Construction and validation of a novel immunological model to predict prognosis in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer, with limited treatment options. In this study, we investigated the role of immune cell infiltration in PDAC progression and constructed an immune-related predictive model for patients with PDAC based on the International Cancer Genome Consortium (ICGC) cohort. Related algorithms have been used to assess the immune microenvironment. Least Absolute Shrinkage and Selection Operator (LASSO) Cox analysis was used to construct the model, and receiver operating characteristic and decision curve analysis analyses were conducted to evaluate its diagnostic and prognostic efficacy. The results demonstrated a correlation between high immune infiltration and better prognosis in PDAC. The immune-related prognostic model (IPM) identified four genes through LASSO Cox analysis, with the high IPM group being associated with a worse prognosis. Cox regression analysis confirmed that IPM is an independent risk factor for PDAC. Validation through analysis of The Cancer Genome Atlas cohort and our own individual tumor samples revealed a similar trend to that observed in the ICGC cohort. Finally, a nomogram incorporating age and IPM demonstrated efficacy in the prognostic evaluation of patients with PDAC. In conclusion, we developed a novel immune-related prognosis prediction model for PDAC that offers new possibilities for the measurement of immunotherapy and prognostic assessment of patients.

Pathological image profiling identifies onco-microbial, tumor immune microenvironment, and prognostic subtypes of colorectal cancer.

Histology slide, tissue microbes, and the host gene expression can be independent prognostic factors of colorectal cancer (CRC), but the underlying associations and biological significance of these multimodal omics remain unknown. Here, we comprehensively profiled the matched pathological images, intratumoral microbes, and host gene expression characteristics in 527 patients with CRC. By clustering these patients based on histology slide features, we classified the patients into two histology slide subtypes (HSS). Onco-microbial community and tumor immune microenvironment (TIME) were also significantly different between the two subtypes (HSS1 and HSS2) of patients. Furthermore, variation in intratumoral microbes-host interaction was associated with the prognostic heterogeneity between HSS1 and HSS2. This study proposes a new CRC classification based on pathological image features and elucidates the process by which tumor microbes-host interactions are reflected in pathological images through the TIME.

Human Pluripotent Stem Cells Derived Endothelial Cells Repair Choroidal Ischemia.

Choroidal atrophy is a common fundus pathological change closely related to the development of age-related macular degeneration (AMD), retinitis pigmentosa, and pathological myopia. Studies suggest that choroidal endothelial cells (CECs) that form the choriocapillaris vessels are the first cells lost in choroidal atrophy. It is found that endothelial cells derived from human pluripotent stem cells (hPSC-ECs) through the MESP1+ mesodermal progenitor stage express CECs-specific markers and can integrate into choriocapillaris. Single-cell RNA-seq (scRNA-seq) studies show that hPSC-ECs upregulate angiogenesis and immune-modulatory and neural protective genes after interacting with ex vivo ischemic choroid. In a rat model of choroidal ischemia (CI), transplantation of hPSC-ECs into the suprachoroidal space increases choroid thickness and vasculature density. Close-up examination shows that engrafted hPSC-ECs integrate with all layers of rat choroidal vessels and last 90 days. Remarkably, EC transplantation improves the visual function of CI rats. The work demonstrates that hPSC-ECs can be used to repair choroidal ischemia in the animal model, which may lead to a new therapy to alleviate choroidal atrophy implicated in dry AMD, pathological myopia, and other ocular diseases.

Radiotherapy plus immune checkpoint inhibitor in prostate cancer.

The immune checkpoint inhibitor (ICI) is a promising strategy for treating cancer. However, the efficiency of ICI monotherapy is limited, which could be mainly attributed to the tumor microenvironment of the "cold" tumor. Prostate cancer, a type of "cold" cancer, is the most common cancer affecting men's health. Radiotherapy is regarded as one of the most effective prostate cancer treatments. In the era of immune therapy, the enhanced antigen presentation and immune cell infiltration caused by radiotherapy might boost the therapeutic efficacy of ICI. Here, the rationale of radiotherapy combined with ICI was reviewed. Also, the scheme of radiotherapy combined with immune checkpoint blockades was suggested as a potential option to improve the outcome of patients with prostate cancer.

