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During the diagnostic workup of lung adenocarcinomas (LAC), pathologists evaluate distinct histological tumor growth patterns. The percentage of each pattern on multiple slides bears prognostic significance. To assist with the quantification of growth patterns, we constructed a pipeline equipped with a convolutional neural network (CNN) and soft-voting as the decision function to recognize solid, micropapillary, acinar, and cribriform growth patterns, and non-tumor areas. Slides of primary LAC were obtained from Cedars-Sinai Medical Center (CSMC), the Military Institute of Medicine in Warsaw and the TCGA portal. Several CNN models trained with 19,924 image tiles extracted from 78 slides (MIMW and CSMC) were evaluated on 128 test slides from the three sites by F1-score and accuracy using manual tumor annotations by pathologist. The best CNN yielded F1-scores of 0.91 (solid), 0.76 (micropapillary), 0.74 (acinar), 0.6 (cribriform), and 0.96 (non-tumor) respectively. The overall accuracy of distinguishing the five tissue classes was 89.24%. Slide-based accuracy in the CSMC set (88.5%) was significantly better ( p  < 2.3E-4) than the accuracy in the MIMW (84.2%) and TCGA (84%) sets due to superior slide quality. Our model can work side-by-side with a pathologist to accurately quantify the percentages of growth patterns in tumors with mixed LAC patterns.

Neoadjuvant chemotherapy (NAC) prior to surgery and immune checkpoint therapy (ICT) have revolutionized bladder cancer management. However, stratification of patients that would benefit most from these modalities remains a major clinical challenge. Here, we combine single nuclei RNA sequencing with spatial transcriptomics and single-cell resolution spatial proteomic analysis of human bladder cancer to identify an epithelial subpopulation with therapeutic response prediction ability. These cells express Cadherin 12 ( CDH12, N-Cadherin 2 ), catenins, and other epithelial markers. CDH12-enriched tumors define patients with poor outcome following surgery with or without NAC. In contrast, CDH12-enriched tumors exhibit superior response to ICT. In all settings, patient stratification by tumor CDH12 enrichment offers better prediction of outcome than currently established bladder cancer subtypes. Molecularly, the CDH12 population resembles an undifferentiated state with inherently aggressive biology including chemoresistance, likely mediated through progenitor-like gene expression and fibroblast activation. CDH12-enriched cells express PD-L1 and PD-L2 and co-localize with exhausted T-cells, possibly mediated through CD49a ( ITGA1 ), providing one explanation for ICT efficacy in these tumors. Altogether, this study describes a cancer cell population with an intriguing diametric response to major bladder cancer therapeutics. Importantly, it also provides a compelling framework for designing biomarker-guided clinical trials. The identification of response biomarkers for surgery, chemotherapy and immune checkpoint therapy in bladder cancer is crucial. Here, single nuclei RNA sequencing and spatial profiling identify a cancer cell population expressing Neural Type Cadherin 2 that associates with distinct treatment outcomes.

Gene expression signatures are commonly used as predictive biomarkers, but do not capture structural features within the tissue architecture. Here we apply a 2-step machine learning framework for quantitative imaging of tumor vasculature to derive a spatially informed, prognostic gene signature. The trained algorithms classify endothelial cells and generate a vascular area mask (VAM) in H&E micrographs of clear cell renal cell carcinoma (ccRCC) cases from The Cancer Genome Atlas (TCGA). Quantification of VAMs led to the discovery of 9 vascular features (9VF) that predicted disease-free-survival in a discovery cohort (n = 64, HR = 2.3). Correlation analysis and information gain identified a 14 gene expression signature related to the 9VF’s. Two generalized linear models with elastic net regularization (14VF and 14GT), based on the 14 genes, separated independent cohorts of up to 301 cases into good and poor disease-free survival groups (14VF HR = 2.4, 14GT HR = 3.33). For the first time, we successfully applied digital image analysis and targeted machine learning to develop prognostic, morphology-based, gene expression signatures from the vascular architecture. This novel morphogenomic approach has the potential to improve previous methods for biomarker development.

