Clinical prognostic significance of xeroderma pigmentosum group C and IFN‑γ in non‑small cell lung cancer

Lung cancer is the most common cancer in the world due to its high incidence and recurrence. Genetic instability is one of the main factors leading to its occurrence, development and poor prognosis. Decreased xeroderma pigmentosum group C (XPC) expression notably enhances the stem cell properties of lung cancer cells and increases their proliferation and migration. Additionally, patients with lung cancer and low XPC expression had a poor prognosis. The purpose of the present study was to analyze the effect of XPC and IFN-γ on the clinical prognosis of patients with non-small cell lung cancer (NSCLC). Lung adenocarcinoma specimens were collected from a total of 140 patients with NSCLC. Additionally, from these 140 patients, 48 paracarcinoma tissue specimens were also collected, which were later used to construct tissue microarrays. The expression of XPC and IFN-γ in cancer tissues and in paraneoplastic tissues was detected using immunohistochemistry. The prognosis and overall survival of patients were determined through telephone follow-up. The results showed a positive correlation between expression of XPC and IFN-γ in NSCLC. Additionally, high expression of both markers was associated with a favorable prognosis in patients with NSCLC. The aforementioned findings suggest that the expression of XPC and IFN-γ has prognostic value in clinical practice and is expected to become a marker for clinical application.

MET fusions and splicing variants is a strong adverse prognostic factor in astrocytoma, isocitrate dehydrogenase mutant

Liu et al. describe the adverse prognostic role of MET fusions and splicing variants in astrocytoma, isocitrate dehydrogenase mutant. On this basis, MET fusions and splicing variants was suggested to be a biomarker for the diagnosis of high-grade astrocytoma, isocitrate dehydrogenase mutant.

Prognostic value of tumor‑associated CD177+ neutrophils in lung adenocarcinoma

The aim of the present study was to detect CD177+ neutrophils in tumor tissues and analyze their association with the clinical characteristics and prognosis of patients with lung adenocarcinoma (LUAD). Immunohistochemistry was used to detect CD177+ neutrophils in tumors and adjacent tissues of 16 patients with LUAD who underwent curative surgical resection. A total of 120 patients with LUAD were recruited, and their clinical data were collected; survival follow-up was performed. CD177+ neutrophils in tumor tissues were detected via immunohistochemistry, and the association between CD177+ neutrophils and clinical characteristics was analyzed. The density of CD177+ neutrophils in tumor tissues and adjacent tissues of patients with LUAD was analyzed using t-test, and the association between CD177+ neutrophils and clinical characteristics was analyzed through the Chi-square test. Survival was calculated using the Kaplan-Meier survival rate curve. Finally, the association between these indicators and the survival of LUAD patients was evaluated using Cox regression analysis. CD177+ neutrophil infiltration was significantly higher in LUAD tumor tissues, and the high density of CD177+ neutrophils was associated with the clinical characteristics of TNM stage, tumor differentiation and poor progression-free and overall survival in LUAD. In conclusion, tumor-associated CD177+ neutrophils associated with malignant progression and poor prognosis may be independent and unfavorable prognostic biomarkers for LUAD.

A 4-gene prognostic index for enhancing acute myeloid leukaemia survival prediction

Despite advancements in utilizing genetic markers to enhance acute myeloid leukaemia (AML) outcome prediction, significant disease heterogeneity persists, hindering clinical management. To refine survival predictions, we assessed the transcriptome of non-acute promyelocytic leukaemia chemotherapy-treated AML patients from five cohorts (n = 975). This led to the identification of a 4-gene prognostic index (4-PI) comprising CYP2E1, DHCR7, IL2RA and SQLE. The 4-PI effectively stratified patients into risk categories, with the high 4-PI group exhibiting TP53 mutations and cholesterol biosynthesis signatures. Single-cell RNA sequencing revealed enrichment for leukaemia stem cell signatures in high 4-PI cells. Validation across three cohorts (n = 671), including one with childhood AML, demonstrated the reproducibility and clinical utility of the 4-PI, even using cost-effective techniques like real-time quantitative polymerase chain reaction. Comparative analysis with 56 established prognostic indexes revealed the superior performance of the 4-PI, highlighting its potential to enhance AML risk stratification. Finally, the 4-PI demonstrated to be potential marker to reclassified patients from the intermediate ELN2017 category to the adverse category. In conclusion, the 4-PI emerges as a robust and straightforward prognostic tool to improve survival prediction in AML patients.

