Pyroptosis-Derived Long Noncoding RNA Profiles Reveal a Novel Signature for Evaluating the Prognosis of Patients With Lung Adenocarcinoma.

PURPOSE: Long noncoding RNAs (lncRNAs) were recently implicated in modifying pyroptosis. Nonetheless, pyroptosis-related lncRNAs and their possible clinical relevance persist largely uninvestigated in lung adenocarcinoma (LUAD). MATERIALS AND METHODS: A sum of 921 samples were collected from three independent data sets. We obtained pyroptosis-related genes from both the Molecular Signatures Database and relevant literature sources and used four machine learning techniques, comprising stepwise Cox, ridge regression, least absolute shrinkage and selection operator, and random forest. Multiple bioinformatics approaches were used to further investigate the underlying mechanisms. RESULTS: In total, 39 differentially expressed pyroptosis genes were identified by comparing normal and tumor samples. Correlation analysis revealed 933 pyroptosis-related lncRNAs. Furthermore, univariate Cox regression determined 11 lncRNAs that exhibited stable associations with prognosis in the three cohorts, which were used to construct the pyroptosis-derived lncRNA signature. After analyzing the optimal results from four machine learning algorithms, we ultimately selected random forest to develop the pyroptosis-derived lncRNA signature. This signature was proven to be an independent prognostic factor and exhibited robust performance in three cohorts. CONCLUSION: We provided novel insight and established a pyroptosis-derived lncRNA signature for patients with LUAD, exhibiting strong predictive capabilities in both the training and validation sets.

The Effects of Abdominal Obesity and Sagittal Imbalance on Sacroiliac Joint Pain After Lumbar Fusion.

BACKGROUND: Postoperative sacroiliac joint pain (SIJP) is a common manifestation of failed back surgery syndrome after a posterior lumbar interbody fusion (PLIF). However, there is currently no consensus on the risk factors for SIJP after PLIF. OBJECTIVES: We explored the effects of abdominal obesity and sagittal imbalance on SIJP after PLIF. STUDY DESIGN: This is a prospective observational cohort study. SETTING: This study occurred at the Department of Spinal Surgery at a hospital affiliated with a medical university. METHODS: A total of 401 patients who underwent PLIF from June 2018 to June 2021 were enrolled in this study. 36 patients experienced postoperative SIJP. In contrast, a matched group comprised 72 non-SIJP patients. We used 1:2 propensity score matching to compare obesity features and sagittal spine parameters in the 2 groups. Inflammatory cytokines and visual analog scale (VAS) scores were measured in the SIJP group. RESULTS: A total of 36 patients (8.98%) experienced SIJP during the follow-up. Compared with the non-SIJP group, patients with postoperative SIJP had a higher body mass index (BMI), greater abdominal obesity, a higher incidence of pelvic incidence-lumbar lordosis greater than 10°, and a higher incidence of a sagittal vertical axis greater than 5 cm (P < 0.05). Receiver operating characteristic curve analysis showed that the area under the curve for waist circumference was greater than that for BMI (0.762 vs. 0.650, P = 0.049). Logistic regression analysis revealed that the risk factors for SIJP were abdominal obesity, a pelvic incidence-lumbar lordosis of greater than 10°, and a sagittal vertical axis greater than 5 cm (P < 0.05). In patients with SIJP, interleukin 6, tumor necrosis factor-α, and VAS scores were higher in the abdominal obesity group than in the non-abdominal obesity group (P < 0.05). LIMITATIONS: There was no uniform diagnosis of SIJP, so the incidence rate of SIJP might not be accurate. CONCLUSIONS: The significant predictors of SIJP were abdominal obesity and sagittal imbalance. Patients with abdominal obesity showed higher levels of inflammatory markers and pain intensity. More attention should be paid to body shape and the angle of correction of lumbar lordosis before lumbar surgery.

Paclitaxel-coated balloon catheter for benign esophageal stenosis in a rabbit model.

