Comparison of the classifiers based on mRNA, microRNA and lncRNA expression and DNA methylation profiles for the tumor origin detection.

Background: Tumor tissue origin detection is of great importance in determining the appropriate course of treatment for cancer patients. Classifiers based on gene expression and DNA methylation profiles have been confirmed to be feasible and reliable to predict the tumor primary. However, few works have been performed to compare the performance of these classifiers based on different profiles. Methods: Using gene expression and DNA methylation profiles from The Cancer Genome Atlas (TCGA) project, eight machine learning methods were employed for the tumor tissue origin detection. We then evaluated the predictive performance using DNA methylation, mRNA, microRNA (miRNA) and long non-coding RNA (lncRNA) expression profiles in a comparative manner. A statistical method was introduced to select the most informative CpG sites. Results: We found that LASSO is the most predictive models based on various profiles. Further analyses indicated that the results derived from DNA methylation (overall accuracy: 97.77%) are better than those derived from mRNA expression (overall accuracy: 88.01%), microRNA expression (overall accuracy: 91.03%) and lncRNA expression (overall accuracy: 95.7%). It has been suggested that we can achieve an overall accuracy >90% using only 1,000 methylated CpG sites for prediction. Conclusion: In this work, we comprehensively evaluated the performance of classifiers based on different profiles for the tumor origin detection. Our findings demonstrated the effectiveness of DNA methylation as biomarker for tracing tumor tissue origin using LASSO and neural network.

Integrated Transcriptome and Metabolome Analysis Reveals Molecular Mechanisms Underlying Resistance to Phytophthora Root Rot.

Soybean production is significantly impacted by Phytophthora root rot (PRR), which is caused by Phytophthora sojae. The nucleotide-binding leucine-rich repeat (NLR) gene family plays a crucial role in plant disease resistance. However, current understanding of the function of soybean NLR genes in resistance to PRR is limited. To address this knowledge gap, transgenic soybean plants overexpressing the NLR gene (Glyma.18g283200) were generated to elucidate the molecular mechanism of resistance. Here, transcript changes and metabolic differences were investigated at three time points (12, 24, and 36 h) after P. sojae infection in hypocotyls of two soybean lines, Dongnong 50 (susceptible line, WT) and Glyma.18g283200 overexpression line (resistant line, OE). Based on the changes in differentially expressed genes (DEGs) in response to P. sojae infection in different lines and at different time points, it was speculated that HOPZ-ACTIVATED RESISTANCE 1 (ZAR1), valine, leucine, and isoleucine degradation, and phytohormone signaling may be involved in the defense response of soybean to P. sojae at the transcriptome level by GO term and KEGG pathway enrichment analysis. Differentially accumulated metabolites (DAMs) analysis revealed that a total of 223 and 210 differential metabolites were identified in the positive ion (POS) and negative ion (NEG) modes, respectively. An integrated pathway-level analysis of transcriptomics (obtained by RNA-seq) and metabolomics data revealed that isoflavone biosynthesis was associated with disease resistance. This work provides valuable insights that can be used in breeding programs aiming to enhance soybean resistance against PRR.

Gonadal Transcriptome Sequencing Analysis Reveals the Candidate Sex-Related Genes and Signaling Pathways in the East Asian Common Octopus, Octopus sinensis.

The East Asian common octopus (Octopus sinensis) is an economically important species among cephalopods. This species exhibits a strict dioecious and allogamous reproductive strategy, along with a phenotypic sexual dimorphism, where the third right arm differentiates into hectocotylus in males. However, our understanding of the molecular mechanisms that underlie sex determination and differentiation in this species remains limited. In the present study, we surveyed gene-expression profiles in the immature male and female gonads of O. sinensis based on the RNA-seq, and a total of 47.83 Gb of high-quality data were generated. Compared with the testis, we identified 8302 differentially expressed genes (DEGs) in the ovary, of which 4459 genes were up-regulated and 3843 genes were down-regulated. Based on the GO enrichment, many GO terms related to sex differentiation were identified, such as sex differentiation (GO: 0007548), sexual reproduction (GO: 0019953) and male sex differentiation (GO: 0046661). A KEGG classification analysis identified three conserved signaling pathways that related to sex differentiation, including the Wnt signaling pathway, TGF-ß signaling pathway and Notch signaling pathway. Additionally, 21 sex-related DEGs were selected, of which 13 DEGs were male-biased, including Dmrt1, Foxn5, Foxj1, Sox30, etc., and 8 DEGs were female-biased, including Sox14, Nanos3, ß-tubulin, Suh, etc. Ten DEGs were used to verify the expression patterns in the testis and ovary using the RT-qPCR method, and the results showed that the expression level shown by RT-qPCR was consistent with that from the RNA-seq, which confirmed the reliability of the transcriptome data. The results presented in this study will not only contribute to our understanding of sex-formation mechanisms in O. sinensis but also provide the foundational information for further investigating the molecular mechanisms that underline its gonadal development and facilitate the sustainable development of octopus artificial breeding.

Molecular and Histopathological Characterization of Metastatic Cutaneous Squamous Cell Carcinomas: A Case-Control Study.

BACKGROUND: A subset of patients affected by cutaneous squamous cell carcinoma (cSCC) can exhibit locally invasive or metastatic tumors. Different staging classification systems are currently in use for cSCC. However, precise patient risk stratification has yet to be reached in clinical practice. The study aims to identify specific histological and molecular parameters characterizing metastatic cSCC. METHODS: Patients affected by metastatic and non-metastatic cSCC (controls) were included in the present study and matched for clinical and histological characteristics. Skin samples from primary tumors were revised for several histological parameters and also underwent gene expression profiling with a commercially available panel testing 770 different genes. RESULTS: In total, 48 subjects were enrolled in the study (24 cases, 24 controls); 67 genes were found to be differentially expressed between metastatic and non-metastatic cSCC. Most such genes were involved in immune regulation, skin integrity, angiogenesis, cell migration and proliferation. CONCLUSION: The combination of histological and molecular profiles of cSCCs allows the identification of features specific to metastatic cSCC, with potential implications for more precise patient risk stratification.

Transcriptomic analysis of bone marrow specimens collected from Miniature Dachshunds diagnosed with non-neoplastic bone marrow disorders.

Non-neoplastic bone marrow disorders are main causes of non-regenerative anemia in dogs. Despite the high incidence of the diseases, their molecular pathophysiology has not been elucidated. We previously reported that Miniature Dachshund (MD) was a predisposed breed to be diagnosed with non-neoplastic bone marrow disorders in Japan, and immunosuppressive treatment-resistant MDs showed higher number of platelets and morphological abnormalities in peripheral blood cells. These data implied that treatment-resistant MDs might possess distinct pathophysiological features from treatment-responsive MDs. Therefore, we conducted transcriptomic analysis of bone marrow specimens to investigate the pathophysiology of treatment-resistant MDs. Transcriptomic analysis comparing treatment-resistant MDs and healthy control dogs identified 179 differentially expressed genes (DEGs). Pathway analysis using these DEGs showed that "Wnt signaling pathway" was a significantly enriched pathway. We further examined the expression levels of DEGs associated with Wnt signaling pathway and confirmed the upregulation of AXIN2 and CCND2 and the downregulation of SFRP2 in treatment-resistant MDs compared with treatment-responsive MDs and healthy control dogs. This alteration implied the activation of Wnt signaling pathway in treatment-resistant MDs. The activation of Wnt signaling pathway has been reported in human patients with myelodysplastic syndrome (MDS), which is characterized by dysplastic features of blood cells. Therefore, the results of this study implied that treatment-resistant MDs have distinct molecular pathological features from treatment-responsive MDs and the pathophysiology of treatment-resistant MDs might be similar to that of human MDS patients.

A clinical impact study of dermatologists' use of diagnostic gene expression profile testing to guide patient management.

Aim: Cutaneous melanocytic neoplasms with diagnostic and/or clinical ambiguity pose patient management challenges. Methods: Six randomized case scenarios with diagnostic/clinical uncertainty were described with/without a benign or malignant diagnostic gene expression profile (GEP) result. Results: Clinical impact was assessed by reporting the mean increase/decrease of management changes normalized to baseline (n = 32 dermatologists). Benign GEP results prompted clinicians to decrease surgical margins (84.2%). Malignant GEP results escalated surgical excision recommendations (100%). A majority (72.2%) reduced and nearly all (98.9%) increased follow-up frequency for benign or malignant GEP results, respectively. There was an overall increase in management plan confidence with GEP results. Conclusion: Diagnostic GEP tests help guide clinical decision-making in a variety of diagnostically ambiguous or clinicopathologically discordant scenarios.

Dermatologists' use of diagnostic gene expression profiles for personalized patient care. When your doctor takes a piece of a mole, that mole is looked at under the microscope by a pathologist. The pathologist is responsible for figuring out if the mole is dangerous or not. Dangerous moles are removed with surgery to make sure all the dangerous tissue is gone. Moles without a health threat are left alone. Sometimes figuring out how dangerous a mole is is difficult. The pathologist may not provide the doctor with enough information for them to know how to treat your mole. There is a test that can provide information on whether your mole is unsafe. This test is called diagnostic gene expression profiling or GEP. In this study, GEP is used to help doctors figure out how to treat a mole and how often the patient should be seen in the office for skin checks. With GEP, important changes in patient treatment were identified. These include the need for an additional surgery, how much healthy tissue should be removed during surgery and how often the patient should be seen in the office. For suspicious moles where the pathology report is unclear, GEP can provide information that leads to more appropriate and personalized patient care.

Ancillary diagnostic gene expression profile testing for ambiguous cutaneous melanocytic lesions helps optimize dermatologist recommendations for excision margin and follow-up.

The potential role of RNA sequencing in diagnosing unexplained insensitivity to conventional chemotherapy in pediatric patients with B-cell acute lymphoblastic leukemia.

Pediatric B-cell acute lymphoblastic leukemia (B-ALL) is a highly heterogeneous disease. According to large-scale RNA sequencing (RNA-seq) data, B-ALL patients can be divided into more than 10 subgroups. However, many genomic defects associated with resistance mechanisms have not yet been identified. As an individual clinical tool for molecular diagnostic risk classification, RNA-seq and gene expression pattern-based therapy could be potential upcoming strategies. In this study, we retrospectively analyzed the RNA-seq gene expression profiles of 45 children whose molecular diagnostic classifications were inconsistent with the response to chemotherapy. The relationship between the transcriptome and chemotherapy response was analyzed. Fusion gene identification was conducted for the included patients who did not have known high-risk associated fusion genes or gene mutations. The most frequently detected fusion gene pair in the high-risk group was the DHRSX duplication, which is a novel finding. Fusions involving ABL1, LMNB2, NFATC1, PAX5, and TTYH3 at onset were more frequently detected in the high-risk group, while fusions involving LFNG, TTYH3, and NFATC1 were frequently detected in the relapse group. According to the pathways involved, the underlying drug resistance mechanism is related to DNA methylation, autophagy, and protein metabolism. Overall, the implementation of an RNA-seq diagnostic system will identify activated markers associated with chemotherapy response, and guide future treatment adjustments.

Genome-wide identification of heavy-metal ATPases genes in Areca catechu: investigating their functionality under heavy metal exposure.

Heavy-metal ATPases (HMAs) play a vital role in plants, helping to transport heavy metal ions across cell membranes.However, insufficient data exists concerning HMAs genes within the Arecaceae family.In this study, 12 AcHMA genes were identified within the genome of Areca catechu, grouped into two main clusters based on their phylogenetic relationships.Genomic distribution analysis reveals that the AcHMA genes were unevenly distributed across six chromosomes. We further analyzed their physicochemical properties, collinearity, and gene structure.Furthermore, RNA-seq data analysis exhibited varied expressions in different tissues of A. catechu and found that AcHMA1, AcHMA2, and AcHMA7 were highly expressed in roots, leaves, pericarp, and male/female flowers. A total of six AcHMA candidate genes were selected based on gene expression patterns, and their expression in the roots and leaves was determined using RT-qPCR under heavy metal stress. Results showed that the expression levels of AcHMA1 and AcHMA3 genes were significantly up-regulated under Cd2 + and Zn2 + stress. Similarly, in response to Cu2+, the AcHMA5 and AcHMA8 revealed the highest expression in roots and leaves, respectively. In conclusion, this study will offer a foundation for exploring the role of the HMAs gene family in dealing with heavy metal stress conditions in A. catechu.