Machine Learning-Based Prediction of Changes in the Clinical Condition of Patients With Complex Chronic Diseases: 2-Phase Pilot Prospective Single-Center Observational Study

BACKGROUND

Functional impairment is one of the most decisive prognostic factors in patients with complex chronic diseases. A more significant functional impairment indicates that the disease is progressing, which requires implementing diagnostic and therapeutic actions that stop the exacerbation of the disease.

OBJECTIVE

This study aimed to predict alterations in the clinical condition of patients with complex chronic diseases by predicting the Barthel Index (BI), to assess their clinical and functional status using an artificial intelligence model and data collected through an internet of things mobility device.

METHODS

A 2-phase pilot prospective single-center observational study was designed. During both phases, patients were recruited, and a wearable activity tracker was allocated to gather physical activity data. Patients were categorized into class A (BI≤20; total dependence), class B (2060; moderate or mild dependence, or independent). Data preprocessing and machine learning techniques were used to analyze mobility data. A decision tree was used to achieve a robust and interpretable model. To assess the quality of the predictions, several metrics including the mean absolute error, median absolute error, and root mean squared error were considered. Statistical analysis was performed using SPSS and Python for the machine learning modeling.

RESULTS

Overall, 90 patients with complex chronic diseases were included: 50 during phase 1 (class A: n=10; class B: n=20; and class C: n=20) and 40 during phase 2 (class B: n=20 and class C: n=20). Most patients (n=85, 94%) had a caregiver. The mean value of the BI was 58.31 (SD 24.5). Concerning mobility aids, 60% (n=52) of patients required no aids, whereas the others required walkers (n=18, 20%), wheelchairs (n=15, 17%), canes (n=4, 7%), and crutches (n=1, 1%). Regarding clinical complexity, 85% (n=76) met patient with polypathology criteria with a mean of 2.7 (SD 1.25) categories, 69% (n=61) met the frailty criteria, and 21% (n=19) met the patients with complex chronic diseases criteria. The most characteristic symptoms were dyspnea (n=73, 82%), chronic pain (n=63, 70%), asthenia (n=62, 68%), and anxiety (n=41, 46%). Polypharmacy was presented in 87% (n=78) of patients. The most important variables for predicting the BI were identified as the maximum step count during evening and morning periods and the absence of a mobility device. The model exhibited consistency in the median prediction error with a median absolute error close to 5 in the training, validation, and production-like test sets. The model accuracy for identifying the BI class was 91%, 88%, and 90% in the training, validation, and test sets, respectively.

CONCLUSIONS

Using commercially available mobility recording devices makes it possible to identify different mobility patterns and relate them to functional capacity in patients with polypathology according to the BI without using clinical parameters.

Prognostic impact of CD68+ tumor-associated macrophages in hepatocellular carcinoma: A meta-analysis

BACKGROUND

Evidence from clinical research suggests that the tumor-associated macrophages (TAMs) were associated with prognosis in hepatocellular carcinoma (HCC). The aim of the present meta-analysis was to conduct a qualitative analysis to explore the prognostic value of CD68 + TAMs in HCC.

METHODS

This study conducted a systematic search in Pubmed, Embase, the Cochrane Library and China National Knowledge Internet from inception of the databases to November 2023. The hazard ratio (HR) and 95% confidence interval (CI) were calculated employing fixed-effect or random-effect models depending on the heterogeneity of the included trials. The Newcastle-Ottawa Scale was used to evaluate the risk of prejudice.

RESULTS

We analyzed 4362 HCC patients. The present research indicated that the expression levels Of CD68 + TAMs were significantly associated with overall survival (OS) (HR = 1.55, 95% CI: 1.30-1.84) and disease-free survival (DFS) (HR = 1.44, 95% CI: 1.17-1.78). Subgroup analysis based on cutoff values showed that the "Median" subgroup showed a pooled HR of 1.66 with a 95% CI ranging from 1.32 to 2.08, which was slightly higher than the "Others" subgroup that exhibited a pooled HR of 1.40 and a 95% CI of 1.07 to 1.84. The "PT" subgroup had the highest pooled HR of 1.68 (95% CI: 1.19-2.37), indicating a worse OS compared to the "IT" (pooled HR: 1.50, 95% CI: 1.13-2.01) and "Mix" (pooled HR: 1.52, 95% CI: 1.03-2.26) subgroups. Moreover, in the sample size-based analysis, studies with more than 100 samples (>100) exhibited a higher pooled HR of 1.57 (95% CI: 1.28 to 1.93) compared to studies with fewer than 100 samples (<100), which had a pooled HR of 1.45 (95% CI: 1.00-2.10).

