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Tumor-Intrinsic Blood and Imaging Correlatives in Advanced Prostate Cancer Treated with Combination Radiopharmaceutical Therapy and Immunotherapy.

The PRINCE trial showed the clinical activity for 177Lu-PSMA-617 in combination with pembrolizumab for metastatic castration-resistant prostate cancer. To refine patient selection and improve response monitoring strategies to this combination, we investigated candidate tumor-intrinsic biomarkers of treatment response and resistance. Methods: We performed circulating tumor DNA (ctDNA), circulating tumor cell (CTC), and PET imaging analyses at baseline, 12 wk on-treatment, and disease progression in participants enrolled in PRINCE (n = 37). We performed targeted sequencing for ctDNA quantification and genomic analysis of more than 70 prostate cancer genes. CTC enumeration was performed on the EpicSciences platform and was combined with selective single-cell whole-genome sequencing. PET imaging included serial PSMA PET as well as 18F-FDG PET imaging at baseline. Results: A low baseline ctDNA fraction and high PSMA avidity in metastatic lesions were linked to superior treatment responses and may have composite biomarker value. Genomic alterations in tumor suppressor genes TP53, RB1, or PTEN were associated with higher 18F-FDG avidity and metabolic tumor volume on 18F-FDG PET imaging and worse prognosis. At 12-wk on-treatment, both ctDNA detection and PSMA PET imaging were strong indicators of response depth and durability. At disease progression, PSMA expression on PET imaging was lower compared with baseline and supported by subclonal remodeling of ctDNA and CTC copy number profiles and by clonal expansions of tumor suppressor gene mutations. Conclusion: We provide the first integrated molecular and imaging insights into determinants of response and resistance to combined radiopharmaceutical therapy and immunotherapy in prostate cancer and propose biomarker strategies to inform future clinical development.

177Lu-PSMA-617↗

Diversification of yeast proteins as an approach for the development of sustainable food systems.

Despite growing trend in sustainable protein sources, yeast proteins have mainly been explored as a source of bioactive peptides using a monospecies and general protein approach. The contribution of highly abundant protein fractions in the yeast proteome to peptide formation remains insufficiently investigated, limiting a comprehensive understanding of yeast proteins as optimized peptide sources. The current review presents a systematic analysis of yeast proteins as emerging protein sources and evaluates the suitability of high-abundance proteins as bioactive peptide precursors by in silico techniques. Moreover, brewery by-product and single-cell yeast protein approaches are compared in terms of composition and techno-functionality whereas peptide formation mechanisms (in situ and ex situ) and regulatory aspects for food applications are also addressed. Cytoplasmic metabolic proteins, particularly glycolytic enzymes (GAPDH), are identified as highly abundant fractions of the yeast proteome. Proteins associated with cell and organelle membranes also contribute substantially based on cellular localization. These findings imply that such proteins may act as key precursors of yeast-derived bioactive peptides. In silico hydrolysis with Alcalase suggests a tendency toward the generation of short-chain peptides (3-11/14 aa), which may support biological activity. Moreover, peptide profiles appear to vary across yeast species, highlighting the role of species diversity in peptide generation. While single-cell yeast protein allows more controlled production than brewery by-products, nucleic acid content in both may limit applications. Overall, yeast proteins appear to be metabolically adaptable and species-diverse sources for various biological peptides.

Saccharomyces cerevisiae↗

MX1 promotes gastric cancer cell migration via inhibiting ANXA2 ubiquitination and degradation.