Improving systemic therapy selection for inflammatory skin diseases: A clinical need survey.

Background: Empirical decisions to select therapies for psoriasis (PSO) and atopic dermatitis (AD) can lead to delays in disease control and increased health care costs. However, routine molecular testing for AD and PSO are lacking. Objective: To examine (1) how clinicians choose systemic therapies for patients with PSO and AD without molecular testing and (2) to determine how often the current approach leads to patients switching medications. Methods: A 20-question survey designed to assess clinician strategies for systemic treatment of AD and PSO was made available to attendees of a national dermatology conference in 2022. Results: Clinicians participating in the survey (265/414, 64% response rate) ranked "reported efficacy" as the most important factor governing treatment choice (P < .001). However, 62% (165/265) of clinicians estimated that 2 or more systemic medications were typically required to achieve efficacy. Over 90% (239/265) of respondents would or would likely find a molecular test to guide therapeutic selection useful. Limitations: To facilitate ease of recall, questions focused on systemic therapies as a whole and not individual therapies. Conclusion: Clinicians want a molecular test to help determine the most efficacious drug for individual patients.

DExplore: An Online Tool for Detecting Differentially Expressed Genes from mRNA Microarray Experiments.

Microarray experiments, a mainstay in gene expression analysis for nearly two decades, pose challenges due to their complexity. To address this, we introduce DExplore, a user-friendly web application enabling researchers to detect differentially expressed genes using data from NCBI's GEO. Developed with R, Shiny, and Bioconductor, DExplore integrates WebGestalt for functional enrichment analysis. It also provides visualization plots for enhanced result interpretation. With a Docker image for local execution, DExplore accommodates unpublished data. To illustrate its utility, we showcase two case studies on cancer cells treated with chemotherapeutic drugs. DExplore streamlines microarray data analysis, empowering molecular biologists to focus on genes of biological significance.

Prognostic biomarkers in melanoma: a 2023 update from clinical trials in different therapeutic scenarios.

INTRODUCTION: Over the past decade, significant advancements in the field of melanoma have included the introduction of a new staging system and the development of immunotherapy and targeted therapies, leading to changes in substage classification and impacting patient prognosis. Despite these strides, early detection remains paramount. The quest for dependable prognostic biomarkers is ongoing, given melanoma's unpredictable nature, especially in identifying patients at risk of relapse. Reliable biomarkers are critical for informed treatment decisions. AREAS COVERED: This review offers a comprehensive review of prognostic biomarkers in the context of clinical trials for immunotherapy and targeted therapy. It explores different clinical scenarios, including adjuvant, metastatic, and neo-adjuvant settings. Key findings suggest that tumor mutational burden, PD-L1 expression, IFN-γ signature, and immune-related factors are promising biomarkers associated with improved treatment responses. EXPERT OPINION: Identifying practical prognostic factors for melanoma therapy is challenging due to the tumor's heterogeneity. Promising biomarkers include tumor mutational burden (TMB), circulating tumor DNA, and those characterizing the tumor microenvironment, especially the immune component. Future research should prioritize large-scale, prospective studies to validate and standardize these biomarkers, emphasizing clinical relevance and real-world applicability. Easily accessible biomarkers have the potential to enhance the precision and effectiveness of melanoma management.

Methylation-driven mechanisms of allergic rhinitis during pollen and non-pollen seasons using integrated bioinformatics analysis.

