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At least 199 records · Page 11Linked to original sources
PubMed2026

Senescent fibroblasts drive CD8+ T cell dysfunction in colorectal cancer via CD36-mediated lipid transfer and peroxidation.

BACKGROUND: Functional exhaustion of tumor-infiltrating CD8+ T cells represents a hallmark of colorectal cancer (CRC) immunosuppression, though its mechanistic drivers remain elusive. Given the established correlation between CRC progression and stromal senescence characterized by pathological lipid accumulation and impaired immunity, we investigated whether and how senescent fibroblasts actively regulate CD8+ T cell dysfunction. METHODS: Single-cell RNA sequencing (scRNA-seq) analysis was conducted to unveil the diverse fibroblast populations and the significant lipid metabolism changes between senescent fibroblasts and non-senescent fibroblasts in human CRC specimens and adjacent normal mucosa. Machine-learning identified senescent fibroblasts with a distinct gene signature. Cell-cell communication analysis was used to evaluate the interactions between senescent fibroblasts and CD8+ T cells in colorectal cancer. Co-culture experiments were conducted among senescent fibroblasts, CD8+ T cells and patient-derived organoids of CRC (CRC-PDOs), with the results evaluated with high-content imaging and propidium iodide/Hoechst 33,342 staining. Flow cytometry, ELISA and lipid pulse-chase with BODIPY FL C16 were performed to detect the alterations of CD8+ T cell cytotoxic function and metabolic status. AOM/DSS-induced CRC mouse model was used to conduct in vivo validation to evaluate whether senolytics could suppress CRC progression. Patients from the Cancer Genome Atlas colorectal cancer cohort were stratified into CD36-high and CD36-low groups by median expression, and drug sensitivity for GDSC2 compounds was predicted computationally using the oncoPredict R package. RESULTS: ScRNA-seq demonstrated the specific cell population presence and divergence of senescent fibroblasts between neoplastic and histologically normal adjacent cell clusters in CRC. Random Forest was employed for cell senescence classification. Feature importance analysis identified five genes as key contributors to the model’s decision process. Cell-cell communication analysis revealed enhanced interactions between senescent fibroblasts and CD8+ T cells in CRC. Co-culture of senescent fibroblasts significantly impaired the cytotoxic functions of CD8+ T cells on CRC-PDOs, which was reflected by the declined proportions of granzyme B (GZMB) + and interferon gamma (IFNγ) + CD8+ T cells and enhanced viability of CRC-PDOs. Mechanistically, the co-culture with senescent fibroblasts promoted the lipid shuttling into CD8+ T cells to induce lipid peroxidation and downstream impairment of cytotoxicity. Furthermore, the inhibition of CD36, the specific scavenger receptor for lipid uptake of CD8+ T cells, effectively suppressed lipid transfer and peroxidation thereby preserving the effector functions of CD8+ T cells and ultimately promoting tumor apoptosis. Complementarily, in vivo senolytic treatment significantly suppressed CRC progression in AOM-DSS CRC mouse models. Top 12 therapeutic agents were identified significantly enhanced predicted efficacy in CD36-high tumors. CONCLUSIONS: Our study identified a substantial population of senescent fibroblasts in human CRC through single cell transcriptomics, machine-learning and clinical biopsies. These senescent fibroblasts impair CD8+ T cell-mediated killing of CRC-PDOs via CD36-dependent lipid transfer, suggesting senolytic targeting of stromal cells as a promising immunotherapeutic strategy for CRC.

Colorectal Neoplasms↗
PubMed2026

NPLOC4 Constructs Tumor Immunosuppressive Microenvironment in Pan-cancer and Hepatocellular Carcinoma.

