Biomarker Expression Patterns Research Articles

NLRP3 Inflammasome Inhibition After Pilocarpine-Induced Status Epilepticus Attenuates Chronic Inflammation in Epileptic Mice.

To investigate the effects of inhibiting the NOD-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome on neuronal damage and chronic pro-inflammatory responses during epileptogenesis in a mouse model of pilocarpine-induced status epilepticus (SE). Mice were randomly allocated into three groups: control, SE, and SE + MCC 950. The expression patterns of M1 and M2 microglial biomarkers in the hippocampus were quantified using Western blotting, quantitative real-time polymerase chain reaction, enzyme-linked immunosorbent assay, and immunofluorescence staining. Additionally, seizure susceptibility, video-electroencephalography recording, Morris water maze test, and brain immunofluorescence staining were performed to evaluate the epileptic brain 4 weeks post-SE. Within 72 hours post-SE, hippocampal microglia demonstrated a preferential polarization towards the M1 phenotype, a trend that was mitigated by NLRP3 inflammasome inhibition. During epileptogenesis, SE mice treated with NLRP3 inflammasome inhibition exhibited reduced neuronal damage, improved cognitive function, decreased seizure susceptibility, and attenuated chronic pro-inflammatory responses. Inhibition of NLRP3 inflammasome post-SE effectively ameliorates neuronal loss, seizure susceptibility, and cognitive dysfunction during epileptogenesis. This neuroprotective effect may be mediated through the mitigation of chronic pro-inflammatory responses within the epileptic brain.

Comprehensive Analysis of Immune Cell Infiltration and M2-Like Macrophage Biomarker Expression Patterns in Atrial Fibrillation.

Macrophages play a crucial role in the progression of AF, closely linked to atrial inflammation and myocardial fibrosis. However, the functions and molecular mechanisms of different phenotypic macrophages in AF are not well understood. This study aims to analyze the infiltration characteristics of atrial immune cells in AF patients and further explore the role and molecular expression patterns of M2 macrophage-related genes in AF. This study integrates single-cell and large-scale sequencing data to analyze immune cell infiltration and molecular characterization of the LAA in patients with AF, using SR as a control group. CIBERSORT assesses immune cell types in LAA tissues; WGCNA identifies signature genes; cell clustering analyzes cell types and subpopulations; cell communication explores macrophage interactions; hdWGCNA identifies M2 macrophage gene modules in AF. AF biomarkers are identified using LASSO and Random Forest, validated with ROC curves and RT-qPCR. Potential molecular mechanisms are inferred through TF-miRNA-mRNA networks and single-gene enrichment analyses. Myeloid cell subsets varied considerably between the AF and SR groups, with a significant increase in M2 macrophages in the AF group. Signals of inflammation and matrix remodeling were observed in AF. M2 macrophage-related genes IGF1, PDK4, RAB13, and TMEM176B were identified as AF biomarkers, with RAB13 and TMEM176B being novel markers. A TF-miRNA-mRNA network was constructed using target genes, which are enriched in the PPAR signaling pathway and fatty acid metabolism. Over infiltration of M2 macrophages may be an important factor in the progression of AF. The M2 macrophage-related genes IGF1, RAB13, TMEM176B and PDK4 may regulate the progression of AF through the PPAR signaling pathway and fatty acid metabolism.

Comprehensive analysis of TROP2, PD-L1, stromal (s)TILs, and HER2 expression patterns in patients (pts) with metastatic HR+HER2- breast cancer.