Most patients with benign esophageal stenosis require multiple or even continuous balloon dilation treatments to achieve symptom relief. In this study, eighteen rabbits were used to establish an esophageal benign stenosis model and were divided into a control group (n = 6), a balloon group (n = 6) and a PTX-coated balloon group (n = 6) to evaluate the feasibility and effectiveness of paclitaxel (PTX)-coated balloons for the rabbit esophageal benign stenosis model. The weight and esophageal diameter were recorded every 2 weeks until 8 weeks post-surgery. Hematoxylin-eosin staining, Masson's trichrome staining and immunohistochemical staining were performed for pathological analysis. Four weeks post-operation, there was a significant difference in weight between the control group and the balloon group (p = 0.01) and between the control group and the PTX balloon group (p = 0.01). There was a significant difference in the esophageal diameter between the balloon group and the PTX balloon group at 8 weeks post-operation (p = 0.02). Four weeks post-operation, the degree of inflammatory cell infiltration in the PTX balloon group was significantly lower than that in the control group (p = 0.002) and balloon group (p = 0.001). The degree of collagen deposition in the PTX balloon group was significantly lower than that in the control group (p = 0.002) and balloon group (p = 0.03). Eight weeks post-operation, the percentage of cells positive for TGF-ß (p < 0.001), the degree of inflammatory cell infiltration (p = 0.02) and the degree of collagen deposition (p = 0.02) in the PTX balloon group were significantly lower than those in the balloon group. Therefore, PTX-coated balloons may alleviate the local inflammatory response and collagen deposition when used during dilation treatment of benign esophageal stenosis.

Application of temperature-sensitive liquid embolic agent loaded with oxaliplatin in the TACE procedure for rabbit VX2 gastric cancer.

As a promising drug delivery system, the temperature-sensitive liquid embolic agent (TempSLE) has yet to be reported in animal experiments in treating gastric cancer. We observed and compared computed tomography (CT) imaging changes, tumor volume, HE staining, and immunohistochemistry after transcatheter arterial chemoembolization (TACE) treatment in rabbit VX2 gastric cancer models to clarify the effectiveness of TempSLE loaded with oxaliplatin (TempSLE/Oxa) in treating gastric cancer. One milliliter TempSLE can be loaded with 20 mg oxaliplatin. The accumulative drug release rate at 30 min was 38.76%, and after 24 h, it reached more than 90%. CT examination 1 week after TACE revealed that the TempSLE/Oxa group presents unenhanced hypodense necrotic foci, the iodinated oil loaded with oxaliplatin (Ioil/Oxa) group presents shrinking tumors but still visible speckled foci of enhancement, and the normal saline (NS) group presents heterogeneous enhancement with larger tumors than before. In the postoperative autopsy of TACE, the tumor volumes of TempSLE/Oxa, Ioil/Oxa, and NS groups were 0.15 ± 0.06 cm3, 0.37 ± 0.11 cm3, and 1.19 ± 0.16 cm3, respectively, all of which were statistically different. The positive vascular endothelial growth factor (VEGF) and proliferating cell nuclear antigen (PCNA) expression percentages in the TempSLE/Oxa, Ioil/Oxa, and NS groups were statistically different and lowest in the TempSLE/Oxa group. In conclusion, the TempSLE can load a high dose of oxaliplatin to meet the demand of clinical applications. TempSLE/Oxa could effectively inhibit tumor cell proliferation and angiogenesis. This study provides experimental evidence for the further clinical application of the TempSLE/Oxa.

Transcatheter arterial chemoembolization combined with apatinib and camrelizumab for unresectable advanced gastric or gastroesophageal junction cancer: a single-arm, single-center, retrospective study.