Antitumor Activity of s-Triazine Derivatives: A Systematic Review.

1,3,5-triazine derivatives, also called s-triazines, are a series of containing-nitrogen heterocyclic compounds that play an important role in anticancer drug design and development. To date, three s-triazine derivatives, including altretamine, gedatolisib, and enasidenib, have already been approved for refractory ovarian cancer, metastatic breast cancer, and leukemia therapy, respectively, demonstrating that the s-triazine core is a useful scaffold for the discovery of novel anticancer drugs. In this review, we mainly focus on s-triazines targeting topoisomerases, tyrosine kinases, phosphoinositide 3-kinases, NADP+-dependent isocitrate dehydrogenases, and cyclin-dependent kinases in diverse signaling pathways, which have been extensively studied. The medicinal chemistry of s-triazine derivatives as anticancer agents was summarized, including discovery, structure optimization, and biological applications. This review will provide a reference to inspire new and original discoveries.

Homolog of Pea SGR Controls Stay-Green in Faba Bean (Vicia faba L.).

Faba bean is an important legume crop consumed as a vegetable or snack food, and its green cotyledons could present an attractive color for consumers. A mutation in SGR causes stay-green in plants. In this study, vfsgr was identified from a green-cotyledon-mutant faba bean, SNB7, by homologous blast between the SGR of pea and the transcriptome of faba bean. Sequence analysis revealed that a SNP at position 513 of the CDS of VfSGR caused a pre-stop codon, resulting in a shorter protein in the green-cotyledon faba bean SNB7. A dCaps marker was developed according to the SNP that caused the pre-stop, and this marker was completely associated with the color of the cotyledon of faba bean. SNB7 stayed green during dark treatment, while the expression level of VfSGR increased during dark-induced senescence in the yellow-cotyledon faba bean HST. Transient expression of VfSGR in Nicotiana. benthamiana leaves resulted in chlorophyll degradation. These results indicate that vfsgr is the gene responsible for the stay-green of faba bean, and the dCaps marker developed in this study provides a molecular tool for the breeding of green-cotyledon faba beans.

Identification of the Immune Subtypes for the Prediction of Metastasis in Pancreatic Neuroendocrine Tumors.

INTRODUCTION: Most patients with pancreatic neuroendocrine tumors (pNETs) present with unresectable or metastatic disease. Increasing evidence shows that the immune cell infiltration patterns play a pivotal role in tumor progression in pNETs. Nonetheless, there has been no comprehensive analysis of the effect of immune infiltration patterns on metastasis. METHODS: The gene expression profiling dataset and clinical data were obtained from the Gene Expression Omnibus database. Estimation of Stromal and Immune Cells in Malignant Tumors using the Expression Data and single-sample Gene Set Enrichment Analysis were used to uncover the landscape of the tumor immune microenvironment. Subtypes based on the immune infiltration patterns were identified by the unsupervised clustering algorithm. Differentially expressed genes were identified using the limma packages of R. Functional enrichment analyses of these genes were carried out using STRING, Kyoto Encyclopedia of Genes and Genomes, and Reactome. RESULTS: The landscape of immune cells in pNET samples was constructed, and three immune cell infiltration subtypes (Immunity-H, Immunity-M, and Immunity-L) were identified. Immune cell infiltration degrees and metastasis were positively correlated. A protein-protein interaction network containing 80 genes was constructed, and functional enrichment revealed that these genes were mainly enriched in immune-related pathways. Eleven metastasis-related genes were differentially expressed among three subtypes, including MMP14, MMP2, MMP12, MMP7, SPARC, MMP19, ITGAV, MMP23B, MMP1, MMP25, and MMP9. There is a certain consistency of immune infiltration pattern between the primary tumor and metastatic tumor samples. CONCLUSION: Our findings may deepen the understanding of the immune-mediated regulatory mechanisms underlying pNETs and may provide some promising targets for immunotherapy.

