Graded expression of the chemokine receptor CX3CR1 marks differentiation states of human and murine T cells and enables cross-species interpretation.

T cells differentiate into functionally distinct states upon antigen encounter. These states are delineated by different cell surface markers for murine and human T cells, which hamper cross-species translation of T cell properties. We aimed to identify surface markers that reflect the graded nature of CD8+ T cell differentiation and delineate functionally comparable states in mice and humans. CITEseq analyses revealed that graded expression of CX3CR1, encoding the chemokine receptor CX3CR1, correlated with the CD8+ T cell differentiation gradient. CX3CR1 expression distinguished human and murine CD8+ and CD4+ T cell states, as defined by migratory and functional properties. Graded CX3CR1 expression, refined with CD62L, accurately captured the high-dimensional T cell differentiation continuum. Furthermore, the CX3CR1 expression gradient delineated states with comparable properties in humans and mice in steady state and on longitudinally tracked virus-specific CD8+ T cells in both species. Thus, graded CX3CR1 expression provides a strategy to translate the behavior of distinct T cell differentiation states across species.

Identification of hyperoxidized PRDX3 as a ferroptosis marker reveals ferroptotic damage in chronic liver diseases.

Ferroptosis, a regulated cell death pathway driven by accumulation of phospholipid peroxides, has been challenging to identify in physiological conditions owing to the lack of a specific marker. Here, we identify hyperoxidized peroxiredoxin 3 (PRDX3) as a marker for ferroptosis both in vitro and in vivo. During ferroptosis, mitochondrial lipid peroxides trigger PRDX3 hyperoxidation, a posttranslational modification that converts a Cys thiol to sulfinic or sulfonic acid. Once hyperoxidized, PRDX3 translocates from mitochondria to plasma membranes, where it inhibits cystine uptake, thereby causing ferroptosis. Applying hyperoxidized PRDX3 as a marker, we determined that ferroptosis is responsible for death of hepatocytes in mouse models of both alcoholic and nonalcoholic fatty liver diseases, the most prevalent chronic liver disorders. Our study highlights the importance of ferroptosis in pathophysiological conditions and opens the possibility to treat these liver diseases with drugs that inhibit ferroptosis.

Human Mast Cell Proteome Reveals Unique Lineage, Putative Functions, and Structural Basis for Cell Ablation.

Mast cells are rare tissue-resident cells of importance to human allergies. To understand the structural basis of principle mast cell functions, we analyzed the proteome of primary human and mouse mast cells by quantitative mass spectrometry. We identified a mast-cell-specific proteome signature, indicative of a unique lineage, only distantly related to other immune cell types, including innate immune cells. Proteome comparison between human and mouse suggested evolutionary conservation of core mast cell functions. In addition to specific proteases and proteins associated with degranulation and proteoglycan biosynthesis, mast cells expressed proteins potentially involved in interactions with neurons and neurotransmitter metabolism, including cell adhesion molecules, ion channels, and G protein coupled receptors. Toward targeted cell ablation in severe allergic diseases, we used MRGPRX2 for mast cell depletion in human skin biopsies. These proteome analyses suggest a unique role of mast cells in the immune system, probably intertwined with the nervous system.

Unsupervised discovery of ancestry-informative markers and genetic admixture proportions in biobank-scale datasets.

Admixture estimation plays a crucial role in ancestry inference and genome-wide association studies (GWASs). Computer programs such as ADMIXTURE and STRUCTURE are commonly employed to estimate the admixture proportions of sample individuals. However, these programs can be overwhelmed by the computational burdens imposed by the 105 to 106 samples and millions of markers commonly found in modern biobanks. An attractive strategy is to run these programs on a set of ancestry-informative SNP markers (AIMs) that exhibit substantially different frequencies across populations. Unfortunately, existing methods for identifying AIMs require knowing ancestry labels for a subset of the sample. This supervised learning approach creates a chicken and the egg scenario. In this paper, we present an unsupervised, scalable framework that seamlessly carries out AIM selection and likelihood-based estimation of admixture proportions. Our simulated and real data examples show that this approach is scalable to modern biobank datasets. OpenADMIXTURE, our Julia implementation of the method, is open source and available for free.

Next-generation plasmids for transgenesis in zebrafish and beyond.

