of central nervous system diseases using the human cerebrospinal fluid (CSF). Ever since, CSF has been analyzed extensively to elucidate the physiological and biochemical bases of neurological disease. The proximity of CSF to the brain makes it a good target for studying the pathophysiology of brain functions, but the barrier function of the CSF also impedes its diagnostic value. Today, measurements to determine alterations in the composition of CSF are central in the differential diagnosis of specific diseases of the central nervous system (CNS). In particular, the analysis of the CSF protein composition provides crucial information in the diagnosis of CNS diseases. This enables the assessment of the physiology of the blood-CSF barrier and of the immunology of intrathecial responses. Besides those routine measurements, protein compositional studies of CSF have been extended recently to many other proteins in the expectation that comprehensive analysis of lower abundance CSF proteins will lead to the discovery of new disease markers. Disease marker discovery by molecular profiling of the CSF tissue has the enormous potential of providing many new disease relevant molecules. New developments in protein profiling techniques hold promise for the discovery and validation of relevant disease markers. In this review, we summarize the current efforts and progress in CSF protein profiling measurements using conventional and current protein analysis tools. We also discuss necessary development in methodology in order to have the highest impact on the study of the molecular composition of CSF proteins.

Brain↗

PubMed2026

Case Report: Pancreatic amphicrine-like carcinoma with acinar differentiation harboring a KANK4-RAF1 gene fusion.

Pancreatic amphicrine-like carcinoma (ALC) is an exceptionally rare neoplasm characterized by simultaneous exocrine and endocrine differentiation within the same tumour cells. These tumours represent a diagnostic challenge because they must be distinguished from mixed neuroendocrine-non-neuroendocrine neoplasms (MiNENs), which consist of morphologically distinct tumour components. We report a case of pancreatic ALC with acinar differentiation harboring a KANK4::RAF1 fusion identified by comprehensive genomic profiling. Histologically, the tumour demonstrated acinar differentiation with expression of trypsin and BCL10 together with neuroendocrine differentiation characterized by synaptophysin and INSM1 expression within the same neoplastic population. Molecular analysis revealed a RAF1 rearrangement, a potentially actionable alteration previously described in a subset of pancreatic acinar carcinomas. The patient showed rapid disease progression despite systemic chemotherapy. Treatment with the MEK inhibitor trametinib was initiated based on the presence of a RAF1 fusion but was discontinued after 1 month because of toxicity, preventing assessment of therapeutic efficacy. This case expands the molecular spectrum of pancreatic ALC with acinar differentiation and highlights the importance of comprehensive molecular profiling in rare pancreatic neoplasms to identify potentially actionable genomic alterations.

Humans↗

PubMed2006

The use of genetic programming in the analysis of quantitative gene expression profiles for identification of nodal status in bladder cancer.

BACKGROUND: Previous studies on bladder cancer have shown nodal involvement to be an independent indicator of prognosis and survival. This study aimed at developing an objective method for detection of nodal metastasis from molecular profiles of primary urothelial carcinoma tissues. METHODS: The study included primary bladder tumor tissues from 60 patients across different stages and 5 control tissues of normal urothelium. The entire cohort was divided into training and validation sets comprised of node positive and node negative subjects. Quantitative expression profiling was performed for a panel of 70 genes using standardized competitive RT-PCR and the expression values of the training set samples were run through an iterative machine learning process called genetic programming that employed an N-fold cross validation technique to generate classifier rules of limited complexity. These were then used in a voting algorithm to classify the validation set samples into those associated with or without nodal metastasis. RESULTS: The generated classifier rules using 70 genes demonstrated 81% accuracy on the validation set when compared to the pathological nodal status. The rules showed a strong predilection for ICAM1, MAP2K6 and KDR resulting in gene expression motifs that cumulatively suggested a pattern ICAM1 > MAP2K6 > KDR for node positive cases. Additionally, the motifs showed CDK8 to be lower relative to ICAM1, and ANXA5 to be relatively high by itself in node positive tumors. Rules generated using only ICAM1, MAP2K6 and KDR were comparably robust, with a single representative rule producing an accuracy of 90% when used by itself on the validation set, suggesting a crucial role for these genes in nodal metastasis. CONCLUSION: Our study demonstrates the use of standardized quantitative gene expression values from primary bladder tumor tissues as inputs in a genetic programming system to generate classifier rules for determining the nodal status. Our method also suggests the involvement of ICAM1, MAP2K6, KDR, CDK8 and ANXA5 in unique mathematical combinations in the progression towards nodal positivity. Further studies are needed to identify more class-specific signatures and confirm the role of these genes in the evolution of nodal metastasis in bladder cancer.