Screening of an annexin-A2-targeted heptapeptide for pancreatic adenocarcinoma localization.

Annexin A2 (ANXA2) encodes an oncoprotein whose expression has been found to correlate with poorer overall survival (OS) of pancreatic adenocarcinoma (PAAD) patients. Although peptides are available for targeting ANXA2, none of these were initially selected to target this protein specifically. Here, we took ANXA2 as a molecular target for PAAD and employed the phage display technique to screen for a new ANXA2-targeted peptide. The resultant heptapeptide, YW7, was firstly labeled with fluorescein isothiocyanate (FITC) to evaluate its selectivity in cellular uptake, and further with the near-infrared fluorescent (NIRF) dye Cy7 to assess in vivo distribution in a mouse model bearing PANC-1 human pancreatic cancer xenografic tumors. We found that both FITC-YW7 and Cy7-YW7 probes showed significantly higher uptake in PANC-1 cells compared to the HPDE6-C7 pancreatic epithelium cells. Mice intravenously injected with Cy7-YW7 showed higher tumor-to-background ratios (TBRs) (~ 2.7-fold) in tumor tissues compared to those injected with Cy7 alone. Our study suggested that YW7 is a novel peptide targeting ANXA2 and Cy7-YW7 is an NIRF probe potentially useful for the early detection of PAAD.

Identification of QTN-by-environment interactions and their candidate genes for soybean seed oil-related traits using 3VmrMLM.

Introduction: Although seed oil content and its fatty acid compositions in soybean were affected by environment, QTN-by-environment (QEIs) and gene-by-environment interactions (GEIs) were rarely reported in genome-wide association studies. Methods: The 3VmrMLM method was used to associate the trait phenotypes, measured in five to seven environments, of 286 soybean accessions with 106,013 SNPs for detecting QTNs and QEIs. Results: Seven oil metabolism genes (GmSACPD-A, GmSACPD-B, GmbZIP123, GmSWEET39, GmFATB1A, GmDGAT2D, and GmDGAT1B) around 598 QTNs and one oil metabolism gene GmFATB2B around 54 QEIs were verified in previous studies; 76 candidate genes and 66 candidate GEIs were predicted to be associated with these traits, in which 5 genes around QEIs were verified in other species to participate in oil metabolism, and had differential expression across environments. These genes were found to be related to soybean seed oil content in haplotype analysis. In addition, most candidate GEIs were co-expressed with drought response genes in co-expression network, and three KEGG pathways which respond to drought were enriched under drought stress rather than control condition; six candidate genes were hub genes in the co-expression networks under drought stress. Discussion: The above results indicated that GEIs, together with drought response genes in co-expression network, may respond to drought, and play important roles in regulating seed oil-related traits together with oil metabolism genes. These results provide important information for genetic basis, molecular mechanisms, and soybean breeding for seed oil-related traits.

4D genetic networks reveal the genetic basis of metabolites and seed oil-related traits in 398 soybean RILs.