INTRODUCTION: NPLOC4 (nuclear protein localization 4 homolog) is mainly involved in DNA damage, cell cycle, and ubiquitination promotion. Nonetheless, the role of NPLOC4 in the tumor immune microenvironment (TIME) and its potential as a promising tumor therapeutic target remains unclear. METHODS: Therefore, analyses of NPLOC4 mRNA and protein expression, RNA subcellular localization, and patient prognosis associated with NPLOC4 expression were conducted across multiple tumor types. Additionally, the correlations between NPLOC4 and immune cells, non-immune cells, and immune molecules within the tumor immune microenvironment (TIME) were investigated. These analyses utilized data from various public resources, including the Genotype-Tissue Expression (GTEx) project, The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), The Human Protein Atlas (HPA), Clinical Proteomic Tumor Analysis Consortium (CPTAC), TIMER2.0, KM-Plotter, The University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN), and Tumor Immune Single-cell Hub 2 (TISCH2). Subsequently, we utilized hepatocellular carcinoma (HCC) patients' cancer and adjacent tissues plus tumor cell lines to verify the differential RNA and protein expression of NPLOC4 via qRT-PCR and immunohistochemistry (IHC). Then, the relationship of NPLOC4 expression level with immune infiltration score, infiltration of effector immune cells, suppressive immune cells, and several vital immune checkpoints was analyzed in HCC immune microenvironment. Furthermore, the distribution of expression of NPLOC4 in various cells in the HCC microenvironment was determined through single-cell sequencing analysis. RESULTS: We discovered that NPLOC4 was up-regulated in a variety of tumors and was correlated with poor prognosis. NPLOC4 not only had the potential as a tumor prognostic marker and therapeutic target but also was strongly linked to immune cells, immune checkpoints, and immune-related molecules and pathways in HCC immune microenvironment. CONCLUSION: In summary, NPLOC4 may serve as a promising target for immunotherapy.

Humans↗
PubMed2002

Influence of genomics on cancer vaccine development from guess to prediction.

After more than 100 years since the first adjuvant for a cancer vaccine was described and more than a decade since the first tumor antigen has been molecularly cloned, it seems possible that cancer vaccines might be integrated into the standard care of cancer patients. Exciting new technologies concerning tumor antigen discovery, vaccine delivery and formulation define the basis for enormous efforts in academia as well as in the pharmaceutical and biotech industry. With the unveiling of the human genome additional targets will emerge that could further enhance vaccine efficacy, specificity and clinical applicability. Most likely therefore, tumor antigen targets which are widely expressed in cancer will be of advantage over patient-oriented approaches due to their favorable cost-to-benefit ratio. Some widely expressed candidate tumor antigens and methods to discover additional widely expressed tumor antigens are discussed here. While the armamentarium of potential tools to cancer vaccine development seems to be endless, only those that are scientifically sound yet economically reasonable will in the end have a chance to become clinically useful cancer vaccines.

Antigens, Neoplasm↗
PubMedDate not supplied

Analysis of the relationship between sex and chromosomal aberrations in colorectal cancer by comparative genomic hybridization.

Colorectal cancer is thought to be more common in men than in women. The chromosomal locations of DNA gains and losses in surgical specimens of colorectal tumours were detected by comparative genomic hybridization and were compared by gender. Five chromosomal regions, 7p, 8p, 8q, Xp and Xq, contained multiple gains that were significantly more common in males than in females, and within these regions, the differences were significant for Xp21, Xp11.3, Xp11.4 and Xq26. Regions 1p, 3q, 11q, 12p, 12q and 15q contained multiple sites of gain that were significantly more common in females than in males. Tumours from male and female patients showed significantly more losses at 11p and 15q, and at 4q and Xq, respectively. The fact that gains in X-chromosomal regions were detected with a significantly higher frequency in tumours from male patients suggests that the difference between the genders might be explained by X-chromosomal inactivation.

Adenocarcinoma↗
PubMed2025

The landscape of structural variation in pediatric cancer.