1062 Background: Immune checkpoint inhibitors (ICI) have shown limited efficacy in hormone receptor positive (HR+) metastatic breast cancer (mBC) and the optimal ICI-based combination is unknown. The TROP2 antibody-drug conjugate sacituzumab govitecan (SG) demonstrated antitumor activity with a 5.5-month median PFS in endocrine refractory HR+ mBC. Given SG's potential for anticancer immunity, we sought to evaluate expression patterns of biomarkers of interest in HR+ mBC. Methods: This retrospective study included pts with HR+HER2- mBC identified at DFCI between 10/2020 and 12/2021 who received 0-1 prior lines of chemotherapy in the metastatic setting and consented to analysis of archival FFPE tissue samples. We aimed to 1) characterize expression patterns of TROP2 (SP295 H-score), PD-L1 (22C3 CPS), sTILs and HER2 (per central pathology review) in the most recent available sample; 2) assess the prognostic value of selected biomarker combinations for overall survival (OS) defined as the time from consent to either death due to any cause or last follow-up (Cox proportional hazard models; p-value <0.05 considered significant). Results: Among 142 pts included, median age at diagnosis was 46 yrs (IQR: 40–56). Baseline characteristics are shown (Table). At least one biomarker was available for 123 subjects (86.6%). TROP2 expression (n=61) was Medium/High (M-H: 101-300) in 43 pts (70.5%) and Low (L: 0-100) in 18 (29.5%). PD-L1 central assessment (n=120) revealed CPS ≥1 (PD-L1+) in 32 pts (26.7%) and <1 (PD-L1-) in 88 (73.3%); only 7 (5.8%) pts had CPS ≥10. sTILs (n=87) were ≥10% in 14 pts (16.1%) and <10% in 73 (83.9%). When analyzing TROP2 and PD-L1 (n=61), 15 pts (24.6%) were TROP2-M-H/PD-L1+, 28 (45.9%) were TROP2-M-H/PD-L1-, 5 (8.2%) were TROP2-L/PD-L1+, and 13 (21.3%) were TROP2-L/PD-L1-. When analyzing TROP2 and sTILs (n=54), 6 pts (11.1%) were TROP2-M-H/sTILs ≥10%, 32 (59.3%) were TROP2-M-H/sTILs <10%, 2 (3.7%) were TROP2-L/sTILs ≥10% and 14 (25.9%) were TROP2-L/sTILs <10%. For TROP2 and HER2 (n=46), 26 pts (56.5%) had TROP2-M-H/HER2-low tumors, 7 (15.2%) TROP2-M-H/HER2-0, 3 (6.5%) TROP2-L/HER2-low, and 10 (21.7%) TROP2-Low/HER2-0. Median OS (n=138) was 43.8 months; stratification for selected biomarker combinations will be presented although no statistical significance was found. Correlations with NGS data and HER2DX are ongoing and will be presented. Conclusions: Analyzing biomarkers of interest in pts with HR+ mBC unveiled diverse patterns, without associations with OS. Patient characteristics. [Table: see text]

A bioprinted sea-and-island multicellular model for dissecting human pancreatic tumor-stroma reciprocity and adaptive metabolism

Pancreatic ductal adenocarcinoma (PDAC) presents a formidable clinical challenge due to its intricate microenvironment characterized by desmoplasia and complex tumor-stroma interactions. Conventional models hinder studying cellular crosstalk for therapeutic development. To recapitulate key features of PDAC masses, this study creates a novel sea-and-island PDAC tumor construct (s&i PTC). The s&i PTC consists of 3D-printed islands of human PDAC cells positioned within an interstitial extracellular matrix (ECM) populated by human cancer-associated fibroblasts (CAFs). This design closely mimics the in vivo desmoplastic architecture and nutrient-poor conditions. The model enables studying dynamic tumor-stroma crosstalk and signaling reciprocity, revealing both known and yet-to-be-discovered multicellular metabolic adaptations. Using the model, we discovered the orchestrated dynamic alterations of CAFs under nutrient stress, resembling critical in vivo human tumor niches, such as the secretion of pro-tumoral inflammatory factors. Additionally, nutrient scarcity induces dynamic alterations in the ECM composition and exacerbates poor cancer cell differentiation—features well-established in PDAC progression. Proteomic analysis unveiled the enrichment of proteins associated with aggressive tumor behavior and ECM remodeling in response to poor nutritional conditions, mimicking the metabolic stresses experienced by avascular pancreatic tumor cores. Importantly, the model's relevance to patient outcomes is evident through an inverse correlation between biomarker expression patterns in the s&i PTCs and PDAC patient survival rates. Key findings include upregulated MMPs and key ECM proteins (such as collagen 11 and TGFβ) under nutrient-avid conditions, known to be regulated by CAFs, alongside the concomitant reduction in E-cadherin expression associated with a poorly differentiated PDAC state under nutrient deprivation. Furthermore, elevated levels of hyaluronic acid (HA) and integrins in response to nutrient deprivation underscore the model's fidelity to the PDAC microenvironment. We also observed increased IL-6 and reduced α-SMA expression under poor nutritional conditions, suggesting a transition of CAFs from myofibroblastic to inflammatory phenotypes under a nutrient stress akin to in vivo niches. In conclusion, the s&i PTC represents a significant advancement in engineering clinically relevant 3D models of PDAC masses. It offers a promising platform for elucidating tumor-stroma interactions and guiding future therapeutic strategies to improve patient outcomes.

The biomarkers for maintenance Cancer stem cell features can be applicable in precision medicine of head and neck squamous cell carcinoma

Cancer stem cells (CSCs) play a crucial role in tumor relapse, proliferation, invasion, and drug resistance in head and neck squamous cell carcinoma (HNSCC). This narrative review aims to synthesize data from articles published between 2019 and 2023 on biomarkers for detecting CSCs in HNSCC and changes in molecular pathways, genetics, epigenetics, and non-coding RNAs (ncRNAs) in CSCs relevant to precision medicine approaches in HNSCC management. The search encompassed 41 in vitro studies and 22 clinical studies. CSCs exhibit diverse molecular profiles and unique biomarker expression patterns, offering significant potential for HNSCC diagnosis, treatment, and prognosis, thereby enhancing patient survival. Their remarkable self-renewal ability and adaptability are closely linked to tumorigenicity development and maintenance. Assessing biomarkers before and after therapy can aid in identifying various cell types associated with cancer progression and relapse. Screening for CSCs, senescent tumor cells, and cells correlated with the senescence process post-treatment has proven highly beneficial. However, the clinical application of precision medicine in HNSCC management is hindered by the lack of specific and definitive CSC biomarkers. Furthermore, our limited understanding of CSC plasticity, governed by genomic, transcriptomic, and epigenomic alterations during tumorigenesis, as well as the bidirectional interaction of CSCs with the tumor microenvironment, underscores the need for further research. Well-designed studies involving large patient cohorts are, therefore, essential to establish a standardized protocol and address these unresolved queries.

HER2 and PD-L1 Expression in Gastric and Gastroesophageal Junction Cancer: Insights for Combinatorial Targeting Approaches.

Gastric and gastroesophageal junction adenocarcinomas (GA/GEJA) are associated with a poor prognosis, primarily due to late disease diagnosis. Human Epidermal Growth Factor Receptor 2 (HER2) overexpression and programmed death-ligand 1 (PD-L1) expression are important biomarkers for treatment selection in locally advanced unresectable and metastatic GA/GEJA, and there is increasing interest in their role in earlier stages of disease. In this study, we aimed to evaluate HER2 and PD-L1 expression in a curative-intent GA/GEJA cohort to describe their expression patterns and analyze the association between HER2 expression and clinicopathological features. HER2 expression was evaluated in surgical and endoscopic submucosal dissection tumor samples, and PD-L1 was evaluated in HER2-positive cases. The clinical cohort included 107 patients, with 8.4% testing positive for HER2 (seven of whom also exhibited a PD-L1 combined positive score of ≥1. HER2 status was not significantly associated with survival outcomes. A pathologist-guided, region-specific analysis revealed that PD-L1 expression rarely overlaps with HER2-positive tumor areas. While the therapeutic implications of these observations remain unknown, these findings suggest that combination strategies targeting HER2 and PD-L1 might be directed toward distinct tumor subclones. The herein disclosed region-specific biomarker expression patterns may have important therapeutic and prognostic impacts, warranting further evaluation.

Breast Cancer Histopathology in the Age of Molecular Oncology.

For more than a century, microscopic histology has been the cornerstone for cancer diagnosis, and breast carcinoma is no exception. In recent years, clinical biomarkers, gene expression profiles, and other molecular tests have shown increasing utility for identifying the key biological features that guide prognosis and treatment of breast cancer. Indeed, the most common histologic pattern-invasive ductal carcinoma of no special type-provides relatively little guidance to management beyond triggering grading, biomarker testing, and clinical staging. However, many less common histologic patterns can be recognized by trained pathologists, which in many cases can be linked to characteristic biomarker and gene expression patterns, underlying mutations, prognosis, and therapy. Herein we describe more than a dozen such histomorphologic subtypes (including lobular, metaplastic, salivary analog, and several good prognosis special types of breast cancer) in the context of their molecular and clinical features.

RGC-32 facilitates pancreatic cancer via activating Wnt/β-catenin signaling.