BACKGROUND: The yield and quality of soybean oil are determined by seed oil-related traits, and metabolites/lipids act as bridges between genes and traits. Although there are many studies on the mode of inheritance of metabolites or traits, studies on multi-dimensional genetic network (MDGN) are limited. RESULTS: In this study, six seed oil-related traits, 59 metabolites, and 107 lipids in 398 recombinant inbred lines, along with their candidate genes and miRNAs, were used to construct an MDGN in soybean. Around 175 quantitative trait loci (QTLs), 36 QTL-by-environment interactions, and 302 metabolic QTL clusters, 70 and 181 candidate genes, including 46 and 70 known homologs, were previously reported to be associated with the traits and metabolites, respectively. Gene regulatory networks were constructed using co-expression, protein-protein interaction, and transcription factor binding site and miRNA target predictions between candidate genes and 26 key miRNAs. Using modern statistical methods, 463 metabolite-lipid, 62 trait-metabolite, and 89 trait-lipid associations were found to be significant. Integrating these associations into the above networks, an MDGN was constructed, and 128 sub-networks were extracted. Among these sub-networks, the gene-trait or gene-metabolite relationships in 38 sub-networks were in agreement with previous studies, e.g., oleic acid (trait)-GmSEI-GmDGAT1a-triacylglycerol (16:0/18:2/18:3), gene and metabolite in each of 64 sub-networks were predicted to be in the same pathway, e.g., oleic acid (trait)-GmPHS-D-glucose, and others were new, e.g., triacylglycerol (16:0/18:1/18:2)-GmbZIP123-GmHD-ZIPIII-10-miR166s-oil content. CONCLUSIONS: This study showed the advantages of MGDN in dissecting the genetic relationships between complex traits and metabolites. Using sub-networks in MGDN, 3D genetic sub-networks including pyruvate/threonine/citric acid revealed genetic relationships between carbohydrates, oil, and protein content, and 4D genetic sub-networks including PLDs revealed the relationships between oil-related traits and phospholipid metabolism likely influenced by the environment. This study will be helpful in soybean quality improvement and molecular biological research.

Effect of Scanning Speed on Properties of Laser Surface Remelted 304 Stainless Steel.

In order to study the microstructure and properties of stainless steel after laser surface remelting, based on the theory of laser surface remelting, a simulation model of nanosecond-pulsed laser surface remelted stainless steel was established to study the evolution law of the Marangoni force of the molten pool during laser surface remelting. A single-lane laser remelting experiment was performed to study the variation of the scanning speed on the remelting width, roughness, and layer microtopography. The "S" scanning path was used to remelt the stainless steel surface to investigate the bonding force between the remelted layer and the substrate, the hardness, microscopic morphology, and corrosion resistance. The results show that the viscosity of the liquid metal in the molten pool increases with the increase of the scanning speed. Larger liquid viscosity and smaller surface tension temperature gradients promote a weaker flow of liquid metal, which reduces the velocity of the liquid metal flow in the molten pool. With the increase of scanning speed, the remelting width gradually decreases, but the roughness gradually increases. When the element content of Cr increases, the element content of Fe and O decreases. The surface is covered with an oxide film, the main components of which are oxides of Cr and Fe, the remelted layer is greater than that of the substrate, and the corrosion resistance is improved. Laser surface remelting technology can improve the structure and properties of 304 stainless steel.

Predicting colorectal cancer tumor mutational burden from histopathological images and clinical information using multi-modal deep learning.

MOTIVATION: Tumor mutational burden (TMB) is an indicator of the efficacy and prognosis of immune checkpoint therapy in colorectal cancer (CRC). In general, patients with higher TMB values are more likely to benefit from immunotherapy. Though whole-exome sequencing is considered the gold standard for determining TMB, it is difficult to be applied in clinical practice due to its high cost. There are also a few DNA panel-based methods to estimate TMB; however, their detection cost is also high, and the associated wet-lab experiments usually take days, which emphasize the need for faster and cheaper alternatives. RESULTS: In this study, we propose a multi-modal deep learning model based on a residual network (ResNet) and multi-modal compact bilinear pooling to predict TMB status (i.e. TMB high (TMB_H) or TMB low(TMB_L)) directly from histopathological images and clinical data. We applied the model to CRC data from The Cancer Genome Atlas and compared it with four other popular methods, namely, ResNet18, ResNet50, VGG19 and AlexNet. We tested different TMB thresholds, namely, percentiles of 10%, 14.3%, 15%, 16.3%, 20%, 30% and 50%, to differentiate TMB_H and TMB_L.For the percentile of 14.3% (i.e. TMB value 20) and ResNet18, our model achieved an area under the receiver operating characteristic curve of 0.817 after 5-fold cross-validation, which was better than that of other compared models. In addition, we also found that TMB values were significantly associated with the tumor stage and N and M stages. Our study shows that deep learning models can predict TMB status from histopathological images and clinical information only, which is worth clinical application.

