Antibiotics-Driven Gut Microbiome Perturbation Alters Immunity to Vaccines in Humans.

Emerging evidence indicates a central role for the microbiome in immunity. However, causal evidence in humans is sparse. Here, we administered broad-spectrum antibiotics to healthy adults prior and subsequent to seasonal influenza vaccination. Despite a 10,000-fold reduction in gut bacterial load and long-lasting diminution in bacterial diversity, antibody responses were not significantly affected. However, in a second trial of subjects with low pre-existing antibody titers, there was significant impairment in H1N1-specific neutralization and binding IgG1 and IgA responses. In addition, in both studies antibiotics treatment resulted in (1) enhanced inflammatory signatures (including AP-1/NR4A expression), observed previously in the elderly, and increased dendritic cell activation; (2) divergent metabolic trajectories, with a 1,000-fold reduction in serum secondary bile acids, which was highly correlated with AP-1/NR4A signaling and inflammasome activation. Multi-omics integration revealed significant associations between bacterial species and metabolic phenotypes, highlighting a key role for the microbiome in modulating human immunity.

A Common Embryonic Origin of Stem Cells Drives Developmental and Adult Neurogenesis.

New neurons arise from quiescent adult neural progenitors throughout life in specific regions of the mammalian brain. Little is known about the embryonic origin and establishment of adult neural progenitors. Here, we show that Hopx+ precursors in the mouse dentate neuroepithelium at embryonic day 11.5 give rise to proliferative Hopx+ neural progenitors in the primitive dentate region, and they, in turn, generate granule neurons, but not other neurons, throughout development and then transition into Hopx+ quiescent radial glial-like neural progenitors during an early postnatal period. RNA-seq and ATAC-seq analyses of Hopx+ embryonic, early postnatal, and adult dentate neural progenitors further reveal common molecular and epigenetic signatures and developmental dynamics. Together, our findings support a "continuous" model wherein a common neural progenitor population exclusively contributes to dentate neurogenesis throughout development and adulthood. Adult dentate neurogenesis may therefore represent a lifelong extension of development that maintains heightened plasticity in the mammalian hippocampus.

A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles.

We previously piloted the concept of a Connectivity Map (CMap), whereby genes, drugs, and disease states are connected by virtue of common gene-expression signatures. Here, we report more than a 1,000-fold scale-up of the CMap as part of the NIH LINCS Consortium, made possible by a new, low-cost, high-throughput reduced representation expression profiling method that we term L1000. We show that L1000 is highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts. We further show that the expanded CMap can be used to discover mechanism of action of small molecules, functionally annotate genetic variants of disease genes, and inform clinical trials. The 1.3 million L1000 profiles described here, as well as tools for their analysis, are available at https://clue.io.

New techniques to identify the tissue of origin for cancer of unknown primary in the era of precision medicine: progress and challenges.

Despite a standardized diagnostic examination, cancer of unknown primary (CUP) is a rare metastatic malignancy with an unidentified tissue of origin (TOO). Patients diagnosed with CUP are typically treated with empiric chemotherapy, although their prognosis is worse than those with metastatic cancer of a known origin. TOO identification of CUP has been employed in precision medicine, and subsequent site-specific therapy is clinically helpful. For example, molecular profiling, including genomic profiling, gene expression profiling, epigenetics and proteins, has facilitated TOO identification. Moreover, machine learning has improved identification accuracy, and non-invasive methods, such as liquid biopsy and image omics, are gaining momentum. However, the heterogeneity in prediction accuracy, sample requirements and technical fundamentals among the various techniques is noteworthy. Accordingly, we systematically reviewed the development and limitations of novel TOO identification methods, compared their pros and cons and assessed their potential clinical usefulness. Our study may help patients shift from empirical to customized care and improve their prognoses.

Therapeutic Inhibition of LincRNA-p21 Protects Against Cardiac Hypertrophy.