Longitudinal studies have indicated the facilitating effect of RGC-32 during diverse disease progression including pancreatic cancer, yet the systematic and detailed effect of RGC-32 during pancreatic cancer is largely unknowable. For this purpose, we took advantage of the pancreatic cancer cell line (BXPC3) with RGC-32 expression and then modulated its expression by lentivirus-mediated knockdown (shRGC-32) and overexpression (pcDNA-RGC-32). To verify the effect of Wnt/β-catenin signaling in RGC-32-based tumorigenicity, we added the agonist CT99021 to the shRGC-32 BXPC3 cell line and pancreatic cancer mouse model. The deficiency in cellular vitality (cell survival, apoptosis, cell cycle) and migration of BXPC3 were sharply rescued by shRGC-32 in vitro. Notably, the aforementioned phenotypes as well as the expression pattern of EMT-associated biomarkers of BXPC3 with shRGC-32 expression could largely rescued by the agonist of Wnt/β-catenin in vitro and in vivo. Our data indicated the facilitating effect of RGC-32 upon pancreatic cancer cell line and mouse model via activating the Wnt/β-catenin signaling, which collectively suggested the feasibility of RGC-32 as a potent diagnostic and therapeutic target of pancreatic cancer in the future.

Investigation of Temporal Patterns of Biomarker Expression from Different Segments of the Kidneys in Healthy Subjects

Investigation of Temporal Patterns of Biomarker Expression from Different Segments of the Kidneys in Healthy Subjects

SCAR: Single-cell and Spatially-resolved Cancer Resources.

Advances in sequencing and imaging technologies offer a unique opportunity to unravel cell heterogeneity and develop new immunotherapy strategies for cancer research. There is an urgent need for a resource that effectively integrates a vast amount of transcriptomic profiling data to comprehensively explore cancer tissue heterogeneity and the tumor microenvironment. In this context, we developed the Single-cell and Spatially-resolved Cancer Resources (SCAR) database, a combined tumor spatial and single-cell transcriptomic platform, which is freely accessible at http://8.142.154.29/SCAR2023 or http://scaratlas.com. SCAR contains spatial transcriptomicdata from 21 tumor tissues and single-cell transcriptomic data from 11 301 352 cells encompassing 395 cancer subtypes and covering a wide variety oftissues, organoids, and cell lines. This resource offers diverse functional modules to address key cancer research questions at multiple levels, including the screening of tumor cell types, metabolic features, cell communication and gene expression patterns within the tumor microenvironment. Moreover, SCAR enables the analysis of biomarker expression patterns and cell developmental trajectories. SCAR also provides a comprehensive analysis of multi-dimensional datasets based on 34 state-of-the-art omics techniques, serving as an essential tool for in-depth mining and understanding of cell heterogeneity and spatial location. The implications of this resource extend to both cancer biology research and cancer immunotherapy development.

Plasticity of circulating tumor cells in small cell lung cancer

Small cell lung cancer (SCLC) is an aggressive neuroendocrine tumor with low five-year survival rates. Recently described molecular phenotypes of SCLC exhibit differential vulnerabilities heralding potential for stratified treatment. Whilst tumor biopsy in SCLC is challenging, circulating tumor cells in the liquid biopsy are prevalent and can be repeatedly sampled accommodating the dynamic plasticity of SCLC phenotypes. The aim of this study was to characterize the heterogeneity of rare circulating cells with confirmed tumor origin and to explore a liquid biopsy approach for future clinical trials of targeted therapies. This study applied the 3rd generation of a previously validated direct imaging platform to 14 chemo-naive SCLC patients and 10 non-cancerous normal donor (ND) samples. Phenotypic heterogeneity of circulating rare cells in SCLC was observed and a patient-level classification model was established to stratify SCLC patients from non-cancerous donors. Eight rare cell groups, with combinations of epithelial, endothelial, and mesenchymal biomarker expression patterns, were phenotypically characterized. The single-cell genomic analysis confirmed the cancer cell plasticity in every rare cell group harboring clonal genomic alterations. This study shows rare cell heterogeneity and confirms cellular plasticity in SCLC providing a valuable resource for better opportunities to discover novel therapeutic targets in SCLC.