Gastric cancer (GC) is a globally lethal malignancy, with invasion and metastasis driving treatment failure and poor prognosis. MX dynamin like GTPase 1 (MX1) shows tumor-specific functional heterogeneity, while its expression, biological functions and molecular mechanisms in GC remain unclear. Here, we explored MX1's clinical significance and its regulatory mechanism in GC cell migration. We integrated public databases and institutional paired clinical samples for bioinformatics analysis of MX1's correlation with clinical outcomes, and verified its pro-migratory effect via Transwell and wound healing assays. Co-immunoprecipitation/mass spectrometry (Co-IP/MS), immunofluorescence and ubiquitination assays were used to identify MX1-interacting proteins and dissect the underlying mechanism, and the Genomics of Drug Sensitivity in Cancer database was applied for chemosensitivity analysis. MX1 was aberrantly upregulated in GC tissues and served as an independent prognostic biomarker, with high expression associated with shortened overall, first-progression and post-progression survival. MX1 promoted GC cell migration and epithelial-mesenchymal transition pathway enrichment, and directly bound Annexin A2 (ANXA2) in the cytoplasm; both were co-enriched in endothelial and epithelial cells by single-cell sequencing. MX1 dose-dependently upregulated ANXA2 protein (without affecting its mRNA) by inhibiting NEDD4L/TRIM65-mediated ANXA2 ubiquitination and degradation, enhancing ANXA2 stability. Additionally, high MX1 expression correlated with increased paclitaxel sensitivity in GC patients based on database analysis, and CCK-8 assays confirmed that MX1 overexpression significantly reduced the paclitaxel IC50 in gastric cancer cells, supporting its potential as a predictive biomarker for paclitaxel efficacy. This study demonstrates that MX1 promotes GC cell migration by suppressing ANXA2 ubiquitination and degradation, highlighting the critical role of the MX1-ANXA2 axis in GC progression. These findings provide novel molecular targets and theoretical support for GC prognostic evaluation, individualized chemotherapy and targeted therapy.

ANXA2↗

Antibody-drug conjugates against multidrug-resistant cancers: Biomarker-guided patient selection, payload engineering, linker chemistry, and bystander effects.

Antibody-drug conjugates (ADCs) are one of the most significant advancements in modern cancer therapeutics. Combining the target selectivity of monoclonal antibodies with the cytotoxic potential of payloads, ADCs effectively kill cancer cells and offer hope to patients with even refractory cancer types. Beyond simply increasing the number of therapeutic options available for cancer patients, ADCs have become a powerful frontline agent in overcoming multidrug resistance (MDR). As one of the most challenging obstacles to effective cancer care, MDR is mediated by ATP-binding cassette (ABC) transporter-mediated drug efflux, target-based mutations, and dysregulated apoptosis. The clinical success of ADCs specifically engineered to overcome MDR, including in heterogeneous tumors and cancer cells that exhibit bypass signaling, is well established. This is especially evident with trastuzumab deruxtecan (T-DXd) in HER2-low, HER2-positive, and HER2-mutant cancers; sacituzumab govitecan (SG) in TROP2-expressing triple-negative breast cancer (TNBC) and urothelial carcinoma; and enfortumab vedotin in Nectin-4-positive bladder cancer. By overcoming MDR, ADCs have enabled more effective treatment algorithms across multiple malignancies. Most importantly, the clinical application of ADCs has become inextricably linked to cancer genomics. HER2 testing has evolved from a two-tiered system to a continuous spectrum including HER2-ultralow, HER2-low, HER2-positive, and ERBB2-mutant categories. Each of these categories exhibits different eligibility guidelines for ADC patient selection. As cancer cells continue to evolve and develop resistance to even ADCs through mutations and variants, researchers and clinicians have used pharmacogenomics to predict ADC response and resistance. To define the genomic architecture of ADC-resistant tumor subpopulations, single-cell transcriptomic studies and liquid biopsy approaches are being used to enable real-time examination of the tumor genome during ADC therapy, thereby optimizing treatment and circumventing resistance driven by emerging mutations and variants. This review provides a comprehensive analysis of the molecular structure of ADCs, the pharmacological principles underlying their potent cytotoxic activity against MDR cancer cells, the genomic and transcriptomic biomarkers that guide ADC patient selection, and the emerging resistance mechanisms that will shape the next generation of promising ADC development.

Humans↗

Single-cell transcriptomic landscape of the southern green stink bug (Nezara viridula) midgut.