Algorithms↗

PubMed2003

Tissue microarray study for classification of breast tumors.

Clinical and pathological heterogeneity of breast cancer hinders selection of appropriate treatment for individual cases. Molecular profiling at gene or protein levels may elucidate the biological variance of tumors and provide a new classification system that correlates better with biological, clinical and prognostic parameters. We studied the immunohistochemical profile of a panel of seven important biomarkers using tumor tissue arrays. The tumor samples were then classified with a monothetic (binary variables) clustering algorithm. Two distinct groups of tumors are characterized by the estrogen receptor (ER) status and tumor grade (p = 0.0026). Four biomarkers, c-erbB2, Cox-2, p53 and VEGF, were significantly overexpressed in tumors with the ER-negative (ER-) phenotype. Eight subsets of tumors were further identified according to the expression status of VEGF, c-erbB2 and p53. The malignant potential of the ER-/VEGF+ subgroup was associated with the strong correlations of Cox-2 and c-erbB2 with VEGF. Our results indicate that this molecular classification system, based on the statistical analysis of immunohistochemical profiling, is a useful approach for tumor grouping. Some of these subgroups have a relative genetic homogeneity that may allow further study of specific genetically-controlled metabolic pathways. This approach may hold great promise in rationalizing the application of different therapeutic strategies for different subgroups of breast tumors.

Algorithms↗

PubMed1985

Immunoreactive parathyroid hormone and calcitonin in plasma and ultrafiltrate before and after haemodialysis.

The effects of haemodialysis on circulating immunoreactive parathyroid hormone (iPTH) and calcitonin (iCT) were determined in relation to alterations in total (Ca) and ionized (Ca2+) plasma calcium. The hormones were measured in plasma, in dialysate and in ultrafiltrate in eight patients with elevated iPTH concentrations. There was a small, but significant reduction in plasma iPTH during haemodialysis concomitant with an increase in Ca and Ca2+. Only small changes were found in plasma iCT during dialysis. Ultrafiltrate iPTH concentrations were reduced from 46% of plasma values at the beginning of dialysis to 27% of plasma values at the end of 4 h dialysis. Gel chromatography of plasma and ultrafiltrate showed corresponding molecular profiles of intact iPTH and hormone fragments suggesting that none of the PTH peptides were restricted by the dialysis membrane. Clearance of intact iPTH (dialysance) was as expected according to molecular weight. From the PTH clearance we calculated that only 5 to 10 micrograms of intact hormone were removed during dialysis. We therefore conclude that the reduction in plasma iPTH during dialysis is probably related to a relative suppression of PTH secretion rather than due to loss of hormone during dialysis.

Adult↗

PubMed2003

Linking laboratory and clinical research: the development of molecularly targeted therapeutics inside the national cancer institute center for cancer research.