BackgroundSpatial multiomics is an emerging field with the potential to transform our understanding of biology and disease, accelerate drug development, and redefine pathology. While spatial transcriptomics has advanced significantly, there remains a critical need for in situ sequencing of variable transcript regions at single-cell resolution in both blood and tissue samples. This is particularly relevant for immune repertoire profiling, where spatial mapping of B and T cell clonotypes offers valuable biological insight.Here, we present Direct-Seq™, a novel technology built on the G4X™ platform that enables in situ sequencing of RNA at subcellular resolution. We applied Direct-Seq to sequence the diverse IgH and TCRβ antigen receptor regions in peripheral blood mononuclear cells (PBMCs), formalin-fixed paraffin-embedded (FFPE) tissues, and fresh frozen (FF) human tonsils.MethodsUsing oligonucleotide probes designed to target the variable (V) and joining (J) regions flanking the highly diverse CDR3 region of IgH and TCRβ transcripts, we performed in situ reverse transcription and clonal amplification on fixed non-stimulated PBMCs. Sequencing was conducted using Singular Genomics’ sequencing-by-synthesis (SBS) chemistry. For tissue applications, 5-µm FFPE tonsil sections were transferred to G4X slides, deparaffinized, and subjected to antigen retrieval. Similarly, 10-µm FF tonsil sections were permeabilized and processed using the same Direct-Seq workflow.ResultsDirect-Seq successfully profiled up to 30% of B cells (relative to CD19+) and T cells (relative to CD3+) in PBMCs. In FFPE tonsil tissue, up to 9% of B cells were captured, while in FF tissue, we detected approximately 20% of both B and T cells. In all sample types, we observed extensive CDR3 sequence diversity. Notably, clonally expanded B cells with identical CDR3 sequences were spatially clustered within germinal centers of the tonsil, demonstrating the high-resolution clonotyping capabilities of Direct-Seq.Furthermore, Direct-seq was combined with multiplexed protein detection using immune-specific markers in the same tissue sections. The results confirmed the spatial correlation between transcript identity and phenotypic protein expression.ConclusionsIn summary, Direct-Seq enables direct, spatially resolved sequencing of IgH and TCRβ transcripts in PBMCs, FFPE and FF tissue samples, uncovering immune cell clonality and distribution. When integrated with high-plex proteomic data, Direct-Seq offers a powerful tool for advancing spatial immunology and disease research.

Cancer immunotherapy trials have had variable success, prompting a search for biomarkers of response. Tertiary lymphoid structures (TLS) have emerged as prognostic for multiple tumor types. These ectopic immunological bodies resemble secondary lymphoid organs with segregated B and T cell zones, but they are heterogeneous in their organization and cellular composition. These features have consequences in terms of prognostication and disease clearance, so there is interest in what drives TLS heterogeneity and corresponding immunological responses. We applied single RNA molecule resolution imaging to study biopsies from triple negative breast tumors harboring TLS where the biopsies were taken longitudinally, prior to therapy, after pembrolizumab and after pembrolizumab with radiation therapy. We developed a computational framework to identify TLS and tumor beds and to align spatial trajectories between the immune and malignant structures for systematic analyses. We identified two tumor types based on immune infiltration profiles in the tumor bed. Immune “infiltrated” tumors were eliminated after pembrolizumab, while “non-infiltrated” tumors saw gains in effector T cells and myeloid cells after pembrolizumab and were cleared after pembrolizumab with RT. TLS from infiltrated tumors had better separation of B and T cell zones and had higher expression of immunoreactivity gene pathways in most cell types. Further, malignant cell MHC expression was higher in the tumor beds of infiltrated tumors, providing one plausible mechanism for the groupings. In non-infiltrated tumors, classical dendritic cells enter the tumor bed from TLS proximal zones after pembrolizumab and bring transcription of the CXCL9 chemokine, which can recruit T cells and promote T cell effector phenotypes and was higher in infiltrated tumors at baseline.