BACKGROUND: Cardiac hypertrophy is an adaptive response to pressure overload aimed at maintaining cardiac function. However, prolonged hypertrophy significantly increases the risk of maladaptive cardiac remodeling and heart failure. Recent studies have implicated long noncoding RNAs in cardiac hypertrophy and cardiomyopathy, but their significance and mechanism(s) of action are not well understood. METHODS: We measured lincRNA-p21 RNA and H3K27ac levels in the hearts of dilated cardiomyopathy patients. We assessed the functional role of lincRNA-p21 in basal and surgical pressure-overload conditions using loss-of-function mice. Genome-wide transcriptome analysis revealed dysregulated genes and pathways. We labeled proteins in proximity to full-length lincRNA-p21 using a novel BioID2-based system. We immunoprecipitated lincRNA-p21-interacting proteins and performed cell fractionation, ChIP-seq (chromatin immunoprecipitation followed by sequencing), and co-immunoprecipitation to investigate molecular interactions and underlying mechanisms. We used GapmeR antisense oligonucleotides to evaluate the therapeutic potential of lincRNA-p21 inhibition in cardiac hypertrophy and associated heart failure. RESULTS: lincRNA-p21 was induced in mice and humans with cardiomyopathy. Global and cardiac-specific lincRNA-p21 knockout significantly suppressed pressure overload-induced ventricular wall thickening, stress marker elevation, and deterioration of cardiac function. Genome-wide transcriptome analysis and transcriptional network analysis revealed that lincRNA-p21 acts in trans to stimulate the NFAT/MEF2 pathway. Mechanistically, lincRNA-p21 is bound to the scaffold protein KAP1. lincRNA-p21 cardiac-specific knockout suppressed stress-induced nuclear accumulation of KAP1, and KAP1 knockdown attenuated cardiac hypertrophy and NFAT activation. KAP1 positively regulates pathological hypertrophy by physically interacting with NFATC4 to promote the overactive status of NFAT/MEF2 signaling. GapmeR antisense oligonucleotide depletion of lincRNA-p21 similarly inhibited cardiac hypertrophy and adverse remodeling, highlighting the therapeutic potential of inhibiting lincRNA-p21. CONCLUSIONS: These findings advance our understanding of the functional significance of stress-induced long noncoding RNA in cardiac hypertrophy and demonstrate the potential of lincRNA-p21 as a novel therapeutic target for cardiac hypertrophy and subsequent heart failure.

The current state of molecular testing in the treatment of patients with solid tumors, 2019.

The world of molecular profiling has undergone revolutionary changes over the last few years as knowledge, technology, and even standard clinical practice have evolved. Broad molecular profiling is now nearly essential for all patients with metastatic solid tumors. New agents have been approved based on molecular testing instead of tumor site of origin. Molecular profiling methodologies have likewise changed such that tests that were performed on patients a few years ago are no longer complete and possibly inaccurate today. As with all rapid change, medical providers can quickly fall behind or struggle to find up-to-date sources to ensure he or she provides optimum care. In this review, the authors provide the current state of the art for molecular profiling/precision medicine, practice standards, and a view into the future ahead.

A Galectin-9-Driven CD11chigh Decidual Macrophage Subset Suppresses Uterine Vascular Remodeling in Preeclampsia.