Background: Allergic rhinitis (AR) is a widespread allergic airway disease that results from a complex interplay between genetic and environmental factors and affects approximately 10%-40% of the global population. Pollen is a common allergen, and exposure to pollen can cause epigenetic changes. However, the mechanism underlying pollen-induced DNA methylation changes and their potential effects on the allergic march are still unclear. The purpose of this study was to explore the methylation-driven mechanisms of AR during the pollen and non-pollen seasons using bioinformatics analysis and to investigate their relationship with asthma. Methods: We downloaded DNA methylation and gene expression data from the GEO database (GSE50387: GSE50222, GSE50101) and identified differentially methylated positions (DMPs) and differentially expressed genes (DEGs) during the pollen and non-pollen seasons using the CHAMP and limma packages. Through correlation analysis, we identified methylation-driven genes and performed pathway enrichment analysis to annotate their functions. We incorporated external data on AR combined with asthma (GSE101720) for analysis to identify key CpGs that promote the transformation of AR to asthma. We also utilized external data on olive pollen allergy (GSE54522) for analysis to validate the methylation-driven genes. Weighted correlation network analysis (WGCNA) was employed to identify gene modules significantly correlated with pollen allergy. We extracted genes related to the key methylation-driven gene ZNF667-AS1 from the significant module and performed pathway intelligent clustering using KOBAS-i. We also utilized gene set enrichment analysis to explore the potential function of ZNF667-AS1. Results: We identified 20 and 24 CpG-Gene pairings during the pollen and non-pollen seasons. After incorporating external data from GSE101720, we found that ZNF667-AS1 is a key gene that may facilitate the transformation of AR into asthma during the pollen season. This finding was further validated in another external dataset, GSE54522, which is associated with pollen allergy. WGCNA identified 17 modules, among which the blue module showed significant correlation with allergies. ZNF667-AS1 was located in the blue module. We performed pathway analysis on the genes correlated with ZNF667-AS1 extracted from the blue module and identified a prominent cluster of pathways in the KOBAS-i results, including Toll-like receptor (TLR) family, MyD88, MAPK, and oxidative stress. Gene set enrichment analysis around cg05508084 (paired with ZNF667-AS1) also indicated its potential involvement in initiating and modulating allergic inflammation from the perspective of TLR and MAPK signaling. Conclusion: We identified methylation-driven genes and their related pathways during the pollen and non-pollen seasons in patients with AR and identified key CpGs that promote the transformation of AR into asthma due to pollen exposure. This study provides new insights into the underlying molecular mechanisms of the transformation of AR to asthma.

Quail GHRL and LEAP2 gene cloning, polymorphism detection, phylogenetic analysis, tissue expression profiling and its association analysis with feed intake.

The GHRL, LEAP2, and GHSR system have recently been identified as important regulators of feed intake in mammals and chickens. However, the complete cloning of the quail GHRL (qGHRL) and quail LEAP2 (qLEAP2) genes, as well as their association with feed intake, remains unclear. This study cloned the entire qGHRL and qLEAP2 cDNA sequence in Chinese yellow quail (Coturnix japonica), including the 5' and 3' untranslated regions. Sanger sequencing analysis revealed no missense mutations in the coding region of qGHRL and qLEAP2. Subsequently, phylogenetic analysis and protein homology alignment were conducted on the qGHRL and qLEAP2 in major poultry species. The findings of this research indicated that the qGHRL and qLEAP2 sequences exhibit a high degree of similarity with those of chicken and turkey. Specifically, the N-terminal 6 amino acids of GHRL mature peptides and all the mature peptide sequence of LEAP2 exhibited consistent patterns across all species examined. The analysis of tissue gene expression profiles indicated that qGHRL was primarily expressed in the proventriculus and brain tissue, whereas qLEAP2 exhibited higher expression levels in the intestinal tissue, kidney, and liver tissue, differing slightly from previous studies conducted on chicken. It is necessary to investigate the significance of elevated expression of qGHRL in brain and qLEAP2 in kidney in the future. Further research has shown that the expression of qLEAP2 can quickly respond to changes in different energy states, whereas qGHRL does not exhibit the same capability. Overall, this study successfully cloned the complete cDNA sequences of qGHRL and qLEAP2, and conducted a comprehensive examination of their tissue expression profiles and gene expression levels in the main expressing organs across different energy states. Our current findings suggested that qLEAP2 is highly expressed in the liver, intestine, and kidney, and its expression level is regulated by feed intake.