Purpose: This study aims to investigate the efficacy and safety of transcatheter arterial chemoembolization (TACE) combined with Apatinib and Camrelizumab for treating unresectable advanced gastric or gastroesophageal junction (G/GEJ) cancer. Material and methods: In this study, data of patients with unresectable advanced G/GEJ cancer who received TACE combined with Apatinib and Camrelizumab from August 2018 to December 2021 was evaluated. After TACE, patients were given intravenous Camrelizumab 200mg every three weeks and oral apatinib 250mg/day for treatment. The primary endpoint was overall survival (OS), and the secondary endpoints were objective response rate (ORR), disease control rate (DCR), and adverse events (AEs). Results: A total of 49 patients were enrolled in this study. The median follow-up time was 14.0 months, and the median OS was 20.0 months (95% CI = 13.6-26.4). Two patients (4.08%) achieved complete remission, 28 patients (57.14%) achieved partial remission, 18 patients (36.73%) had stable disease, and 1 patient (2.04%) had disease progression. The ORR was 61.22%, and the DCR was 97.96%. Multivariate Cox regression analysis indicated that age (HR 4.74, 95% CI = 1.674-13.440, P=0.003) and multiple distant metastases (HR 20.916, 95% CI = 4.094-106.808, P = 0.001) were independent risk factors for OS. Most AEs were classified as grade 1-2, the most common being RCCEP (69.39%). There were 5 cases of grade 3-4 adverse events (10.20%). No patients discontinued or reduced the treatment dose due to AEs, and all patients received symptomatic treatment. Conclusion: TACE combined with Apatinib and Camrelizumab is a safe and effective therapeutic option for patients with unresectable advanced G/GEJ cancer, which can significantly improve the median OS and ORR of patients. And the adverse events (AEs) are tolerable and manageable.

Bevacizumab-loaded CalliSpheres beads: in vitro loading, release profiles and application in rabbit liver VX2 tumor model.

Background: Bevacizumab loaded drug-eluting beads have the potential to reduce TACE related VEGF expression. The purpose of this study was to investigate the in vitro loading, and release profiles of bevacizumab (BEV) loaded on Callispheres beads (CB) and its application in rabbit liver VX2 tumor model. Methods: CB with sizes of 100-300 um and 300-500 um were divided into 5 groups, respectively. BEV with different content was prepared for CB loading, releasing and detected in the solution at different time points. The diameters of CB in each group were measured under a light microscope to calculate the shrinkage rate. The rabbit with VX2 liver model were divided into control group, CB-TACE group, CB-TACE+BEV group, and BEV group. The data of blood test, CT image, HE and IHC staining were compared and analyzed. Results: The shrinkage rate of the 100-300 um CB was 2.6-7.2%, while the 300-500 um CB was 0.2-7.1%. The BEV-loaded CB (BEV-CB) has a burst release during the first hour and following gradually released with time. The release profiles of 100-300 um CB reach 34% in 24 hours, while the 300-500 um CB to 25.8%. BEV-CB with sizes of 100-300 um was chosen to perform transcatheter arterial chemoembolization (TACE). The results showed that BEV-CB-TACE not only gradually increased the content of BEV in serum and organ tissue but also reduced the level of VEGF in serum. Pathological results suggested that the expression of HIF-1 was elevated while VEGF and MVD decreased when compared to the other groups. Conclusion: In conclusion, this study confirms that Callispheres beads could efficiency loaded BEV. BEV-CB-TACE has a good safety and effectiveness, and its application could reduce the level of VEGF-A in serum in the treatment of VX2 tumors.

Immunosenescence: molecular mechanisms and diseases.

Infection susceptibility, poor vaccination efficacy, age-related disease onset, and neoplasms are linked to innate and adaptive immune dysfunction that accompanies aging (known as immunosenescence). During aging, organisms tend to develop a characteristic inflammatory state that expresses high levels of pro-inflammatory markers, termed inflammaging. This chronic inflammation is a typical phenomenon linked to immunosenescence and it is considered the major risk factor for age-related diseases. Thymic involution, naïve/memory cell ratio imbalance, dysregulated metabolism, and epigenetic alterations are striking features of immunosenescence. Disturbed T-cell pools and chronic antigen stimulation mediate premature senescence of immune cells, and senescent immune cells develop a proinflammatory senescence-associated secretory phenotype that exacerbates inflammaging. Although the underlying molecular mechanisms remain to be addressed, it is well documented that senescent T cells and inflammaging might be major driving forces in immunosenescence. Potential counteractive measures will be discussed, including intervention of cellular senescence and metabolic-epigenetic axes to mitigate immunosenescence. In recent years, immunosenescence has attracted increasing attention for its role in tumor development. As a result of the limited participation of elderly patients, the impact of immunosenescence on cancer immunotherapy is unclear. Despite some surprising results from clinical trials and drugs, it is necessary to investigate the role of immunosenescence in cancer and other age-related diseases.

Systematic analysis of transcriptome signature for improving outcomes in lung adenocarcinoma.

PURPOSE: The updated guidelines highlight gene expression-based multigene panel as a critical tool to assess overall survival (OS) and improve treatment for lung adenocarcinoma (LUAD) patients. Nevertheless, genome-wide expression signatures are still limited in real clinical utility because of insufficient data utilization, a lack of critical validation, and inapposite machine learning algorithms. METHODS: 2330 primary LUAD samples were enrolled from 11 independent cohorts. Seventy-six algorithm combinations based on ten machine learning algorithms were applied. A total of 108 published gene expression signatures were collected. Multiple pharmacogenomics databases and resources were utilized to identify precision therapeutic drugs. RESULTS: We comprehensively developed a robust machine learning-derived genome-wide expression signature (RGS) according to stably OS-associated RNAs (OSRs). RGS was an independent risk element and remained robust and reproducible power by comparing it with general clinical parameters, molecular characteristics, and 108 published signatures. RGS-based stratification possessed different biological behaviors, molecular mechanisms, and immune microenvironment patterns. Integrating multiple databases and previous studies, we identified that alisertib was sensitive to the high-risk group, and RITA was sensitive to the low-risk group. CONCLUSION: Our study offers an appealing platform to screen dismal prognosis LUAD patients to improve clinical outcomes by optimizing precision therapy.

Recent advances and applications of CRISPR-Cas9 in cancer immunotherapy.

The incidence and mortality of cancer are the major health issue worldwide. Apart from the treatments developed to date, the unsatisfactory therapeutic effects of cancers have not been addressed by broadening the toolbox. The advent of immunotherapy has ushered in a new era in the treatments of solid tumors, but remains limited and requires breaking adverse effects. Meanwhile, the development of advanced technologies can be further boosted by gene analysis and manipulation at the molecular level. The advent of cutting-edge genome editing technology, especially clustered regularly interspaced short palindromic repeats (CRISPR-Cas9), has demonstrated its potential to break the limits of immunotherapy in cancers. In this review, the mechanism of CRISPR-Cas9-mediated genome editing and a powerful CRISPR toolbox are introduced. Furthermore, we focus on reviewing the impact of CRISPR-induced double-strand breaks (DSBs) on cancer immunotherapy (knockout or knockin). Finally, we discuss the CRISPR-Cas9-based genome-wide screening for target identification, emphasis the potential of spatial CRISPR genomics, and present the comprehensive application and challenges in basic research, translational medicine and clinics of CRISPR-Cas9.

Machine learning algorithm-generated and multi-center validated melanoma prognostic signature with inspiration for treatment management.

BACKGROUND: Although immunotherapy and targeted treatments have dramatically improved the survival of melanoma patients, the intra- or intertumoral heterogeneity and drug resistance have hindered the further expansion of clinical benefits. METHODS: The 96 combination frames constructed by ten machine learning algorithms identified a prognostic consensus signature based on 1002 melanoma samples from nine independent cohorts. Clinical features and 26 published signatures were employed to compare the predictive performance of our model. RESULTS: A machine learning-based prognostic signature (MLPS) with the highest average C-index was developed via 96 algorithm combinations. The MLPS has a stable and excellent predictive performance for overall survival, superior to common clinical traits and 26 collected signatures. The low MLPS group with a better prognosis had significantly enriched immune-related pathways, tending to be an immune-hot phenotype and possessing potential immunotherapeutic responses to anti-PD-1, anti-CTLA-4, and MAGE-A3. On the contrary, the high MLPS group with more complex genomic alterations and poorer prognoses is more sensitive to the BRAF inhibitor dabrafenib, confirmed in patients with BRAF mutations. CONCLUSION: MLPS could independently and stably predict the prognosis of melanoma, considered a promising biomarker to identify patients suitable for immunotherapy and those with BRAF mutations who would benefit from dabrafenib.

