Macrophage heterogeneity and oncogenic mechanisms in lung adenocarcinoma: insights from scRNA-seq analysis and predictive modeling

BackgroundMacrophages play a dual role in the tumor microenvironment(TME), capable of secreting pro-inflammatory factors to combat tumors while also promoting tumor growth through angiogenesis and immune suppression. This study aims to explore the characteristics of macrophages in lung adenocarcinoma (LUAD) and establish a prognostic model based on macrophage-related genes.MethodWe performed scRNA-seq analysis to investigate macrophage heterogeneity and their potential pseudotime evolutionary processes. Specifically, we used scRNA-seq data processing, intercellular communication analysis, pseudotime trajectory analysis, and transcription factor regulatory analysis to reveal the complexity of macrophage subpopulations. Data from The Cancer Genome Atlas (TCGA) was used to assess the impact of various macrophage subtypes on LUAD prognosis. Univariate Cox regression was applied to select prognostic-related genes from macrophage markers. We constructed a prognostic model using Lasso regression and multivariate Cox regression, categorizing LUAD patients into high and low-risk groups based on the median risk score. The model’s performance was validated across multiple external datasets. We also examined differences between high and low-risk groups in terms of pathway enrichment, mutation information, tumor microenvironment(TME), and immunotherapy efficacy. Finally, RT-PCR confirmed the expression of model genes in LUAD, and cellular experiments explored the carcinogenic mechanism of COL5A1.ResultsWe found that signals such as SPP1 and MIF were more active in tumor tissues, indicating potential oncogenic roles of macrophages. Using macrophage marker genes, we developed a robust prognostic model for LUAD that effectively predicts prognosis and immunotherapy efficacy. A nomogram was constructed to predict LUAD prognosis based on the model’s risk score and other clinical features. Differences between high and low-risk groups in terms of TME, enrichment analysis, mutational landscape, and immunotherapy efficacy were systematically analyzed. RT-PCR and cellular experiments supported the oncogenic role of COL5A1.ConclusionOur study identified potential oncogenic mechanisms of macrophages and their impact on LUAD prognosis. We developed a prognostic model based on macrophage marker genes, demonstrating strong performance in predicting prognosis and immunotherapy efficacy. Finally, cellular experiments suggested COL5A1 as a potential therapeutic target for LUAD

Large and tunable magnetoresistance in van der Waals Ferromagnet/Semiconductor junctions

Magnetic tunnel junctions (MTJs) with conventional bulk ferromagnets separated by a nonmagnetic insulating layer are key building blocks in spintronics for magnetic sensors and memory. A radically different approach of using atomically-thin van der Waals (vdW) materials in MTJs is expected to boost their figure of merit, the tunneling magnetoresistance (TMR), while relaxing the lattice-matching requirements from the epitaxial growth and supporting high-quality integration of dissimilar materials with atomically-sharp interfaces. We report TMR up to 192% at 10 K in all-vdW Fe3GeTe2/GaSe/Fe3GeTe2 MTJs. Remarkably, instead of the usual insulating spacer, this large TMR is realized with a vdW semiconductor GaSe. Integration of two-dimensional ferromagnets in semiconductor-based vdW junctions offers gate-tunability, bias dependence, magnetic proximity effects, and spin-dependent optical-selection rules. We demonstrate that not just the magnitude, but also the TMR sign is tuned by the applied bias or the semiconductor thickness, enabling modulation of highly spin-polarized carriers in vdW semiconductors

Large and tunable magnetoresistance in van der Waals ferromagnet/semiconductor junctions

Magnetic tunnel junctions (MTJs) with conventional bulk ferromagnets separated by a nonmagnetic insulating layer are key building blocks in spintronics for magnetic sensors and memory. A radically different approach of using atomically-thin van der Waals (vdW) materials in MTJs is expected to boost their figure of merit, the tunneling magnetoresistance (TMR), while relaxing the lattice-matching requirements from the epitaxial growth and supporting high-quality integration of dissimilar materials with atomically-sharp interfaces. We report TMR up to 192% at 10 K in all-vdW Fe3GeTe2/GaSe/Fe3GeTe2 MTJs. Remarkably, instead of the usual insulating spacer, this large TMR is realized with a vdW semiconductor GaSe. Integration of semiconductors into the MTJs offers energy-band-tunability, bias dependence, magnetic proximity effects, and spin-dependent optical-selection rules. We demonstrate that not only the magnitude of the TMR is tuned by the semiconductor thickness but also the TMR sign can be reversed by varying the bias voltages, enabling modulation of highly spin-polarized carriers in vdW semiconductors