Machine Learning Reveals Impacts of Smoking on Gene Profiles of Different Cell Types in Lung.

Smoking significantly elevates the risk of lung diseases such as chronic obstructive pulmonary disease (COPD) and lung cancer. This risk is attributed to the harmful chemicals in tobacco smoke that damage lung tissue and impair lung function. Current research on the impact of smoking on gene expression in specific lung cells is limited. This study addresses this gap by analyzing gene expression profiles at the single-cell level from 43,539 lung endothelial cells, 234,349 lung epithelial cells, 189,843 lung immune cells, and 16,031 lung stromal cells using advanced machine learning techniques. The data, categorized by different lung cell types, were classified into three smoking states: active smoker, former smoker, and never smoker. Each cell sample encompassed 28,024 feature genes. Employing an incremental feature selection method within a computational framework, several specific genes have been identified as potential markers of smoking status in different lung cell types. These include B2M, EEF1A1, and TPT1 in lung endothelial cells; FTL and MT-ATP8 in lung epithelial cells; HLA-B and HLA-C in lung immune cells; and HSP90B1 and LCN2 in lung stroma cells. Additionally, this study developed quantitative rules for representing the gene expression patterns related to smoking. This research highlights the potential of machine learning in oncology, enhancing our molecular understanding of smoking's harm and laying the groundwork for future mechanism-based studies.

Detection and identification of factors in the atrium responsible for blood pressure regulation in patients with hypertension.

Resection of the left atrial appendage reportedly improves blood pressure in patients with hypertension. This study aimed to validate the transcriptional profiles of atrial genes responsible for blood pressure regulation in patients with hypertension as well as to identify the molecular mechanisms in rat biological systems. RNA sequencing data of left atrial appendages from patients with (n = 6) and without (n = 6) hypertension were subjected to unsupervised principal component analysis (PCA). Reduction of blood pressure was reflected by third and ninth principal components PC3 and PC9, and that eighteen transcripts, including endothelin-1, were revealed by PCA-based pathway analysis. Resection of the left atrial appendage in hypertensive rats improved their blood pressure accompanied by a decrease in serum endothelin-1 concentration. Expression of the endothelin-1 gene in the atrium and atrial appendectomy could play roles in blood pressure regulation in humans and rats.

Transcriptomic Analysis of Type 2 Diabetes Mellitus Combined with Lower Extremity Atherosclerotic Occlusive Disease.

Background: The pathological damage mechanism of type 2 diabetes (T2D) and macroangiopathy is extremely complex, and T2D and arteriosclerosis obliterans have different biological behaviors and clinical features. To explore the mechanism of lower extremity arteriosclerosis occlusion (LEAOD) in T2D patients, we utilized RNA-seq to identify unique gene expression signatures of T2D and LEAOD through transcriptomic analysis. Methods: We obtained blood samples and performed RNA sequencing from four patients with T2D, five of whom had LEAOD. Another six age- and gender-matched blood samples from healthy volunteers were used for control. By exploring the general and specific differential expression analysis after transcriptome sequencing, specific gene expression patterns of T2D and LEAOD were verified. Results: Transcriptome analysis found differentially expressed genes in T2D, and T2D + LEAOD (vs normal) separately, of which 35/486 (T2D/T2D + LEAOD) were up-regulated and 1290/2970 (T2D/T2D + LEAOD) were down-regulated. A strong overlap of 571 genes across T2D, LEAOD, and coexisting conditions was mainly involved in extracellular exosomes and the transcription process. By exploring the sex difference gene expression features between T2D, T2D + LEAOD, and healthy controls, we noticed that sex chromosome-associated genes do not participate in the sexual dimorphism gene expression profiles of T2D and LEAOD. Protein-Protein Interaction Network analysis and drug target prediction provided the drug candidates to treat T2D and LEAOD. Conclusion: This study provides some evidence at the transcript level to uncover the association of T2D with LEAOD. The screened hub genes and predicted target drugs may be therapeutic targets.