BACKGROUND: Preeclampsia is a serious disease of pregnancy that lacks early diagnosis methods or effective treatment, except delivery. Dysregulated uterine immune cells and spiral arteries are implicated in preeclampsia, but the mechanistic link remains unclear. METHODS: Single-cell RNA sequencing and spatial transcriptomics were used to identify immune cell subsets associated with preeclampsia. Cell-based studies and animal models including conditional knockout mice and a new preeclampsia mouse model induced by recombinant mouse galectin-9 were applied to validate the pathogenic role of a CD11chigh subpopulation of decidual macrophages (dMφ) and to determine its underlying regulatory mechanisms in preeclampsia. A retrospective preeclampsia cohort study was performed to determine the value of circulating galectin-9 in predicting preeclampsia. RESULTS: We discovered a distinct CD11chigh dMφ subset that inhibits spiral artery remodeling in preeclampsia. The proinflammatory CD11chigh dMφ exhibits perivascular enrichment in the decidua from patients with preeclampsia. We also showed that trophoblast-derived galectin-9 activates CD11chigh dMφ by means of CD44 binding to suppress spiral artery remodeling. In 3 independent preeclampsia mouse models, placental and plasma galectin-9 levels were elevated. Galectin-9 administration in mice induces preeclampsia-like phenotypes with increased CD11chigh dMφ and defective spiral arteries, whereas galectin-9 blockade or macrophage-specific CD44 deletion prevents such phenotypes. In pregnant women, increased circulating galectin-9 levels in the first trimester and at 16 to 20 gestational weeks can predict subsequent preeclampsia onset. CONCLUSIONS: These findings highlight a key role of a distinct perivascular inflammatory CD11chigh dMφ subpopulation in the pathogenesis of preeclampsia. CD11chigh dMφ activated by increased galectin-9 from trophoblasts suppresses uterine spiral artery remodeling, contributing to preeclampsia. Increased circulating galectin-9 may be a biomarker for preeclampsia prediction and intervention.

A scalable unsupervised learning of scRNAseq data detects rare cells through integration of structure-preserving embedding, clustering and outlier detection.

Single-cell RNA-seq analysis has become a powerful tool to analyse the transcriptomes of individual cells. In turn, it has fostered the possibility of screening thousands of single cells in parallel. Thus, contrary to the traditional bulk measurements that only paint a macroscopic picture, gene measurements at the cell level aid researchers in studying different tissues and organs at various stages. However, accurate clustering methods for such high-dimensional data remain exiguous and a persistent challenge in this domain. Of late, several methods and techniques have been promulgated to address this issue. In this article, we propose a novel framework for clustering large-scale single-cell data and subsequently identifying the rare-cell sub-populations. To handle such sparse, high-dimensional data, we leverage PaCMAP (Pairwise Controlled Manifold Approximation), a feature extraction algorithm that preserves both the local and the global structures of the data and Gaussian Mixture Model to cluster single-cell data. Subsequently, we exploit Edited Nearest Neighbours sampling and Isolation Forest/One-class Support Vector Machine to identify rare-cell sub-populations. The performance of the proposed method is validated using the publicly available datasets with varying degrees of cell types and rare-cell sub-populations. On several benchmark datasets, the proposed method outperforms the existing state-of-the-art methods. The proposed method successfully identifies cell types that constitute populations ranging from 0.1 to 8% with F1-scores of 0.91 0.09. The source code is available at https://github.com/scrab017/RarPG.

Cooperative Response to Endocardial Notch Reveals Interaction With Hippo Pathway.

BACKGROUND: The endocardium is a crucial signaling center for cardiac valve development and maturation. Genetic analysis has identified several human endocardial genes whose inactivation leads to bicuspid aortic valve formation and calcific aortic valve disease, but knowledge is very limited about the role played in valve development and disease by noncoding endocardial regulatory regions and upstream factors. METHODS: We manipulated Notch signaling in mouse embryonic endocardial cells by short-term and long-term coculture with OP9 stromal cells expressing Notch ligands and inhibition of Notch activity. We examined the transcriptional profile and chromatin accessibility landscape for each condition, integrated transcriptomic, transcription factor occupancy, chromatin accessibility, and proteomic datasets. We generated in vitro and in vivo models with CRISPR-Cas9-edited deletions of various noncoding regulatory elements and validated their regulatory potential. RESULTS: We identified primary and secondary transcriptional responses to Notch ligands in the mouse embryonic endocardium, and a NOTCH-dependent transcriptional signature in valve development and disease. By defining the changes in the chromatin accessibility landscape and integrating with the landscape in developing mouse endocardium and adult human valves, we identify potential noncoding regulatory elements, validated selected candidates, propose interacting cofactors, and define the timeframe of their regulatory activity. Additionally, we found cooperative transcriptional repression with Hippo pathway by inhibiting nuclear Yap (Yes-associated protein) activity in the endocardium during cardiac valve development. CONCLUSIONS: Sequential Notch-dependent transcriptional regulation in the embryonic endocardium involves multiple factors. Notch activates certain noncoding elements through these factors and simultaneously suppresses elements that could hinder cardiac valve development and homeostasis. Biorxviv: https://www.biorxiv.org/content/10.1101/2023.03.23.533882v1.full.

