Senescence-related genes analysis in breast cancer reveals the immune microenvironment and implications for immunotherapy

Despite the advent of precision therapy for breast cancer (BRCA) treatment, some individuals are still unable to benefit from it and have poor survival prospects as a result of the disease's high heterogeneity. Cell senescence plays a crucial role in the tumorigenesis, progression, and immune regulation of cancer and has a major impact on the tumor microenvironment. To find new treatment strategies, we aimed to investigate the potential significance of cell senescence in BRCA prognosis and immunotherapy. We created a 9-gene senescence-related signature. We evaluated the predictive power and the role of signatures in the immune microenvironment and infiltration. In vitro tests were used to validate the expression and function of the distinctive critical gene ACTC1. Our risk signature allows BRCA patients to receive a Predictive Risk Signature (PRS), which may be used to further categorize a patient's response to immunotherapy. Compared to conventional clinicopathological characteristics, PRS showed strong predictive efficacy and precise survival prediction. Moreover, PRS subgroups were examined for altered pathways, mutational patterns, and possibly useful medicines. Our research offers suggestions for incorporating senescence-based molecular classification into risk assessment and ICI therapy decision-making.

The combination treatment of oncolytic adenovirus H101 with nivolumab for refractory advanced hepatocellular carcinoma: an open-label, single-arm, pilot study

BACKGROUND

H101, an innovative oncolytic adenovirus, has shown potential in modifying the tumor microenvironment from immunologically 'cold' to 'hot'. When combined with nivolumab, a programmed cell death protein 1 inhibitor, this synergy may offer substantial therapeutic benefits beyond the capabilities of each agent alone.

PATIENTS AND METHODS

In this pilot study, we assessed the efficacy and safety of combining H101 with nivolumab in advanced hepatocellular carcinoma (HCC) patients who failed prior systemic therapy. The participants received initial oncolytic virus (OV) pretreatment with intratumoral H101 injections (5.0 × 1011 vp/0.5 ml/vial, two vials per lesion) on days 1 and 3. Combination therapy started on day 8, with H101 administered every 2 or 4 weeks and nivolumab (240 mg) injections every 2 weeks. Treatment continued up to 12 months or until disease progression, intolerable toxicity, consent withdrawal, or study conclusion. The primary endpoint was the objective response rate (ORR).

RESULTS

Between March 2020 and March 2022, 18 of 21 screened patients were assessable, showing an ORR of 11.1% [two cases of partial response (PR) and five cases of stable disease], with extrahepatic injections often leading to favorable outcomes. The disease control rate stood at 38.9%, with a 6-month survival rate of 88.9%. Median progression-free survival was 2.69 months, and overall survival (OS) was 15.04 months. Common adverse events included low-grade fever (100%) and pain related to centesis (33.3%), and no grade 3/4 events were reported. Significantly, local H101 injection showed potential in reversing immune checkpoint inhibitor resistance, evidenced by over 2.5 years of extended OS in PR cases with low α-fetoprotein. Additionally, decreasing neutrophil-to-lymphocyte ratio during OV pretreatment may predict positive outcomes.

CONCLUSIONS

This study demonstrates the potential efficacy of combining H101 with nivolumab in treating refractory advanced HCC, with well-tolerated toxicities.

Amivantamab plus chemotherapy with and without lazertinib in EGFR-mutant advanced NSCLC after disease progression on osimertinib: primary results from the phase III MARIPOSA-2 study

BACKGROUND

Amivantamab plus carboplatin-pemetrexed (chemotherapy) with and without lazertinib demonstrated antitumor activity in patients with refractory epidermal growth factor receptor (EGFR)-mutated advanced non-small-cell lung cancer (NSCLC) in phase I studies. These combinations were evaluated in a global phase III trial.

PATIENTS AND METHODS

A total of 657 patients with EGFR-mutated (exon 19 deletions or L858R) locally advanced or metastatic NSCLC after disease progression on osimertinib were randomized 2 : 2 : 1 to receive amivantamab-lazertinib-chemotherapy, chemotherapy, or amivantamab-chemotherapy. The dual primary endpoints were progression-free survival (PFS) of amivantamab-chemotherapy and amivantamab-lazertinib-chemotherapy versus chemotherapy. During the study, hematologic toxicities observed in the amivantamab-lazertinib-chemotherapy arm necessitated a regimen change to start lazertinib after carboplatin completion.

RESULTS

All baseline characteristics were well balanced across the three arms, including by history of brain metastases and prior brain radiation. PFS was significantly longer for amivantamab-chemotherapy and amivantamab-lazertinib-chemotherapy versus chemotherapy [hazard ratio (HR) for disease progression or death 0.48 and 0.44, respectively; P < 0.001 for both; median of 6.3 and 8.3 versus 4.2 months, respectively]. Consistent PFS results were seen by investigator assessment (HR for disease progression or death 0.41 and 0.38 for amivantamab-chemotherapy and amivantamab-lazertinib-chemotherapy, respectively; P < 0.001 for both; median of 8.2 and 8.3 versus 4.2 months, respectively). Objective response rate was significantly higher for amivantamab-chemotherapy and amivantamab-lazertinib-chemotherapy versus chemotherapy (64% and 63% versus 36%, respectively; P < 0.001 for both). Median intracranial PFS was 12.5 and 12.8 versus 8.3 months for amivantamab-chemotherapy and amivantamab-lazertinib-chemotherapy versus chemotherapy (HR for intracranial disease progression or death 0.55 and 0.58, respectively). Predominant adverse events (AEs) in the amivantamab-containing regimens were hematologic, EGFR-, and MET-related toxicities. Amivantamab-chemotherapy had lower rates of hematologic AEs than amivantamab-lazertinib-chemotherapy.

CONCLUSIONS

Amivantamab-chemotherapy and amivantamab-lazertinib-chemotherapy improved PFS and intracranial PFS versus chemotherapy in a population with limited options after disease progression on osimertinib. Longer follow-up is needed for the modified amivantamab-lazertinib-chemotherapy regimen.

Neural Endophenotype Assessment in Zebrafish Larvae Using Optomotor and ZebraBox Locomotion Assessment

Due to the highly conserved genetics across the central nervous system, the easily probed visual system can act as an endophenotype for assessing neurological function. Here, we describe a psychophysics approach to assess visually driven swimming behavior in the high-throughput zebrafish genetic model system. We use the optomotor response test together with general locomotion behavior to assess neural processing while excluding motor defects related to muscle function.

A Statistical Framework for Assessing the Relationship between Biomarkers and Clinical Endpoints in Alzheimer's Disease

Changes in biomarker levels of Alzheimer's disease (AD) reflect underlying pathophysiological changes in the brain and can provide evidence of direct and downstream treatment effects linked to disease modification. Recent results from clinical trials of anti-amyloid β (Aβ) treatments have raised the question of how to best characterize the relationship between AD biomarkers and clinical endpoints. Consensus methodology for assessing such relationships is lacking, leading to inconsistent evaluation and reporting. In this review, we provide a statistical framework for reporting treatment effects on early and late accelerating AD biomarkers and assessing their relationship with clinical endpoints at the subject and group levels. Amyloid positron emission tomography (PET), plasma p-tau, and tau PET follow specific trajectories during AD and are used as exemplar cases to contrast biomarkers with early and late progression. Subject-level correlation was assessed using change from baseline in biomarkers versus change from baseline in clinical endpoints, and interpretation of the correlation is dependent on the biomarker and disease stage. Group-level correlation was assessed using the placebo-adjusted treatment effects on biomarkers versus those on clinical endpoints in each trial. This correlation leverages the fundamental advantages of randomized placebo-controlled trials and assesses the predictivity of a treatment effect on a biomarker or clinical benefit. Harmonization in the assessment of treatment effects on biomarkers and their relationship to clinical endpoints will provide a wealth of comparable data across clinical trials and may yield new insights for the treatment of AD.

Analysis of the mechanism of Sophorae Flavescentis Radix in the treatment of intractable itching based on network pharmacology and molecular docking

OBJECTIVE

Sophorae Flavescentis Radix (Kuh-seng, SFR), a Traditional Chinese Medicine (TCM), is widely used alone or within a TCM formula to treat pruritus, especially histamine-independent intractable itching. In the previous study, potential antipruritic active components of the SFR were screened based on cell membrane immobilized chromatography (CMIC), revealing oxymatrine (OMT) as an antipruritic agent. However, the low oral bioavailability (OB) of OMT cannot explain the antipruritic effect of SFR when administered orally in clinic. In this study, we investigated the antipruritic effects and underlying mechanisms of orally administered SFR.

MATERIALS AND METHODS

A network pharmacology and molecular docking were employed to screen the active components of SFR and predict their binding to disease-related target proteins, while the potential mechanisms were explored with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The binding energy between components and target proteins was calculated by molecular docking.

RESULTS

The SFR-components-targets-intractable itching Protein-Protein Interactions (PPI) network was established, and 22 active components and 42 targets were screened. The GO enrichment analysis showed that the key target genes of SFR were related to nuclear receptors, transcription factors, and steroid hormone receptors. The results of the KEGG enrichment pathway analysis include Hepatitis B, epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor resistance, advanced glycation end product (AGE)-receptor for AGE (RAGE) signaling pathway in diabetic complications, etc. Molecular docking showed that three key target proteins in the network, the vascular endothelial growth factor A (VEGFA), epidermal growth factor receptor (EGFR) and caspase-3 (CASP3), have higher binding activities with inermine, phaseolin and kushenol O, respectively; the binding energy of each pair is stronger than that of the target protein-corresponding inhibitors.

CONCLUSIONS

The complexity of the SFR-components-targets-intractable itching network demonstrated the holistic treatment effect of SFR on intractable itching. The partial coherence between results screened by CMIC in the previous study and network pharmacology demonstrated the potential of network pharmacology in active component screening. Inermine screened from both CMIC and network pharmacology is a VEGFA inhibitor, which possibly accounts for the antipruritic effect of orally administered SFR.

The role of ATP binding cassette (ABC) transporters in breast cancer: Evaluating prognosis, predicting immunity, and guiding treatment

Breast cancer is currently the most prevalent form of cancer worldwide. Nevertheless, there remains limited clarity regarding our understanding of the tumor microenvironment and metabolic characteristics associated with it. ATP-binding cassette (ABC) transporters are the predominant transmembrane transporters found in organisms. Therefore, it is essential to investigate the role of ABC transporters in breast cancer. Transcriptome data from breast cancer patients were downloaded from the TCGA database. ABC transporter-related genes were obtained from the Genecards database. By LASSO regression, ABC-associated prognostic signature was constructed in breast cancer. Subsequently, immune microenvironment analysis was performed. Finally, cell experiments were performed to verify the function of ABCB7 in the breast cancer cell lines MDA-MB-231 and MCF-7. Using the ABC transporter-associated signature, we calculated a risk score for each breast cancer patient. Patients with breast cancer were subsequently categorized into high-risk and low-risk groups, utilizing the median risk score as the threshold. Notably, patients in the high-risk group exhibited significantly worse prognosis (P<0.05). Additionally, differences were observed in terms of immune cell infiltration levels, immune correlations, and gene expression of immune checkpoints between the two groups. Functional experiments conducted on breast cancer cell lines MDA-MB-231 and MCF-7 demonstrated that ABCB7 knockdown significantly diminished cell activity, proliferation, invasion, and migration. These findings emphasize the significance of understanding ABC transporter-mediated metabolic and transport characteristics in breast cancer, offering promising directions for further research and potential therapeutic interventions.

Digging out the biology properties of tRNA-derived small RNA from black hole

An unique subclass of functional non-coding RNAs generated by transfer RNA (tRNA) under stress circumstances is known as tRNA-derived small RNA (tsRNA). tsRNAs can be divided into tRNA halves and tRNA-derived fragments (tRFs) based on the different cleavage sites. Like microRNAs, tsRNAs can attach to Argonaute (AGO) proteins to target downstream mRNA in a base pairing manner, which plays a role in rRNA processing, gene silencing, protein expression and viral infection. Notably, tsRNAs can also directly bind to protein and exhibit functions in transcription, protein modification, gene expression, protein stabilization, and signaling pathways. tsRNAs can control the expression of tumor suppressor genes and participate in the initiation of cancer. It can also mediate the progression of diseases by regulating cell viability, migration ability, inflammatory factor content and autophagy ability. Precision medicine targeting tsRNAs and drug therapy of plant-derived tsRNAs are expected to be used in clinical practice. In addition, liquid biopsy technology based on tsRNAs indicates a new direction for the non-invasive diagnosis of diseases.