Artificial intelligence-driven consensus gene signatures for improving bladder cancer clinical outcomes identified by multi-center integration analysis.

To accurately predict the prognosis and further improve the clinical outcomes of bladder cancer (BLCA), we leveraged large-scale data to develop and validate a robust signature consisting of small gene sets. Ten machine-learning algorithms were enrolled and subsequently transformed into 76 combinations, which were further performed on eight independent cohorts (n = 1218). We ultimately determined a consensus artificial intelligence-derived gene signature (AIGS) with the best performance among 76 model types. In this model, patients with high AIGS showed a higher risk of mortality, recurrence, and disease progression. AIGS is not only independent of traditional clinical traits [(e.g., American Joint Committee on Cancer (AJCC) stage)] and molecular features (e.g., TP53 mutation) but also demonstrated superior performance to these variables. Comparisons with 58 published signatures also indicated that AIGS possessed the best performance. Additionally, the combination of AIGS and AJCC stage could achieve better performance. Patients with low AIGS scores were sensitive to immunotherapy, whereas patients with high AIGS scores might benefit from seven potential therapeutics: BRD-K45681478, 1S,3R-RSL-3, RITA, U-0126, temsirolimus, MRS-1220, and LY2784544. Additionally, some mutations (TP53 and RB1), copy number variations (7p11.2), and a methylation-driven target were characterized by AIGS-related multi-omics alterations. Overall, AIGS provides an attractive platform to optimize decision-making and surveillance protocol for individual BLCA patients.

Six macrophage-associated genes in synovium constitute a novel diagnostic signature for osteoarthritis.

Background: Synovial macrophages play important roles in the formation and progression of osteoarthritis (OA). This study aimed to explore the biological and clinical significance of macrophage-associated genes (MAGs) in OA. Methods: The OA synovial gene expression profiles GSE89408 and GSE82107 were obtained from the GEO database. Single-sample gene set enrichment analysis (ssGSEA) and GSEA were employed to decipher differences in immune infiltration and macrophage-associated biological pathways, respectively. Protein-protein interaction (PPI) network analysis and machine learning were utilized to establish a macrophage-associated gene diagnostic signature (MAGDS). RT-qPCR was performed to test the expression of key MAGs in murine models. Results: OA synovium presented high levels of immune infiltration and activation of macrophage-associated biological pathways. A total of 55 differentially expressed MAGs were identified. Using PPI analysis and machine learning, a MAGDS consisting of IL1B, C5AR1, FCGR2B, IL10, IL6, and TYROBP was established for OA diagnosis (AUC = 0.910) and molecular pathological evaluation. Patients with high MAGDS scores may possess higher levels of immune infiltration and expression of matrix metalloproteinases (MMPs), implying poor biological alterations. The diagnostic value of MAGDS was also validated in an external cohort (AUC = 0.886). The expression of key MAGs was validated in a murine model using RT-qPCR. Additionally, a competitive endogenous RNA network was constructed to reveal the potential posttranscriptional regulatory mechanisms. Conclusions: We developed and validated a MAGDS model with the ability to accurately diagnose and characterize biological alterations in OA. The six key MAGs may also be latent targets for immunoregulatory therapy.

Integrative pharmacogenomics revealed three subtypes with different immune landscapes and specific therapeutic responses in lung adenocarcinoma.