Plasma S1P Orchestrates the Reverse Transendothelial Migration of Aortic Intimal Myeloid Cells in Mice.

BACKGROUND: Myeloid cells (MCs) reside in the aortic intima at regions predisposed to atherosclerosis. Systemic inflammation triggers reverse transendothelial migration (RTM) of intimal MCs into the arterial blood, which orchestrates a protective immune response that clears intracellular pathogens from the arterial intima. Molecular pathways that regulate RTM remain poorly understood. S1P (sphingosine-1-phosphate) is a lipid mediator that regulates immune cell trafficking by signaling via 5 G-protein-coupled receptors (S1PRs [S1P receptors]). We investigated the role of S1P in the RTM of aortic intimal MCs. METHODS: Intravenous injection of lipopolysaccharide was used to model a systemic inflammatory stimulus that triggers RTM. CD11c+ intimal MCs in the lesser curvature of the ascending aortic arch were enumerated by en face confocal microscopy. Local gene expression was evaluated by transcriptomic analysis of microdissected intimal cells. RESULTS: In wild-type C57BL/6 mice, lipopolysaccharide induced intimal cell expression of S1pr1, S1pr3, and Sphk1 (a kinase responsible for S1P production). Pharmacological modulation of multiple S1PRs blocked lipopolysaccharide-induced RTM and modulation of S1PR1 and S1PR3 reduced RTM in an additive manner. Cre-mediated deletion of S1pr1 in MCs blocked lipopolysaccharide-induced RTM, confirming a role for myeloid-specific S1PR1 signaling. Global or hematopoietic deficiency of Sphk1 reduced plasma S1P levels, the abundance of CD11c+ MCs in the aortic intima, and blunted lipopolysaccharide-induced RTM. In contrast, plasma S1P levels, the abundance of intimal MCs, and lipopolysaccharide-induced RTM were rescued in Sphk1-/- mice transplanted with Sphk1+/+ or mixed Sphk1+/+ and Sphk1-/- bone marrow. Stimulation with lipopolysaccharide increased endothelial permeability and intimal MC exposure to circulating factors such as S1P. CONCLUSIONS: Functional and expression studies support a novel role for S1P signaling in the regulation of lipopolysaccharide-induced RTM and the homeostatic maintenance of aortic intimal MCs. Our data provide insight into how circulating plasma mediators help orchestrate intimal MC dynamics.

Molecular Changes Implicate Angiogenesis and Arterial Remodeling in Systemic Sclerosis-Associated and Idiopathic Pulmonary Hypertension.

BACKGROUND: Pulmonary hypertension (PH) is a common complication of systemic sclerosis (SSc) and a leading cause of mortality among patients with this disease. PH can also occur as an idiopathic condition (idiopathic pulmonary arterial hypertension). Investigation of transcriptomic alterations in vascular populations is critical to elucidating cellular mechanisms underlying pathobiology of SSc-associated and idiopathic PH. METHODS: We analyzed single-cell RNA sequencing profiles of endothelial and perivascular mesenchymal populations from explanted lung tissue of patients with SSc-associated PH (n=16), idiopathic pulmonary arterial hypertension (n=3), and healthy controls (n=15). Findings were validated by immunofluorescence staining of explanted human lung tissue. RESULTS: Three disease-associated endothelial populations emerged. Two angiogenic endothelial cell (EC) subtypes markedly expanded in SSc-associated PH lungs: tip ECs expressing canonical tip markers PGF and APLN and phalanx ECs expressing genes associated with vascular development, endothelial barrier integrity, and Notch signaling. Gene regulatory network analysis suggested enrichment of Smad1 and PPAR-γ (peroxisome proliferator-activated receptor-γ) regulon activities in these 2 populations, respectively. Mapping of potential ligand-receptor interactions highlighted Notch, apelin-APJ, and angiopoietin-Tie signaling pathways between angiogenic ECs and perivascular cells. Transitional cells, expressing both endothelial and pericyte/smooth muscle cell markers, provided evidence for the presence of endothelial-to-mesenchymal transition. Transcriptional programs associated with arterial endothelial dysfunction implicated VEGF-A (vascular endothelial growth factor-A), TGF-ß1, angiotensin, and TNFSF12/TWEAK in the injury/remodeling phenotype of PH arterial ECs. CONCLUSIONS: These data provide high-resolution insights into the complexity and plasticity of the pulmonary endothelium in SSc-associated PH and idiopathic pulmonary arterial hypertension and provide direct molecular insights into soluble mediators and transcription factors driving PH vasculopathy.

Dissecting genetic architecture of rare dystonia: genetic, molecular and clinical insights.

BACKGROUND: Dystonia is one of the most common movement disorders. To date, the genetic causes of dystonia in populations of European descent have been extensively studied. However, other populations, particularly those from the Middle East, have not been adequately studied. The purpose of this study is to discover the genetic basis of dystonia in a clinically and genetically well-characterised dystonia cohort from Turkey, which harbours poorly studied populations. METHODS: Exome sequencing analysis was performed in 42 Turkish dystonia families. Using co-expression network (CEN) analysis, identified candidate genes were interrogated for the networks including known dystonia-associated genes and genes further associated with the protein-protein interaction, animal model-based characteristics and clinical findings. RESULTS: We identified potentially disease-causing variants in the established dystonia genes (PRKRA, SGCE, KMT2B, SLC2A1, GCH1, THAP1, HPCA, TSPOAP1, AOPEP; n=11 families (26%)), in the uncommon forms of dystonia-associated genes (PCCB, CACNA1A, ALDH5A1, PRKN; n=4 families (10%)) and in the candidate genes prioritised based on the pathogenicity of the variants and CEN-based analyses (n=11 families (21%)). The diagnostic yield was found to be 36%. Several pathways and gene ontologies implicated in immune system, transcription, metabolic pathways, endosomal-lysosomal and neurodevelopmental mechanisms were over-represented in our CEN analysis. CONCLUSIONS: Here, using a structured approach, we have characterised a clinically and genetically well-defined dystonia cohort from Turkey, where dystonia has not been widely studied, and provided an uncovered genetic basis, which will facilitate diagnostic dystonia research.

Genome-wide identification of walnut (Juglans regia) PME gene family members and expression analysis during infection with Cryptosphaeria pullmanensis pathogens.

Walnuts exhibit a higher resistance to diseases, though they are not completely immune. This study focuses on the Pectin methylesterase (PME) gene family to investigate whether it is involved in disease resistance in walnuts. These 21 genes are distributed across 12 chromosomes, with four pairs demonstrating homology. Variations in conserved motifs and gene structures suggest diverse functions within the gene family. Phylogenetic and collinear gene pairs of the PME family indicate that the gene family has evolved in a relatively stable way. The cis-acting elements and gene ontology enrichment of these genes, underscores their potential role in bolstering walnuts' defense mechanisms. Transcriptomic analyses were conducted under conditions of Cryptosphaeria pullmanensis infestation and verified by RT-qPCR. The results showed that certain JrPME family genes were activated in response, leading to the hypothesis that some members may confer resistance to the disease.