Understanding the molecular basis of the pathways regulating the cancer cell promises to revolutionize clinical practice. The results of genomic- an proteomic-based studies at the National Cancer Center Institute Center for Cancer Research (NCI CCR) include the indentation of a molecular biomarker for ovarian cancer based on serum proteomic patterns that permits early detection and a new method for the diagnostic and prognostic assessment of subclasses of diffuse large B-cell lymphoma based on molecular criteria. The biological informativeness of molecularly based diagnostic categories confers the additional clinical advantage of identifying molecular pathways that can be selectively targeted for treatment. Molecular profiling of clear cell renal carcinoma, eg, has revealed that it responds to antiangiogenic agents. Moreover, targeted immunomodulatory interventions are proving effective against many cancers. The discovery and development of molecularly based means for detecting, diagnosis, and treating cancer are central priorities of the NCI CCR, which provides an interactive environment encouraging multidisciplinary collaborations, especially among basic and clinical investigators. Its infrastructure supports the iterative flow of information from the bench to the bedside and from the bedside to the bench, expediting the delivery of molecularly based therapeutics to cancer patients.

Antineoplastic Agents↗

PubMed2026

CERTOMICS: trusted single-cell multiomics pipeline for high-resolution profiling of adoptive cellular immunotherapies.

SUMMARY: Adoptive cellular immunontherapies, such as chimeric antigen receptor (CAR) T cell therapy, have transformed cancer treatment, yet challenges such as resistance, relapse, and high costs limit their efficacy and accessibility. A comprehensive understanding of cellular heterogeneity and molecular profiles is essential to improve these therapies. Advanced single-cell multiomics technologies have the power to analyze the complex interactions between CAR-engineered cells, immune cells, and tumor cells. However, standardized single-cell multiomics computational pipelines specifically tailored to CAR-engineered cell products are lacking. Due to the synthetic nature of CAR transgenes, additional steps for reliable identification and characterization of CAR-positive cells are required but not included in existing data-processing workflows. To address this, we present CERTOMICS, a Nextflow-based, CAR-aware pipeline offering enhanced CERTainty in immunophenotyping and data interpretation, tailored for single-cell multiOMICSprofiling of adoptive cellular immunotherapies. The pipeline standardizes processing 10x Genomics single-cell multiomics data and integrates CAR-specific identification and quality control. Additionally, a curated repository of CAR construct sequences and annotation data is provided, serving as an extensible resource to support the analysis and development of CAR T cell therapies. AVAILABILITY AND IMPLEMENTATION: Detailed documentation of this pipeline, along with a resource on latest FDA-approved CAR therapies is available on our website: https://fraunhofer-izi.github.io/Living-Drugs-Wiki/. The data underlying this article are available on GitHub at https://github.com/fraunhofer-izi/CERTOMICS. The code is also published on Zenodo at https://doi.org/10.5281/zenodo.18709693.

Multiomics↗

PubMed2026

Anaplastic lymphoma kinase immunohistochemical positivity in high-grade pulmonary neuroendocrine carcinoma: an actionable signal or merely a shadow?

AIMS: Anaplastic lymphoma kinase (ALK) rearrangements are actionable drivers in non-small cell lung carcinoma (NSCLC), but the biological significance of ALK-immunohistochemistry (IHC) positivity in high-grade pulmonary neuroendocrine carcinoma (NEC) remains unclear. This study evaluated the diagnostic and therapeutic implications of discordant ALK IHC and genomic findings and the role of multimodal molecular testing in resolving them. METHODS: We retrospectively analysed eight South Asian patients (Indian and Nepali) with de novo high-grade pulmonary NEC and diffuse ALK immunoreactivity treated at a tertiary cancer centre in India. Comprehensive molecular profiling using DNA- and RNA-based next-generation sequencing (NGS) and ALK fluorescence in situ hybridisation (where tissue was adequate) was performed. Clinical outcomes and responses to ALK-targeted tyrosine kinase inhibitors (TKIs) were assessed. RESULTS: ALK IHC positivity was observed in 8 of 100 selectively tested cases among 319 high-grade pulmonary NECs diagnosed between 2019 and 2025. The cohort included seven SCLCs (one combined adenocarcinoma-SCLC) and one large-cell neuroendocrine carcinoma (LCNEC). Median age was 51 years; 75% were female and 87.5% never-smokers. Among five comprehensively profiled cases, true ALK rearrangements were confirmed in two (one LCNEC and one SCLC), both detectable only by RNA sequencing. Durable benefit from ALK-TKI therapy was seen only in the molecularly confirmed LCNEC case (>16 months), whereas ALK IHC-positive but NGS-negative cases progressed rapidly. CONCLUSIONS: True ALK rearrangements in high-grade pulmonary NEC are rare but highly actionable. ALK IHC alone is an unreliable predictor of therapeutic benefit. RNA-based sequencing is essential for fusion detection. Comprehensive molecular confirmation, with RNA sequencing as the preferred modality, should precede any initiation of ALK-targeted therapy in high-grade pulmonary NEC.