Interaction, immune infiltration characteristics and prognostic modeling of efferocytosis-related subtypes in glioblastoma

BACKGROUND

Efferocytosis is a biological process in which phagocytes remove apoptotic cells and vesicles from tissues. This process is initiated by the release of inflammatory mediators from apoptotic cells and plays a crucial role in resolving inflammation. The signals associated with efferocytosis have been found to regulate the inflammatory response and the tumor microenvironment (TME), which promotes the immune escape of tumor cells. However, the role of efferocytosis in glioblastoma multiforme (GBM) is not well understood and requires further investigation.

METHODS

In this study, we conducted a comprehensive analysis of 22 efferocytosis-related genes (ERGs) by searching for studies related to efferocytosis. Using bulk RNA-Seq and single-cell sequencing data, we analyzed the expression and mutational characteristics of these ERGs. By using an unsupervised clustering algorithm, we obtained ERG clusters from 549 GBM patients and evaluated the immune infiltration characteristics of each cluster. We then identified differential genes (DEGs) in the two ERG clusters and classified GBM patients into different gene clusters using univariate cox analysis and unsupervised clustering algorithms. Finally, we utilized the Boruta algorithm to screen for prognostic genes and reduce dimensionality, and the PCA algorithm was applied to create a novel efferocytosis-related scoring system.

RESULTS

Differential expression of ERGs in glioma cell lines and normal cells was analyzed by rt-PCR. Cell function experiments, on the other hand, validated TIMD4 as a tumor risk factor in GBM. We found that different ERG clusters and gene clusters have distinct prognostic and immune infiltration profiles. The ERG signature we developed provides insight into the tumor microenvironment of GBM. Patients with lower ERG scores have a better survival rate and a higher likelihood of benefiting from immunotherapy.

CONCLUSIONS

Our novel efferocytosis-related signature has the potential to be used in clinical practice for risk stratification of GBM patients and for selecting individuals who are likely to respond to immunotherapy. This can help clinicians design appropriate targeted therapies before initiating clinical treatment.

Combining single-cell sequencing and spatial transcriptome sequencing to identify exosome-related features of glioblastoma and constructing a prognostic model to identify BARD1 as a potential therapeutic target for GBM patients

Background

Glioblastoma (GBM) is a malignant primary brain tumor. This study focused on exploring the exosome-related features of glioblastoma to better understand its cellular composition and molecular characteristics.

Methods

Single-cell RNA sequencing (scRNA-seq) and spatial transcriptome RNA sequencing (stRNA-seq) were used to analyze the heterogeneity of glioblastomas. After data integration, cell clustering, and annotation, five algorithms were used to calculate scores for exosome-related genes(ERGs). Cell trajectory analysis and intercellular communication analysis were performed to explore exosome-related communication patterns. Spatial transcriptome sequencing data were analyzed to validate the findings. To further utilize exosome-related features to aid in clinical decision-making, a prognostic model was constructed using GBM's bulk RNA-seq.

Results

Different cell subpopulations were observed in GBM, with Monocytes/macrophages and malignant cells in tumor samples showing higher exosome-related scores. After identifying differentially expressed ERGs in malignant cells, pseudotime analysis revealed the cellular status of malignant cells during development. Intercellular communication analysis highlighted signaling pathways and ligand-receptor interactions. Spatial transcriptome sequencing confirmed the high expression of exosome-related gene features in the tumor core region. A prognostic model based on six ERGs was shown to be predictive of overall survival and immunotherapy outcome in GBM patients. Finally, based on the results of scRNA-seq and prognostic modeling as well as a series of cell function experiments, BARD1 was identified as a novel target for the treatment of GBM.

Conclusion

This study provides a comprehensive understanding of the exosome-related features of GBM in both scRNA-seq and stRNA-seq, with malignant cells with higher exosome-related scores exhibiting stronger communication with Monocytes/macrophages. In terms of spatial data, highly scored malignant cells were also concentrated in the tumor core region. In bulk RNA-seq, patients with a high exosome-related index exhibited an immunosuppressive microenvironment, which was accompanied by a worse prognosis as well as immunotherapy outcomes. Prognostic models constructed using ERGs are expected to be independent prognostic indicators for GBM patients, with potential implications for personalized treatment strategies for GBM. Knockdown of BARD1 in GBM cell lines reduces the invasive and value-added capacity of tumor cells, and thus BARD1-positively expressing malignant cells are a risk factor for GBM patients.

[Analysis of respiratory syncytial virus nonstructural protein 1 amino acid variation and clinical characteristics]

Objective: To investigate the relationship between amino acid variations of respiratory syncytial virus (RSV) nonstructural protein (NS) 1 and the clinical characteristics. Method: A retrospective case review was conducted. From December 2018 to January 2020, a total of 81 cases of hospitalized children who were tested only positive for RSV by RT-PCR or PCR at the Department of Respiratory Medicine, Children's Hospital of Chongqing Medical University were included in the study. The NS1 genes of RSV subtype A and subtype B were amplified by PCR and sequenced. The amino acid sequences were analyzed. The Chi-square test and Mann-Whitney rank sum test were used to compare the clinical characteristics and type Ⅰ interferon levels of children with or without NS1 variation in the variation and non-variation groups. Results: Among 81 cases, there were 58 males and 23 females. There were 11 cases in the variation group, the age of onset was 2.0 (1.0, 11.0) months, included 4 cases of subtype A (variant sites were: 2 cases for Lys33Gln, one case for Gly2Asp, Pro67Ser, Leu137Phe, respectively) and 7 cases of subtype B (variant sites were: two cases for Val121Ile, one case for Tyr30Cys, Val65Met, Asn85Ser, Ser118Asn, Asp124Asn, respectively). These variant sites all appeared at a very low frequency 0.08 (0.04, 0.29) % in the NCBI PROTEIN database. There were 70 cases in non-variation group, the onset age was 3.5 (1.0, 7.0) months. The proportion of dyspnea in the variation group was higher than that in the non-variation group (10/11 vs. 47% (33/70), χ²=7.31, P<0.01). Conclusions: There are some variant sites in nonstructural protein NS1 of RSV. Children may be prone to have dyspnea with NS1 variations.

A pretreatment scheme for plasmid extraction contained sugar, high concentration lysozyme and mild lysozyme removal

To address the issue of low efficiency in extracting plasmid DNA (pDNA) from Lactobacillus plantarum by breaking the cell wall, we proposed an effective pretreatment scheme. This study investigated the impacts of lysozyme concentrations and glucose, as well as centrifugal forces during lysozyme removal in the pretreatment system. The efficiency of pDNA extraction was assessed using non-staining method, acridine orange staining method (AO staining) and agarose gel electrophoresis (AGE). Furthermore, the glucose high lysozyme method was compared to the commercial kit method and the lysozyme removal method using L. plantarum PC518, 9L15, JS193 and Staphylococcus aureus USA300. The results indicated that the pDNA extraction concentrations from the four tested strains were increased by 8.9, 7.2, 8.5 and 3.6 times, respectively, compared to the commercial kit method. Furthermore, they increased by 1.9, 1.5, 1.8, and 1.4 times, respectively, compared to the lysozyme removal method. The maximum average concentration of pDNA extraction (from L. plantarum PC518) reached 590.8 ± 31.9 ng/ul. In conclusion, the incorporation of sugar, high concentration lysozyme and mild lysozyme removal proved to be effective enhancements in improving the efficiency of pDNA extraction from L. plantarum. Using the pretreatment scheme, the concentration of pDNA extraction was significantly increased, approaching levels comparable to pDNA extraction from Gram-negative bacteria.

Single-cell sequencing analysis of peripheral blood in patients with moyamoya disease

BACKGROUND

At present, the etiology of moyamoya disease is not clear, and it is necessary to explore the mechanism of its occurrence and development. Although some bulk sequencing data have previously revealed transcriptomic changes in Moyamoya disease, single-cell sequencing data has been lacking.

METHODS

Two DSA(Digital Subtraction Angiography)-diagnosed patients with moyamoya disease were recruited between January 2021 and December 2021. Their peripheral blood samples were single-cell sequenced. CellRanger(10 x Genomics, version 3.0.1) was used to process the raw data, demultiplex cellular barcodes, map reads to the transcriptome, and dowm-sample reads(as required to generate normalized aggregate data across samples). There were 4 normal control samples, including two normal samples GSM5160432 and GSM5160434 of GSE168732, and two normal samples of GSE155698, namely GSM4710726 and GSM4710727. Weighted co-expression network analysis was used to explore the gene sets associated with moyamoya disease. GO analysis and KEGG analysis were used to explore gene enrichment pathways. Pseudo-time series analysis and cell interaction analysis were used to explore cell differentiation and cell interaction.

RESULTS

For the first time, we present a peripheral blood single cell sequencing landscape of Moyamoya disease, revealing cellular heterogeneity and gene expression heterogeneity. In addition, by combining with WGCNA analysis in public database and taking intersection, the key genes in moyamoya disease were obtained. namely PTP4A1, SPINT2, CSTB, PLA2G16, GPX1, HN1, LGALS3BP, IFI6, NDRG1, GOLGA2, LGALS3. Moreover, pseudo-time series analysis and cell interaction analysis revealed the differentiation of immune cells and the relationship between immune cells in Moyamoya disease.

CONCLUSIONS

Our study can provide information for the diagnosis and treatment of moyamoya disease.

Application of lung ultrasound in monitoring bronchopulmonary dysplasia and pulmonary arterial pressure in preterm infants

OBJECTIVE

The aim of this study was to evaluate the application value of lung ultrasound in monitoring bronchopulmonary dysplasia (BPD) and pulmonary artery pressure in premature infants.

PATIENTS AND METHODS

A total of 98 preterm infants diagnosed with BPD in the Fourth Hospital in Shijiazhuang were recruited, and their disease severity was classified as mild (n=32), moderate (n=33), or severe BPD (n=33) based on gestational age and oxygen concentration. Lung ultrasonography of the children was performed. The correlation between lung ventilation scores and disease severity was statistically analyzed, and the discrete optimization results were documented. The pulmonary hypertension indexes of the three groups of children were compared.

RESULTS

Aberrant alterations of the pleural line were observed in all included children, and the B-line rose as the disease progressed. The duration of invasive ventilation, medication, and hospital stay increased with disease exacerbation (p<0.05). The three groups significantly differed in terms of ultrasound pulmonary ventilation scores and clinical severity (p<0.05). Only mild BDP was identified by lung ultrasound on the first day of birth (T1), and severe BDP was detectable during the first and second week (T2-T3) as well as the third and fourth week (T4-T5). Severe BPD was associated with significantly higher levels of pulmonary hypertension indices vs. mild and moderate BPD (p<0.05).

CONCLUSIONS

Pulmonary ultrasonography demonstrates great potential to predict pulmonary hypertension in children and assesses the disease severity. Pulmonary ultrasound allows for dynamical real-time observation of the pulmonary lesions in children with pulmonary hypertension, thereby revealing the severity of pulmonary hypertension in premature children.

Significance of liquid-liquid phase separation (LLPS)-related genes in breast cancer: a multi-omics analysis

Currently, the role of liquid-liquid phase separation (LLPS) in cancer has been preliminarily explained. However, the significance of LLPS in breast cancer is unclear. In this study, single cell sequencing datasets GSE188600 and GSE198745 for breast cancer were downloaded from the GEO database. Transcriptome sequencing data for breast cancer were downloaded from UCSC database. We divided breast cancer cells into high-LLPS group and low-LLPS group by down dimension clustering analysis of single-cell sequencing data set, and obtained differentially expressed genes between the two groups. Subsequently, weighted co-expression network analysis (WGCNA) was performed on transcriptome sequencing data, and the module genes most associated with LLPS were obtained. COX regression and Lasso regression were performed and the prognostic model was constructed. Subsequently, survival analysis, principal component analysis, clinical correlation analysis, and nomogram construction were used to evaluate the significance of the prognostic model. Finally, cell experiments were used to verify the function of the model's key gene, PGAM1. We constructed a LLPS-related prognosis model consisting of nine genes: POLR3GL, PLAT, NDRG1, HMGB3, HSPH1, PSMD7, PDCD2, NONO and PGAM1. By calculating LLPS-related risk scores, breast cancer patients could be divided into high-risk and low-risk groups, with the high-risk group having a significantly worse prognosis. Cell experiments showed that the activity, proliferation, invasion and healing ability of breast cancer cell lines were significantly decreased after knockdown of the key gene PGAM1 in the model. Our study provides a new idea for prognostic stratification of breast cancer and provides a novel marker: PGAM1.