Transgenesis is an essential technique for any genetic model. Tol2-based transgenesis paired with Gateway-compatible vector collections has transformed zebrafish transgenesis with an accessible modular system. Here, we establish several next-generation transgenesis tools for zebrafish and other species to expand and enhance transgenic applications. To facilitate gene regulatory element testing, we generated Gateway middle entry vectors harboring the small mouse beta-globin minimal promoter coupled to several fluorophores, CreERT2 and Gal4. To extend the color spectrum for transgenic applications, we established middle entry vectors encoding the bright, blue-fluorescent protein mCerulean and mApple as an alternative red fluorophore. We present a series of p2A peptide-based 3' vectors with different fluorophores and subcellular localizations to co-label cells expressing proteins of interest. Finally, we established Tol2 destination vectors carrying the zebrafish exorh promoter driving different fluorophores as a pineal gland-specific transgenesis marker that is active before hatching and through adulthood. exorh-based reporters and transgenesis markers also drive specific pineal gland expression in the eye-less cavefish (Astyanax). Together, our vectors provide versatile reagents for transgenesis applications in zebrafish, cavefish and other models.

GLDADec: marker-gene guided LDA modeling for bulk gene expression deconvolution.

Inferring cell type proportions from bulk transcriptome data is crucial in immunology and oncology. Here, we introduce guided LDA deconvolution (GLDADec), a bulk deconvolution method that guides topics using cell type-specific marker gene names to estimate topic distributions for each sample. Through benchmarking using blood-derived datasets, we demonstrate its high estimation performance and robustness. Moreover, we apply GLDADec to heterogeneous tissue bulk data and perform comprehensive cell type analysis in a data-driven manner. We show that GLDADec outperforms existing methods in estimation performance and evaluate its biological interpretability by examining enrichment of biological processes for topics. Finally, we apply GLDADec to The Cancer Genome Atlas tumor samples, enabling subtype stratification and survival analysis based on estimated cell type proportions, thus proving its practical utility in clinical settings. This approach, utilizing marker gene names as partial prior information, can be applied to various scenarios for bulk data deconvolution. GLDADec is available as an open-source Python package at https://github.com/mizuno-group/GLDADec.

Biofilm marker discovery with cloud-based dockerized metagenomics analysis of microbial communities.

In an environment, microbes often work in communities to achieve most of their essential functions, including the production of essential nutrients. Microbial biofilms are communities of microbes that attach to a nonliving or living surface by embedding themselves into a self-secreted matrix of extracellular polymeric substances. These communities work together to enhance their colonization of surfaces, produce essential nutrients, and achieve their essential functions for growth and survival. They often consist of diverse microbes including bacteria, viruses, and fungi. Biofilms play a critical role in influencing plant phenotypes and human microbial infections. Understanding how these biofilms impact plant health, human health, and the environment is important for analyzing genotype-phenotype-driven rule-of-life functions. Such fundamental knowledge can be used to precisely control the growth of biofilms on a given surface. Metagenomics is a powerful tool for analyzing biofilm genomes through function-based gene and protein sequence identification (functional metagenomics) and sequence-based function identification (sequence metagenomics). Metagenomic sequencing enables a comprehensive sampling of all genes in all organisms present within a biofilm sample. However, the complexity of biofilm metagenomic study warrants the increasing need to follow the Findability, Accessibility, Interoperability, and Reusable (FAIR) Guiding Principles for scientific data management. This will ensure that scientific findings can be more easily validated by the research community. This study proposes a dockerized, self-learning bioinformatics workflow to increase the community adoption of metagenomics toolkits in a metagenomics and meta-transcriptomics investigation. Our biofilm metagenomics workflow self-learning module includes integrated learning resources with an interactive dockerized workflow. This module will allow learners to analyze resources that are beneficial for aggregating knowledge about biofilm marker genes, proteins, and metabolic pathways as they define the composition of specific microbial communities. Cloud and dockerized technology can allow novice learners-even those with minimal knowledge in computer science-to use complicated bioinformatics tools. Our cloud-based, dockerized workflow splits biofilm microbiome metagenomics analyses into four easy-to-follow submodules. A variety of tools are built into each submodule. As students navigate these submodules, they learn about each tool used to accomplish the task. The downstream analysis is conducted using processed data obtained from online resources or raw data processed via Nextflow pipelines. This analysis takes place within Vertex AI's Jupyter notebook instance with R and Python kernels. Subsequently, results are stored and visualized in Google Cloud storage buckets, alleviating the computational burden on local resources. The result is a comprehensive tutorial that guides bioinformaticians of any skill level through the entire workflow. It enables them to comprehend and implement the necessary processes involved in this integrated workflow from start to finish. This manuscript describes the development of a resource module that is part of a learning platform named "NIGMS Sandbox for Cloud-based Learning" https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [1] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.