Noninvasive identification of molecular biomarkers of hepatocellular carcinoma in HCV-Egyptian patients

BackgroundThis study was performed to investigate the expression of different biomarkers in patients with hepatocellular carcinoma and its connection with detective biomarkers. To achieve this objective, seventy subjects were examined in this study, sub-grouped to forty HCC patients and thirty HCV-affected patients with matched thirty healthy individuals. The study involved several groups of participants who were matched based on their age and gender.MethodsThe expression pattern of biomarkers was monitored by quantitative polymerase chain reaction (qRT-PCR). Finally, we utilized a ROC curve to investigate the predictive accurateness of those distinct biomarkers as well as a traditional tumor marker, AFP, in detecting HCC cases.ResultsThe baseline biomarker expression levels were markedly greater in HCC patients than in those affected by HCV or healthy subjects. We stated that the sensitivity and the specificity of the different biomarkers alone did not improve than that of AFP alone. When comparing AFP with different biomarkers, the diagnostic validity improves only when combining with CK-1.ConclusionsOverall, our results indicate that CK-1 mRNA expression could help as a noninvasive tumor biomarker for HCC prognosis and diagnosis when combining with AFP.

Precise profiling of exosomal biomarkers via programmable curved plasmonic nanoarchitecture-based biosensor for clinical diagnosis of Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disease of complex pathogenesis, with overt symptoms following disease progression. Early AD diagnosis is challenging due to the lack of robust biomarkers and limited patient access to diagnostics via neuroimaging and cerebrospinal fluid (CSF) tests. Exosomes present in body fluids are attracting attention as diagnostic biomarkers that directly reflect neuropathological features within the brain. In particular, exosomal miRNAs (exomiRs) signatures are involved in AD pathogenesis, showing a different expression between patients and the healthy controls (HCs). However, low yield and high homologous nature impede the accuracy and reproducibility of exosome blood-based AD diagnostics. Here, we developed a programmable curved plasmonic nanoarchitecture-based biosensor to analyze exomiRs in clinical serum samples for accurate AD diagnosis. To allow the detection of exomiRs in serum at attomolar levels, nanospaces (e.g., nanocrevice and nanocavity) were introduced into the nanostructures to dramatically increase the spectral sensitivity by adjusting the bending angle of the plasmonic nanostructure through sodium chloride concentration control. The developed biosensor classifies individuals into AD, mild cognitive impairment (MCI) patients, and HCs through profiling and quantifying exomiRs. Furthermore, integrating analysis expression patterns of multiple exosomal biomarkers improved serum-based diagnostic performance (average accuracy of 98.22%). Therefore, precise, highly sensitive serum-derived exosomal biomarker detection-based plasmonic biosensor has a robust capacity to predict the molecular pathologic of neurodegenerative disease, progression of cognitive decline, MCI/AD conversion, as well as early diagnosis and treatment.

Detection of multiple biomarkers associated with satellite cell fate in the contused skeletal muscle of rats for wound age estimation.

From the perspective of forensic wound age estimation, experiments related to skeletal muscle regeneration after injury have rarely been reported. Here, we examined the time-dependent expression patterns of multiple biomarkers associated with satellite cell fate, including the transcription factor paired box 7 (Pax7), myoblast determination protein (MyoD), myogenin, and insulin-like growth factor (IGF-1), using immunohistochemistry, western blotting, and quantitative real-time PCR in contused skeletal muscle. An animal model of skeletal muscle contusion was established in 30 Sprague-Dawley male rats, and another five rats were employed as non-contused controls. Morphometrically, the data obtained from the numbers of Pax7 + , MyoD + , and myogenin + cells were highly correlated with the wound age. Pax7, MyoD, myogenin, and IGF-1 expression patterns were upregulated after injury at both the mRNA and protein levels. Pax7, MyoD, and myogenin protein expression levels confirmed the results of the morphometrical analysis. Additionally, the relative quantity of IGF-1 protein > 0.92 suggested a wound age of 3 to 7days. The relative quantity of Pax7 mRNA > 2.44 also suggested a wound age of 3 to 7days. Relative quantities of Myod1, Myog, and Igf1 mRNA expression > 2.78, > 7.80, or > 3.13, respectively, indicated a wound age of approximately 3days. In conclusion, the expression levels of Pax7, MyoD, myogenin, and IGF-1 were upregulated in a time-dependent manner during skeletal muscle wound healing, suggesting the potential for using them as candidate biomarkers for wound age estimation in skeletal muscle.