Background: Pharmacogenomics is crucial for individualized drug therapy and plays an increasingly vital role in precision medicine decision-making. However, pharmacogenomics-based molecular subtypes and their potential clinical significance remain primarily unexplored in lung adenocarcinoma (LUAD). Methods: A total of 2065 samples were recruited from eight independent cohorts. Pharmacogenomics data were generated from the profiling of relative inhibition simultaneously in mixtures (PRISM) and the genomics of drug sensitivity in cancer (GDSC) databases. Multiple bioinformatics approaches were performed to identify pharmacogenomics-based subtypes and find subtype-specific properties. Results: Three reproducible molecular subtypes were found, which were independent prognostic factors and highly associated with stage, survival status, and accepted molecular subtypes. Pharmacogenomics-based subtypes had distinct molecular characteristics: S-Ⅰ was inflammatory, proliferative, and immune-evasion; S-Ⅱ was proliferative and genetics-driven; S-III was metabolic and methylation-driven. Finally, our study provided subtype-guided personalized treatment strategies: Immune checkpoint blockers (ICBs), doxorubicin, tipifarnib, AZ628, and AZD6244 were for S-Ⅰ; Cisplatin, camptothecin, roscovitine, and A.443654 were for S-Ⅱ; Docetaxel, paclitaxel, vinorelbine, and BIBW2992 were for S-III. Conclusion: We provided a novel molecular classification strategy and revealed three pharmacogenomics-based subtypes for LUAD patients, which uncovered potential subtype-related and patient-specific therapeutic strategies.

ALOX12: A Novel Insight in Bevacizumab Response, Immunotherapy Effect, and Prognosis of Colorectal Cancer.

Colorectal cancer is a highly malignant cancer with poor prognosis and mortality rates. As the first biological agent approved for metastatic colorectal cancer (mCRC), bevacizumab was confirmed to exhibit good performance when combined with chemotherapy and immunotherapy. However, the efficacy of both bevacizumab and immunotherapy is highly heterogeneous across CRC patients with different stages. Thus, exploring a novel biomarker to comprehensively assess the prognosis and bevacizumab and immunotherapy response of CRC is of great significance. In our study, weighted gene co-expression network analysis (WGCNA) and the receiver operating characteristic (ROC) curves were employed to identify bevacizumab-related genes. After verification in four public cohorts and our internal cohort, ALOX12 was identified as a key gene related to bevacizumab response. Prognostic analysis and in vitro experiments further demonstrated that ALOX12 was closely associated with the prognosis, tumor proliferation, invasion, and metastasis. Multi-omics data analysis based on mutation and copy number variation (CNV) revealed that RYR3 drove the expression of ALOX12 and the deletion of 17p12 inhibited ALOX12 expression, respectively. Moreover, we interrogated the relationship between ALOX12 and immune cells and checkpoints. The results exhibited that high ALOX12 expression predicted a higher immune infiltration and better immunotherapy response, which was further validated in Tumor Immune Dysfunction and Exclusion (TIDE) and Subclass Mapping (SubMap) methods. Above all, our study provides a stable biomarker for clinical protocol optimization, prognostic assessment, precise treatment, and individualized treatment of CRC.

SCG2: A Prognostic Marker That Pinpoints Chemotherapy and Immunotherapy in Colorectal Cancer.

Background: Fluorouracil (FU)-based chemotherapy regimens are indispensable in the comprehensive treatment of colorectal cancer (CRC). However, the heterogeneity of treated individuals and the severe adverse effects of chemotherapy results in limited overall benefit. Methods: Firstly, Weighted gene co-expression network analysis (WGCNA) identified modules tightly associated with chemotherapy response. Then, the in-house cohort and prognostic cohorts from TCGA and GEO were subjected to Cox proportional hazards model and survival analysis to ascertain the predictable function of SCG2 on the prognosis of CRC patients. Finally, we performed In vitro experiments, functional analysis, somatic mutation, and copy number variation research to explore the biological characteristics of SCG2. Results: We identified red and green as the modules most associated with chemotherapy response, in which SCG2 was considered a risky factor with higher expression predicting poorer prognosis. SCG2 expression in the APC non-mutation group was remarkably higher than in the mutation group. The mutation frequencies of amplified genes differed significantly between different SCG2 expression subgroups. Besides, CRC cell lines with SCG2 knockdown have reduced invasive, proliferative, and proliferative capacity. We discovered that the SCG2 high expression subgroup was the immune hot type and considered more suitable for immunotherapy. Conclusion: This study demonstrates the clinical significance and biological characteristics of SCG2, which could serve as a promising biomarker to identify patients who may benefit from chemotherapy and immunotherapy.