Predicting recurrence and metastasis risk of endometrial carcinoma via prognostic signatures identified from multi-omics data.

Objectives: Endometrial carcinoma (EC) is one of the three major gynecological malignancies, in which 15% - 20% patients will have recurrence and metastasis. Though there are many studies on the prognosis on this cancer, the performances of existing models evaluating the risk of its recurrence and metastasis are yet to be improved. In addition, a comprehensive multi-omics analyses on the prognostic signatures of EC are on demand. In this study, we aimed to construct a relatively stable and reliable model for predicting recurrence and metastasis of EC. This will help determine the risk level of patients and choose appropriate adjuvant therapy, thereby avoiding improper treatment, and improving the prognosis of patients. Methods: The mRNA, microRNA (miRNA), long non-coding RNA (lncRNA), copy number variation (CNV) data and clinical information of patients with EC were downloaded from The Cancer Genome Atlas (TCGA). Differential expression analyses were performed between the recurrence or metastasis group and the non-recurrence/metastasis group. Then, we screened potential prognostic markers from the four kinds of omics data respectively and established prediction models using three classifiers. Results: We achieved differential expressed mRNAs, lncRNAs, miRNAs and CNVs between the two groups. According to feature selection scores by the random forest algorithm, 275 CNV features, 50 lncRNA features, 150 miRNA features and 150 mRNA features were selected, respectively. And the prediction model constructed by the features of lncRNA data using random forest method showed the best performance, with an area under the curve of 0.763, and an accuracy of 0.819 under 10-fold cross-validation. Conclusion: We developed a computational model using omics information, which is able to predicting recurrence and metastasis risk of EC accurately.

Treatment of ankylosing spondylitis complicated with a thoracolumbar Andersson lesion by posterior closed osteotomy, debridement and fusion through the fracture line.

BACKGROUND: An Andersson lesion (AL) is a fatigue fracture occurring across three columns in ankylosing spondylitis (AS), resulting in spinal pseudarthrosis (SP) formation, most commonly in the thoracolumbar segment. However, there is still great controversy and few reports on the best surgical method for the treatment of AS combined with thoracolumbar AL. The purpose of this study was to investigate the efficacy of posterior closed osteotomy, debridement and fusion through the fracture line for the treatment of this disease. METHODS: The clinical data of 13 patients (male 8, female 5, mean age 50.6 years) with AS combined with thoracolumbar AL treated with posterior closed osteotomy, debridement and fusion through the fracture line were retrospectively analysed. The following parameters of the full-length lateral spine radiographs were measured preoperatively and at the last follow-up: cervical 7 tilt (C7T), global kyphosis (GK), thoracic kyphosis (TK), thoracolumbar kyphosis (TLK), local kyphosis (LK), angle of the fusion levels (AFL), lumbar lordosis (LL), pelvic incidence (PI), pelvic tilt (PT), sacral slope (SS) and sagittal vertical axis (SVA). The visual analog scale (VAS), Oswestry disability index (ODI) and Scoliosis Research Society-22 (SRS-22) scores were recorded preoperatively and at the last follow-up. RESULTS: The mean operation time was 345 min, the mean blood loss was 673 mL, and the mean follow-up time was 21.9 months. Compared with the preoperative values, the C7T, GK, TK, TLK, LK, AFL, PT, SS and SVA values of all patients were significantly improved at the last follow-up (P < 0.05); GK improved from 81.62 ± 16.11 to 50.15 ± 8.55, with an average of 31° of correction (F = 75.945, P<0.001). The VAS, ODI and SRS-22 scores also significantly improved (P < 0.05). At the last follow-up, bone fusion was found in all fracture ends. One patient developed numbness in the lower limbs after surgery and recovered after 3 months of rehabilitation; none of the remaining patients experienced postoperative complications. CONCLUSIONS: Posterior closed osteotomy, debridement and fusion through the fracture line completely removes the necrotic tissue around the SP, relieves symptoms, and corrects kyphosis simultaneously. It reduces the tension behind the fracture line or changes the tension into compressive stress, enabling stable repair of the fracture and avoiding anterior surgery. It is a safe and effective operation.