Structural variants (SVs) account for over 60% of the driver variants in pediatric cancer, and in many cases act as the cancer initiating event. To study SVs from a pan-cancer perspective, we analyzed 1,616 pediatric cancer genomes in 16 major cancer types of hematological malignancies (n = 908), brain tumors (n = 183), and solid tumors (n = 525) and compared their profiles to those of 2,203 adult cancers. The SV burden varied ~100-fold across pediatric cancer types and demonstrated an 8- to 16-fold reduction compared to adult brain and solid tumors but was comparable in pediatric versus adult hematological malignancies. Recurrent SV hotspots occurred uniquely in pediatric acute lymphoblastic leukemias (ALLs) in proximity to RAG-mediated recombination signal sequences (RSS) and disrupted multiple immune-related loci as well as 69 genes, which often involved cryptic RSS sites. By contrast, such hotspots affected only immune-related loci but not driver genes in adult lymphoid cancers. Eight SV signatures extracted from the cohort had varying distributions across cancer types, with clustered translocations reflecting templated insertions in osteosarcoma, and medium-sized deletions (10 kb to 1 Mb) enriched in cancers with RAG-mediated deletions. Intra-patient evolutionary analysis in 13 patients with multiple spatiotemporally distinct samples revealed that RAG-mediated recombination in leukemia and complex rearrangements in solid tumors occurred both early in disease initiation and continuously during later diversification, contributing to clonal heterogeneity. Finally, we found that both driver genes and fragile sites were the two genomic regions most frequently disrupted by SVs. The unique and diverse SV landscapes that emerged from this comprehensive analysis expand the scope of RSS-mediated mutagenesis in pediatric ALL and will be a valuable resource for guiding future functional studies and the design of clinical genomic testing in pediatric cancer.

Journal Article↗
PubMed2003

Pooled analysis of loss of heterozygosity in breast cancer: a genome scan provides comparative evidence for multiple tumor suppressors and identifies novel candidate regions.

Somatic loss of heterozygosity (LOH) has been widely reported in breast cancer as a means of identifying putative tumor-suppressor genes. However, individual studies have rarely spanned more than a single chromosome, and the varying criteria used to declare LOH complicate efforts to formally differentiate regions of consistent versus sporadic (random) loss. We report here the compilation of an extensive database from 151 published LOH studies of breast cancer, with summary data from >15,000 tumors and primary allelotypes from >4,300 tumors. Allelic loss was evaluated at 1,168 marker loci, with large variation in the density of informative observations across the genome. Using studies in which primary allelotype information was available, we employed a likelihood-based approach with a formal chromosomal instability and selection model. The approach seeks direct evidence for preferential loss at each locus compared with nearby loci, accounts for heterogeneity across studies, and enables the direct comparison of candidate regions across the genome. Striking preferential loss was observed (in descending order of significance) in specific regions of chromosomes 7q, 16q, 13q, 17p, 8p, 21q, 3p, 18q, 2q, and 19p, as well as other regions, in many cases coinciding with previously identified candidate genes or known fragile sites. Many of these observations were not possible from any single LOH study, and our results suggest that many previously reported LOH results are not systematic or reproducible. Our approach provides a comparative framework for further investigation of regions exhibiting LOH and identifies broad genomic regions for which there exist few data.

Alleles↗
PubMed2002

Altered methylation patterns in cancer cell genomes: cause or consequence?

CpG islands are associated with at least half of all cellular genes and are normally methylation-free. Dense methylation of cytosine residues within islands causes strong and heritable transcriptional silencing. Such silencing normally occurs almost solely at genes subject to genomic imprinting or to X chromosome inactivation. Aberrant methylation of CpG islands associated with tumor suppressor genes has been proposed to contribute to carcinogenesis. However, questions of mechanisms underlying the cancer changes and the precise consequences for tumorigenesis exist in the field, and must continue to be addressed before the importance of abnormalities in genomic methylation patterns in carcinogenesis can be fully understood. In this article, two workers in DNA methylation, one concentrating on cancer biology and the other on developmental biology, address recurrent questions about cancer epigenetics from different perspectives. The goal is to highlight important controversies in the field which can be productive targets of ongoing and future research.

Animals↗
PubMed1995

Cloning of no tI-cleaved genomic DNA fragments appearing as spots in 2D gel electrophoresis.