Association Between Abdominal Obesity and Subsequent Vertebral Fracture Risk.

BACKGROUND: Obesity had been previously considered to be a protective factor against osteoporosis or fractures; however, recent research indicates that obesity, especially abdominal obesity, may increase the risk of some types of fractures. OBJECTIVE: We explored the effects of abdominal obesity on subsequent vertebral fracture (SVF) after percutaneous vertebral augmentation (PVA). STUDY DESIGN: A prospective observational cohort study. SETTING: Department of Spinal Surgery of a hospital affiliated with a medical university. METHODS: A total of 390 women and 237 men aged > 50 years suffering from osteoporotic vertebral fracture (OVF) were included. Weight, height, bone mineral density (BMD), abdominal circumference, and other basic information were measured at baseline and 1-year follow-up visit. RESULTS: During follow-up, 80 (33.7%) men and 143 (36.7%) women incurred SVF. Greater waist circumference (WC) and waist-to-hip ratio (WHR) increased the risk of SVF in men (WC: HR 1.83, P = 0.016; WHR: HR 1.63, P = 0.045) and women (WC: HR 2.75, P = 0.001; WHR: HR 2.63, P = 0.001) after adjustment for BMD and other potential confounders. Compared with normal BMI, being overweight was associated with lower SVF risk (women: HR 0.55, P = 0.044; men: HR 0.46, P = 0.046), and obesity was associated with greater SVF risk (women: HR 4.53, P < 0.001; men: HR 3.77, P < 0.001) in both genders. We observed a nonlinear relationship between BMI and SVF with a U-shaped curve; after adjusting BMD, this became a reverse J-curve. LIMITATIONS: There was no further statistical analysis of the relationship between abdominal obesity and other fracture sites. Asymptomatic SVF may underestimate the impact of abdominal obesity on the occurrence of SVF. CONCLUSIONS: Abdominal obesity was significantly associated with a higher risk of SVF after PVA. Management of body type after PVA may be an effective prevention strategy against SVF.

Integrated Analysis of Multi-Omics Alteration, Immune Profile, and Pharmacological Landscape of Pyroptosis-Derived lncRNA Pairs in Gastric Cancer.

Background: Recent evidence demonstrates that pyroptosis-derived long non-coding RNAs (lncRNAs) have profound impacts on the initiation, progression, and microenvironment of tumors. However, the roles of pyroptosis-derived lncRNAs (PDLs) in gastric cancer (GC) remain elusive. Methods: We comprehensively analyzed the multi-omics data of 839 GC patients from three independent cohorts. The previous gene set enrichment analysis embedding algorithm was utilized to identify PDLs. A gene pair pipeline was developed to facilitate clinical translation via qualitative relative expression orders. The LASSO algorithm was used to construct and validate a pyroptosis-derived lncRNA pair prognostics signature (PLPPS). The associations between PLPPS and multi-omics alteration, immune profile, and pharmacological landscape were further investigated. Results: A total of 350 PDLs and 61,075 PDL pairs in the training set were generated. Cox regression revealed 15 PDL pairs associated with overall survival, which were utilized to construct the PLPPS model via the LASSO algorithm. The high-risk group demonstrated adverse prognosis relative to the low-risk group. Remarkably, genomic analysis suggested that the lower tumor mutation burden and gene mutation frequency (e.g., TTN, MUC16, and LRP1B) were found in the high-risk group patients. The copy number variants were not significantly different between the two groups. Additionally, the high-risk group possessed lower immune cell infiltration abundance and might be resistant to a few chemotherapeutic drugs (including cisplatin, paclitaxel, and gemcitabine). Conclusion: PDLs were closely implicated in the biological process and prognosis of GC, and our PLPPS model could serve as a promising tool to advance prognostic management and personalized treatment of GC patients.

Gene Expression Profile Reveals a Prognostic Signature of Non-MSI-H/pMMR Colorectal Cancer.