Strategy and Efficacy of Surgery for Congenital Cervicothoracic Scoliosis with or without Hemivertebra Osteotomy.

OBJECTIVE: Cervicothoracic scoliosis will cause severe deformities in the early stage, and its structure is complex and the surgical methods are varied. The purpose of this research is to explore the indication and analyze the corrective effect of the two different posterior approach surgical strategies, including correction with fusion and hemivertebra osteotomy, for congenital cervicothoracic scoliosis deformities in children and adolescents. METHODS: This was a retrospective study of 21 patients with cervicothoracic scoliosis who received surgical treatment from January 2010 to June 2020, including nine cases of posterior hemivertebra osteotomy and fusion surgery and 12 cases of posterior correction and fusion alone. The Cobb angle, T1 tilt angle, clavicular angle, neck tilt angle, radiographic shoulder height, sagittal vertical axis, coronal balance distance, and local kyphosis angle were measured preoperatively, postoperatively, and at the last follow-up. Posterior approach hemivertebra resection or correction with fusion surgery was adopted based on the different individual characteristics of deformity such as main curve Cobb angle, growth potential, and flexibility. Patients were divided into two groups (osteotomy group and nonosteotomy group) according to whether a hemivertebra osteotomy was performed, and the corrective results in the two groups were compared. Paired-sample t tests or independent-sample t tests were used. RESULTS: The median follow-up after surgery of the 21 patients was 36 months (range, 18-72 months). The Cobb angle was corrected from 45.81° ± 14.23° preoperatively to 10.48° ± 5.56° postoperatively (correction rate, 77.78% ± 8.93%). The T1 tilt angle decreased from 15.26° ± 7.08° preoperatively to 3.33° ± 2.14° postoperatively (correction rate,73.42% ± 21.86%). The radiographic shoulder height was corrected from 1.13 ± 0.74 cm preoperatively to 0.52 ± 0.42 cm postoperatively (correction rate, 39.51% ± 35.65%). The clavicular angle improved from 2.52° ± 1.55° preoperatively to 1.16° ± 0.96° postoperatively (correction rate, 47.18% ± 35.84%). No significant differences were found at the last follow-up (p > 0.05). The Cobb angle of the main curve, T1 tilt angle, clavicular angle, cervical tilt angle, and shoulder height difference were similar in the two groups (p > 0.05). CONCLUSIONS: Posterior approach hemivertebra resection or correction with fusion surgery can be used in the treatment of congenital cervicothoracic scoliosis with satisfactory results, and the surgeon can make an individualized surgical plan according to individual characteristics of deformity.

The mungbean VrP locus encoding MYB90, an R2R3-type MYB protein, regulates anthocyanin biosynthesis.

Anthocyanins are water-soluble pigments present in several tissues/parts of plants. The pigments provide color and are wildly known for health benefits for human, insect attraction for plant pollination, and stress resistance in plants. Anthocyanin content variations in mungbean [Vigna radiata (L.) Wilczek] were first noticed a long time ago, but the genetic mechanism controlling the anthocyanins in mungbean remains unknown. An F2 population derived from the cross between purple-hypocotyl (V2709) and green-hypocotyl (Sulv1) mungbeans was used to map the VrP locus controlling purple hypocotyl. The VrP locus was mapped to a 78.9-kb region on chromosome 4. Sequence comparison and gene expression analysis identified an R2R3-MYB gene VrMYB90 as the candidate gene for the VrP locus. Haplotype analysis using 124 mungbean accessions suggested that 10 single nucleotide polymorphisms (SNPs) in exon 3 may lead to an abolished expression of VrMYB90 and an absence of anthocyanin accumulation in the hypocotyl of Sulv1 and KPS2. The overexpression of VrMYB90 in mungbean hairy root, tobacco leaf, and Arabidopsis resulted in anthocyanin accumulation (purple color). Gene expression analysis demonstrated that VrMYB90 regulated anthocyanin accumulation in the hypocotyl, stem, petiole, and flowers, and the expression was sensitive to light. VrMYB90 protein may upregulate VrDFR encoding dihydroflavonol 4-reductase at the late biosynthesis step of anthocyanins in mungbeans. These results suggest that VrMYB90 is the dominator in the spatiotemporal regulation of anthocyanin biosynthesis. Our results provide insight into the biosynthesis mechanism of anthocyanin and a theoretical basis for breeding mungbeans.