BACKGROUND: The southern green stink bug (SGSB), Nezara viridula, is a globally distributed hemipteran pest that damages many economically important crops. Its midgut supports digestion, defense, symbiosis, and interactions with orally delivered control agents, yet the cellular composition of this tissue remains poorly characterized. We therefore developed a single-cell transcriptomic atlas of the N. viridula midgut. RESULTS: Single-cell RNA sequencing of two biological replicates yielded a quality-filtered data set of 13,763 cells. Unsupervised clustering identified 12 transcriptionally distinct populations with putative annotations, including a stem cell/enteroblast (SC/EB)-like population, seven enterocyte-related populations, goblet-like cells, enteroendocrine cells, visceral muscle cells, and an extracellular-matrix-associated epithelial population. Enterocyte-related populations accounted for more than 77% of recovered cells. Putative annotations were assigned primarily from marker gene enrichment and homology to markers reported in other insects. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses identified population-associated functional enrichment patterns, and pseudotime analysis suggested transcriptional relationships between the SC/EB-like population and several enterocyte- and secretory-associated populations without establishing developmental lineages. Immune- and defense-associated transcripts were preferentially enriched in the pEC2 population, and genes associated with symbiont recognition, insecticide action, xenobiotic transport, and orally delivered double-stranded RNA showed population-biased expression. Descriptive comparisons with published insect midgut data sets identified shared and data-set-specific patterns among annotated populations. CONCLUSION: This atlas provides the first single-cell transcriptomic resource for a stink bug midgut and establishes a descriptive cellular framework for SGSB midgut biology. The dataset prioritizes candidate genes and cell populations for future spatial validation, functional testing, and studies of hemipteran midgut physiology, symbiosis, immunity, and pest-management-relevant traits. © 2026 Society of Chemical Industry.

Nezara viridula↗

Genomic characterization of a hypervirulent Aeromonas veronii NN0115 from Nile tilapia and head kidney transcriptome of infected fish reveals B-cell-dominated immune response with specific immunoglobulin downregulation.

Aeromonas veronii is a pathogen of multiple fish species, yet systematic understanding of its infection in Nile tilapia (Oreochromis niloticus) remains limited. A dominant strain, NN0115, was isolated from a natural outbreak and identified as A. veronii by 16S rRNA and whole-genome average nucleotide identity (ANI, 96.33%). Experimental infection revealed high virulence (LD50 = 3.41 × 106 CFU/mL, equivalent to 8.53 × 104 CFU/fish). The genome is 4.58 Mb (58.57% GC) and encodes 4216 proteins. Virulence factor analysis identified 1253 genes, dominated by motility-related (264) and immune modulation (208) factors. Genomic island GI2 harbors 7 virulence genes and two dual-function resistance-virulence genes. The strain is resistant to 9 of 25 agents tested but carries three RND efflux pump genes whose predicted resistance was not phenotypically observed. The head kidney transcriptome of tilapia at 24 h post-bacterial infection identified 773 differentially expressed genes; among them, 57 were immunoglobulin (Ig) genes, and 56 were down-regulated. Integration of published single-cell transcriptomic data showed that non-Ig B-cell marker genes were down-regulated by 32%, whereas Ig genes were reduced by 63%, indicating selective transcriptional suppression of Ig genes rather than a general decrease in B-cell transcriptional activity. Together, this study provides a comprehensive characterization of a highly virulent A. veronii from Nile tilapia and reveals that selective downregulation of B-cell Ig genes is the dominant transcriptional feature of the host head kidney response.

Animals↗

Single-cell sequencing reveals synovial fluid γδ T-cell expansion in equine experimental osteoarthritis.