Exploring the current landscape of single-cell RNA sequencing applications in gastric cancer research.

Gastric cancer (GC) represents a major global health burden and is responsible for a significant number of cancer-related fatalities. Its complex nature, characterized by heterogeneity and aggressive behaviour, poses considerable challenges for effective diagnosis and treatment. Single-cell RNA sequencing (scRNA-seq) has emerged as an important technique, offering unprecedented precision and depth in gene expression profiling at the cellular level. By facilitating the identification of distinct cell populations, rare cells and dynamic transcriptional changes within GC, scRNA-seq has yielded valuable insights into tumour progression and potential therapeutic targets. Moreover, this technology has significantly improved our comprehension of the tumour microenvironment (TME) and its intricate interplay with immune cells, thereby opening avenues for targeted therapeutic strategies. Nonetheless, certain obstacles, including tumour heterogeneity and technical limitations, persist in the field. Current endeavours are dedicated to refining protocols and computational tools to surmount these challenges. In this narrative review, we explore the significance of scRNA-seq in GC, emphasizing its advantages, challenges and potential applications in unravelling tumour heterogeneity and identifying promising therapeutic targets. Additionally, we discuss recent developments, ongoing efforts to overcome these challenges, and future prospects. Although further enhancements are required, scRNA-seq has already provided valuable insights into GC and holds promise for advancing biomedical research and clinical practice.

Molecular classification and biomarkers of outcome with immunotherapy in extensive-stage small-cell lung cancer: analyses of the CASPIAN phase 3 study.

BACKGROUND: We explored potential predictive biomarkers of immunotherapy response in patients with extensive-stage small-cell lung cancer (ES-SCLC) treated with durvalumab (D) + tremelimumab (T) + etoposide-platinum (EP), D + EP, or EP in the randomized phase 3 CASPIAN trial. METHODS: 805 treatment-naïve patients with ES-SCLC were randomized (1:1:1) to receive D + T + EP, D + EP, or EP. The primary endpoint was overall survival (OS). Patients were required to provide an archived tumor tissue block (or ≥ 15 newly cut unstained slides) at screening, if these samples existed. After assessment for programmed cell death ligand-1 expression and tissue tumor mutational burden, residual tissue was used for additional molecular profiling including by RNA sequencing and immunohistochemistry. RESULTS: In 182 patients with transcriptional molecular subtyping, OS with D ± T + EP was numerically highest in the SCLC-inflamed subtype (n = 10, median 24.0 months). Patients derived benefit from immunotherapy across subtypes; thus, additional biomarkers were investigated. OS benefit with D ± T + EP versus EP was greater with high versus low CD8A expression/CD8 cell density by immunohistochemistry, but with no additional benefit with D + T + EP versus D + EP. OS benefit with D + T + EP versus D + EP was associated with high expression of CD4 (median 25.9 vs. 11.4 months) and antigen-presenting and processing machinery (25.9 vs. 14.6 months) and MHC I and II (23.6 vs. 17.3 months) gene signatures, and with higher MHC I expression by immunohistochemistry. CONCLUSIONS: These findings demonstrate the tumor microenvironment is important in mediating better outcomes with D ± T + EP in ES-SCLC, with canonical immune markers associated with hypothesized immunotherapy mechanisms of action defining patient subsets that respond to D ± T. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03043872.

Validation of the RSClin risk calculator in the National Cancer Data Base.

BACKGROUND: Guidelines recommend the use of genomic assays such as OncotypeDx to aid in decisions regarding the use of chemotherapy for hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer. The RSClin prognostic tool integrates OncotypeDx and clinicopathologic features to predict distant recurrence and chemotherapy benefit, but further validation is needed before broad clinical adoption. METHODS: This study included patients from the National Cancer Data Base (NCDB) who were diagnosed with stage I-III HR+/HER2- breast cancer from 2010 to 2020 and received adjuvant endocrine therapy with or without chemotherapy. RSClin-predicted chemotherapy benefit was stratified into low (<3% reduction in distant recurrence), intermediate (3%-5%), and high (>5%). Cox models were used to model mortality adjusted for age, comorbidity index, insurance, and race/ethnicity. RESULTS: A total of 285,441 patients were identified for inclusion from the NCDB, with an average age of 60 years and a median follow-up of 58 months. Chemotherapy was associated with improved overall survival only for those predicted to have intermediate (adjusted hazard ratio [aHR], 0.68; 95% confidence interval [CI], 0.60-0.79) and high benefit per RSClin (aHR, 0.66; 95% CI, 0.61-0.72). Consistent benefit was seen in the subset with a low OncotypeDx score (<26) and intermediate (aHR, 0.66; 95% CI, 0.53-0.82) or high (aHR, 0.71; 95% CI, 0.58-0.86) RSClin-predicted benefit. No survival benefit with chemotherapy was seen in patients with a high OncotypeDx score (≥26) and low benefit per RSClin (aHR, 1.70; 95% CI, 0.41-6.99). CONCLUSIONS: RSClin may identify high-risk patients who benefit from treatment intensification more accurately than OncotypeDx, and further prospective study is needed.

Correlation between breast cancer subtypes determined by immunohistochemistry and n-COUNTER PAM50 assay: a real-world study.

PURPOSE: Molecular subtyping based on gene expression profiling (i.e., PAM50 assay) aids in determining the prognosis and treatment of breast cancer (BC), particularly in hormone receptor (HR)-positive/human epidermal growth factor receptor 2 (HER2)-negative tumors, where luminal A and B subtypes have different prognoses and treatments. Several surrogate classifications have been proposed for distinguishing between the luminal A and B subtypes. This study determines the accuracy of local immunohistochemistry (IHC) techniques for classifying HR-positive/HER2-negative (HR+/HER2-) tumors according to intrinsic subtypes using the nCOUNTER PAM50 assay as reference and the HR status definition according the ASCO/CAP recommendations. METHODS: Molecular subtypes resulting from nCOUNTER PAM50 performed in our laboratory between 2014 and 2020 were correlated with three different proxy surrogates proposed in the literature based on ER, PR, HER2, and Ki67 expression with different cut-off values. Concordance was measured using the level of agreement and kappa statistics. RESULTS: From 1049 samples with the nCOUNTER test, 679 and 350 were luminal A and B subtypes, respectively. Only a poor-to-fair correlation was observed between the three proxy surrogates and real genomic subtypes as determined by nCOUNTER PAM50. Moreover, 5-11% and 18-36% of the nCOUNTER PAM50 luminal B and A tumors were classified as luminal A and B, respectively, by these surrogates. CONCLUSION: The concordance between luminal subtypes determined by three different IHC-based classifiers and the nCOUNTER PAM50 assay was suboptimal. Thus, a significant proportion of luminal A and B tumors as determined by the surrogate classifiers could be undertreated or over-treated.

Clinical evaluation of deep learning-based risk profiling in breast cancer histopathology and comparison to an established multigene assay.