Spatiotemporal ATF3 Expression Determines VSMC Fate in Abdominal Aortic Aneurysm.

BACKGROUND: Abdominal aortic aneurysm (AAA) is a catastrophic disease with little effective therapy, likely due to the limited understanding of the mechanisms underlying AAA development and progression. ATF3 (activating transcription factor 3) has been increasingly recognized as a key regulator of cardiovascular diseases. However, the role of ATF3 in AAA development and progression remains elusive. METHODS: Genome-wide RNA sequencing analysis was performed on the aorta isolated from saline or Ang II (angiotensin II)-induced AAA mice, and ATF3 was identified as the potential key gene for AAA development. To examine the role of ATF3 in AAA development, vascular smooth muscle cell-specific ATF3 knockdown or overexpressed mice by recombinant adeno-associated virus serotype 9 vectors carrying ATF3, or shRNA-ATF3 with SM22α (smooth muscle protein 22-α) promoter were used in Ang II-induced AAA mice. In human and murine vascular smooth muscle cells, gain or loss of function experiments were performed to investigate the role of ATF3 in vascular smooth muscle cell proliferation and apoptosis. RESULTS: In both Ang II-induced AAA mice and patients with AAA, the expression of ATF3 was reduced in aneurysm tissues but increased in aortic lesion tissues. The deficiency of ATF3 in vascular smooth muscle cell promoted AAA formation in Ang II-induced AAA mice. PDGFRB (platelet-derived growth factor receptor ß) was identified as the target of ATF3, which mediated vascular smooth muscle cell proliferation in response to TNF-alpha (tumor necrosis factor-α) at the early stage of AAA. ATF3 suppressed the mitochondria-dependent apoptosis at the advanced stage by upregulating its direct target BCL2. Our chromatin immunoprecipitation results also demonstrated that the recruitment of NFκB1 and P300/BAF/H3K27ac complex to the ATF3 promoter induces ATF3 transcription via enhancer activation. NFKB1 inhibitor (andrographolide) inhibits the expression of ATF3 by blocking the recruiters NFKB1 and ATF3-enhancer to the ATF3-promoter region, ultimately leading to AAA development. CONCLUSIONS: Our results demonstrate a previously unrecognized role of ATF3 in AAA development and progression, and ATF3 may serve as a novel therapeutic and prognostic marker for AAA.

mHTT Seeding Activity: A Marker of Disease Progression and Neurotoxicity in Models of Huntington's Disease.

Self-propagating, amyloidogenic mutant huntingtin (mHTT) aggregates may drive progression of Huntington's disease (HD). Here, we report the development of a FRET-based mHTT aggregate seeding (FRASE) assay that enables the quantification of mHTT seeding activity (HSA) in complex biosamples from HD patients and disease models. Application of the FRASE assay revealed HSA in brain homogenates of presymptomatic HD transgenic and knockin mice and its progressive increase with phenotypic changes, suggesting that HSA quantitatively tracks disease progression. Biochemical investigations of mouse brain homogenates demonstrated that small, rather than large, mHTT structures are responsible for the HSA measured in FRASE assays. Finally, we assessed the neurotoxicity of mHTT seeds in an inducible Drosophila model transgenic for HTTex1. We found a strong correlation between the HSA measured in adult neurons and the increased mortality of transgenic HD flies, indicating that FRASE assays detect disease-relevant, neurotoxic, mHTT structures with severe phenotypic consequences in vivo.

Novel markers of MCL1 inhibitor sensitivity in triple-negative breast cancer cells.

Triple-negative breast cancer (TNBC) is an aggressive breast cancer sub-type with limited treatment options and poor prognosis. Currently, standard treatments for TNBC include surgery, chemotherapy, and anti-PDL1 therapy. These therapies have limited efficacy in advanced stages. Myeloid-cell leukemia 1 (MCL1) is an anti-apoptotic BCL2 family protein. High expression of MCL1 contributes to chemotherapy resistance and is associated with a worse prognosis in TNBC. MCL1 inhibitors are in clinical trials for TNBC, but response rates to these inhibitors can vary and predictive markers are lacking. Currently, we identified a 4-member (AXL, ETS1, IL6, EFEMP1) gene signature (GS) that predicts MCL1 inhibitor sensitivity in TNBC cells. Factors encoded by these genes regulate signaling pathways to promote MCL1 inhibitor resistance. Small molecule inhibitors of the GS factors can overcome resistance and sensitize otherwise resistant TNBC cells to MCL1 inhibitor treatment. These findings offer insights into potential therapeutic strategies and tumor stratification for MCL1 inhibitor use in TNBC.