OBJECTIVE: Define temporal cellular changes following joint injury using single-cell RNA sequencing in experimental equine posttraumatic osteoarthritis (PTOA). METHODS: PTOA was induced in 4 Quarter Horses (3 to 5 years) via carpal osteochondral fragmentation and high-speed treadmill exercise. Synovial fluid (SF) cells and synovium were sampled over 18 weeks (November 2023 to April 2024). Single-cell suspensions were processed (10x Genomics Chromium iX), then aligned to the equine genome (Cell Ranger). Downstream analysis was completed in the R Seurat package. Differential gene expression (log2[fold change] > 1; P < .05) and differential abundance analyses were performed (P < .1). RESULTS: Cartilage injury had a modest impact on gene expression changes and cell abundance shifts in SF. Integrated analysis of 90,323 SF cells across 4 time points revealed 9 distinct cell types, primarily T cells (73 &#xb1; 19%) followed by myeloid cells (20 &#xb1; 13%). Subcluster analysis of T cells revealed 9 transcriptomically distinct subtypes (3 CD8, 2 CD4, 3 &#x3b3;&#x3b4;, and 1 cycling). Differential abundance analyses of temporal changes identified increased &#x3b3;&#x3b4; T and decreased CD4+ T-cell subsets in joints over time. Expanded populations of IL-23 receptor-positive &#x3b3;&#x3b4; T cells exhibited increased T-helper 17 signatures. CONCLUSIONS: IL-23 receptor-positive &#x3b3;&#x3b4; T-cell expansion, associated with joint inflammation, occurred in PTOA. Limitations include small sample size and individual heterogeneity; further investigation over extended timeframe is necessary to confirm whether later stages of the experimental model reflect natural chronic OA. CLINICAL RELEVANCE: Cellular immunotherapy targeting &#x3b3;&#x3b4; T cells and IL-23/IL-17 blockade may warrant investigation to mitigate equine OA progression.

equine↗

Dynamic evolution of chaperone-mediated autophagy is associated with tumor microenvironment remodeling and prognostic stratification in lung adenocarcinoma: insights from single-cell transcriptomics, ensemble machine learning, and experimental validation.

BACKGROUND: Lung adenocarcinoma (LUAD) shows prognostic heterogeneity, and tumor-node-metastasis (TNM) staging is limited for individualized management. Chaperone-mediated autophagy (CMA) maintains proteostasis, but its role during adenocarcinoma in situ (AIS)-minimally invasive adenocarcinoma (MIA)-invasive adenocarcinoma (IAC) progression remains unclear. METHODS: Single-cell RNA sequencing (scRNA-seq) data from GSE189357 and bulk transcriptomes from The Cancer Genome Atlas (TCGA)-LUAD and Gene Expression Omnibus (GEO) cohorts were integrated. CMA activity, cell-cell communication, weighted gene co-expression network analysis (WGCNA), tumor-normal differential expression, machine-learning survival modeling, tumor microenvironment (TME) features, drug sensitivity, and EPC1 function were analyzed. RESULTS: CMA-high tumor epithelial cells increased from AIS (58.1%) to MIA (65.7%) but declined in IAC (44.4%; p < 0.001). CMA-low cells preferentially received fibroblast-derived extracellular matrix cues. A CMA-negatively correlated module identified 69 core genes. Random survival forest (RSF) performed best among 117 machine-learning combinations (mean concordance index > 0.873). High-risk patients had worse survival across cohorts, and the risk score was independently associated with overall survival (hazard ratio = 16.013, 95% confidence interval: 9.579-26.768, p < 0.001). High-risk tumors showed proliferative activation and M0 macrophage enrichment, whereas low-risk tumors showed stronger immune-related signaling. EPC1 overexpression suppressed malignant phenotypes in A549 cells. CONCLUSION: CMA dynamics are associated with stromal and immune remodeling during LUAD progression. A CMA-based model provides robust prognostic stratification and may offer a basis for future TME-guided studies.

Chaperone-mediated autophagy↗

Lactylation-related immune-metabolic dysregulation defines prognostic and therapeutic stratification in lung adenocarcinoma.

BACKGROUND: Lactylation links lactate metabolism with inflammatory signaling and immune regulation in tumors. However, its cellular distribution and translational value in lung adenocarcinoma (LUAD) remain unclear. METHODS: Single-cell RNA-sequencing datasets GSE189357 and GSE171145 were integrated to characterize lactylation-related activity, intercellular communication, and malignant epithelial cell states in LUAD. Single-cell-derived lactylation-related differentially expressed genes were mapped to TCGA-LUAD and multiple GEO cohorts. Univariate Cox regression and machine learning algorithms were used to construct a lactylation-related prognostic signature (LRPS). The associations of LRPS with prognosis, immunotherapy response, drug sensitivity, genomic alterations, immune infiltration, and inflammation- and metabolism-related pathways were evaluated. KRT7 was further validated using virtual knockout analysis, spatial transcriptomics, and in vitro and in vivo experiments. RESULTS: lactylation-related transcriptional activity showed heterogeneous distribution across LUAD cell populations and was associated with altered cell-cell communication. In malignant epithelial cells, LRTS-high and LRTS-low states exhibited distinct metabolic, inflammatory, and tumor-related pathway activities. LRPS showed stable prognostic performance in TCGA-LUAD and multiple GEO cohorts and remained an independent prognostic factor. Low LRPS was associated with greater potential benefit from immunotherapy, whereas different LRPS groups displayed distinct drug sensitivity, genomic alteration, and immune microenvironment patterns. KRT7 was highly expressed in LUAD and associated with poor prognosis. KRT7 knockdown suppressed LUAD cell proliferation, migration, invasion, colony formation, and tumor growth in vivo. CONCLUSIONS: This study identifies lactylation-related immune-metabolic dysregulation as a clinically relevant feature of LUAD and develops a single-cell-guided LRPS for prognosis and therapeutic stratification. KRT7 emerged as an LRPS-related functional candidate with experimentally supported roles in malignant LUAD phenotypes.