IMMUNOHISTOCHEMISTRY↗

PubMed2004

Using gene expression profiling to differentiate benign versus malignant thyroid tumors.

DNA microarrays allow quick and complete evaluation of a cell's transcriptional activity. Expression genomics is very powerful in that it can generate expression data for a large number of genes simultaneously across multiple samples. In cancer research, an intriguing application of expression arrays includes assessing the molecular components of the neoplastic process and utilizing the data for cancer classification (Miller LD, et al. Cancer Cell 2002;2:353-61). Classification of human cancers into distinct groups based on their molecular profile rather than their histological appearance may prove to be more relevant to specific cancer diagnoses and cancer treatment regimes. Several attempts to formulate a consensus about classification and treatment of thyroid carcinoma based on standard histopathological analysis have resulted in published guidelines for diagnosis and initial disease management (Sherman SI. Lancet 2003;361:501-11). In the past few decades, no improvement has been made in the differential diagnosis of thyroid tumors by fine needle aspiration biopsy, specifically suspicious or indeterminate thyroid lesions, suggesting that a new approach to this should be explored. Therefore, in this study, we developed a gene expression approach to diagnose benign versus malignant thyroid lesions in 73 patients with thyroid tumors. We successfully built a 10 and 6 gene model able to differentiate benign versus malignant thyroid tumors. Our results support the premise that a molecular classification system for thyroid tumors is possible, and this in turn may provide a more accurate diagnostic tool for the clinician managing patients with suspicious thyroid lesions.

Diagnosis, Differential↗

PubMed2006

Transcriptosome and serum cytokine profiling of an atypical case of myelodysplastic syndrome with progression to acute myelogenous leukemia.

A Native American-Indian female presenting with anemia and thrombocytosis was diagnosed with myelodysplastic syndrome (MDS, refractory anemia). Over the course of 5 years she developed cytopenias and periods of leukocytosis with normal bone marrow (BM) blast counts, features of an unclassifiable MDS/MPS syndrome. The patient ultimately progressed to acute myelogenous leukemia (AML, FAB M2) and had a normal karyotype throughout her course. The episodes of leukocytosis were associated with infectious complications. Transformation to AML was characterized by a BM blast percentage of 49%. Peripheral blood and BM samples were obtained for serum protein analysis and gene expression profiling (GEP) to elucidate her disease process. An ELISA assay of the serum analyzed approximately 80 cytokines, which demonstrated that hepatocyte growth factor/scatter factor and insulin-like growth factor binding protein 1 were markedly elevated compared to normal. GEP demonstrated a unique "tumor molecular profile," which included overexpression of oncogenes (HOXA9, N-MYC, KOC1), proliferative genes (PAWR, DLG5, AKR1C3), invasion/metastatic genes (FN1, N-CAM-1, ITGB5), pro-angiogenesis genes (c-Kit), and down regulation of tumor suppressor genes (SUI1, BARD1) and anti-apoptotic genes (PGLYRP, SERPINB2, MPO). Hence, a biomics approach has provided insight into elucidating disease mechanisms, molecular prognostic factors, and discovery of novel targets for therapeutic intervention.

Aged↗

PubMed2004

Proteomics/genomics and signaling in lymphocytes.