RLGS (Restriction Landmark Genomic Scanning) is a simple and rapid scanning of genomic DNA in two-dimensional electrophoresis. Human genomic DNA is first cleaved by NotI, and the cleaved ends are radio-labeled and cleaved further by EcoRV, followed by size-fractionation by first dimensional electrophoresis. The sample is then cleaved in situ by the second enzyme HinfI and resolved by the second dimensional electrophoresis. Nearly 2,000 spots emerge with spot intensities reflecting the copy number in the genome. Because of the resolving power and capacity to scan the entire genome, RLGS has been used to monitor genomic aberrations and imprinting. Here, we report a means of cloning the DNA in spots. The DNA was eluted and ligated to biotinylated NotI and HinfI likers followed by affinity separation using streptavidin. The ligated fragment was recovered by EcoRV cleavage, the target sequence of which was located in the NotI linker and amplified by PCR using a primer pair, the sequences of which lie in the linkers. The products were then cloned into a vector for further tests. An amplified spot in stomach cancer genomic DNA and a dwindling spot in liver cancer genomic DNA were taken as examples for cloning.

Base Sequence↗
PubMed2026

Stromal Hedgehog Signaling Drives Segment-Specific Malignant Transformation of Gastrointestinal Stem Cells by Producing Bone Morphogenetic Protein Antagonists.

BACKGROUND & AIMS: Hedgehog signaling plays a complex role in epithelial-stromal interactions, but its effects on gastrointestinal stem cells mediated by heterogeneous stromal cell populations remain incompletely defined. Here, we investigate how stromal Hedgehog signaling regulates gastric stem cells and tumorigenesis in a segment-specific manner. METHODS: We genetically activated Hedgehog signaling in distinct stromal cell lineages using Col1a2-, Pdgfra-, Gli1-, Acta2-, and Prrx1-CreERT mouse lines, combined with lineage tracing, RNA sequencing, chromatin immunoprecipitation-quantitative polymerase chain reaction, and pharmacologic interventions. Human gastric cancer data from The Cancer Genome Atlas were also analyzed. RESULTS: We show that genetic activation of Hedgehog signaling in stromal cells marked by Col1a2, Pdgfra, or Gli1, but not by Acta2, induces tumorigenesis in the stomach and gastroesophageal junction, but not in the small or large intestine. Hedgehog signaling increases the expression of multiple bone morphogenetic protein antagonists in gastric but not colonic stromal cells, via Gli1-mediated transcription. These bone morphogenetic protein antagonists, in turn, activate Wnt/β-catenin signaling in gastric stem cells, driving their proliferation and initiating gastric cancer expressing CD44 and Sox9, but not Lgr5. Activating bone morphogenetic protein or inhibiting Wnt signaling blocks tumor initiation. Analysis of patient data from The Cancer Genome Atlas reveals elevated Hedgehog signaling in gastric cancers, which correlates with suppressed bone morphogenetic protein signaling. CONCLUSIONS: These findings uncover a gastrointestinal segment-specific oncogenic role for Hedgehog signaling in Col1a2+Acta2- stromal cells, mediated through the bone morphogenetic protein-Wnt-β-catenin axis.

BMP Antagonists↗
PubMed1996

p53 tumor suppressor gene status and the degree of genomic instability in sporadic colorectal cancers.

BACKGROUND: Genomic instability reflects the propensity and the susceptibility of the genome to acquire multiple alterations and, in turn, is believed to be a driving force behind multistep carcinogenesis. Although the molecular basis of genomic instability in sporadic colorectal cancers remains largely a mystery, mutation of the p53 tumor suppressor gene (also known as TP53) has been proposed to play an integral role in this process. However, a dilemma exists in that p53 mutation appears to be a late event in the progression of sporadic colorectal tumors, whereas genomic instability, serving as a facilitator of tumor progression, is envisioned as occurring early in this process. PURPOSE: We evaluated the relationship between p53 mutation and the major form of genomic instability in sporadic colorectal tumors, namely, that involving DNA breakage, which leads to chromosomal translocations, insertions, deletions, and gene amplification. METHODS: Fifty-eight sporadic colorectal tumors that had been previously evaluated for genomic instability were analyzed for p53 mutations. These tumors were from consecutively diagnosed patients. Genomic instability was quantified by use of inter-simple sequence repeat polymerase chain reaction analysis that employed (CA)8RG and (CA)8RY primers (R = purine [A or G]; Y = pyrimidine [C or T]); a genomic instability index (a measure of the number of alterations in tumor DNA in comparison with normal DNA, expressed as a percent) was calculated for each tumor. Mutation of the p53 gene in exons 5-9 was determined by use of single-strand conformational polymorphism-polymerase chain reaction analysis and DNA sequencing. Chi-squared analysis was used to determine the statistical significance of differences between groups of tumors. Reported P values are two-sided. RESULTS: p53 mutations were identified in 29 (50%) of the 58 tumors. The median genomic instability index value was 3.3%. Nineteen (65.5%) of the 29 tumors with p53 mutations had genomic instability indices that were less than the median value (range, 0%-2.6%); the remaining 10 (34.5%) tumors had genomic instability indices that were greater than the median (range, 3.9%-13.0%). Eleven (37.9%) of the 29 tumors with wild-type p53 genes had genomic instability indices that were less than the median value (range, 0%-2.6%), whereas the remaining 18 tumors had genomic instability indices above the median (range, 3.9%-11.7%). There was a statistically significant association between a lesser degree of genomic instability and the presence of p53 mutations (P = .032). CONCLUSIONS AND IMPLICATIONS: Tumors with no or minimal evidence of genomic instability are more likely to harbor p53 mutations than tumors with evidence of substantial genomic instability. p53 mutations play an important role in the development of cancers but do not appear to initiate or promote genomic instability in sporadic colorectal tumors.

Chromosome Aberrations↗
PubMed2026

Bioinformatic analysis reveals the potential association of ESRP1 with the splicing of cytoskeleton-associated genes in doxorubicin-resistant MCF7 breast cancer cells.

BACKGROUND: Breast cancer remains one of the most prevalent malignancies among women, with doxorubicin resistance posing a significant challenge that undermines treatment success and survival outcomes. Aberrant alternative splicing (AS), driven by dysregulation or mutations in splicing factors (SFs), is implicated in cancer initiation, progression, and drug resistance. This study aims to investigate the association of the epithelial cell-specific splicing factor ESRP1 with doxorubicin resistance in breast cancer, focusing on how ESRP1 deficiency correlates with AS changes that promote chemoresistance. METHODS: We analyzed RNA-sequencing (RNA-seq) data from doxorubicin-resistant (MCF7-DR) and parental (MCF7) breast cancer cell lines to identify enhanced alternative splicing events (ASEs) and changes in ESRP1 expression; we further leveraged The Cancer Genome Atlas (TCGA)-BRCA cohort to construct an SF-RASE correlation network for screening core SFs (including ESRP1). An integrative analysis combining crosslinking immunoprecipitation (CLIP-seq) data and The Cancer Genome Atlas (TCGA) database was performed to validate ESRP1 binding targets and assess the association between ESRP1-related splicing and cytoskeleton organization. RESULTS: We observed extensive AS changes and significantly downregulated ESRP1 expression in MCF7-DR cells. Integrative analysis identified 61 high-confidence ASEs that correlate with ESRP1 expression. Further bioinformatic integration suggests that ESRP1 expression is associated with the splicing patterns of SPTBN1, MAP2K7, FGFR3, and CYB561A3-four genes involved in cytoskeleton organization-though direct experimental verification to confirm a causal regulatory relationship between ESRP1 and the splicing of these genes is still pending. CONCLUSIONS: Our findings suggest that ESRP1 expression is closely associated with doxorubicin resistance in breast cancer cells, with concomitant alterations in key ASEs linked to cytoskeletal remodeling that correlate with ESRP1. Exploring the ESRP1-related splicing network may offer new strategies to overcome chemoresistance and improve patient outcomes. However, the small cell line sample size (n = 2 per group) constrains the robustness of ASE and SF-ASE correlation findings, and these results should be interpreted with caution and require further validation with larger sample cohorts.

Alternative splicing↗
PubMed2004

Genomic DNA-chip hybridization reveals a higher incidence of genomic amplifications in pancreatic cancer than conventional comparative genomic hybridization and leads to the identification of novel candidate genes.

Genomic analyses aimed at the detection of high-level DNA amplifications were performed on 13 widely used pancreatic cancer cell lines and 6 pancreatic tumor specimens. For these analyses, array-based comparative genomic hybridization (Matrix-CGH) onto dedicated microarrays was used. In comparison with chromosomal CGH (eight amplifications), a >3-fold number of DNA amplifications was detected (n = 29). The most frequent amplifications mapped to 7p12.3 (three pancreatic cancer cell lines and three pancreatic tumor specimens), 8q24 (four pancreatic cancer cell lines and one pancreatic tumor specimen), 11q13 (three pancreatic cancer cell lines and three pancreatic tumor specimens), and 20q13 (four pancreatic cancer cell lines and three pancreatic tumor specimens). Genes contained in the consensus regions were MYC (8q24), EGFR (7p12.3), and FGF3 (11q13). In six of seven pancreatic cancer cell lines and pancreatic tumor specimens with 20q13 amplifications, the novel candidate gene NFAT C2, which plays a role in the activation of cytokines, was amplified. Other amplifications also affected genes for which a pathogenetic role in pancreatic carcinoma has not been described, such as BCL10 and BCL6, two members of the BCL family. A subset of amplified genes was checked for overexpression by means of real-time PCR, revealing the highest expression levels for BCL6 and BCL10. Thus, Matrix-CGH allows the detection of a high number of amplifications, resulting in the identification of novel candidate genes in pancreatic cancer.

Aged↗
PubMed2026

Yes-Associated Protein (YAP)1 and β-Catenin Immunohistochemistry as a Surrogate Marker for GTF2I-Mutant Type A/AB Thymomas.

Thymomas are rare thymic epithelial tumors classified by the World Health Organization into type A/AB thymomas, which commonly harbor GTF2I mutations and behave indolently, and type B thymomas and thymic carcinomas, in which these mutations are less common. Type A and AB thymomas are uniquely enriched for a recurrent somatic hotspot mutation in GTF2I p. L424H; yet, this gene is rarely included in clinical sequencing panels, limiting its diagnostic utility. Yes-associated protein (YAP)1, the principal effector of the Hippo signaling pathway, and β-catenin, the central transcriptional effector of the Wnt pathway, have emerging roles in thymoma biology; however, their relationship to GTF2I mutation status and histologic subtype has not been systematically characterized. We analyzed The Cancer Genome Atlas thymoma data set and an institutional cohort of 38 thymic epithelial tumors to evaluate YAP1 and β-catenin immunohistochemistry (IHC) as surrogate markers for GTF2I mutation status and histologic classification. In The Cancer Genome Atlas data set, YAP1 and CTNNB1 mRNA expression were markedly elevated in type A/AB thymomas relative to type B and carcinoma subtypes, and GTF2I-mutant tumors exhibited significantly higher YAP1 mRNA expression than GTF2I-wildtype tumors. Targeted next-generation sequencing of our institutional cohort confirmed enrichment of the canonical GTF2I p. L424H hotspot in indolent subtypes. By IHC, both nuclear YAP1 positivity and cytoplasmic β-catenin localization were significantly more frequent in indolent thymomas. Cytoplasmic β-catenin demonstrated high specificity (94%) for indolent histology, supporting its use in diagnostically challenging cases such as type A versus type B3 distinction on small biopsies. YAP1 IHC showed a high negative predictive value for GTF2I mutations, such that a YAP1-negative result reliably excludes a GTF2I-mutant tumor. These findings implicate crosstalk between Hippo and Wnt signaling in GTF2I-mutant thymomas and position YAP1 and β-catenin IHC as accessible, cost-effective surrogates for molecular subtyping in a tumor where standard sequencing panels have limited coverage.

GTF2I↗
PubMed2026

Profiling Dectin-2-Positive Tumor-Associated Macrophages Across Human Cancers by Immunohistochemistry.