Sentinel lymph node risk prognostication in primary cutaneous melanoma through tissue-based profiling, potentially redefining the need for sentinel lymph node biopsy.

PURPOSE OF REVIEW: The role of Sentinel Lymph Node Biopsy (SLNB) is pivotal in the contemporary staging of cutaneous melanoma. In this review, we examine advanced molecular testing platforms like gene expression profiling (GEP) and immunohistochemistry (IHC) as tools for predicting the prognosis of sentinel lymph nodes. We compare these innovative approaches with traditional staging assessments. Additionally, we delve into the shared genetic and protein markers between GEP and IHC tests and their relevance to melanoma biology, exploring their prognostic and predictive characteristics. Finally, we assess alternative methods to potentially obviate the need for SLNB altogether. RECENT FINDINGS: Progress in adjuvant melanoma therapy has diminished the necessity of Sentinel Lymph Node Biopsy (SLNB) while underscoring the importance of accurately identifying high-risk stage I and II melanoma patients who may benefit from additional anti-tumor interventions. The clinical application of testing through gene expression profiling (GEP) or immunohistochemistry (IHC) is gaining traction, with platforms such as DecisionDx, Merlin Assay (CP-GEP), MelaGenix GEP, and Immunoprint coming into play. Currently, extensive validation studies are in progress to incorporate routine molecular testing into clinical practice. However, due to significant methodological limitations, widespread clinical adoption of tissue-based molecular testing remains elusive at present. SUMMARY: While various tissue-based molecular testing platforms have the potential to stratify the risk of sentinel lymph node positivity (SLNP), most suffer from significant methodological deficiencies, including limited sample size, lack of prospective validation, and limited correlation with established clinicopathological variables. Furthermore, the genes and proteins identified by individual gene expression profiling (GEP) or immunohistochemistry (IHC) tests exhibit minimal overlap, even when considering the most well-established melanoma mutations. However, there is hope that the ongoing prospective trial for the Merlin Assay may safely reduce the necessity for SLNB procedures if successful. Additionally, the MelaGenix GEP and Immunoprint tests could prove valuable in identifying high-risk stage I-II melanoma patients and potentially guiding their selection for adjuvant therapy, thus potentially reducing the need for SLNB. Due to the diverse study designs employed, effective comparisons between GEP or IHC tests are challenging, and to date, there is no study directly comparing the clinical utility of these respective GEP or IHC tests.

Relationship between donor-derived cell-free DNA and tissue-based rejection-related transcripts in heart transplantation.

BACKGROUND: Endomyocardial biopsy (EMB)-based traditional microscopy remains the gold standard for the detection of cardiac allograft rejection, despite its limitation of inherent subjectivity leading to inter-reader variability. Alternative techniques now exist to surveil for allograft injury and classify rejection. Donor-derived cell-free DNA (dd-cfDNA) testing is now a validated blood-based assay used to surveil for allograft injury. The molecular microscope diagnostic system (MMDx) utilizes intragraft rejection-associated transcripts (RATs) to classify allograft rejection and identify injury. The use of dd-cfDNA and MMDx together provides objective molecular insight into allograft injury and rejection. The aim of this study was to measure the diagnostic agreement between dd-cfDNA and MMDx and assess the relationship between dd-cfDNA and MMDx-derived RATs, which may provide further insight into the pathophysiology of allograft rejection and injury. METHODS: This is a retrospective observational study of 156 EMB evaluated with traditional microscopy and MMDx. All samples were paired with dd-cfDNA from peripheral blood before EMB (up to 9 days). Diagnostic agreement between traditional histopathology, MMDx, and dd-cfDNA (threshold of 0.20%) was compared for assessment of allograft injury. In addition, the relationship between dd-cfDNA and individual RAT expression levels from MMDx was evaluated. RESULTS: MMDx characterized allograft tissue as no rejection (62.8%), antibody-mediated rejection (ABMR) (26.9%), T-cell-mediated rejection (TCMR) (5.8%), and mixed ABMR/TCMR (4.5%). For the diagnosis of any type of rejection (TCMR, ABMR, and mixed rejection), there was substantial agreement between MMDx and dd-cfDNA (76.3% agreement). All transcript clusters (group of gene sets designated by MMDx) and individual transcripts considered abnormal from MMDx had significantly elevated dd-cfDNA. In addition, a positive correlation between dd-cfDNA levels and certain MMDx-derived RATs was observed. Tissue transcript clusters were correlated with dd-cfDNA scores, including DSAST, GRIT, HT1, QCMAT, and S4. For individual transcripts, tissue ROBO4 was significantly correlated with dd-cfDNA in both nonrejection and rejection as assessed by MMDx. CONCLUSIONS: Collectively, we have shown substantial diagnostic agreement between dd-cfDNA and MMDx. Furthermore, based on the findings presented, we postulate a common pathway between the release of dd-cfDNA and expression of ROBO4 (a vascular endothelial-specific gene that stabilizes the vasculature) in the setting of antibody-mediated rejection, which may provide a mechanistic rationale for observed elevations in dd-cfDNA in AMR, compared to acute cellular rejection.

