Epigenetic regulation during cancer transitions across 11 tumour types.

Chromatin accessibility is essential in regulating gene expression and cellular identity, and alterations in accessibility have been implicated in driving cancer initiation, progression and metastasis1-4. Although the genetic contributions to oncogenic transitions have been investigated, epigenetic drivers remain less understood. Here we constructed a pan-cancer epigenetic and transcriptomic atlas using single-nucleus chromatin accessibility data (using single-nucleus assay for transposase-accessible chromatin) from 225 samples and matched single-cell or single-nucleus RNA-sequencing expression data from 206 samples. With over 1 million cells from each platform analysed through the enrichment of accessible chromatin regions, transcription factor motifs and regulons, we identified epigenetic drivers associated with cancer transitions. Some epigenetic drivers appeared in multiple cancers (for example, regulatory regions of ABCC1 and VEGFA; GATA6 and FOX-family motifs), whereas others were cancer specific (for example, regulatory regions of FGF19, ASAP2 and EN1, and the PBX3 motif). Among epigenetically altered pathways, TP53, hypoxia and TNF signalling were linked to cancer initiation, whereas oestrogen response, epithelial-mesenchymal transition and apical junction were tied to metastatic transition. Furthermore, we revealed a marked correlation between enhancer accessibility and gene expression and uncovered cooperation between epigenetic and genetic drivers. This atlas provides a foundation for further investigation of epigenetic dynamics in cancer transitions.

Proteogenomic data and resources for pan-cancer analysis.

The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigates tumors from a proteogenomic perspective, creating rich multi-omics datasets connecting genomic aberrations to cancer phenotypes. To facilitate pan-cancer investigations, we have generated harmonized genomic, transcriptomic, proteomic, and clinical data for >1000 tumors in 10 cohorts to create a cohesive and powerful dataset for scientific discovery. We outline efforts by the CPTAC pan-cancer working group in data harmonization, data dissemination, and computational resources for aiding biological discoveries. We also discuss challenges for multi-omics data integration and analysis, specifically the unique challenges of working with both nucleotide sequencing and mass spectrometry proteomics data.

Pan-cancer proteogenomics connects oncogenic drivers to functional states.

Cancer driver events refer to key genetic aberrations that drive oncogenesis; however, their exact molecular mechanisms remain insufficiently understood. Here, our multi-omics pan-cancer analysis uncovers insights into the impacts of cancer drivers by identifying their significant cis-effects and distal trans-effects quantified at the RNA, protein, and phosphoprotein levels. Salient observations include the association of point mutations and copy-number alterations with the rewiring of protein interaction networks, and notably, most cancer genes converge toward similar molecular states denoted by sequence-based kinase activity profiles. A correlation between predicted neoantigen burden and measured T cell infiltration suggests potential vulnerabilities for immunotherapies. Patterns of cancer hallmarks vary by polygenic protein abundance ranging from uniform to heterogeneous. Overall, our work demonstrates the value of comprehensive proteogenomics in understanding the functional states of oncogenic drivers and their links to cancer development, surpassing the limitations of studying individual cancer types.

Integrative multi-omic cancer profiling reveals DNA methylation patterns associated with therapeutic vulnerability and cell-of-origin.

DNA methylation plays a critical role in establishing and maintaining cellular identity. However, it is frequently dysregulated during tumor development and is closely intertwined with other genetic alterations. Here, we leveraged multi-omic profiling of 687 tumors and matched non-involved adjacent tissues from the kidney, brain, pancreas, lung, head and neck, and endometrium to identify aberrant methylation associated with RNA and protein abundance changes and build a Pan-Cancer catalog. We uncovered lineage-specific epigenetic drivers including hypomethylated FGFR2 in endometrial cancer. We showed that hypermethylated STAT5A is associated with pervasive regulon downregulation and immune cell depletion, suggesting that epigenetic regulation of STAT5A expression constitutes a molecular switch for immunosuppression in squamous tumors. We further demonstrated that methylation subtype-enrichment information can explain cell-of-origin, intra-tumor heterogeneity, and tumor phenotypes. Overall, we identified cis-acting DNA methylation events that drive transcriptional and translational changes, shedding light on the tumor's epigenetic landscape and the role of its cell-of-origin.

MsNRAMP2 Enhances Tolerance to Iron Excess Stress in Nicotiana tabacum and MsMYB Binds to Its Promoter.