Immunotherapy↗

Atherosclerotic plaque fibroblasts derive from adventitial and medial Pdgfra-lineage-positive cells and predominantly maintain fibroblast identity.

AIMS: Fibroblasts are mesenchymal cells in the healthy vascular adventitia. In atherosclerosis, single-cell sequencing datasets suggest fibroblasts are abundant in plaques. However, their identity, origin, and fate during plaque progression remain unclear, which we aim to unravel here. APPROACH AND RESULTS: To robustly define fibroblast identity, origin, and fate, we employed meta-analyses of 54 single-cell RNA sequencing libraries, including murine smooth muscle cell (Myh11) and endothelial cell (EC) (Cdh5) lineage reporter mice with and without atherosclerosis; human control and atherosclerotic arteries; and murine adventitia and atherosclerotic plaques processed separately from low-density lipoprotein (LDL) receptor knockout (Ldlr-/-) mice. These meta-analyses showed that murine and human plaque fibroblast identity was robustly defined by Pdgfra, Pi16, Cygb, and Serpinf1 mRNA. Ninety-five percent of plaque fibroblasts do not derive from the Myh11 lineage, while no Cdh5-lineage-positive cells were present in the fibroblast cluster. We identified five murine arterial fibroblast subsets in atherosclerotic murine aorta: progenitor fibroblasts, matrix fibroblasts, inflammatory fibroblasts, an EC-like fibroblast subset, detected in both adventitia and plaques, and Col5a3+ fibroblasts, unique to the adventitia. We next studied fibroblast identity, origin, and fate using pseudotime analysis and Pdgfra-CreERT2/tdTomato lineage reporter mice (Pdgfra Lin+). Healthy Pdgfra Lin+ reporter mice showed predominant adventitial tdTomato expression, and infrequent medial and intimal Pdgfra Lin+ cells co-expressing MYH11 and PECAM1, respectively. The Pdgfra Lin+ plaque area increased with diet duration. Pdgfra Lin+ cells largely maintain fibroblast identity in the plaque, while <10% co-express SMC markers (MYH11, SM22&#x3b1;), or contribute to ACTA2+ cap cells. ECs gaining mesenchymal markers are transcriptionally distinct from Cdh5-lineage-negative fibroblasts gaining EC markers. Plaque-resident EC-like fibroblasts displayed a mesenchymal-to-endothelial transition transcriptome, which was induced in human primary fibroblasts in vitro by starvation, and dampened or reversed by IL1B, TGFB1, TGFB3, and oxidized LDL. Cross-species integration showed that all murine plaque fibroblasts were conserved in human atherosclerosis, with one additional subset partially resembling murine subsets, and three human-specific subsets. Importantly, human fibroblast subsets differentially correlated to human plaque traits, with EC-like fibroblasts correlating to plaque instability. CONCLUSION: Our results indicate that 95% of plaque-residing fibroblasts are Myh11 Lin- Plaque fibroblasts have a dual origin, predominantly adventitial Pdgfra Lin+ progenitor fibroblasts, with a minor contribution from medial Pdgfra Lin+ &#xa0;Myh11+ SMCs. Most plaque fibroblasts maintain fibroblast identity. Murine plaque fibroblast subsets were conserved in human atherosclerosis. EC-like fibroblasts are linked to human plaque instability. Intervening in progenitor-to-specific fibroblast transitions could present a new avenue to promote plaque stability in atherosclerosis.

Atherosclerosis↗

Pan-cancer single-cell atlas of immunotherapy response identifies ZNF385A as a regulator of immune evasion in small cell lung cancer.

Although immune checkpoint inhibitors (ICIs) have revolutionized the treatment landscape of solid tumors, response rates in patients with small cell lung cancer (SCLC) remain limited, and acquired resistance is highly prevalent. The underlying mechanisms of this immunotherapy resistance remain to be fully elucidated. Clinically, SCLC typically manifests as an "immune-cold" tumor, characterized by a low abundance of CD8+ T cell infiltration and the rare formation of tertiary lymphoid structures (TLS). While DNA damage repair (DDR) is closely linked to innate immune responses, how DDR networks orchestrate the SCLC immune microenvironment remains obscure. In this study, we integrated single-cell transcriptomic data (comprising 344,447 high-quality cells) from six cancer types (BCC, CRC, HCC, HNSCC, iCCA, and SCLC). Our comparative analysis revealed a fundamental depletion of TLS-associated cellular subpopulations (e.g., CXCL13+ CD8+ T cells, HLA-DRB5+ B cells, and CXCL9+ dendritic cells) in SCLC, which was significantly correlated with aberrant DDR activity. Through high-dimensional weighted gene co-expression network analysis (hdWGCNA), we identified ZNF385A as the core hub gene within the DDR-associated module. ZNF385A is highly expressed in SCLC and is associated with poorer prognosis. In vitro, ZNF385A depletion suppressed SCLC cell proliferation and induced apoptosis, accompanied by R-loop accumulation and activation of cGAS-STING signaling, indicating a potential link between ZNF385A, genomic stability and tumor-intrinsic innate immune signaling. Collectively, these findings identify ZNF385A as a potential regulator associated with TLS deficiency and immune evasion in SCLC.

Immunotherapy resistance↗

Identification of molecular subtypes in clear cell renal cell carcinoma based on chromatin regulators and tumor immune microenvironment profiling.

In the histological classification of renal cell carcinoma, clear cell renal cell carcinoma (ccRCC) accounts for the highest proportion and is the most common subtype. Despite advances in management, it continues to be associated with considerable incidence and mortality. Although surgery and systemic therapies are available, their efficacy is constrained by pronounced intratumoral heterogeneity and treatment resistance. Identifying robust biomarkers and clarifying the underlying biological mechanisms are therefore essential to improving diagnosis, risk stratification and therapeutic decision-making. In this work, we identified two ccRCC molecular subtypes displaying divergent chromatin regulator (CR) profiles and different clinical prognoses. Using the genes differentially expressed between these subgroups, we constructed a CR-related score (CRS) that effectively stratified patients according to survival. More analysis concluded that the low expression of CR was more linked with the immune-activated tumors, which encompassed the immune pathway enrichment, as well as the elevation of numerous immune cell subtypes. Moreover, elevated CRS was associated with improved immunotherapy responsiveness. Drug-sensitivity analyses nominated several candidate agents, and SMARCD3 knockdown in 786-O cells inhibited proliferation and migration and reduced sensitivity to masitinib. Collectively, these findings support the prognostic and therapeutic relevance of CR-related states in ccRCC and provide a framework for future experimental validation of chromatin-regulated tumor-immune interactions.

Humans↗

Integrative multi-omics reveals a fibroblast-centered, ZFHX3-prioritized regulatory framework linking sick sinus syndrome and atrial fibrillation.