PURPOSE: To evaluate the Stratipath Breast tool for image-based risk profiling and compare it with an established prognostic multigene assay for risk profiling in a real-world case series of estrogen receptor (ER)-positive and human epidermal growth factor receptor 2 (HER2)-negative early breast cancer patients categorized as intermediate risk based on classic clinicopathological variables and eligible for chemotherapy. METHODS: In a case series comprising 234 invasive ER-positive/HER2-negative tumors, clinicopathological data including Prosigna results and corresponding HE-stained tissue slides were retrieved. The digitized HE slides were analysed by Stratipath Breast. RESULTS: Our findings showed that the Stratipath Breast analysis identified 49.6% of the clinically intermediate tumors as low risk and 50.4% as high risk. The Prosigna assay classified 32.5%, 47.0% and 20.5% tumors as low, intermediate and high risk, respectively. Among Prosigna intermediate-risk tumors, 47.3% were stratified as Stratipath low risk and 52.7% as high risk. In addition, 89.7% of Stratipath low-risk cases were classified as Prosigna low/intermediate risk. The overall agreement between the two tests for low-risk and high-risk groups (N = 124) was 71.0%, with a Cohen's kappa of 0.42. For both risk profiling tests, grade and Ki67 differed significantly between risk groups. CONCLUSION: The results from this clinical evaluation of image-based risk stratification shows a considerable agreement to an established gene expression assay in routine breast pathology.

Construction of immune-related gene pairs signature to predict the overall survival of multiple myeloma patients based on whole bone marrow gene expression profiling.

Multiple myeloma (MM) is a plasma cell dyscrasia that is characterized by the uncontrolled proliferation of malignant PCs in the bone marrow. Due to immunotherapy, attention has returned to the immune system in MM, and it appears necessary to identify biomarkers in this area. In this study, we created a prognostic model for MM using immune-related gene pairs (IRGPs), with the advantage that it is not affected by technical bias. After retrieving microarray data of MM patients, bioinformatics analyses like COX regression and least absolute shrinkage and selection operator (LASSO) were used to construct the signature. Then its prognostic value is assessed via time-dependent receiver operating characteristic (ROC) and the Kaplan-Meier (KM) analysis. We also used XCELL to examine the status of immune cell infiltration among MM patients. 6-IRGP signatures were developed and proved to predict MM prognosis with a P-value of 0.001 in the KM analysis. Moreover, the risk score was significantly associated with clinicopathological characteristics and was an independent prognostic factor. Of note, the combination of age and ß2-microglobulin with risk score could improve the accuracy of determining patients' prognosis with the values of the area under the curve (AUC) of 0.73 in 5 years ROC curves. Our model was also associated with the distribution of immune cells. This novel signature, either alone or in combination with age and ß2-microglobulin, showed a good prognostic predictive value and might be used to guide the management of MM patients in clinical practice.

Beyond Hormones: Investigating the Impact of Progesterone Receptor Membrane Component 1 in Lung Adenocarcinoma.

Progesterone Receptor Membrane Component 1 (PGRMC1) is a candidate oncogene with a prominent involvement in the pathogenesis of diverse cancers (ovarian, thyroid, breast, colon, head, and neck). Our study ascertains the ability of PGRMC1 to influence WNT members in the non-small cell lung cancer subtype-lung adenocarcinoma (LUAD) and participates in augmented cell proliferation and migration. Both computational and in vitro experimental analyses were performed in this study. Gene silencing, in vitro assays, gene expression & and protein expression studies were performed to ascertain the role of PGRMC1 in LUAD cells. The computational analysis, PGRMC1 gene level expression was analysed using the microarray gene expression omnibus datasets (GSE27262; GSE18842) to compare LUAD tumours and normal tissues. Concurrently, the gene expression profiling interactive analysis of PGRMC1 and Kaplan-Meier survival analysis revealed a decreasing patient survival rate with an increasing PGRMC1 gene expression in LUAD tumour samples. Interestingly, the experimental gene silencing studies were conducted in vitro (si-PGRMC1 Vs si-Control) to understand the essential role of PGRMC1 in regulating WNT-associated genes (WNT1, WNT5A, and WNT11). Comparative experimental cell migration and spheroid formation assays (si-PGRMC1 Vs si-Control) in vitro showed a strong association between PGRMC1 and LUAD. In vitro expression analysis using real-time PCR and western blot further confirmed the connecting link between PGRMC1 and WNT5A compared to other WNT member genes (WNT1 and WNT11) in LUAD. The computational and experimental analyses agreed with one another.