Domestication and improvement genes reveal the differences of seed size- and oil-related traits in soybean domestication and improvement.

To address domestication and improvement studies of soybean seed size- and oil-related traits, a series of domesticated and improved regions, loci, and candidate genes were identified in 286 soybean accessions using domestication and improvement analyses, genome-wide association studies, quantitative trait locus (QTL) mapping and bulked segregant analyses in this study. As a result, 534 candidate domestication regions (CDRs) and 458 candidate improvement regions (CIRs) were identified in this study and integrated with those in five and three previous studies, respectively, to obtain 952 CDRs and 538 CIRs; 1469 loci for soybean seed size- and oil-related traits were identified in this study and integrated with those in Soybase to obtain 433 QTL clusters. The two results were intersected to obtain 245 domestication and 221 improvement loci for the above traits. Around these trait-related domestication and improvement loci, 7 domestication and 7 improvement genes were found to be truly associated with these traits, and 372 candidate domestication and 87 candidate improvement genes were identified using gene expression, SNP variants in genome, miRNA binding, KEGG pathway, DNA methylation, and haplotype analysis. These genes were used to explain the trait changes in domestication and improvement. As a result, the trait changes can be explained by their frequencies of elite haplotypes, base mutations in coding region, and three factors affecting their expression levels. In addition, 56 domestication and 15 improvement genes may be valuable for future soybean breeding. This study can provide useful gene resources for future soybean breeding and molecular biology research.

A Systematic Framework for Identifying Prognostic Genes in the Tumor Microenvironment of Colon Cancer.

As one of the most common cancers of the digestive system, colon cancer is a predominant cause of cancer-related deaths worldwide. To investigate prognostic genes in the tumor microenvironment of colon cancer, we collected 461 colon adenocarcinoma (COAD) and 172 rectal adenocarcinoma (READ) samples from The Cancer Genome Atlas (TCGA) database, and calculated the stromal and immune scores of each sample. We demonstrated that stromal and immune scores were significantly associated with colon cancer stages. By analyzing differentially expressed genes (DEGs) between two stromal and immune score groups, we identified 952 common DEGs. The significantly enriched Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) terms for these DEGs were associated with T-cell activation, immune receptor activity, and cytokine-cytokine receptor interaction. Through univariate Cox regression analysis, we identified 22 prognostic genes. Furthermore, nine key prognostic genes, namely, HOXC8, SRPX, CCL22, CD72, IGLON5, SERPING1, PCOLCE2, FABP4, and ARL4C, were identified using the LASSO Cox regression analysis. The risk score of each sample was calculated using the gene expression of the nine genes. Patients with high-risk scores had a poorer prognosis than those with low-risk scores. The prognostic model established with the nine-gene signature was able to effectively predict the outcome of colon cancer patients. Our findings may help in the clinical decisions and improve the prognosis for colon cancer.

NUDT1 Could Be a Prognostic Biomarker and Correlated with Immune Infiltration in Clear Cell Renal Cell Carcinoma.

Background: Clear cell renal cell carcinoma (ccRCC) is a malignant tumor with high morbidity and mortality. As a member of the Nudix hydrolase superfamily, Nudix (nucleoside diphosphate-linked moiety X)-type motif 1 (NUDT1) is closely related to the occurrence and development of cancer. Our study aims to explore the role of NUDT1 in ccRCC and its relationship with immune infiltration. Methods: The NUDT1 expression matrix and corresponding clinical information were obtained from The Cancer Genome Atlas (TCGA) database. The expression difference of NUDT1 in ccRCC and its relationship with the clinical characteristics were investigated using R software. Kaplan-Meier (K-M) analysis, univariate Cox regression, multivariate Cox regression, receiver operating characteristic (ROC) curve, and nomogram were utilized to evaluate the survival and prognosis of patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were utilized to explore the function of differential genes in low- or high-expression group of NUDT1. TCGA dataset and Tumor IMmune Estimation Resource (TIMER) database were utilized to explore the relationship between NUDT1 and immune infiltration. Finally, TCGA dataset was utilized for gene set enrichment analysis (GSEA). Results: NUDT1 was not only overexpressed in ccRCC but also significantly correlated with clinicopathological features (P < 0.05). K-M survival analysis showed that upregulated NUDT1 was closely related to the decrease of overall survival (OS) and progression-free survival (PFS) in ccRCC patients. Multivariate Cox regression revealed that NUDT1 was a independent prognostic indicator (HR = 1.437, 95% CI: 1.065-1.939, P=0.018). The ROC curve showed that NUDT1 had a certain accuracy in predicting the outcome of ccRCC patiens. Furthermore, a total of 150 coexpressed genes and 1,886 differentially expressed genes (DEGs) were identified. GO/KEGG and GSEA results suggested that NUDT1 and its DEGs were involved in the immune-related pathways. NUDT1 expression was positively correlated with infiltrating levels of regulatory T cells (Tregs), CD8+ T cells, follicular helper T cells, and M0 macrophages. In addition, NUDT1 was positively related to immune checkpoints, such as PD-1, LAG3, CTLA4, and CD70, in ccRCC. Conclusion: NUDT1 plays a key role in the prognosis and immune cell infiltration of ccRCC patients, indicating its potential use as a prognostic biomarker and therapeutic target.

Expression of Cyclin D1 gene in ovarian cancer and effect of silencing its expression on ovarian cancer cells based on the Oncomine database.

We aimed to analyze the expression of Cyclin D1 (CCND1) gene in ovarian cancer and the influence of silencing its expression on ovarian cancer cells based on the Oncomine database. The expression of CCND1 gene in ovarian cancer was analyzed by utilizing the relevant information in different tumors and Oncomine database. The correlation between CCDN1 expression level and prognosis of ovarian cancer was analyzed by the online database Kaplan-Meier (kmplot.com). The expression of CCND1 gene in ovarian cancer and the effect of silencing its expression on cancer cells were analyzed by cell experiments. After mining and comprehensively analyzing 7 studies on the differential expression of CCND1 gene in ovarian cancer tissue and normal ovarian tissue included in the Oncomine database, it was found that the median value of CCND1 gene ranked 218.0 (P = 8.03 × 10-6) among all differentially expressed genes, suggesting that CCND1 gene expression in ovarian cancer tissue was higher than that in normal ovarian tissue. Adib Ovarian, Bonome Ovarian and Hendrix Ovarian microarrays revealed that the expression of CCND1 gene in ovarian cancer tissue was significantly higher than that in normal ovarian tissue (P < 0.05). Kaplan-Meier Plotter database showed that the overall survival and progression-free survival of ovarian cancer patients with high CCND1 expression were significantly shorter than those of patients with low CCND1 expression (P < 0.05). The expression levels of CCND1 gene in normal ovarian epithelial cells and SKOV3 ovarian cancer cells were detected by RT-PCR. The expression of CCND1 gene was significantly higher in SKOV3 group than that in control group (P < 0.01). Flow cytometry revealed that the percentage of cells in G0/G1 phase was significantly higher, while that in S phase was lower in SKOV3 + siCCND1 group than the values of SKOV3 and SKOV3 + siNC groups (P < 0.05). The apoptosis rate of ovarian cancer cells was significantly higher in SKOV3 + siCCND1 group than those of SKOV3 and SKOV3 + siNC groups (P < 0.01). CCND1 gene is highly expressed in ovarian cancer tissue and related to prognosis. Preoperative evaluation of CCND1 gene expression in ovarian cancer patients may benefit the assessment of risk and prognosis.