OBJECTIVE: To define shared genetic and multi-scale mechanisms underlying comorbidity between sick sinus syndrome (SSS) and atrial fibrillation (AF). METHODS: We integrated genome-wide association study (GWAS) summary statistics for SSS and AF with Genotype-Tissue Expression (GTEx) expression and splicing quantitative trait loci (eQTL/sQTL), atrial single-cell and spatial transcriptomics, and epigenomics. We identified trait-relevant tissues and pathways, prioritized shared cell types, quantified genome-wide and local genetic sharing, detected joint loci by cross-trait meta-analysis, and linked loci to regulatory programs via colocalization and cell-prioritized co-expression networks. RESULTS: Both traits showed strongest enrichment in cardiac tissue, especially Heart Atrial Appendage. Fibroblasts from the left atrial appendage were consistently prioritized as the key shared cell population. SSS and AF displayed significant positive genome-wide genetic correlation, with multiple locally shared regions, including six major loci. Cross-trait meta-analysis identified eight joint-phenotype SNPs implicating four susceptibility genes. ZFHX3 was the leading tissue-cell-gene candidate, acting as a hub in fibroblast co-expression modules and colocalizing with cardiac regulatory signals. CONCLUSION: Shared liability for SSS and AF is highly tissue- and cell-specific, converging on regulatory networks in atrial appendage fibroblasts, with ZFHX3 serving as a central mechanistic and biomarker node.

Humans↗

A Multi-omics Regulated Cell Death Framework Defines Immune Phenotypes and Guides Precision Therapy in Colorectal Cancer.

Colorectal cancer (CRC) is molecularly and immunologically heterogeneous, contributing to variable treatment response. Because regulated cell death (RCD) intersects with tumor metabolism, immune regulation, and therapeutic susceptibility, we built an RCD-centered framework for CRC stratification. Multi-cohort transcriptomic data were used to infer RCD subtypes with non-negative matrix factorization (NMF) and non-negative least squares (NNLS). Genomic, bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomic datasets were integrated to characterize subtype-associated biology. Machine-learning models were developed for immunotherapy response and survival-risk estimation. Candidate compounds were screened by GDSC2-based drug-sensitivity modeling and molecular docking, and FSTL3 was functionally assessed in vitro. The framework separated CRC samples into two RCD-related phenotypes resembling immune-hot and immune-cold states. RCD1 showed immune activation and higher mutational burden, whereas RCD2 showed immune-suppressed features, intratumoral heterogeneity, and aggressive biology. RCD-associated signatures showed potential for predicting immunotherapy response and survival risk. Dasatinib was prioritized for immune-cold, high-risk tumors, with preliminary evidence supporting its activity in CRC cells, while functional assays suggested a role for FSTL3 in growth, invasion, epithelial-mesenchymal transition, and apoptosis regulation. These findings suggest that RCD-based multi-omics analysis may refine CRC stratification and help generate therapeutic hypotheses.

Colorectal cancer↗

Unveiling the power of TIIC: A prognostic tool for esophageal adenocarcinoma.

BACKGROUND: Esophageal adenocarcinoma (EAC) remains a lethal malignancy with limited prognostic tools for guiding immunotherapy. Tumor-infiltrating immune cells (TIICs) play a critical role in EAC prognosis and treatment response. METHODS: We integrated single-cell RNA sequencing and bulk transcriptome data from TCGA and GEO databases. TIIC-specific RNAs were identified via tissue specificity index calculation combined with machine learning feature selection. Twenty machine learning algorithms were benchmarked to construct an optimal TIIC signature score (TIIC-Score) based on the comprehensive C-index. Immunotherapy response, genomic mutation, and copy number variation were analyzed. Summary-data-based Mendelian randomization (SMR) and two-sample Mendelian randomization (MR) were performed to explore genetic associations. Core prognostic TIIC-related genes were functionally validated in esophageal cancer cell lines through loss-of-function assays. RESULTS: The TIIC-Score demonstrated robust prognostic value for 1-, 2-, and 3-year overall survival across multiple cohorts, outperforming 22 published models. High TIIC-Score was associated with poor survival and increased chromosomal instability. Mutation profiling revealed high frequencies of TP53 (78.2%), TTN (48.7%), and SYNE1 (30.8%). MR analysis identified a significant association between gastro-oesophageal reflux and EAC risk at SNP rs8130507. Functionally, CCNI was upregulated in esophageal cancer cells, and its knockdown suppressed malignant phenotypes while promoting apoptosis, supporting its pro-tumorigenic role. CONCLUSION: The TIIC-Score provides a novel prognostic framework for EAC that effectively stratifies patient risk and may help identify individuals most likely to benefit from immunotherapy.