Recent technological advances in genomics, proteomics and bioinformatics have offered new insights into the molecular mechanisms that underlie lymphocyte signaling and function, and the development of new tools in these areas has opened up new avenues for biological investigation. By adding a quantitative dimension to lymphocyte proteome profiling, molecular machines and spatiotemporal regulatory processes can now be analyzed using such discovery-driven approaches. Biologists employing genomic and proteomic tools are gathering data at increasing speed and their struggle to extract maximal biological information is helped by new software tools that enable the detailed comparison of multiple datasets.

Animals↗

PubMed2004

Tissue array-based predictions of pathobiology, prognosis, and response to treatment for renal cell carcinoma therapy.

Renal cell carcinoma is the most lethal of the common urologic malignancies, with approximately 40% of patients eventually dying of cancer progression. Approximately one third of patients present with metastatic disease, and up to 40% treated for localized disease have a recurrence. Historically, clinical factors have been used as prognostic markers for patients with renal cell carcinoma. Recent advances in the understanding of the pathogenesis, behavior, and molecular biology of renal cell carcinoma have paved the way for developments that may enhance early diagnosis, better predict tumor prognosis, and improve survival for renal cell carcinoma patients. Furthermore, reliable predictive factors are essential for the stratification of patients into clinically meaningful categories, which can be used to provide patients with counseling regarding prognosis, select treatment modalities, and determine eligibility for clinical trials. This has led to the creation of integrated staging systems that predict outcome by combining pathological and clinical variables. Although staging has been improved with the development of integrated systems, molecular tumor markers are expected to revolutionize the staging of renal cell carcinoma in the future. The development of methods based on gene and tissue arrays has created a powerful tool for evaluating hundreds to thousands of tumors simultaneously with histologic, immunohistochemical, and chromosomal analyses. Gene array analysis permits rapid molecular profiling, and tissue arrays enable the analysis of protein expression profiles on specimens to determine their potential clinical significance and role in renal cell carcinoma biology. This article reviews the tissue array-based predictors of pathobiology, prognosis, response to treatment, and potential molecular targets for therapy of renal cell carcinoma.

Algorithms↗

PubMed1999

Selective estrogen receptor modulators: tissue selectivity and differential uterine effects.

Selective estrogen receptor modulators (SERMs) are compounds that bind to estrogen receptors and produce estrogen-like (agonist) effects in some tissues and estrogen-blocking (antagonist) effects in other tissues. One of the goals of SERM research has been to develop compounds that provide the potential benefits of estrogen in the skeleton and cardiovascular system, but avoid the negative effects of estrogen in other tissues. Estrogen therapy has been consistently associated with endometrial stimulation, including glandular proliferation, hyperplasia and cancer. In contrast, the presence or degree of endometrial stimulation observed with SERMs varies by compound. The purpose of this review is to differentiate the endometrial effects of compounds that display a SERM-like profile. Molecular mechanisms involving SERM binding to estrogen receptors, preclinical uterine effects in both tissue culture and animal models, and endometrial findings in clinical experience are discussed. There are several SERMs commercially available or in development. The favorable safety profile of raloxifene in the uterus differentiates it from the others. Future SERM development will continue to focus on finding compounds that exhibit minimal endometrial stimulation.

Animals↗

PubMed2000

The natural history of bladder cancer. Implications for therapy.

Transitional cell carcinoma of the bladder is comprised of a variety of cancer diatheses that manifest a spectrum of distinct biologic potentials. Although these diseases have traditionally been classified as "superficial" and "muscle invasive" on the basis of their histologic appearance (depth of penetration of the "bladder wall" and corresponding prognosis) the pathways presumably followed by the various forms of these cancers imply an even greater complexity. These disparate pathways may reflect different events in carcinogenesis, which may determine subsequent development and risk for either recurrence or progression. In addition, biologic activity and malignant potential for each type of cancer may be associated with distinctive molecular and genetic alterations. These considerations may provide an opportunity to expand traditional staging systems in creating molecular profiles that may more precisely characterize the biologic potential of these tumor diatheses. Although there are far more questions than answers concerning how these alterations may effect the natural history of bladder cancer, molecular-based identification of bladder cancer patients at greatest risk for progression may ultimately improve clinical management.