CONCLUSIONS

The analysis suggests that CD68 + TAMs were significantly associated with unfavorable OS and DFS in HCC patients, and may be served as a promising prognostic biomarker in HCC. However, more large-scale trials are needed to study the clinical value of TAMs in HCC.

Investigating the Cell Origin and Liver Metastasis Factors of Colorectal Cancer by Single-Cell Transcriptome Analysis

Background

Colorectal cancer (CRC) is one of the deadliest causes of death by cancer worldwide. Liver metastasis (LM) is the main cause of death in patients with CRC. Therefore, identification of patients with the greatest risk of liver metastasis is critical for early treatment and reduces the mortality of patients with colorectal cancer liver metastases.

Methods

Initially, we characterized cell composition through single-cell transcriptome analysis. Subsequently, we employed copy number variation (CNV) and pseudotime analysis to delineate the cellular origins of LM and identify LM-related epithelial cells (LMECs). The LM-index was constructed using machine learning algorithms to forecast the relative abundance of LMECs, reflecting the risk of LM. Furthermore, we analyzed drug sensitivity and drug targeted gene expression in LMECs and patients with a high risk of LM. Finally, functional experiments were conducted to determine the biological roles of metastasis-related gene in vitro.

Results

Single-cell RNA sequencing analysis revealed different immune landscapes between primary CRC and LM tumor. LM originated from chromosomal variants with copy number loss of chr1 and chr6p and copy number gain of chr7 and chr20q. We identified the LMECs cluster and found LM-associated pathways such as Wnt/beta-catenin signaling and KRAS signaling. Subsequently, we identified ten metastasis-associated genes, including SOX4, and established the LM-index, which correlates with poorer prognosis, higher stage, and advanced age. Furthermore, we screened two drugs as potential candidates for treating LM, including Linsitinib_1510, Lapatinib_1558. Immunohistochemistry results demonstrated significantly elevated SOX4 expression in tumor samples compared to normal samples. Finally, in vitro experiments verified that silencing SOX4 significantly inhibited tumor cell migration and invasion.

Conclusion

This study reveals the possible cellular origin and driving factors of LM in CRC at the single cell level, and provides a reference for early detection of CRC patients with a high risk of LM.

Integrating Patient-Reported Outcomes Into Prognostication in Gastroesophageal Cancer: Results of a Population-Based Retrospective Cohort Analysis

BACKGROUND

Patient-reported outcomes measures (PROM) are self-reflections of an individual's physical functioning and emotional well-being. The Edmonton Symptom Assessment Scale (ESAS) is a simple and validated PRO tool of 10 common symptoms and a patient-reported functional status (PRFS) measure. The prognostic value of this tool is unknown in patients with gastroesophageal cancer (GEC). In this study, we examined the association between the ESAS score and overall survival (OS) in patients with GEC, the prognostication difference between ESAS and Eastern Cooperative Oncology Group (ECOG), and assessed the correlation between PRFS and the physician-reported ECOG performance status (PS).

METHODS

The study was a retrospective cohort study of 211 patients with GEC with localized (stages I-III) and metastatic disease who completed at least one baseline ESAS prior to treatment. Patients were grouped into 3 cohorts based on ESAS score. OS was assessed using the Kaplan-Meier method, and the concordance index (c-index) was calculated for ESAS and physician-reported ECOG. The agreement between PRFS and physician-ECOG was also assessed.

RESULTS

In total, 211 patients were included. The median age was 60.8 years; 90% of patients were ECOG PS 0-1; 38% of patients were stages I-III, while 62% were de novo metastatic patients. Median OS in low, moderate, high symptom burden (SB) patients' cohorts was 19.17 m, 16.39 mm, and 12.68 m, respectively (P < .04). The ability to predict death was similar between physician-ECOG and ESAS (c-index 0.56 and 0.5753, respectively) and PRFS and physician-ECOG (c-index of 0.5615 and 0.5545, respectively). The PS agreement between patients and physicians was 50% with a weighted Kappa of 0.27 (95% CI: 0.17-0.38).