Use of the 40-gene Expression Profile (40-GEP) Test in Medicare-eligible Patients Diagnosed with Cutaneous Squamous Cell Carcinoma (cSCC) to Guide Adjuvant Radiation Therapy (ART) Decisions Leads to a Significant Reduction in Healthcare Costs.

Objective: Adjuvant radiation therapy (ART) is often recommended for high-risk cSCC patients but carries significant costs and risks. This study aims to determine if utilizing the 40-GEP test to guide ART can reduce healthcare costs in cSCC management. Methods: Medical claims data with new diagnoses of cSCC for the 12 months ending June 2022 in the Medicare (≥65 years) population (source: IQVIA claims database) were obtained and normalized to the general population for missingness. CPT codes associated with radiation therapy within one-year post diagnosis were used to establish adjuvant RT use (defined as 'ART'). Average weighted direct costs for four major ART modalities were calculated from published studies and (IQVIA). Sensitivity analysis was used to assess the financial impact of ART treatment using varying distributions of 40-GEP Class results. Results: Normalized medical claims data identified 22,917 Medicare-eligible cSCC patients who received ART within the United States. The weighted average direct cost for ART, which includes the four most used CPT code-defined modalities (IGRT, IMRT, IMPT, and XRT), was $60,693 per patient, amounting to an annual projected ART cost of $1.4 billion. Using the distribution of 40-GEP results from published studies, utilization of a 40-GEP test result to avoid ART in these patients could save up to $972 million in Medicare-eligible population. Sensitivity analysis shows, depending upon the distribution of the 40-GEP results, that for every 10% of Class 2A test results omitting ART, an extra $38-66 million in annual savings is expected. Limitations: Potential limitations include a need for more comprehensive patient information and the cost of ART-related complications. Conclusion: Utilizing the 40-GEP test results to guide ART decision-making would result in material savings to Medicare.

Emerging prognostic biomarkers in advanced cutaneous melanoma: a literature update.

INTRODUCTION: Over the past two years, the scientific community has witnessed an exponential growth in research focused on identifying prognostic biomarkers for melanoma, both in pre-clinical and clinical settings. This surge in studies reflects the need of developing effective prognostic indicators in the field of melanoma. AREAS COVERED: The aim of this work is to review the scientific literature on the most recent findings on the development or validation of prognostic biomarkers in melanoma, in the attempt of providing both clinicians and researchers with an updated broad synopsis of prognostic biomarkers in cutaneous melanoma. EXPERT OPINION: While the field of prognostic biomarkers in melanoma appears promising, there are several complexities and limitations to address. The interdependence of clinical, histological, and molecular features requires accurate classification of different biomarker families. Correlation does not imply causation, and adjustments for confounding factors are often overlooked. In this scenario, large-scale studies based on high-quality clinical trial data can provide more reliable evidence. It is essential to avoid oversimplification by focusing on a single biomarker, as the interactions among multiple factors contribute to define the disease course and patient's outcome. Furthermore, implementing well-supported evidence in real-life settings can help advance prognostic biomarker research in melanoma.