Iron(Fe) is a trace metal element necessary for plant growth, but excess iron is harmful to plants. Natural resistance-associated macrophage proteins (NRAMPs) are important for divalent metal transport in plants. In this study, we isolated the MsNRAMP2 (MN_547960) gene from alfalfa, the perennial legume forage. The expression of MsNRAMP2 is specifically induced by iron excess. Overexpression of MsNRAMP2 conferred transgenic tobacco tolerance to iron excess, while it conferred yeast sensitivity to excess iron. Together with the MsNRAMP2 gene, MsMYB (MN_547959) expression is induced by excess iron. Y1H indicated that the MsMYB protein could bind to the "CTGTTG" cis element of the MsNRAMP2 promoter. The results indicated that MsNRAMP2 has a function in iron transport and its expression might be regulated by MsMYB. The excess iron tolerance ability enhancement of MsNRAMP2 may be involved in iron transport, sequestration, or redistribution.

Astaxanthin prevents osteoarthritis by blocking Rspo2-mediated Wnt/ß-catenin signaling in chondrocytes and abolishing Rspo2-related inflammatory factors in macrophages.

Chondrocyte degeneration and classically activated macrophage (AM)-related inflammation play critical roles in osteoarthritis (OA). Here, we explored the effects of astaxanthin and Rspo2 on OA in vitro and in vivo. We observed that the Rspo2 gene was markedly elevated in synovial tissues of OA patients compared with healthy controls. In 2D cultures, Rspo2 and inflammatory factors were enhanced in AMs compared with nonactivated macrophages (NMs), and the protein expression levels of Rspo2, ß-catenin, and inflammatory factors were increased, and anabolic markers were reduced in osteoarthritic chondrocytes (OACs) compared to normal chondrocytes (NCs). Astaxanthin reversed these changes in AMs and OACs. Furthermore, Rspo2 shRNA significantly abolished inflammatory factors and elevated anabolic markers in OACs. In NCs cocultured with AM, and in OACs cocultured with AMs or NMs, astaxanthin reversed these changes in these coculture systems and promoted secretion of Rspo2, ß-catenin and inflammatory factors and suppressed anabolic markers compared to NCs or OACs cultured alone. In AMs, coculture with NCs resulted in a slight elevation of Rspo2 and AM-related genes, but not protein expression, compared to culture alone, but when cocultured with OACs, these inflammatory mediators were significantly enhanced at both the gene and protein levels. Astaxanthin reversed these changes in all the groups. In vivo, we observed a deterioration in cartilage quality after intra-articular injection of Rspo2 associated with medial meniscus (DMM)-induced instability in the OA group, and astaxanthin was protective in these groups. Our results collectively revealed that astaxanthin attenuated the process of OA by abolishing Rspo2 both in vitro and in vivo.

Optimal surgical treatment for periprosthetic distal femoral fractures after total knee arthroplasty: a Bayesian-based network analysis.

BACKGROUND: The surgical methods for periprosthetic distal femoral fractures (PDFFs) after total knee arthroplasty included locking compression plate (LCP), retrograde intramedullary nailing (RIMN), and distal femoral replacement (DFR). However, the optimal treatment remains controversial. We performed a network meta-analysis (NMA) to provide the optimal surgical method for PDFFs. MATERIALS AND METHODS: Electronic databases, including Embase, Web of Science, Cochrane Library, and PubMed, were searched for studies that compared LCP, RIMN, and DFR for PDFFs. The quality of the included studies was assessed according to the Newcastle-Ottawa scale. Pairwise meta-analysis was performed by Review Manager version 5.4. The NMA was conducted in Aggregate Data Drug Information System software version 1.16.5. We calculated odds ratios (ORs) and 95% confidence intervals (CIs) for postoperative complications and reoperations. RESULTS: A total of 19 studies and 1198 patients were included, of whom 733 for LCP, 282 for RIMN, and 183 for DFR. Pairwise meta-analysis comparing LCP to RIMN and LCP to DFR showed no significant difference in complications and reoperations except that RIMN had a higher risk of malunion comparing to LCP (OR 3.05; 95% CI 1.46-6.34; P = 0.003). No statistically significant effects were found in the NMA of overall complications, infection, and reoperation. However, results of rank probabilities showed that DFR ranked best in overall complications and reoperation, RIMN ranked best in infection but worst in reoperation, and LCP ranked worst in infection and middle in reoperation. DISCUSSION: We found similar complication rate and reoperation rate between LCP, RIMN, and DFR. The results of rank probabilities favored DFR, and further studies with high-level evidence are expected to verify the optimal surgical method for PDFFs. LEVEL OF EVIDENCE: Level II; network meta-analysis.

Learning Social Relations and Spatiotemporal Trajectories for Next Check-in Inference.