Effects of warming on seed germination of woody species in temperate secondary forests

Seed germination, a critical stage of the plant life cycle providing a link between seeds and seedlings, is commonly temperature-dependent. The global average surface temperature is expected to rise, but little is known about the responses of seed germination of woody plants in temperate forests to warming. In the present study, dried seeds of 23 common woody species in temperate secondary forests were incubated at three temperature sequences without cold stratification and after experiencing cold stratification. We calculated five seed germination indices and the comprehensive membership function value that summarized the above indicators. Compared to the control, +2 and +4 °C treatments without cold stratification shortened germination time by 14% and 16% and increased the germination index by 17% and 26%, respectively. For stratified seeds, +4 °C treatment increased germination percentage by 49%, and +4 and +2 °C treatments increased duration of germination and the germination index, and shortened mean germination time by 69%, 458%, 29% and 68%, 110%, 12%, respectively. The germination of Fraxinus rhynchophylla and Larix kaempferi were most sensitive to warming without and with cold stratification, respectively. Seed germination of shrubs was the least sensitive to warming among functional types. These findings indicate warming (especially extreme warming) will enhance the seedling recruitment of temperate woody species, primarily via shortening the germination time, particularly for seeds that have undergone cold stratification. In addition, shrubs might narrow their distribution range.

Identification of high-risk factors associated with mortality at 1-, 3-, and 5-year intervals in gastric cancer patients undergoing radical surgery and immunotherapy: an 8-year multicenter retrospective analysis

Background

Combining immunotherapy with surgical intervention is a prevailing and radical therapeutic strategy for individuals afflicted with gastric carcinoma; nonetheless, certain patients exhibit unfavorable prognoses even subsequent to this treatment regimen. This research endeavors to devise a machine learning algorithm to recognize risk factors with a high probability of inducing mortality among patients diagnosed with gastric cancer, both prior to and during their course of treatment.

Methods

Within the purview of this investigation, a cohort of 1015 individuals with gastric cancer were incorporated, and 39 variables encompassing diverse features were recorded. To construct the models, we employed three distinct machine learning algorithms, specifically extreme gradient boosting (XGBoost), random forest (RF), and k-nearest neighbor algorithm (KNN). The models were subjected to internal validation through employment of the k-fold cross-validation technique, and subsequently, an external dataset was utilized to externally validate the models.

Results

In comparison to other machine learning algorithms employed, the XGBoost algorithm demonstrated superior predictive capacity regarding the risk factors that affect mortality after combination therapy in gastric cancer patients for a duration of one year, three years, and five years posttreatment. The common risk factors that significantly impacted patient survival during the aforementioned time intervals were identified as advanced age, tumor invasion, tumor lymph node metastasis, tumor peripheral nerve invasion (PNI), multiple tumors, tumor size, carcinoembryonic antigen (CEA) level, carbohydrate antigen 125 (CA125) level, carbohydrate antigen 72-4 (CA72-4) level, and H. pylori infection.

Conclusion

The XGBoost algorithm can assist clinicians in identifying pivotal prognostic factors that are of clinical significance and can contribute toward individualized patient monitoring and management.

A novel T-cell exhaustion-related feature can accurately predict the prognosis of OC patients