Companion diagnostic requirements for spatial biology using multiplex immunofluorescence and multispectral imaging.

Immunohistochemistry has long been held as the gold standard for understanding the expression patterns of therapeutically relevant proteins to identify prognostic and predictive biomarkers. Patient selection for targeted therapy in oncology has successfully relied upon standard microscopy-based methodologies, such as single-marker brightfield chromogenic immunohistochemistry. As promising as these results are, the analysis of one protein, with few exceptions, no longer provides enough information to draw effective conclusions about the probability of treatment response. More multifaceted scientific queries have driven the development of high-throughput and high-order technologies to interrogate biomarker expression patterns and spatial interactions between cell phenotypes in the tumor microenvironment. Such multi-parameter data analysis has been historically reserved for technologies that lack the spatial context that is provided by immunohistochemistry. Over the past decade, technical developments in multiplex fluorescence immunohistochemistry and discoveries made with improving image data analysis platforms have highlighted the importance of spatial relationships between certain biomarkers in understanding a patient's likelihood to respond to, typically, immune checkpoint inhibitors. At the same time, personalized medicine has instigated changes in both clinical trial design and its conduct in a push to make drug development and cancer treatment more efficient, precise, and economical. Precision medicine in immuno-oncology is being steered by data-driven approaches to gain insight into the tumor and its dynamic interaction with the immune system. This is particularly necessary given the rapid growth in the number of trials involving more than one immune checkpoint drug, and/or using those in combination with conventional cancer treatments. As multiplex methods, like immunofluorescence, push the boundaries of immunohistochemistry, it becomes critical to understand the foundation of this technology and how it can be deployed for use as a regulated test to identify the prospect of response from mono- and combination therapies. To that end, this work will focus on: 1) the scientific, clinical, and economic requirements for developing clinical multiplex immunofluorescence assays; 2) the attributes of the Akoya Phenoptics workflow to support predictive tests, including design principles, verification, and validation needs; 3) regulatory, safety and quality considerations; 4) application of multiplex immunohistochemistry through lab-developed-tests and regulated in vitro diagnostic devices.

Identification of potential M2 macrophage-associated diagnostic biomarkers in coronary artery disease.

M2 macrophages have been reported to be important in the progression of coronary artery disease (CAD). Thus, the present study aims at exploring the diagnostic value of M2 macrophage-associated genes in CAD. Transcriptome profile of CAD and control samples were downloaded from Gene Expression Omnibus database. The proportion of immune cells was analyzed using cell type identification by estimating relative subsets of RNA transcripts. Weighted Gene Co-expression Network Analysis (WGCNA) was carried out to screen the relevant module associated with M2 macrophages. Differential CAD and control samples of expressed genes (DEGs) were identified by the limma R package. Functional enrichment analysis by means of the clusterProfiler R package. Least absolute shrinkage and selection operator (LASSO) and random forest (RF) algorithms were carried out to select signature genes. Receiver operating curves (ROC) were plotted to evaluate the diagnostic value of selected signature genes. The expressions of potential diagnostic markers were validated by RT-qPCR. The ceRNA network of diagnostic biomarkers was constructed via miRwalk and Starbase database. CMap database was used to screen candidate drugs in the treatment of CAD by targeting diagnostic biomarkers. A total of 166 M2 macrophage-associated genes were identified by WGCNA. By intersecting those genes with 879 DEGs, 53 M2 macrophage-associated DEGs were obtained in the present study. By LASSO, RF, and ROC analyses, C1orf105, CCL22, CRYGB, FRK, GAP43, REG1P, CALB1, and PTPN21 were identified as potential diagnostic biomarkers. RT-qPCR showed the consistent expression patterns of diagnostic biomarkers between GEO dataset and clinical samples. Perhexiline, alimemazine and mecamylamine were found to be potential drugs in the treatment of CAD. We identified eight M2 macrophage-associated diagnostic biomarkers and candidate drugs for the CAD treatment.

Expression patterns of uPAR, TF and EGFR and their potential as targets for molecular imaging in oropharyngeal squamous cell carcinoma.