Studies have demonstrated that non-MSI-H/pMMR colorectal cancer (CRC) has a worse prognosis and relapse rate than microsatellite instability-high (MSI-H)/mismatch repair deficient (dMMR) CRC. Hence, searching for a novel tool to advance the prognostic management of non-MSI-H/pMMR CRC is vital. In this study, using three independent public cohorts and a clinical in-house cohort, we developed and validated a microsatellite stable-associated signature (MSSAS). The initial signature establishment was performed in GSE39582 (n = 454). This was followed by independent validation of this signature in The Cancer Genome Atlas-CRC (n = 312), GSE39084 (n = 54), and in-house cohort (n = 146). As a result, MSSAS was proven to be an independent risk factor for overall survival and relapse-free survival in non-MSI-H/pMMR CRC. Receiver operating characteristic analysis showed that MSSAS had a stable and accurate performance in all cohorts for 1, 3, and 5 years, respectively. Further analysis suggested that MSSAS performed better than age, gender, and the T, N, M, and AJCC stages, adjuvant chemotherapy, tumor mutation burden, neoantigen, and TP53, KRAS, BRAF, and PIK3CA mutations. The clinical validation was executed to further ensure the robustness and clinical feasibility of this signature. In conclusion, MSSAS might be a robust and promising biomarker for advancing clinical management of non-MSI-H/pMMR CRC.

Clinical Significance and Immune Landscape of a Pyroptosis-Derived LncRNA Signature for Glioblastoma.

Introduction: Pyroptosis was recently implicated in the initiation and progression of tumors, including glioblastoma (GBM). This study aimed to explore the clinical significance of pyroptosis-related lncRNAs (PRLs) in GBM. Methods: Three independent cohorts were retrieved from the TCGA and CGGA databases. The consensus clustering and weighted gene coexpression network analysis (WGCNA) were applied to identify PRLs. The LASSO algorithm was employed to develop and validate a pyroptosis-related lncRNA signature (PRLS) in three independent cohorts. The molecular characteristics, clinical significances, tumor microenvironment, immune checkpoints profiles, and benefits of chemotherapy and immunotherapy regarding to PRLS were also explored. Results: In the WGCNA framework, a key module that highly correlated with pyroptosis was extracted for identifying PRLs. Univariate Cox analysis further revealed the associations between PRLs and overall survival. Based on the expression profiles of PRLs, the PRLS was initially developed in TCGA cohort (n = 143) and then validated in two CGGA cohorts (n = 374). Multivariate Cox analysis demonstrated that our PRLS model was an independent risk factor. More importantly, this signature displayed a stable and accurate performance in predicting prognosis at 1, 3, and 5 years, with all AUCs above 0.7. The decision curve analysis also indicated that our signature had promising clinical application. In addition, patients with high PRLS score suggested a more abundant immune infiltration, higher expression of immune checkpoint genes, and better response to immunotherapy but worse to chemotherapy. Conclusion: A novel pyroptosis-related lncRNA signature with a robust performance was constructed and validated in multiple cohorts. This signature provided new perspectives for clinical management and precise treatments of GBM.

Role of LncRNAs in the Epithelial-Mesenchymal Transition in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a type of primary liver cancer with a high incidence and mortality rate. HCC develops insidiously, and most newly diagnosed cases are in the middle and advanced stages. The epithelial-mesenchymal transition (EMT) is a vital mechanism underlying metastasis in patients with advanced HCC. EMT is a multistep and complex procedure. The promotion and inhibition of EMT directly affect the migration and invasion of HCC. LncRNAs are involved in the epigenetic modification of genes, regulation of gene transcription, and posttranslational modification of proteins. LncRNAs also play important roles in regulating EMT progression in HCC and are promising biomarkers and therapeutic targets. This review focused on summarizing the mechanism by which lncRNAs regulate EMT in HCC. In particular, lncRNAs were reported to primarily act as RNA sponges, and the regulation of EMT involves major signaling pathways. Finally, we reviewed the mechanisms by which lncRNAs are involved in drug resistance and discussed the clinical prospects and potential challenges of utilizing lncRNAs to treat HCC.