The phenomenon of T Cell exhaustion (TEX) entails a progressive deterioration in the functionality of T cells within the immune system during prolonged conflicts with chronic infections or tumors. In the context of ovarian cancer immunotherapy, the development, and outcome of treatment are closely linked to T-cell exhaustion. Hence, gaining an in-depth understanding of the features of TEX within the immune microenvironment of ovarian cancer is of paramount importance for the management of OC patients. To this end, we leveraged single-cell RNA data from OC to perform clustering and identify T-cell marker genes utilizing the Unified Modal Approximation and Projection (UMAP) approach. Through GSVA and WGCNA in bulk RNA-seq data, we identified 185 TEX-related genes (TEXRGs). Subsequently, we transformed ten machine learning algorithms into 80 combinations and selected the most optimal one to construct TEX-related prognostic features (TEXRPS) based on the mean C-index of the three OC cohorts. In addition, we explored the disparities in clinicopathological features, mutational status, immune cell infiltration, and immunotherapy efficacy between the high-risk (HR) and low-risk (LR) groups. Upon the integration of clinicopathological features, TEXRPS displayed robust predictive power. Notably, patients in the LR group exhibited a superior prognosis, higher tumor mutational load (TMB), greater immune cell infiltration abundance, and enhanced sensitivity to immunotherapy. Lastly, we verified the differential expression of the model gene CD44 using qRT-PCR. In conclusion, our study offers a valuable tool to guide clinical management and targeted therapy of OC.

Integrating multiple machine learning methods to construct glutamine metabolism-related signatures in lung adenocarcinoma

Background

Glutamine metabolism (GM) is known to play a critical role in cancer development, including in lung adenocarcinoma (LUAD), although the exact contribution of GM to LUAD remains incompletely understood. In this study, we aimed to discover new targets for the treatment of LUAD patients by using machine learning algorithms to establish prognostic models based on GM-related genes (GMRGs).

Methods

We used the AUCell and WGCNA algorithms, along with single-cell and bulk RNA-seq data, to identify the most prominent GMRGs associated with LUAD. Multiple machine learning algorithms were employed to develop risk models with optimal predictive performance. We validated our models using multiple external datasets and investigated disparities in the tumor microenvironment (TME), mutation landscape, enriched pathways, and response to immunotherapy across various risk groups. Additionally, we conducted in vitro and in vivo experiments to confirm the role of LGALS3 in LUAD.

Results

We identified 173 GMRGs strongly associated with GM activity and selected the Random Survival Forest (RSF) and Supervised Principal Components (SuperPC) methods to develop a prognostic model. Our model's performance was validated using multiple external datasets. Our analysis revealed that the low-risk group had higher immune cell infiltration and increased expression of immune checkpoints, indicating that this group may be more receptive to immunotherapy. Moreover, our experimental results confirmed that LGALS3 promoted the proliferation, invasion, and migration of LUAD cells.

Conclusion

Our study established a prognostic model based on GMRGs that can predict the effectiveness of immunotherapy and provide novel approaches for the treatment of LUAD. Our findings also suggest that LGALS3 may be a potential therapeutic target for LUAD.

Mast cell marker gene signature: prognosis and immunotherapy response prediction in lung adenocarcinoma through integrated scRNA-seq and bulk RNA-seq

Background

Mast cells, comprising a crucial component of the tumor immune milieu, modulate neoplastic progression by secreting an array of pro- and antitumorigenic factors. Numerous extant studies have produced conflicting conclusions regarding the impact of mast cells on the prognosis of patients afflicted with lung adenocarcinoma (LUAD).

Methods

Employing single-cell RNA sequencing (scRNA-seq) analysis, mast cell-specific marker genes in LUAD were ascertained. Subsequently, a mast cell-related genes (MRGs) signature was devised to stratify LUAD patients into high- and low-risk cohorts based on the median risk value. Further investigations were conducted to assess the influence of distinct risk categories on the tumor microenvironment. The prognostic import and capacity to prognosticate immunotherapy benefits of the MRGs signature were corroborated using four external cohorts. Ultimately, the functional roles of SYAP1 were validated through in vitro experimentation.

Results

After scRNA-seq and bulk RNA-seq data analysis, we established a prognostic signature consisting of nine MRGs. This profile effectively distinguished favorable survival outcomes in both the training and validation cohorts. In addition, we identified the low-risk group as a population more effective for immunotherapy. In cellular experiments, we found that silencing SYAP1 significantly reduced the proliferation, invasion and migratory capacity of LUAD cells while increasing apoptosis.

Conclusion

Our MRGs signature offers valuable insights into the involvement of mast cells in determining the prognosis of LUAD and may prove instrumental as a navigational aid for immunotherapy selection, as well as a predictor of immunotherapy response in LUAD patients.