Evolutionary insights into sequence modifications governing chitin recognition and chitinase inactivity in YKL-40 (HC-gp39, CHI3L1).

YKL-40, also known as human cartilage glycoprotein-39 (HC-gp39) or CHI3L1, shares structural similarities with chitotriosidase (CHIT1), an active chitinase, but lacks chitinase activity. Despite being a biomarker for inflammatory disorders and cancer, the reasons for YKL-40's inert chitinase function have remained elusive. This study reveals that the loss of chitinase activity in YKL-40 has risen from multiple sequence modifications influencing its chitin affinity. Contrary to the common belief associating the lack of chitinase activity with amino acid substitutions in the catalytic motif, attempts to activate YKL-40 by creating two amino acid mutations in the catalytic motif (MT-YKL-40) proved ineffective. Subsequent exploration that included creating chimeras of MT-YKL-40 and CHIT1 catalytic domains (CatDs) identified key exons responsible for YKL-40 inactivation. Introducing YKL-40 exons 3, 6, or 8 into CHIT1 CatD resulted in chitinase inactivation. Conversely, incorporating CHIT1 exons 3, 6, and 8 into MT-YKL-40 led to its activation. Our recombinant proteins exhibited properly formed disulfide bonds, affirming a defined structure in active molecules. Biochemical and evolutionary analysis indicated that the reduced chitinase activity of MT-YKL-40 correlates with specific amino acids in exon 3. M61I and T69W substitutions in CHIT1 CatD diminished chitinase activity and increased chitin binding. Conversely, substituting I61 with M and W69 with T in MT-YKL-40 triggered chitinase activity while reducing the chitin-binding activity. Thus, W69 plays a crucial role in a unique subsite within YKL-40. These findings emphasize that YKL-40, though retaining the structural framework of a mammalian chitinase, has evolved to recognize chitin while surrendering chitinase activity.

Dominance complementation of parental heading date alleles of Hd1, Ghd7, DTH8, and PRR37 confers transgressive late maturation in hybrid rice.

Rice (Oryza sativa L.) is a short-day plant whose heading date is largely determined by photoperiod sensitivity (PS). Many parental lines used in hybrid rice breeding have weak PS, but their F1 progenies have strong PS and exhibit an undesirable transgressive late-maturing phenotype. However, the genetic basis for this phenomenon is unclear. Therefore, effective methods are needed for selecting parents to create F1 hybrid varieties with the desired PS. In this study, we used bulked segregant analysis with F1 Ningyou 1179 (strong PS) and its F2 population, and through analyzing both parental haplotypes and PS data for 918 hybrid rice varieties, to identify the genetic basis of transgressive late maturation which is dependent on dominance complementation effects of Hd1, Ghd7, DTH8, and PRR37 from both parents rather than from a single parental genotype. We designed a molecular marker-assisted selection system to identify the genotypes of Hd1, Ghd7, DTH8, and PRR37 in parental lines to predict PS in F1 plants prior to crossing. Furthermore, we used CRISPR/Cas9 technique to knock out Hd1 in Ning A (sterile line) and Ning B (maintainer line) and obtained an hd1-NY material with weak PS while retaining the elite agronomic traits of NY. Our findings clarified the genetic basis of transgressive late maturation in hybrid rice and developed effective methods for parental selection and gene editing to facilitate the breeding of hybrid varieties with the desired PS for improving their adaptability.

Cancer-associated fibroblasts: a versatile mediator in tumor progression, metastasis, and targeted therapy.

Tumor microenvironment (TME) has been demonstrated to play a significant role in tumor initiation, progression, and metastasis. Cancer-associated fibroblasts (CAFs) are the major component of TME and exhibit heterogeneous properties in their communication with tumor cells. This heterogeneity of CAFs can be attributed to various origins, including quiescent fibroblasts, mesenchymal stem cells (MSCs), adipocytes, pericytes, endothelial cells, and mesothelial cells. Moreover, single-cell RNA sequencing has identified diverse phenotypes of CAFs, with myofibroblastic CAFs (myCAFs) and inflammatory CAFs (iCAFs) being the most acknowledged, alongside newly discovered subtypes like antigen-presenting CAFs (apCAFs). Due to these heterogeneities, CAFs exert multiple functions in tumorigenesis, cancer stemness, angiogenesis, immunosuppression, metabolism, and metastasis. As a result, targeted therapies aimed at the TME, particularly focusing on CAFs, are rapidly developing, fueling the promising future of advanced tumor-targeted therapy.