The proliferation of location-aware social networks (LSNs) has facilitated the research of user mobility modeling and check-in prediction, thereby benefiting various downstream applications such as precision marketing and urban management. Most of the existing studies only focus on predicting the spatial aspect of check-ins, whereas the joint inference of the spatial and temporal aspects more fits the real application scenarios. Moreover, although social relations have been extensively studied in a recommender system, only a few efforts have been observed in the next check-in location prediction, leaving room for further improvement. In this article, we study the next check-in inference problem, which demands the joint inference of the next check-in location (Where) and time (When) for a target user (Who). We devise a model named ARNPP-GAT, which combines an attention-based recurrent neural point process with a graph attention networks. The core technical insight of ARNPP-GAT is to integrate user long-term representation learning, short-term behavior modeling, and temporal point process into a unified architecture. Specifically, ARNPP-GAT first leverages graph attention networks to learn the long-term representation of users by encoding their social relations. More importantly, the ARNPP endows the model with the capability of characterizing the effects of past check-in events and performing multitask learning to yield the next check-in time and location prediction. Empirical results on two real-world data sets demonstrate that ARNPP-GAT is superior compared with several competitors, validating the contributions of multitask learning and social relation modeling.

GmABCG5, an ATP-binding cassette G transporter gene, is involved in the iron deficiency response in soybean.

Iron deficiency is a major nutritional problem causing iron deficiency chlorosis (IDC) and yield reduction in soybean, one of the most important crops. The ATP-binding cassette G subfamily plays a crucial role in substance transportation in plants. In this study, we cloned the GmABCG5 gene from soybean and verified its role in Fe homeostasis. Analysis showed that GmABCG5 belongs to the ABCG subfamily and is subcellularly localized at the cell membrane. From high to low, GmABCG5 expression was found in the stem, root, and leaf of young soybean seedlings, and the order of expression was flower, pod, seed stem, root, and leaf in mature soybean plants. The GUS assay and qRT-PCR results showed that the GmABCG5 expression was significantly induced by iron deficiency in the leaf. We obtained the GmABCG5 overexpressed and inhibitory expressed soybean hairy root complexes. Overexpression of GmABCG5 promoted, and inhibition of GmABCG5 retarded the growth of soybean hairy roots, independent of nutrient iron conditions, confirming the growth-promotion function of GmABCG5. Iron deficiency has a negative effect on the growth of soybean complexes, which was more obvious in the GmABCG5 inhibition complexes. The chlorophyll content was increased in the GmABCG5 overexpression complexes and decreased in the GmABCG5 inhibition complexes. Iron deficiency treatment widened the gap in the chlorophyll contents. FCR activity was induced by iron deficiency and showed an extraordinary increase in the GmABCG5 overexpression complexes, accompanied by the greatest Fe accumulation. Antioxidant capacity was enhanced when GmABCG5 was overexpressed and reduced when GmABCG5 was inhibited under iron deficiency. These results showed that the response mechanism to iron deficiency is more actively mobilized in GmABCG5 overexpression seedlings. Our results indicated that GmABCG5 could improve the plant's tolerance to iron deficiency, suggesting that GmABCG5 might have the function of Fe mobilization, redistribution, and/or secretion of Fe substances in plants. The findings provide new insights into the ABCG subfamily genes in the regulation of iron homeostasis in plants.

Genome-wide association study uncovers major genetic loci associated with flowering time in response to active accumulated temperature in wild soybean population.

Flowering time and active accumulated temperature (AAT) are two key factors that limit the expanded production especially for soybean across different regions. Wild soybean provides an important germplasm for functional genomics study in cultivar soybean. However, the studies on genetic basis underlying flowering time in response to AAT especially in wild soybean were rarely reported. In this study, we used 294 wild soybean accessions derived from major soybean production region characterized by different AAT in Northeast of China. Based on genome-wide association study (GWAS), we identified 96 SNPs corresponded to 342 candidate genes that significantly associated with flowering time recorded in two-year experiments. Gene Ontology enrichment analysis suggests that the pathways of photosynthesis light reaction and actin filament binding were significantly enriched. We found three lead SNPs with -log10(p-value) > 32 across the two-year experiments, i.e., Chr02:9490318, Chr04:8545910 and Chr09:49553555. Linkage disequilibrium block analysis shows 28 candidate genes within the genomic region centered on the lead SNPs. Among them, expression levels of three genes (aspartic peptidase 1, serine/threonine-protein kinase and protein SCAR2-like) were significantly differed between two subgroups possessing contrasting flowering time distributed at chromosome 2, 4 and 9, respectively. There are 6, 7 and 3 haplotypes classified on the coding regions of the three genes, respectively. Collectively, accessions with late flowering time phenotype are typically derived from AAT zone 1, which is associated with the haplotypic distribution and expression levels of the three genes. This study provides an insight into a potential mechanism responsible for flowering time in response to AAT in wild soybean, which could promote the understanding of genetic basis for other major crops.

Comparison of locking compression plate and distal femoral replacement for periprosthetic distal femoral fractures: a retrospective study.

OBJECTIVE: To compare the clinical outcomes of locking compression plate (LCP) and distal femoral replacement (DFR) for periprosthetic distal femoral fractures (PDFFs) after total knee arthroplasty. METHODS: This retrospective study identified patients with PDFFs in an institutional database between January 2012 and December 2021. Demographic data and clinical outcomes, including postoperative complications, reoperation, 1-year mortality, Knee Society Scores (KSS) and Knee Society Functional Score (KSFS) were analysed. RESULTS: In total, 12 patients treated with LCP and six patients treated with DFR were included. There was no significant difference between the LCP and DFR groups in terms of postoperative complications (25.0% versus 33.3%, respectively), reoperation (8.3% versus 0.0%), respectively, 1-year mortality (8.3% versus 16.7%, respectively) or mean ± SD KSS (80.3 ± 8.3 versus 78.0 ± 2.5, respectively). However, the mean ± SD KSFS was significantly better for patients with LCP than for those with DFR (51.8 ± 12.5 versus 37.0 ± 6.7, respectively). CONCLUSION: DFR provides similar clinical outcomes compared with LCP for PDFFs. Patients with advanced age may benefit from DFR to allow early weight bearing.

Genome-Wide Association Study of Partial Resistance to P. sojae in Wild Soybeans from Heilongjiang Province, China.

Phytophthora root rot (PRR) is a destructive disease of soybeans (Glycine max (L.) Merr) caused by Phytophthora sojae (P. sojae). The most effective way to prevent the disease is growing resistant or tolerant varieties. Partial resistance provides a more durable resistance against the pathogen compared to complete resistance. Wild soybean (Glycine soja Sieb. & Zucc.) seems to be an extraordinarily important gene pool for soybean improvement due to its high level of genetic variation. In this study, 242 wild soybean germplasms originating from different regions of Heilongjiang province were used to identify resistance genes to P. sojae race 1 using a genome-wide association study (GWAS). A total of nine significant SNPs were detected, repeatedly associated with P. sojae resistance and located on chromosomes 1, 10, 12, 15, 17, 19 and 20. Among them, seven favorable allelic variations associated with P. sojae resistance were evaluated by a t-test. Eight candidate genes were predicted to explore the mechanistic hypotheses of partial resistance, including Glysoja.19G051583, which encodes an LRR receptor-like serine/threonine protein kinase protein, Glysoja.19G051581, which encodes a receptor-like cytosolic serine/threonine protein kinase protein. These findings will provide additional insights into the genetic architecture of P. sojae resistance in a large sample of wild soybeans and P. sojae-resistant breeding through marker-assisted selection.

HuNAC20 and HuNAC25, Two Novel NAC Genes from Pitaya, Confer Cold Tolerance in Transgenic Arabidopsis.

NAC transcription factors are one of the largest families of transcriptional regulators in plants, and members of the gene family play vital roles in regulating plant growth and development processes including biotic/abiotic stress responses. However, little information is available about the NAC family in pitaya. In this study, we conducted a genome-wide analysis and a total of 64 NACs (named HuNAC1-HuNAC64) were identified in pitaya (Hylocereus). These genes were grouped into fifteen subgroups with diversities in gene proportions, exon-intron structures, and conserved motifs. Genome mapping analysis revealed that HuNAC genes were unevenly scattered on all eleven chromosomes. Synteny analysis indicated that the segmental duplication events played key roles in the expansion of the pitaya NAC gene family. Expression levels of these HuNAC genes were analyzed under cold treatments using qRT-PCR. Four HuNAC genes, i.e., HuNAC7, HuNAC20, HuNAC25, and HuNAC30, were highly induced by cold stress. HuNAC7, HuNAC20, HuNAC25, and HuNAC30 were localized exclusively in the nucleus. HuNAC20, HuNAC25, and HuNAC30 were transcriptional activators while HuNAC7 was a transcriptional repressor. Overexpression of HuNAC20 and HuNAC25 in Arabidopsis thaliana significantly enhanced tolerance to cold stress through decreasing ion leakage, malondialdehyde (MDA), and H2O2 and O2- accumulation, accompanied by upregulating the expression of cold-responsive genes (AtRD29A, AtCOR15A, AtCOR47, and AtKIN1). This study presents comprehensive information on the understanding of the NAC gene family and provides candidate genes to breed new pitaya cultivars with tolerance to cold conditions through genetic transformation.