Developmental genes in metazoan genomes are surrounded by dense clusters of conserved noncoding elements (CNEs). CNEs exhibit unexplained extreme levels of sequence conservation, with many acting as developmental long-range enhancers. Clusters of CNEs define the span of regulatory inputs for many important developmental regulators and have been described previously as genomic regulatory blocks (GRBs). Their function and distribution around important regulatory genes raises the question of how they relate to 3D conformation of these loci. Here, we show that clusters of CNEs strongly coincide with topological organisation, predicting the boundaries of hundreds of topologically associating domains (TADs) in human and Drosophila . The set of TADs that are associated with high levels of noncoding conservation exhibit distinct properties compared to TADs devoid of extreme noncoding conservation. The close correspondence between extreme noncoding conservation and TADs suggests that these TADs are ancient, revealing a regulatory architecture conserved over hundreds of millions of years. Metazoan genomes contain many clusters of conserved noncoding elements. Here, the authors provide evidence that these clusters coincide with distinct topologically associating domains in humans and Drosophila , revealing a conserved regulatory genomic architecture.

The blond Irishman bought the car used in the Real IRA attack at Ealing from a dealer a fortnight ago. He paid pounds 424 cash for the e-registered grey Saab 9000. Deputy Assistant CommissionerDavid Fry, head of the Yard's Anti- Terrorist Branch, said: \"This was a calculated evil act by people who are seeking to maim and kill. \"The task for the police was made much more difficult, if not impossible, by the failure to give a precise location. \"It is fortunate indeed that we are not dealing with mass murder and people critically injured. \"This was a barbaric act on the streets of our capital city. I am satisfied it is an evil deed committed by a dissident republican group and it has similarities to other attacks we have suffered in the capital and in Northern Ireland perpetrated by the Real IRA.\" DID YOU SEE IT? A police image of a Saab 9000 like the bomb car; INJURED: [Richard Seaman] yesterday; RESCUE: Pub DJ [Stuart Bottomley]; IN RUINS: Shattered shops and debris in the street at; Ealing yesterday. The bomb left 80 shops flooded from a burst water main and caused road and rail chaos; SCARED: Danielle

The blond Irishman bought the car used in the Real IRA attack at Ealing from a dealer a fortnight ago. He paid pounds 424 cash for the e-registered grey Saab 9000. DID YOU SEE IT? A police image of a Saab 9000 like the bomb car; INJURED: [Richard Seaman] yesterday; RESCUE: Pub DJ [Stuart Bottomley]; IN RUINS: Shattered shops and debris in the street at; Ealing yesterday. The bomb left 80 shops flooded from a burst water main and caused road and rail chaos; SCARED: Danielle

The thioredoxin system, which consists of thioredoxin (Trx), nicotinamide adenine dinucleotide phosphate (NADPH) and thioredoxin reductase (TrxR), has emerged as a major anti-oxidant involved in the maintenance of cellular physiology and survival. Dysregulation in this system has been associated with metabolic, cardiovascular, and malignant disorders. Thioredoxin-interacting protein (TXNIP), also known as vitamin D-upregulated protein or thioredoxin-binding-protein-2, functions as a physiological inhibitor of Trx, and pathological suppression of Trx by TXNIP has been demonstrated in diabetes and cardiovascular diseases. Furthermore, TXNIP effects are partially Trx-independent; these include direct activation of inflammation and inhibition of glucose uptake. Many of the effects of TXNIP are initiated by its dissociation from intra-nuclear binding with Trx or other SH-containing proteins: these effects include its migration to cytoplasm, modulating stress responses in mitochondria and endoplasmic reticulum, and also potentially activating apoptotic pathways. TXNIP also interacts with the nitric oxide (NO) signaling system, with apparent suppression of NO effect. TXNIP production is modulated by redox stress, glucose levels, hypoxia and several inflammatory activators. In recent studies, it has been shown that therapeutic agents including insulin, metformin, angiotensin converting enzyme inhibitors and calcium channel blockers reduce TXNIP expression, although it is uncertain to what extent TXNIP suppression contributes to their clinical efficacy. This review addresses the role of TXNIP in health and in cardiovascular and metabolic disorders. Finally, the potential advantages (and disadvantages) of pharmacological suppression of TXNIP in cardiovascular disease and diabetes are summarized