Streptococcus pyogenes Cas9 ribonucleoprotein delivery for efficient, rapid and marker-free gene editing in Trypanosoma and Leishmania.

Kinetoplastids are unicellular eukaryotic flagellated parasites found in a wide range of hosts within the animal and plant kingdoms. They are known to be responsible in humans for African sleeping sickness (Trypanosoma brucei), Chagas disease (Trypanosoma cruzi), and various forms of leishmaniasis (Leishmania spp.), as well as several animal diseases with important economic impact (African trypanosomes, including Trypanosoma congolense). Understanding the biology of these parasites necessarily implies the ability to manipulate their genomes. In this study, we demonstrate that transfection of a ribonucleoprotein complex, composed of recombinant Streptococcus pyogenes Cas9 (SpCas9) and an in vitro-synthesized guide RNA, results in rapid and efficient genetic modifications of trypanosomatids, in marker-free conditions. This approach was successfully developed to inactivate, delete, and mutate candidate genes in various stages of the life cycle of T. brucei and T. congolense, and Leishmania promastigotes. The functionality of SpCas9 in these parasites now provides, to the research community working on these parasites, a rapid and efficient method of genome editing, without requiring plasmid construction and selection by antibiotics but requires only cloning and PCR screening of the clones. Importantly, this approach is adaptable to any wild-type parasite.

Dysregulation of murine long noncoding single-cell transcriptome in nonalcoholic steatohepatitis and liver fibrosis.

LncRNAs comprise a heterogeneous class of RNA-encoding genes typified by low expression, nuclear enrichment, high tissue-specificity, and functional diversity, but the vast majority remain uncharacterized. Here, we assembled the mouse liver noncoding transcriptome from >2000 bulk RNA-seq samples and discovered 48,261 liver-expressed lncRNAs, a majority novel. Using these lncRNAs as a single-cell transcriptomic reference set, we elucidated lncRNA dysregulation in mouse models of high fat diet-induced nonalcoholic steatohepatitis and carbon tetrachloride-induced liver fibrosis. Trajectory inference analysis revealed lncRNA zonation patterns across the liver lobule in each major liver cell population. Perturbations in lncRNA expression and zonation were common in several disease-associated liver cell types, including nonalcoholic steatohepatitis-associated macrophages, a hallmark of fatty liver disease progression, and collagen-producing myofibroblasts, a central feature of liver fibrosis. Single-cell-based gene regulatory network analysis using bigSCale2 linked individual lncRNAs to specific biological pathways, and network-essential regulatory lncRNAs with disease-associated functions were identified by their high network centrality metrics. For a subset of these lncRNAs, promoter sequences of the network-defined lncRNA target genes were significantly enriched for lncRNA triplex formation, providing independent mechanistic support for the lncRNA-target gene linkages predicted by the gene regulatory networks. These findings elucidate liver lncRNA cell-type specificities, spatial zonation patterns, associated regulatory networks, and temporal patterns of dysregulation during hepatic disease progression. A subset of the liver disease-associated regulatory lncRNAs identified have human orthologs and are promising candidates for biomarkers and therapeutic targets.

GOWDL: gene ontology-driven wide and deep learning model for cell typing of scRNA-seq data.

Single-cell RNA-sequencing (scRNA-seq) allows for obtaining genomic and transcriptomic profiles of individual cells. That data make it possible to characterize tissues at the cell level. In this context, one of the main analyses exploiting scRNA-seq data is identifying the cell types within tissue to estimate the quantitative composition of cell populations. Due to the massive amount of available scRNA-seq data, automatic classification approaches for cell typing, based on the most recent deep learning technology, are needed. Here, we present the gene ontology-driven wide and deep learning (GOWDL) model for classifying cell types in several tissues. GOWDL implements a hybrid architecture that considers the functional annotations found in Gene Ontology and the marker genes typical of specific cell types. We performed cross-validation and independent external testing, comparing our algorithm with 12 other state-of-the-art predictors. Classification scores demonstrated that GOWDL reached the best results over five different tissues, except for recall, where we got about 92% versus 97% of the best tool. Finally, we presented a case study on classifying immune cell populations in breast cancer using a hierarchical approach based on GOWDL.