Proteogenomic and metabolomic characterization of human glioblastoma.

Glioblastoma (GBM) is the most aggressive nervous system cancer. Understanding its molecular pathogenesis is crucial to improving diagnosis and treatment. Integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs provides insights to GBM biology. We identify key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation, as well as potential targets for EGFR-, TP53-, and RB1-altered tumors. Immune subtypes with distinct immune cell types are discovered using bulk omics methodologies, validated by snRNA-seq, and correlated with specific expression and histone acetylation patterns. Histone H2B acetylation in classical-like and immune-low GBM is driven largely by BRDs, CREBBP, and EP300. Integrated metabolomic and proteomic data identify specific lipid distributions across subtypes and distinct global metabolic changes in IDH-mutated tumors. This work highlights biological relationships that could contribute to stratification of GBM patients for more effective treatment.

Whole-genome characterization of lung adenocarcinomas lacking the RTK/RAS/RAF pathway.

RTK/RAS/RAF pathway alterations (RPAs) are a hallmark of lung adenocarcinoma (LUAD). In this study, we use whole-genome sequencing (WGS) of 85 cases found to be RPA(-) by previous studies from The Cancer Genome Atlas (TCGA) to characterize the minority of LUADs lacking apparent alterations in this pathway. We show that WGS analysis uncovers RPA(+) in 28 (33%) of the 85 samples. Among the remaining 57 cases, we observe focal deletions targeting the promoter or transcription start site of STK11 (n = 7) or KEAP1 (n = 3), and promoter mutations associated with the increased expression of ILF2 (n = 6). We also identify complex structural variations associated with high-level copy number amplifications. Moreover, an enrichment of focal deletions is found in TP53 mutant cases. Our results indicate that RPA(-) cases demonstrate tumor suppressor deletions and genome instability, but lack unique or recurrent genetic lesions compensating for the lack of RPAs. Larger WGS studies of RPA(-) cases are required to understand this important LUAD subset.

Proteogenomic insights into the biology and treatment of HPV-negative head and neck squamous cell carcinoma.

We present a proteogenomic study of 108 human papilloma virus (HPV)-negative head and neck squamous cell carcinomas (HNSCCs). Proteomic analysis systematically catalogs HNSCC-associated proteins and phosphosites, prioritizes copy number drivers, and highlights an oncogenic role for RNA processing genes. Proteomic investigation of mutual exclusivity between FAT1 truncating mutations and 11q13.3 amplifications reveals dysregulated actin dynamics as a common functional consequence. Phosphoproteomics characterizes two modes of EGFR activation, suggesting a new strategy to stratify HNSCCs based on EGFR ligand abundance for effective treatment with inhibitory EGFR monoclonal antibodies. Widespread deletion of immune modulatory genes accounts for low immune infiltration in immune-cold tumors, whereas concordant upregulation of multiple immune checkpoint proteins may underlie resistance to anti-programmed cell death protein 1 monotherapy in immune-hot tumors. Multi-omic analysis identifies three molecular subtypes with high potential for treatment with CDK inhibitors, anti-EGFR antibody therapy, and immunotherapy, respectively. Altogether, proteogenomics provides a systematic framework to inform HNSCC biology and treatment.

Author Correction: Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples.

Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20128-w.

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

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.

Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma.

To explore the biology of lung adenocarcinoma (LUAD) and identify new therapeutic opportunities, we performed comprehensive proteogenomic characterization of 110 tumors and 101 matched normal adjacent tissues (NATs) incorporating genomics, epigenomics, deep-scale proteomics, phosphoproteomics, and acetylproteomics. Multi-omics clustering revealed four subgroups defined by key driver mutations, country, and gender. Proteomic and phosphoproteomic data illuminated biology downstream of copy number aberrations, somatic mutations, and fusions and identified therapeutic vulnerabilities associated with driver events involving KRAS, EGFR, and ALK. Immune subtyping revealed a complex landscape, reinforced the association of STK11 with immune-cold behavior, and underscored a potential immunosuppressive role of neutrophil degranulation. Smoking-associated LUADs showed correlation with other environmental exposure signatures and a field effect in NATs. Matched NATs allowed identification of differentially expressed proteins with potential diagnostic and therapeutic utility. This proteogenomics dataset represents a unique public resource for researchers and clinicians seeking to better understand and treat lung adenocarcinomas.