Large room-temperature magnetoresistance in van der Waals ferromagnet/semiconductor junctions

The magnetic tunnel junction (MTJ) is the core component in memory technologies, such as the magnetic random-access memory, magnetic sensors and programmable logic devices. In particular, MTJs based on two-dimensional (2D) van der Waals (vdW) heterostructures offer unprecedented opportunities for low power consumption and miniaturization of spintronic devices. However, their operation at room temperature remains a challenge. Here, we report a large tunnel magnetoresistance (TMR) of up to 85% at room temperature (T = 300 K) in vdW MTJs based on a thin (< 10 nm) semiconductor spacer WSe2 layer embedded between two Fe3GaTe2 electrodes with intrinsic above-room-temperature ferromagnetism. The TMR in the MTJ increases with decreasing temperature up to 164% at T = 10 K. The demonstration of TMR in ultra-thin MTJs at room-temperature opens a realistic and promising route for next-generation spintronic applications beyond the current state of the art

Disease-specific U1 spliceosomal RNA mutations in mature B-cell neoplasms

Recurrent mutations in the third base of U1 spliceosomal RNA responsible for marked splicing and expression abnormalities have been described in chronic lymphocytic leukemia (CLL) and some solid tumors. However, the clinical significance of these mutations in large and independent CLL cohorts as well as their presence in other B-cell neoplasms is unknown. Here we characterized U1 mutations in 1670 CLL and 363 mature B-cell lymphomas. We confirmed that the g.3A&gt;C U1 mutation is found in 3.5% of CLL, which conferred rapid disease progression independently of the main biological and clinical prognostic markers of the disease. Additionally, a recurrent g.9C&gt;T mutation was found in 1.5% of CLL causing downstream splicing alterations and associated with adverse prognosis. We also identified a g.4C&gt;T mutation in 10% of diffuse large B-cell lymphomas of the germinal center subtype and a g.7A&gt;G mutation in 30% of EBV-negative Burkitt lymphomas, both of which altered the splicing pattern of multiple genes. This study reveals novel, recurrent, and tumor-specific U1 mutations in mature B-cell neoplasms with biological and prognostic implications, thus establishing U1 as a novel pan-B-cell malignancy driver gene

Sex differences in oncogenic mutational processes.

Sex differences have been observed in multiple facets of cancer epidemiology, treatment and biology, and in most cancers outside the sex organs. Efforts to link these clinical differences to specific molecular features have focused on somatic mutations within the coding regions of the genome. Here we report a pan-cancer analysis of sex differences in whole genomes of 1983 tumours of 28 subtypes as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We both confirm the results of exome studies, and also uncover previously undescribed sex differences. These include sex-biases in coding and non-coding cancer drivers, mutation prevalence and strikingly, in mutational signatures related to underlying mutational processes. These results underline the pervasiveness of molecular sex differences and strengthen the call for increased consideration of sex in molecular cancer research

Cancer LncRNA Census reveals evidence for deep functional conservation of long noncoding RNAs in tumorigenesis.

Long non-coding RNAs (lncRNAs) are a growing focus of cancer genomics studies, creating the need for a resource of lncRNAs with validated cancer roles. Furthermore, it remains debated whether mutated lncRNAs can drive tumorigenesis, and whether such functions could be conserved during evolution. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we introduce the Cancer LncRNA Census (CLC), a compilation of 122 GENCODE lncRNAs with causal roles in cancer phenotypes. In contrast to existing databases, CLC requires strong functional or genetic evidence. CLC genes are enriched amongst driver genes predicted from somatic mutations, and display characteristic genomic features. Strikingly, CLC genes are enriched for driver mutations from unbiased, genome-wide transposon-mutagenesis screens in mice. We identified 10 tumour-causing mutations in orthologues of 8 lncRNAs, including LINC-PINT and NEAT1, but not MALAT1. Thus CLC represents a dataset of high-confidence cancer lncRNAs. Mutagenesis maps are a novel means for identifying deeply-conserved roles of lncRNAs in tumorigenesis

Analyses of non-coding somatic drivers in 2,658 cancer whole genomes.

The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts