Identification and Validation of a Novel Tertiary Lymphoid Structures-Related Prognostic Gene Signature in Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors originating from the digestive system. Tertiary lymphoid structures (TLS), non-lymphoid tissues outside of the lymphoid organs, are closely connected to chronic inflammation and tumorigenesis. However, the detailed relationship between TLS and HCC prognosis remained unclear. In this study, we aimed to construct a TLS-related gene signature for predicting the prognosis of HCC patients. Methods: The Cancer Genome Atlas (TCGA) clinical data from 369 HCC tissues and 50 normal liver tissues were utilized to examine the differential expression of TLS-related genes. Based on least absolute shrinkage and selection operator (LASSO) Cox regression analysis, the prognostic model was constructed using the TCGA cohort and validated in the GSE14520 cohort and International Cancer Genome Consortium (ICGC) cohort. The Kaplan-Meier (KM) and receiver operating characteristic (ROC) curves were employed to validate the predictive ability of the prognostic model. Furthermore, Cox regression analysis was applied to identify whether the TLS score could be employed as an independent prognosis factor. A nomogram was developed to predict the survival probability of HCC patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed for TLS-related genes. Genetic mutation analysis, the CIBERSORT algorithm, and single-sample gene set enrichment analysis (ssGSEA) were used to assess the tumor mutation landscape and immune infiltration. Finally, the role of the TLS score in HCC therapy was investigated. Results: Six genes were included in the construction of our prognostic model (CETP, DNASE1L3, PLAC8, SKAP1, C7, and VNN2), and we validated its accuracy. Survival analysis showed that patients in the high-TLS score group had a significantly better overall survival than those in the low-TLS score group. Univariate, multivariate Cox regression analysis and the establishment of a nomogram indicated that the TLS score could independently function as a potential prognostic marker. A significant association between TLS score and immunity was revealed by an analysis of gene alterations and immune cell infiltration. In addition, two subtypes of the TLS score could accurately predict the effectiveness of sorafenib, transcatheter arterial chemoembolization (TACE), and immunotherapy in HCC patients. Conclusion: In this research, we conducted and validated a prognostic model associated with TLS that may be helpful for predicting clinical outcomes and treatment responsiveness for HCC patients.

A New Ferroptosis-Related Long Non-Coding RNA Risk Model Predicts the Prognosis of Patients With Papillary Thyroid Cancer.

Background: Ferroptosis is a novel form of regulated cell death that involves in cancer progression. However, the role of ferroptosis-related long non-coding RNAs (lncRNAs) in papillary thyroid cancer (PTC) remains to be elucidated. The purpose of this paper was to clarify the prognostic value of ferroptosis-related lncRNAs in PTC. Methods: The transcriptome data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. The correlation between ferroptosis-related genes (FRGs) and lncRNA was determined using Pearson correlation analysis. Multivariate Cox regression model (P < 0.01) was performed to establish a ferroptosis-related lncRNAs risk model. Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curves, risk curve and nomograms were then performed to assess the accuracy and clinical applicability of prognostic models. The correlations between the prognosis model and clinicopathological variables, immune and m6A were analyzed. Finally, in vitro assays were performed to verify the role of LINC00900, LINC01614 and PARAL1 on the proliferation, migration and invasion in TPC-1 and BCPAP cells, as well as the relationship between three lncRNAs and ferroptosis. Results: A five-ferroptosis-related lncRNAs (PARAL1, LINC00900, DPH6-DT, LINC01614, LPP-AS2) risk model was constructed. Based on the risk score, samples were divided into the high- and low-risk groups. Patients in the low-risk group had better prognosis than those in high-risk group. Compared to traditional clinicopathological features, risk score was more accurate in predicting prognosis in patients with PTC. Additionally, the difference of immune cell, function and checkpoints was observed between two groups. Moreover, experiments showed that LINC00900 promoted the proliferation, migration and invasion in TPC-1 and BCPAP cells, while LINC01614 and PARAL1 revealed opposite effects, all of which were related to ferroptosis. Conclusions: In summary, we identified a five-ferroptosis-related lncRNAs risk model to predict the prognosis of PTC. Furthermore, our study also revealed that LINC00900 functioned as a tumor suppressor lncRNA, LINC01614 and PARAL1 as an oncogenic lncRNA in PTC.

RBMS1 reflects a distinct microenvironment and promotes tumor progression in ocular melanoma.

Ocular melanoma, including uveal melanoma (UM) and conjunctival melanoma (CM), is the most common ocular cancer among adults with a high rate of recurrence and poor prognosis. Loss of epigenetic homeostasis disturbed gene expression patterns, resulting in oncogenesis. Herein, we comprehensively analyzed the DNA methylation, transcriptome profiles, and corresponding clinical information of UM patients through multiple machine-learning algorithms, finding that a methylation-driven gene RBMS1 was correlated with poor clinical outcomes of UM patients. RNA-seq and single-cell RNA-seq analyses revealed that RBMS1 reflected diverse tumor microenvironments, where high RBMS1 expression marked an immune active TME. Furthermore, we found that tumor cells were identified to have the higher communication probability in RBMS1+ state. The functional enrichment analysis revealed that RBMS1 was associated with pigment granule and melanosome, participating in cell proliferation as well as apoptotic signaling pathway. Biological experiments were performed and demonstrated that the silencing of RBMS1 inhibited ocular melanoma proliferation and promoted apoptosis. Our study highlighted that RBMS1 reflects a distinct microenvironment and promotes tumor progression in ocular melanoma, contributing to the therapeutic customization and clinical decision-making.

Accurate prediction of all-cause mortality in patients with metabolic dysfunction-associated steatotic liver disease using electronic health records.

INTRODUCTION AND OBJECTIVES: Despite the huge clinical burden of MASLD, validated tools for early risk stratification are lacking, and heterogeneous disease expression and a highly variable rate of progression to clinical outcomes result in prognostic uncertainty. We aimed to investigate longitudinal electronic health record-based outcome prediction in MASLD using a state-of-the-art machine learning model. PATIENTS AND METHODS: n = 940 patients with histologically-defined MASLD were used to develop a deep-learning model for all-cause mortality prediction. Patient timelines, spanning 12 years, were fully-annotated with demographic/clinical characteristics, ICD-9 and -10 codes, blood test results, prescribing data, and secondary care activity. A Transformer neural network (TNN) was trained to output concomitant probabilities of 12-, 24-, and 36-month all-cause mortality. In-sample performance was assessed using 5-fold cross-validation. Out-of-sample performance was assessed in an independent set of n = 528 MASLD patients. RESULTS: In-sample model performance achieved AUROC curve 0.74-0.90 (95 % CI: 0.72-0.94), sensitivity 64 %-82 %, specificity 75 %-92 % and Positive Predictive Value (PPV) 94 %-98 %. Out-of-sample model validation had AUROC 0.70-0.86 (95 % CI: 0.67-0.90), sensitivity 69 %-70 %, specificity 96 %-97 % and PPV 75 %-77 %. Key predictive factors, identified using coefficients of determination, were age, presence of type 2 diabetes, and history of hospital admissions with length of stay >14 days. CONCLUSIONS: A TNN, applied to routinely-collected longitudinal electronic health records, achieved good performance in prediction of 12-, 24-, and 36-month all-cause mortality in patients with MASLD. Extrapolation of our technique to population-level data will enable scalable and accurate risk stratification to identify people most likely to benefit from anticipatory health care and personalized interventions.

Prognostic value of global longitudinal strain in patients with preserved left ventricular systolic function: A cardiac magnetic resonance real-world study.

BACKGROUND: Myocardial strain is a more sensitive parameter for cardiac function evaluation than left ventricular ejection fraction (LVEF). This study aimed to assess the predictive value of left ventricular global longitudinal strain (LV-GLS) by feature tracking-cardiac magnetic resonance (FT-CMR) imaging in patients with known or suspected coronary artery disease (CAD) with preserved left ventricular systolic function. METHODS: This retrospective cohort analysis enrolled patients with known or suspected CAD who underwent cardiac magnetic resonance imaging from September 2017 to December 2019. LV-GLS was analyzed via feature-tracking analysis. Patients with LVEF <50% were excluded. The composite outcome comprised all-cause death, non-fatal myocardial infarction, and heart failure. RESULTS: There was a total of 2613 patients. Mean follow-up duration was 39.7 ± 13.9 months. During follow-up, 194 patients (7.4%) experienced a composite outcome. The best cutoff of LV-GLS in the prediction of composite outcome from receiver operating characteristics was -14.4%. Patients were classified into 2 groups according to the LV-GLS; 1489 (57.0%) had LV-GLS <-14.4% and 1124 (43.0%) had LV-GLS ≥-14.4%. Patients with LV-GLS ≥-14.4% had a significantly higher rate of composite outcome than LV-GLS <-14.4% patients (3.59 vs. 1.39 per 100 person-years, respectively; p < 0.001). Multivariable analysis showed that patients with LV-GLS ≥-14.4% had a significantly higher risk of experiencing a composite outcome event compared to global longitudinal strain <-14.4% patients (adjusted hazard ratio: 1.83, 95% confidence interval: 1.28-2.61; p = 0.001). CONCLUSION: LV-GLS by FT-CMR was shown to be useful for predicting the prognosis of patients with known or suspected CAD with preserved left ventricular systolic function. LV-GLS -14.4% was the identified cutoff for prognostic determination.

Interaction between inflammatory bowel disease, physical activity, and myokines: Assessment of serum irisin levels.

Inflammatory bowel disease (IBD), including Crohn's disease and ulcerative colitis, showed a wide spectrum of intestinal and extra-intestinal manifestations, which rendered the patients physically inactive and impaired their quality of life. It has been found that physical activity is a non-pharmacological intervention that improves the quality of life for those patients. Irisin is one member of the myokines secreted by muscle contraction during exercise and could be used as an anti-inflammatory biomarker in assessing the physical activity of IBD patients. In addition, experimental studies showed that exogenous irisin significantly decreased the inflammatory markers and the histological changes of the intestinal mucosa observed in experimental colitis. Furthermore, irisin produces changes in the diversity of the microbiota. Therefore, endogenous or exogenous irisin, via its anti-inflammatory effects, will improve the health of IBD patients and will limit the barriers to physical activity in patients with IBD.

GNL3L exhibits pro-tumor activities via NF-κB pathway as a poor prognostic factor in acute myeloid leukemia.

Acute myeloid leukemia (AML) is the leukemia with the worst prognosis, and current knowledge of AML pathogenesis and available therapies for AML remain limited. 40% of AML patients exhibit elevated nuclear factor kappa B (NF-κB) activity, which provides a compelling rationale for targeting the NF-κB pathway in AML. Guanine nucleotide-binding protein-like 3-like protein (GNL3L) is a recently identified pro-oncogene that promotes NF-κB activation in a variety of malignancies. For the first time, we comprehensively examined GNL3L expression in AML, reporting GNL3L as a poor prognostic factor in three independent AML cohorts. GNL3L enhanced RELA activity, activated NF-κB, promoted AML cell proliferation, resisted apoptosis, and encouraged cytarabine resistance in AML. In conclusion, these data suggest a role for GNL3L in the malignant process of AML and as a promising therapeutic target.

ECT2 promotes the occurrence and is a prognostic biomarker of head and neck squamous cell carcinoma.

Background: Epithelial Cell Transforming Sequence 2 (ECT2) has been implicated in various tumorigenic processes, including proliferation, migration, and invasion. However, its specific role in head and neck squamous cell carcinoma (HNSCC) remains unclear. Methods: This study integrates transcriptomic and single-cell RNA sequencing (scRNA-seq) data to explore the potential role of ECT2 in HNSCC. Differential expression analysis, cell-based assays (including CCK-8 for proliferation, transwell for migration, invasion assays, and flow cytometry for apoptosis and cell cycle analysis), and enrichment analysis were employed to investigate ECT2 expression levels and its regulatory effects on cellular phenotypes. Additionally, Mendelian randomization analysis was utilized to identify genes causally related to HNSCC using publicly available Genome-Wide Association Study (GWAS) data. Results: ECT2 is highly expressed in HNSCC samples and its downregulation inhibits proliferation, migration, invasion, induces apoptosis, and affects the cell cycle transition in HSC-3 cells. Furthermore, differential analysis revealed significant differences in the immune microenvironment and drug sensitivity between high and low ECT2 expression groups. The pathways enriched in different groups include CCR and its related chemokines, as well as HLA in antigen presentation and immune response. There are also significant differences in the sensitivity to drugs such as bortezomib and dasatinib between the two groups. Prognostic models constructed from prognosis-related genes showed significant differences in prognosis between high and low-risk groups. Integration of scRNA-seq data identified Monocyte clusters as high-scoring cell clusters based on genes interacting with ECT2.Mendelian randomization analysis identified three genes (LGALS2, SLC11A1, and TKT) causally related to HNSCC within this cell cluster. Conclusion: The findings suggest that ECT2 overexpression is associated with the survival rate of HNSCC, indicating its potential as a prognostic biomarker for this malignancy.

Elevated RACGAP1 Expression Enhances Malignant Potential in Lung Adenocarcinoma and Serves as a Prognostic Factor.

Background: While RACGAP1 is identified as a potential oncogene, its specific role in lung adenocarcinoma (LUAD) remains unclear. Methods: First, we conducted a comprehensive analysis of the role of RACGAP1 across 33 types of cancer. Subsequently, we investigated the expression levels of RACGAP1 and its impact on prognosis using data from The Cancer Genome Atlas (TCGA) database. We utilized single-cell sequencing data to explore the tumor-related processes of RACGAP1 in LUAD and validated our findings through experimental verification. Employing a consensus clustering (CC) approach, we subdivided LUAD patients into two subtypes based on RACGAP1 cell cycle-related genes (RrCCGs). These subtypes exhibited significant differences in tumor characteristics, lymph node metastasis, and recurrence. Furthermore, we evaluated the prognostic influence of RrCCGs using univariate Cox regression and least absolute shrinkage and selection operator regression models (LASSO), successfully establishing a prognostic model. Results: RACGAP1 is frequently overexpressed in various tumors and can impact the prognosis of patients with LUAD. Additionally, experimental evidence has demonstrated that low expression of RACGAP1 favors tumor cell apoptosis and restoration of the cell cycle, while high expression promotes invasion and metastasis. Through CC analysis of RrCCGs, patients were classified into two groups, with survival analysis revealing distinct prognoses and stages between the two groups. Furthermore, Cox and LASSO regression successfully constructed a prognostic model with robust predictive capability.

An anoikis-related gene signature predicts prognosis, drug sensitivity, and immune microenvironment in cholangiocarcinoma.

Background: Cholangiocarcinoma is a malignant invasive biliary tract carcinoma with a poor prognosis. Anoikis-related genes are prognostic features of a variety of cancers. However, the value of prognostication and therapeutic effect of anoikis-related genes in cholangiocarcinoma have not been reported. The aim of this research was developing an ARGs signature associated with cholangiocarcinoma patients. Methods: We introduced transcriptome data to discover genes that were differentially expressed in cholangiocarcinoma. Subsequently, WGCNA was utilized to screen critical module genes in reference to anoikis. The univariate Cox, Lasso regression and Kaplan-Meier survival were executed to build a prognostic signature. We further performed gene functional enrichment, immune microenvironment and immunotherapy analysis between two risk subgroups. Finally, the pRRophetic algorithm was applied to compare the half inhibitory concentration value of several drugs. Results: A grand total of 1844 genes with differential expression related to the cholangiocarcinoma patients were identified. Furthermore, we obtained 2678 key module genes related to anoikis. Then, a prognostic signature was developed using the 6 prognostic genes (FXYD2, PCBD1, C1RL, GMNN, LAMA4 and HACL1). Independent prognostic analysis showed that risk score and alcohol could function as separate prognostic variables. We found cetain distinction in the immune microenvironment between the two risk subgroups. Moreover, immunotherapy evaluation showed that the anoikis-related gene signature could be applied as a therapy predictor. Finally, Chemotherapeutic drug sensitivity results showed that the low-risk group responded better to bosutinib, gefitinib, gemcitabine, and paclitaxel, while the high-risk group responded better to axitinib, cisplatin, and imatinib. Conclusion: The prognostic signature comprised of FXYD2, PCBD1, C1RL, GMNN, LAMA4 and HACL1 based on anoikis-related genes was established, which provided theoretical basis and reference value for the research and treatment of cholangiocarcinoma.

Identification of a disulfidptosis-related prognostic signature for prediction of the effect of treatment in patients with endometrial carcinoma.

Background: Disulfide, an essential compounds family, has diverse biological activity and can affect the dynamic balance between physiological and pathological states. A recently published study found that aberrant accumulation of disulfide had a lethal effect on cells. This mechanism of cell death, named disulfidptosis, differs from other known cell death mechanisms, including cuproptosis, apoptosis, necroptosis, and pyroptosis. The relationship between disulfidptosis and development of cancer, in particular endometrial carcinoma, remains unclear. Methods: To address this knowledge gap, we performed a preliminary analysis of samples from The Cancer Genome Atlas database. The samples were divided equally into a training group and a test group. A total of 2308 differentially expressed genes were extracted, and 11 were used to construct a prognostic model. Results: Based on the risk score calculated using the prognostic model, the samples were divided into a high-risk group and a low-risk group. Survival time, tumor mutation burden, and microsatellite instability scores differed significantly between the two groups. Furthermore, a between-group difference in treatment effect was predicted. Comparison with other models in the literature indicated that this prognostic model had better predictive anility. Conclusion: The results of this study provide a general framework for understanding the relationship between disulfidptosis and endometrial cancer that could be used for clinical evaluation and selection of appropriate personalized treatment strategies.

Prognostic significance of hemoglobin, albumin, lymphocyte, and platelet (HALP) score in breast cancer: a propensity score-matching study.

BACKGROUND: The hemoglobin-albumin-lymphocyte-platelet (HALP) score functions as a comprehensive index that assesses the systemic inflammatory response, nutritional, and immune status. This study aimed to explore the relationship between preoperative HALP score and the prognosis of BC patients and to develop predictive nomograms. METHODS: Clinicopathological data were collected for BC patients who underwent mastectomy between December 2010 and April 2014 from Sun Yat-sen University Cancer Center. The optimal cutoff value for HALP was determined by maximally selected rank statistics for overall survival data. Propensity score matching (PSM) was applied to develop comparable cohorts of high-HALP group and low-HALP group. Kaplan-Meier curves and Cox regression analyses were performed to determine the impact of HALP on BC patients. Prognostic nomograms were developed based on the multivariate Cox regression method. Then, the concordance index (C-index), calibration plots, and decision curves analysis (DCA) were applied to evaluate the prognostic performance of the nomograms. RESULTS: A total of 1,856 patients were included as the primary cohort, and 1,470 patients were matched and considered as the PSM cohort. In the primary cohort, the 5-year overall survival (OS) and progression-free survival (PFS) rates for high-HALP group (≥ 47.89) and low-HALP group (< 47.89) were 94.4% vs. 91.0% (P = 0.005) and 87.8% vs. 82.1% (P = 0.005), respectively. Similar results were observed in PSM cohort (5-year OS, 94.3% vs. 90.8%, P = 0.015; 5-year PFS, 87.5% vs. 83.2%, P = 0.036). Notably, multivariate Cox regression analysis in the PSM cohort showed that HALP could independently predict BC patient prognosis in both OS (HR: 0.596, 95%CI [0.405-0.875], P = 0.008) and PFS (HR: 0.707, 95%CI [0.538-0.930], P = 0.013). OS and PFS nomograms showed excellent predictive performance with the C-indexes of 0.783 and 0.720, respectively. The calibration plots and DCA also indicated the good predictability of the nomograms. Finally, subgroup analysis further demonstrated a favorable impact of HALP on both OS and PFS. CONCLUSION: Preoperative HALP score can be used as a reliable independent predictor of OS and PFS in BC patients, and the nomograms may provide a personalized treatment strategy.

What prognostic factors have impacted the efficacy of immune checkpoint inhibitors in patients with recurrent or metastatic oral cancer?

BACKGROUND: Immune checkpoint inhibitors (ICIs) are widely adapted for recurrent or metastatic head and neck cancer (RM-HNC), and various studies on its prognostic factors have been reported. We aimed to elucidate the prognostic factors of ICI treatment for RM oral cancer (RM-OC) in a retrospective study. METHODS: We retrospectively reviewed patients with RM-OC treated with ICIs (nivolumab and pembrolizumab) at our department from May 2017 to February 2023. The objective response rate (ORR) for ICI treatment and the relationship between several potential prognostic factors, progression-free survival (PFS), and overall survival (OS) were analyzed statistically. RESULTS: The investigation enrolled 31 patients, 16 with nivolumab and 15 with pembrolizumab. There were no significant differences in the ORR or disease control rate between the nivolumab and pembrolizumab groups (p = 0.4578 and 0.2524). In multivariate analysis, the prognostic nutritional index (PNI) and C-reactive protein to albumin ratio (CAR) exhibited statistical correlations with PFS, whereas the use of antibiotics and proton pump inhibitors (PPIs), neutrophil to lymphocyte ratio (NLR), and PNI demonstrated statistical associations with OS. CONCLUSION: Our findings imply that the use of antibiotics and PPIs, which can modify the gut microbiota, may also serve as a prognostic determinant for ICI treatment in RM-OC, consistent with previous studies. Additionally, PNI may be essential in affecting the survival rates of both PFS and OS and could be an exceedingly valuable inflammatory biomarker for RM-OC.

Immunotherapy-relevance of a candidate prognostic score for Acute Myeloid Leukemia.

Background: Acute Myeloid Leukemia (AML) exhibits a wide array of phenotypic manifestations, progression patterns, and heterogeneous responses to immunotherapies, suggesting involvement of complex immunobiological mechanisms. This investigation aimed to develop an integrated prognostic model for AML by incorporating cancer driver genes, along with clinical and phenotypic characteristics of the disease, and to assess its implications for immunotherapy responsiveness. Methods: Critical oncogenic driver genes linked to survival were identified by screening primary effector and corresponding gene pairs using data from The Cancer Genome Atlas (TCGA), through univariate Cox proportional hazard regression analysis. This was independently verified using dataset GSE37642. Primary effector genes were further refined using LASSO regression. Transcriptomic profiling was quantified using multivariate Cox regression, and the derived prognostic score was subsequently validated. Finally, a multivariate Cox regression model was developed, incorporating the transcriptomic score along with clinical parameters such as age, gender, and French-American-British (FAB) classification subtype. The 'Accurate Prediction Model of AML Overall Survival Score' (APMAO) was developed and subsequently validated. Investigations were conducted into functional pathway enrichment, alterations in the gene mutational landscape, and the extent of immune cell infiltration associated with varying APMAO scores. To further investigate the potential of APMAO scores as a predictive biomarker for responsiveness to cancer immunotherapy, we conducted a series of analyses. These included examining the expression profiles of genes related to immune checkpoints, the interferon-gamma signaling pathway, and m6A regulation. Additionally, we explored the relationship between these gene expression patterns and the Tumor Immune Dysfunction and Exclusion (TIDE) dysfunction scores. Results: Through the screening of 95 cancer genes associated with survival and 313 interacting gene pairs, seven genes (ACSL6, MAP3K1, CHIC2, HIP1, PTPN6, TFEB, and DAXX) were identified, leading to the derivation of a transcriptional score. Age and the transcriptional score were significant predictors in Cox regression analysis and were integral to the development of the final APMAO model, which exhibited an AUC greater than 0.75 and was successfully validated. Notable differences were observed in the distribution of the transcriptional score, age, cytogenetic risk categories, and French-American-British (FAB) classification between high and low APMAO groups. Samples with high APMAO scores demonstrated significantly higher mutation rates and pathway enrichments in NFKB, TNF, JAK-STAT, and NOTCH signaling. Additionally, variations in immune cell infiltration and immune checkpoint expression, activation of the interferon-γ pathway, and expression of m6A regulators were noted, including a negative correlation between CD160, m6A expression, and APMAO scores. Conclusion: The combined APMAO score integrating transcriptional and clinical parameters demonstrated robust prognostic performance in predicting AML survival outcomes. It was linked to unique phenotypic characteristics, distinctive immune and mutational profiles, and patterns of expression for markers related to immunotherapy sensitivity. These observations suggest the potential for facilitating precision immunotherapy and advocate for its exploration in upcoming clinical trials.

Identifying and evaluating a disulfidptosis-related gene signature to predict prognosis in colorectal adenocarcinoma patients.

Disulfidptosis, a regulated form of cell death, has been recently reported in cancers characterized by high SLC7A11 expression, including invasive breast carcinoma, lung adenocarcinoma, and hepatocellular carcinoma. However, its role in colon adenocarcinoma (COAD) has been infrequently discussed. In this study, we developed and validated a prognostic model based on 20 disulfidptosis-related genes (DRGs) using LASSO and Cox regression analyses. The robustness and practicality of this model were assessed via a nomogram. Subsequent correlation and enrichment analysis revealed a relationship between the risk score, several critical cancer-related biological processes, immune cell infiltration, and the expression of oncogenes and cell senescence-related genes. POU4F1, a significant component of our model, might function as an oncogene due to its upregulation in COAD tumors and its positive correlation with oncogene expression. In vitro assays demonstrated that POU4F1 knockdown noticeably decreased cell proliferation and migration but increased cell senescence in COAD cells. We further investigated the regulatory role of the DRG in disulfidptosis by culturing cells in a glucose-deprived medium. In summary, our research revealed and confirmed a DRG-based risk prediction model for COAD patients and verified the role of POU4F1 in promoting cell proliferation, migration, and disulfidptosis.

Risk factors and prognostic analysis of right ventricular dysfunction after lung resection for NSCLC.

Objectives: Lung cancer is the leading cause of cancer death, and 80-85% of all lung cancer cases are non-small cell lung cancer (NSCLC). Surgical resection is the standard treatment for early-stage NSCLC. However, lung resection, a surgical procedure, can result in complications and increased mortality. Recent studies have shown a significant correlation between complications after lung resection and right ventricular dysfunction. Methods: Transthoracic echocardiography-derived right ventricular-pulmonary artery coupling (RV-PAC) was utilized to assess right ventricular function in these patients. Multivariate logistic regression analysis was also conducted to assess risk factors independently associated with RV-PA uncoupling. The 3- and 5-year cumulative survival rates were estimated with Kaplan-Meier curves, and differences between groups were analyzed using the Mantel-Cox log-rank test. Results: RV-PA uncoupling was defined as a TAPSE/PASP value < 0.67 mm/mm Hg according to spline analysis. The results of multivariable logistic regression analysis indicated that diabetes is an independent risk factor for right ventricular dysfunction after lung resection in patients with NSCLC. Kaplan-Meier analysis revealed a significant decrease in the survival rate of patients with RV-PA uncoupling at both the 3-year follow-up (73% vs 40%, p < 0.001) and 5-year follow-up (64% vs 37%, p < 0.001). Conclusions: After lung resection for NSCLC, the patient's right ventricular function predicts prognosis. Patients with right ventricular dysfunction, particularly those with diabetes mellitus, have a worse prognosis. It is crucial to actively prevent and correct risk factors to reduce the mortality rate in these patients.

Prognostic value of systemic immune-inflammation index in patients with metastatic renal cell carcinoma treated with systemic therapy: a meta-analysis.

Objective: A novel systemic immune-inflammation index (SII), based on the neutrophils, lymphocytes, and platelet counts, is associated with the prognosis of several cancers, including non-metastatic renal cell carcinoma (RCC). In the present study, we evaluate the prognostic significance of SII in patients with metastatic RCC (mRCC) treated with systemic therapy. Method: Relevant studies were searched comprehensively from Web of Science, PubMed, Embase and the Cochrane Library up to January 2024. The pooled hazard ratio (HR) and 95% confidence interval (CI) were extracted from each study to evaluate the prognostic value of SII in patients with mRCC treated with tyrosine kinase inhibitor (TKI) or immune checkpoint inhibitor (ICI). Results: A total of 12 studies including 4,238 patients were included in the final analysis. High SII was significantly correlated to poor overall survival (OS, HR = 1.88; 95% CI 1.60-2.21; P < 0.001) and progression-free survival (PFS, HR = 1.66; 95% CI 1.39-1.99; P < 0.001). Stratified by therapy, high SII was also related to the poor OS (TKI: HR = 1.63, P < 0.001; ICI: HR = 2.27, P < 0.001) and PFS (TKI: HR = 1.67, P < 0.001; ICI: HR = 1.88, P = 0.002). Conclusion: In conclusion, high SII could serve as an unfavorable factor in patients with mRCC treated with systemic therapy. Stratified by therapies, the elevated SII was also associated with worse prognosis. Whereas, more prospective and large-scale studies are warranted to validate our findings. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024522831, identifier CRD42024522831.

Geriatric Nutritional Risk Index as Prognostic Marker for Elderly Patients With Small Cell Lung Cancer.

Background/Aim: The Geriatric Nutritional Risk Index (GNRI) indicates nutritional status based on serum albumin concentration and ideal body weight. Pretreatment GNRI has been suggested as a prognostic factor for various malignancies. However, little is known about the clinical value of GNRI for small-cell lung cancer (SCLC), especially in elderly patients. Patients and Methods: We retrospectively analyzed 53 elderly (≥71) patients with extensive-disease (ED) SCLC treated with first-line platinum-doublet chemotherapy in relation to the pretreatment GNRI level in a real-world setting. Results: Thirty-six patients with a low GNRI (<92) had statistically poorer progression-free survival (PFS) and overall survival (OS) than 17 patients with a high GNRI (≥92) (median PFS=80 days vs. 133 days, respectively; p=0.002; median OS=123 days vs. 274 days, respectively; p=0.004). In a multivariate analysis, a low GNRI was also an independent poor prognostic factor for PFS [hazard ratio (HR)=0.396; 95% confidence interval (CI)=0.199-0.789; p=0.008] and OS (HR=0.295; 95%CI=0.143-0.608; p<0.001). Conclusion: The GNRI might be a predictive and prognostic marker in elderly patients with ED-SCLC treated with platinum-doublet chemotherapy.

A Concordance Between Clinical and Pathological Tumor Staging of Oral Squamous Cell Carcinoma: An Institutional Study.

BACKGROUND: Among oral diseases, oral cancer is the primary cause of death and poses a serious health risk. Primary tumor (T) - regional lymph node (N) - distant metastasis (M) comprising (TNM) staging is crucial for planning treatment strategies for patients with oral squamous cell carcinoma (OSCC). AIM: This study evaluated the predictive accuracy of clinical TNM staging of OSCC to histopathological staging (pTNM) in an institutional setting. MATERIALS AND METHODS: Fifty-four consecutive histologically confirmed, surgically treated OSCC cases were evaluated for TNM staging. The study compared the clinical staging at the time of surgery with the pathological staging obtained from excisional biopsy reports. Microsoft Excel (Microsoft® Corp., Redmond, WA, USA) was used for the data compilation and descriptive analysis. The chi-square test, analysis of variance (ANOVA), and Tukey's Honest Significant Difference (HSD) posthoc test were used to compare the data for statistical significance with p value <0.05 using Statistical Package for the Social Sciences (IBM SPSS Statistics for Windows, IBM Corp., Version 23.0, Armonk, NY). RESULTS: The alveolar mucosa (n=22, 40.74%) was the most frequently occurring site, followed by the tongue (n=17, 31.48%). Out of the 54 included cases, based on clinical tumor size, there were T1 (n=6), T2 (n=13), T3 (n=13), T4a (n=16) and T4b (n=6). T2 tumors were usually upstaged (n=7) while T4a (n=8) tumors were most often downstaged. T4a (n=8) had the best concordance between clinical and histopathological staging, followed by T2, T3, and T1. In nodal status, N1 showed the most variation. The chi-squared test showed statistical significance for tumor size comparison (p <0.001) and nodal status comparison (p=0.002). ANOVA test did not show any statistical significance. Tukey's HSD posthoc test showed statistical significance (p=0.034) for N0 and N1 status. The highest concordance was shown by N0 and N1 followed by N2b. CONCLUSION: Preoperative radiological and clinical assessments are essential for deciding on a patient's course of treatment. However, not all patients may require radiographs to determine tumor size or nodal status assessment. Accurate diagnosis is vital for the treatment planning of OSCC.

Establishment of an ovarian cancer exhausted CD8+T cells-related genes model by integrated analysis of scRNA-seq and bulk RNA-seq.

Ovarian cancer (OC) was the fifth leading cause of cancer death and the deadliest gynecological cancer in women. This was largely attributed to its late diagnosis, high therapeutic resistance, and a dearth of effective treatments. Clinical and preclinical studies have revealed that tumor-infiltrating CD8+T cells often lost their effector function, the dysfunctional state of CD8+T cells was known as exhaustion. Our objective was to identify genes associated with exhausted CD8+T cells (CD8TEXGs) and their prognostic significance in OC. We downloaded the RNA-seq and clinical data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. CD8TEXGs were initially identified from single-cell RNA-seq (scRNA-seq) datasets, then univariate Cox regression, the least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression were utilized to calculate risk score and to develop the CD8TEXGs risk signature. Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, time-dependent receiver operating characteristics (ROC), nomogram, and calibration were conducted to verify and evaluate the risk signature. Gene set enrichment analyses (GSEA) in the risk groups were used to figure out the closely correlated pathways with the risk group. The role of risk score has been further explored in the homologous recombination repair deficiency (HRD), BRAC1/2 gene mutations and tumor mutation burden (TMB). A risk signature with 4 CD8TEXGs in OC was finally built in the TCGA database and further validated in large GEO cohorts. The signature also demonstrated broad applicability across various types of cancer in the pan-cancer analysis. The high-risk score was significantly associated with a worse prognosis and the risk score was proven to be an independent prognostic biomarker. The 1-, 3-, and 5-years ROC values, nomogram, calibration, and comparison with the previously published models confirmed the excellent prediction power of this model. The low-risk group patients tended to exhibit a higher HRD score, BRCA1/2 gene mutation ratio and TMB. The low-risk group patients were more sensitive to Poly-ADP-ribose polymerase inhibitors (PARPi). Our findings of the prognostic value of CD8TEXGs in prognosis and drug response provided valuable insights into the molecular mechanisms and clinical management of OC.