Carcinoma in Situ↗

PubMed1999

Genetics and the biologic basis of sarcomas.

Identification of genetic alterations has contributed greatly to the understanding of sarcoma biology. Additionally, detection of these abnormalities is providing new tools for the diagnosis of sarcomas. In this paper, three important new genetic findings from the past year are reviewed, including the t(12;15) translocation of congenital fibrosarcoma, mutation of the putative tumor suppressor gene hSNF5/INI1 in malignant rhabdoid tumor, and the association of c-kit mutations with gastrointestinal stromal tumor. Highlighted are important studies concerning mechanisms of chromosomal translocation, functions of sarcoma-specific fusion proteins, genetic abnormalities other than translocations, molecular diagnosis, and molecular profiling of gene expression. Particular emphasis is placed on information obtained with comparative genomic hybridization and microarray techniques, because these powerful technologies will facilitate the rapid acquisition of data that provide insight into the molecular genetic and biologic basis of sarcomas.

Chromosome Aberrations↗

PubMed2006

Differences in microbial activity and microbial populations of peat associated with suppression of damping-off disease caused by Pythium sylvaticum.

The microbiological characteristics associated with disease-suppressive peats are unclear. We used a bioassay for Pythium sylvaticum-induced damping-off of cress seedlings to identify conducive and suppressive peats. Microbial activity in unconditioned peats was negatively correlated with the counts of P. sylvaticum at the end of the bioassay. Denaturing gradient gel electrophoresis (DGGE) profiling and clone library analyses of small-subunit rRNA gene sequences from two suppressive and two conducive peats differed in the bacterial profiles generated and the diversity of sequence populations. There were also significant differences between bacterial sequence populations from suppressive and conducive peats. The frequencies of a number of microbial groups, including the Rhizobium-Agrobacterium group (specifically sequences similar to those for the genera Ochrobactrum and Zoogloea) and the Acidobacteria, increased specifically in the suppressive peats, although no single bacterial group was associated with disease suppression. Fungal DGGE profiles varied little over the course of the bioassay; however, two bands associated specifically with suppressive samples were detected. Sequences from these bands corresponded to Basidiomycete yeast genera. Although the DGGE profiles were similar, fungal sequence diversity also increased during the bioassay. Sequences highly similar to those of Cryptococcus increased in relative abundance during the bioassay, particularly in the suppressive samples. This study highlights the importance of using complementary approaches to molecular profiling of complex populations and provides the first report that basidiomycetous yeasts may be associated with the suppression of Pythium-induced diseases in peats.

Basidiomycota↗

PubMed2004

Recent advances in defining the hematopoietic stem cell niche.

PURPOSE OF REVIEW: Hematopoietic stem cells are thought to reside in discrete cellular spaces termed "niches." The cellular elements and matrix surrounding the stem cell within the niche constitute the microenvironment. The purpose of this review is to discuss recent reports that have begun to elucidate the geographic location, key cellular type, and molecular mechanisms operating in stem cell niches. RECENT FINDINGS: Studies that have revealed the osteoblast as the key in vivo cellular element of the adult stem cell niche are the most significant recent findings. Additional studies have highlighted the importance of the Notch and Wingless (Wnt) signaling pathways in the hematopoietic microenvironment. Genomewide expression screens have been used to perform molecular profiling of stromal cell lines that serve as surrogate stem cell niches. These profiles have revealed novel regulatory molecules and have reinforced the roles of classic developmental morphogens in the niche space. The transcriptional profiling from these screens suggests that it is highly unlikely that a single factor or signal transduction pathway will control stem cell properties. SUMMARY: This review highlights the recent advances made toward elucidating the cellular and molecular attributes of the hematopoietic stem cell niche. Complete knowledge of the cellular architecture and molecular mechanisms in stem cell niches is essential to understanding the basic stem cell behaviors of self-renewal and differentiation.

Animals↗