The clinical introduction of molecular imaging for the management of oropharyngeal squamous cell carcinoma (OPSCC) relies on the identification of relevant cancer-specific biomarkers. The application of three membrane-bound receptors, namely urokinase-type plasminogen activator receptor (uPAR), tissue factor (TF) and EGFR have been previously explored for targeted imaging and therapeutic strategies in a broad range of solid cancers. The present study aimed to investigate the expression patterns of uPAR, EGFR and TF by immunohistochemistry (IHC) to evaluate their potential for targeted imaging and prognostic value in OPSCC. In a retrospective cohort of 93 patients with primary OPSCC, who were balanced into the 45 human papillomavirus (HPV)-positive and 48 HPV-negative groups, the IHC-determined expression profiles of uPAR, TF and EGFR in large biopsy or tumor resection specimens were analyzed. Using the follow-up data, overall survival (OS) and recurrence-free survival were measured. Specifically, associations between survival outcome, biomarker expression and clinicopathological factors were examined using Cox proportional hazards model and log-rank test following Kaplan-Meier statistics. After comparing the expression pattern of biomarkers within the tumor compartment with that in the adjacent normal tissues, uPAR and TF exhibited a highly tumor-specific expression pattern, whereas EGFR showed a homogeneous expression within the tumor compartment as well as a consistent expression in the normal mucosal epithelium and salivary gland tissues. The positive expression rate of uPAR, TF and EGFR in the tumors was 98.9, 76.3 and 98.9%, respectively. No statistically significant association between biomarker expression and survival outcome could be detected. Higher uPAR expression levels had a trend towards reduced OS according to results from univariate analysis (P=0.07; hazard ratio=2.01; 95% CI=0.92-4.37). Taken together, these results suggest that uPAR, TF and EGFR may be suitable targets for molecular imaging and therapy in OPSCC. In particular, uPAR may be an attractive target owing to their high positive expression rates in tumors and a highly tumor-specific expression pattern.

Diagnostic value of abnormal chromosome 3p genes in small‑cell lung cancer

The diagnosis of small cell lung carcinoma (SCLC) remains a great challenge. Changes in chromosome 3p (chr3) genes are usually observed in the pathogenesis of lung cancer, which suggests that these chr3 genes may be a diagnostic marker in the early stage of SCLC. The present study explored the diagnostic value of the chr3 gene in SCLC using Bioinformatics. Furthermore, reverse transcription-quantitative PCR (RT-qPCR) was used to reveal the expression patterns of diagnostic biomarkers in human pulmonary alveolar epithelial cells and in the SCLC cell line NCI-H146. A total of 33 differentially expressed (DE) chr3 genes and 1,156 module genes associated with clinical features of patients with SCLC were identified and functional enrichment analysis indicated that all these genes were significantly enriched in cell cycle terms. The area under the receiver operating characteristic curve demonstrated that the overlapping genes of the DE-chr3 and module genes, namely cell division cycle 25 A (CDC25A), FYVE and coiled-coil domain autophagy adaptor 1 (FYCO1) and lipid raft linker 1 (RFTN1), were relatively accurate in distinguishing normal from SCLC samples, and may thus be considered diagnostic biomarkers. CDC25A was overexpressed in SCLC samples, while FYCO1 and RFTN1 were highly expressed in normal samples, as evidenced by the RT-qPCR results. Single-gene gene set enrichment analysis suggested that the diagnostic biomarkers were significantly associated with cell cycle, ATP-binding cassette transporter, immune cell differentiation, immune response and multiple respiratory disease pathways. Furthermore, a total of 141 drugs were predicted by The Comparative Toxicogenomics Database to be able to modulate the expression of the diagnostic biomarkers, of which 8 drugs were shared among the three aforementioned diagnostic biomarkers. The present study identified three novel and powerful diagnostic biomarkers for SCLC based on chr3 genes. Suggestions for the development and selection of drugs for clinical treatment based on diagnostic biomarkers were also provided.

Interpatient Heterogeneity in Drug Response and Protein Biomarker Expression of Recurrent Ovarian Cancer.