Learning single-cell chromatin accessibility profiles using meta-analytic marker genes.

MOTIVATION: Single-cell assay for transposase accessible chromatin using sequencing (scATAC-seq) is a valuable resource to learn cis-regulatory elements such as cell-type specific enhancers and transcription factor binding sites. However, cell-type identification of scATAC-seq data is known to be challenging due to the heterogeneity derived from different protocols and the high dropout rate. RESULTS: In this study, we perform a systematic comparison of seven scATAC-seq datasets of mouse brain to benchmark the efficacy of neuronal cell-type annotation from gene sets. We find that redundant marker genes give a dramatic improvement for a sparse scATAC-seq annotation across the data collected from different studies. Interestingly, simple aggregation of such marker genes achieves performance comparable or higher than that of machine-learning classifiers, suggesting its potential for downstream applications. Based on our results, we reannotated all scATAC-seq data for detailed cell types using robust marker genes. Their meta scATAC-seq profiles are publicly available at https://gillisweb.cshl.edu/Meta_scATAC. Furthermore, we trained a deep neural network to predict chromatin accessibility from only DNA sequence and identified key motifs enriched for each neuronal subtype. Those predicted profiles are visualized together in our database as a valuable resource to explore cell-type specific epigenetic regulation in a sequence-dependent and -independent manner.

A cyclical marker system enables indefinite series of oligonucleotide-directed gene editing in Chlamydomonas reinhardtii.

CRISPR/Cas9 gene editing in the model green alga Chlamydomonas reinhardtii relies on the use of selective marker genes to enrich for non-selectable target mutations. This becomes challenging when many sequential modifications are required in a single cell line, as useful markers are limited. Here, we demonstrate a cyclical selection process which only requires a single marker gene to identify an almost infinite sequential series of CRISPR-based target gene modifications. We used the NIA1 (Nit1, NR; nitrate reductase) gene as the selectable marker in this study. In the forward stage of the cycle, a stop codon was engineered into the NIA1 gene at the CRISPR target location. Cells retaining the wild-type NIA1 gene were killed by chlorate, while NIA1 knockout mutants survived. In the reverse phase of the cycle, the stop codon engineered into the NIA1 gene during the forward phase was edited back to the wild-type sequence. Using nitrate as the sole nitrogen source, only the reverted wild-type cells survived. By using CRISPR to specifically deactivate and reactivate the NIA1 gene, a marker system was established that flipped back and forth between chlorate- and auxotrophic (nitrate)-based selection. This provided a scarless cyclical marker system that enabled an indefinite series of CRISPR edits in other, non-selectable genes. We demonstrate that this 'Sequential CRISPR via Recycling Endogenous Auxotrophic Markers (SCREAM)' technology enables an essentially limitless series of genetic modifications to be introduced into a single cell lineage of C. reinhardtii in a fast and efficient manner to complete complex genetic engineering.

Comprehensive pan-cancer analysis of the C2ORF40 expression: Infiltration associations and prognostic implications.

In recent years, C2ORF40 has been identified as a tumor suppressor gene with multiple functions, including roles in cell proliferation, migration, and senescence. To explore the role of the C2ORF40 gene in different tumors, we used multiple databases for analysis. Compared to adjacent normal tissues, C2ORF40 is downregulated in a variety of malignant tumors, including tumors such as breast cancer, colorectal cancer, bladder cancer, hepatocellular carcinoma and prostate cancer. Notably, low expression of the gene is significantly associated with poor overall survival and relapse-free survival rates. In specific cancers including colon cancer and prostate cancer, the expression of C2ORF40 is correlated with the infiltration of CAFs. C2ORF40 is also involved in biological processes such as cell apoptosis and regulation of protein stability. In conclusion, C2ORF40 can hold promise as a prognostic marker for pan-cancer analysis.

Upcycling HOXB13: enhancing prostate cancer detection with a novel antibody†.

Prostate cancer is one of the most prevalent and, upon metastasis, deadliest cancers in men. Timely identification is essential for effective treatment. Furthermore, accurate determination of prostatic origin is crucial for personalized therapy once the cancer has spread. However, current prostate cancer screening methods are lacking. A recent article in The Journal of Pathology addresses this issue by utilizing an improved antibody to reevaluate HOXB13 as a lineage marker for prostate cancer. The study's findings support the concept that, despite decreased expression in advanced prostate cancer, HOXB13 remains highly suitable for determining prostatic origin due to its androgen receptor independence, high specificity, and sensitivity. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.