Esophageal adenocarcinoma↗

Protocol to identify genes required for cardiomyocyte development using Perturb-Seq.

While Perturb-Seq combines CRISPR-based screening with single-cell RNA sequencing (scRNA-seq), large-scale experiments are costly and its application during development is complicated by differentiation heterogeneity. Here, we present a protocol to identify genes required for cardiomyocyte development using Perturb-Seq. We describe steps for sgRNA (single guide RNA) library cloning and infection, cardiomyocyte differentiation, cell hashing, super loading, and scRNA-seq. We then detail procedures for sequencing, mapping, and data analysis. For complete details on the use and execution of this protocol, please refer to Sivakumar et al.1.

CRISPR↗

FAP+ pericyte-like cells promote monocyte differentiation into tumor-associated macrophages in glioblastoma.

Glioblastoma (GBM) is a highly aggressive primary brain tumor characterized by profound immunosuppression that facilitates tumor progression and promotes therapeutic resistance. Fibroblast activation protein (FAP), a recognized theranostic target in multiple cancers, is upregulated in GBM and predominantly expressed by pericyte-like stromal cells. Here we identify a role for FAP&#x207a; pericyte-like cells in shaping the GBM immune microenvironment through monocyte recruitment and differentiation. Analysis of The Cancer Genome Atlas (TCGA) datasets, supported by reverse-transcription quantitative PCR and immunohistochemistry, revealed that elevated FAP expression-serving as a proxy for the abundance of FAP&#x207a; pericyte-like cells-is associated with an immune-enriched tumor microenvironment characterized by higher macrophage abundance and elevated expression of M2 polarization markers. Spatial analyses, including immunofluorescence and spatial transcriptomics, demonstrated that immunosuppressive macrophages preferentially localize in proximity to FAP&#x207a; pericytes. Single-cell RNA sequencing identified these FAP&#x207a; cells as a distinct perivascular stromal subset with a unique expression pattern of extracellular matrix components and cytokines, including CCL2 and CSF1, with corresponding receptors expressed on myeloid cells. Functional assays using patient-derived FAP&#x207a; pericyte-like cells confirmed their ability to attract monocytes via soluble mediators and to promote their differentiation and polarization into tumor-associated macrophages with immunoregulatory features, partly mediated by the CSF1-CSF1R axis. Orthotopic co-implantation experiments in mice further supported their capacity to enhance myeloid infiltration in vivo. Consistent with these biological effects, a transcriptional signature characteristic of FAP&#x207a; pericytes correlated with worse overall survival in patients with GBM. Together, these findings position FAP&#x207a; pericyte-like cells as modulators of the GBM immune landscape, fostering a tumor-permissive niche by promoting the differentiation of circulating monocytes into immunoregulatory macrophages. Targeting this stromal population may offer new therapeutic avenues to reprogram tumor-associated immune responses in GBM.

Journal Article↗

Distinct depressive-like behavioural phenotypes in mice exhibit unique patterns of transcriptional perturbations across habenular cell subtypes.

Major depressive disorder (MDD) is characterized by substantial heterogeneity, which hinders attempts to associate distinct symptoms with specific neural mechanisms. The lateral habenula (LHb) is a key brain region involved in negative affect and reward processing, but the molecular changes in the LHb that lead to mood disorders remain unclear. Here, we combined chronic social defeat stress (CSDS), behavioural phenotyping, and single-cell RNA sequencing to examine cell-type and subregion-specific transcriptional changes in the mouse habenula. Mice were classified into behavioural phenotypes reflecting social avoidance, anhedonia, passive coping, resilience, or susceptibility. We identified nine major habenular cell classes and found distinct phenotype-associated transcriptional signatures across both neurons and glia. Distinct transcriptional signatures were observed in LHb neurons of susceptible animals and in oligodendrocytes of resilient animals. Subregional analysis revealed that the oval-medial LHb accounted for most stress-related transcriptional changes, while the HbX subregion displayed a unique molecular signature associated with passive coping behaviour. These findings highlight the cellular heterogeneity of stress responses within the habenula and will pave the way for identifying potential targets for precision psychiatry approaches in depression.

Journal Article↗