PURPOSE: To characterize the prevalence and distribution of Dectin-2-positive macrophages across human tumors and develop a research immunohistochemistry (IHC) assay to assess Dectin-2 in cancer tissues. MATERIALS AND METHODS: C-type lectin domain family 6 member A (CLEC6A), the gene encoding Dectin-2, was evaluated across 38 tumor types using The Cancer Genome Atlas. A fit-for-purpose Dectin-2 IHC assay was developed using a monoclonal antibody selected from screening 11 anti-Dectin-2 antibodies. Assay performance was supported by Dectin-2-expressing and parental cell line controls, macrophage-associated staining patterns, and comparison with an orthogonal CLEC6A in situ hybridization method using RNAscope. Dectin-2 expression was assessed in tissue microarrays (n = 553 samples) across 6 cancer types and whole tissue sections (n = 137) across 7 cancer types. RESULTS: The Cancer Genome Atlas analysis identified enriched CLEC6A expression in several tumor types, including non-small cell lung cancer (NSCLC), triple-negative breast cancer (TNBC), and subsets of head and neck cancer (HNC) and colorectal cancer (CRC). By IHC, Dectin-2-positive macrophages were detected across tumor types, with notable heterogeneity within and across cancer types. In tissue microarrays, NSCLC showed the highest frequency of Dectin-2-positive macrophage infiltration, with 38% of cases with staining ≥1% of tumor area. Whole tissue section analysis confirmed and expanded these findings, with ≥50% of NSCLC, melanoma, HNC, TNBC, and CRC samples showing Dectin-2-positive macrophages in ≥1% tumor area. CONCLUSIONS: Dectin-2 expression was observed in subsets of tumor-associated macrophages across multiple human cancers, with relatively enriched expression in NSCLC, melanoma, HNC, TNBC, and CRC. To our knowledge, this study represents the first broad protein-level characterization of Dectin-2 across multiple human tumor types, identifies cancers with relatively enriched Dectin-2-positive macrophage infiltration, and provides a foundation for future translational studies of Dectin-2-targeted therapies.

Humans↗
PubMed2006

Of mice and men: cancer gene discovery using comparative oncogenomics.

With the proliferation of high-throughput technologies to profile the cancer genome, methods to distinguish causal from bystander genetic events are needed. Two recent reports by Zender et al. and Kim et al. in Cell use genetically defined mouse models to serve as biological filters to mine the human cancer genome. Integration of high-resolution copy number profiles of mouse tumor models and human tumors identified cIAP1 and Yap as oncogenes in human hepatocellular carcinoma, while NEDD9 was identified as a metastasis gene in human melanoma. Together, these reports demonstrate that a comparative oncogenomics approach can identify genes causally involved in oncogenesis and metastasis.

Adaptor Proteins, Signal Transducing↗
PubMed2025

GE-IA-NAM: gene-environment interaction analysis via imaging-assisted neural additive model.

MOTIVATION: Gene-environment (G-E) interaction analysis is crucial in cancer research, offering insights into how genetic and environmental factors jointly influence cancer outcomes. Most existing G-E interaction methods are regression-based, which may lack flexibility to capture complex data patterns. Recent advances have investigated deep neural network-based G-E models. However, these methods may be more vulnerable to information deficiency due to challenges such as limited sample size and high dimensionality. Apart from genetic and environmental data, pathological images have emerged as a widely accessible and informative resource for cancer modeling, presenting its potential to enhance G-E modeling. RESULTS: We propose the pathological imaging-assisted neural additive model for G-E analysis (GE-IA-NAM). The flexible and interpretable additive network architecture is adopted to account for individualized effects associated with genetic factors, environmental factors, and their interactions. To improve G-E modeling, an assisted-learning strategy is investigated, which adopts a joint analysis to integrate information from pathological images. Simulations and the analysis of lung and skin cancer datasets from The Cancer Genome Atlas demonstrate the competitive performance of the proposed method. AVAILABILITY AND IMPLEMENTATION: Python code implementing the proposed method is available at https://github.com/Mr-maoge/NAM-IA-GE. The data that support the findings in this article are openly available in TCGA (The Cancer Genome Atlas) at https://portal.gdc.cancer.gov/.

Gene-Environment Interaction↗