Simple SummaryRecurrent ovarian-cancer patients face low 5-year survival rates despite chemotherapy. Oncologists may choose from a variety of guideline-recommended second-line therapeutic options without knowing which one works best. Thus, therapy alterations and adjustments are often required. We analyzed the response that 30 tumor lesions had to certain treatments in our patient-derived ovarian-cancer spheroid model. In addition, we characterized samples by immunohistochemical staining for new druggable molecular targets. Our results might help in tailoring future therapies for individual patients with recurrent ovarian cancer.Recurrent ovarian-cancer patients face low 5-year survival rates despite chemotherapy. A variety of guideline-recommended second-line therapies are available, but they frequently result in trial-and-error treatment. Alterations and adjustments are common in the treatment of recurrent ovarian cancer. The drug response of 30 lesions obtained from 22 relapsed ovarian cancer patients to different chemotherapeutic and molecular agents was analyzed with the patient-derived ovarian-cancer spheroid model. The profile of druggable biomarkers was immunohistochemically assessed. The second-line combination therapy of carboplatin with gemcitabine was significantly superior to the combination of carboplatin with PEGylated liposomal doxorubicin (p < 0.0001) or paclitaxel (p = 0.0007). Except for treosulfan, all nonplatinum treatments tested showed a lesser effect on tumor spheroids compared to that of platinum-based therapies. Treosulfan showed the highest efficacy of all nonplatinum agents, with significant advantage over vinorelbine (p < 0.0001) and topotecan (p < 0.0001), the next best agents. The comparative testing of a variety of treatment options in the ovarian-cancer spheroid model resulted in the identification of more effective regimens for 30% of patients compared to guideline-recommended therapies. Recurrent cancers obtained from different patients revealed profound interpatient heterogeneity in the expression pattern of druggable protein biomarkers. In contrast, different lesions obtained from the same patient revealed a similar drug response and biomarker expression profile. Biological heterogeneity observed in recurrent ovarian cancers might explain the strong differences in the clinical drug response of these patients. Preclinical drug testing and biomarker profiling in the ovarian-cancer spheroid model might help in optimizing treatment management for individual patients.

High Dual Expression of the Biomarkers CD44v6/α2β1 and CD44v6/PD-L1 Indicate Early Recurrence after Colorectal Hepatic Metastasectomy.

Simple SummaryDistant metastasis in colorectal cancer still correlates with poor prognosis, emphasizing the high need for new diagnostic and therapeutic strategies. In the present study, liver and lung metastases revealed profound differences in the expression pattern of metastasis-driving protein biomarkers. This suggests the adaption of the therapy to the biology of the metastatic organ site. High expression of the cell adhesion molecule CD44v6 and high dual expression of CD44v6, combined with the cell adhesion molecules integrin α2β1, as well as the checkpoint inhibitor molecule PD-L1, correlated significantly with early recurrence after hepatectomy, in a substantial number of liver metastatic patients. These findings suggest the need for the implementation of biological risk factors into clinical risk scores, aiming to make the prognosis of the individual patient more precise. Further, dual expression of protein biomarkers that are druggable, such as CD44v6/α2β1 and CD44v6/PD-L1, can identify high-risk patients for targeted therapy that might provide a survival benefit.Considering the biology of CRC, distant metastases might support the identification of high-risk patients for early recurrence and targeted therapy. Expression of a panel of druggable, metastasis-related biomarkers was immunohistochemically analyzed in 53 liver (LM) and 15 lung metastases (LuM) and correlated with survival. Differential expression between LM and LuM was observed for the growth factor receptors IGF1R (LuM 92.3% vs. LM 75.8%, p = 0.013), EGFR (LuM 68% vs. LM 41.5%, p = 0.004), the cell adhesion molecules CD44v6 (LuM 55.7% vs. LM 34.9%, p = 0.019) and α2β1 (LuM 88.3% vs. LM 58.5%, p = 0.001) and the check point molecule PD-L1 (LuM 6.1% vs. LM 3.3%, p = 0.005). Contrary, expression of HGFR, Hsp90, Muc1, Her2/neu, ERα and PR was comparable in LuM and LM. In the LM cohort (n = 52), a high CD44v6 expression was identified as an independent factor of poor prognosis (PFS: HR 2.37, 95% CI 1.18–4.78, p = 0.016). High co-expression of CD44v6/α2β1 (HR 4.14, 95% CI 1.65–10.38, p = 0.002) and CD44v6/PD-L1 (HR 2.88, 95% CI 1.21–6.85, p = 0.017) indicated early recurrence after hepatectomy, in a substantial number of patients (CD44v6/α2β1: 11 (21.15%) patients; CD44v6/PD-L1: 12 (23.1%) patients). Dual expression of druggable protein biomarkers may refine prognostic prediction and stratify high-risk patients for new therapeutic concepts, depending on the metastatic location.