CONCLUSION

Patient's SB seems to carry a prognostic significance. ESAS and physician-reported ECOG exhibit comparable prognostic values. Physicians and patients can frequently have divergent opinions on PS. ESAS takes a patient-centered approach and should be encouraged in practice among patients with GEC as an additional tool for prognostication.

Predictive and Prognostic Biomarkers in Patients With Mycosis Fungoides and Sézary Syndrome (BIO-MUSE): Protocol for a Translational Study

BACKGROUND

Cutaneous T-cell lymphoma (CTCL) is a rare group of lymphomas that primarily affects the skin. Mycosis fungoides (MF) is the most common form of CTCL and Sézary syndrome (SS) is more infrequent. Early stages (IA-IIA) have a favorable prognosis, while advanced stages (IIB-IVB) have a worse prognosis. Around 25% of patients with early stages of the disease will progress to advanced stages. Malignant skin-infiltrating T-cells in CTCL are accompanied by infiltrates of nonmalignant T-cells and other immune cells that produce cytokines that modulate the inflammation. Skin infection, often with Staphylococcus aureus, is frequent in advanced stages and can lead to sepsis and death. S. aureus has also been reported to contribute to the progression of the disease. Previous reports indicate a shift from Th1 to Th2 cytokine production and dysfunction of the skin barrier in CTCL. Treatment response is highly variable and often unpredictable, and there is a need for new predictive and prognostic biomarkers.

OBJECTIVE

This prospective translational study aims to identify prognostic biomarkers in the blood and skin of patients with MF and SS.

METHODS

The Predictive and Prognostic Biomarkers in Patients With MF and SS (BIO-MUSE) study aims to recruit 120 adult patients with MF or SS and a control group of 20 healthy volunteers. The treatments will be given according to clinical routine. The sampling of each patient will be performed every 3 months for 3 years. The blood samples will be analyzed for lactate dehydrogenase, immunoglobulin E, interleukins, thymus and activation-regulated chemokine, and lymphocyte subpopulations. The lymphoma microenvironment will be investigated through digital spatial profiling and single-cell RNA sequencing. Microbiological sampling and analysis of skin barrier function will be performed. The life quality parameters will be evaluated. The results will be evaluated by the stage of the disease.

RESULTS

Patient inclusion started in 2021 and is still ongoing in 2023, with 18 patients and 20 healthy controls enrolled. The publication of selected translational findings before the publication of the main results of the trial is accepted.

CONCLUSIONS

This study aims to investigate blood and skin with a focus on immune cells and the microbiological environment to identify potential new prognostic biomarkers in MF and SS.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04904146; https://www.clinicaltrials.gov/study/NCT04904146.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/55723.

Identifying the predictive role and the related drugs of oxidative stress genes in the hepatocellular carcinoma

BACKGROUND AND AIMS

Oncogenesis and tumor development have been related to oxidative stress (OS). The potential diagnostic utility of OS genes in hepatocellular carcinoma (HCC), however, remains uncertain. As a result, this work aimed to create a novel OS related-genes signature that could be used to predict the survival of HCC patients and to screen OS related-genes drugs that might be used for HCC treatment.

METHODS

We used The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database to acquire mRNA expression profiles and clinical data for this research and the GeneCards database to obtain OS related-genes. Following that, biological functions from Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed on differentially expressed OS-related genes (DEOSGs). Subsequently, the prognostic risk signature was constructed based on DEOSGs from the TCGA data that were screened by using univariate cox analysis, and the Least Absolute Shrinkage and Selection Operator (LASSO) regression, and multivariate cox analysis. At the same time, we developed a prognostic nomogram of HCC patients based on risk signature and clinical-pathological characteristics. The GEO data was used for validation. We used the receiver operating characteristic (ROC) curve, calibration curves, and Kaplan-Meier (KM) survival curves to examine the prediction value of the risk signature and nomogram. Finally, we screened the differentially expressed OS genes related drugs.

RESULTS

We were able to recognize 9 OS genes linked to HCC prognosis. In addition, the KM curve revealed a statistically significant difference in overall survival (OS) between the high-risk and low-risk groups. The area under the curve (AUC) shows the independent prognostic value of the risk signature model. Meanwhile, the ROC curves and calibration curves show the strong prognostic power of the nomogram. The top three drugs with negative ratings were ZM-336372, lestaurtinib, and flunisolide, all of which inversely regulate different OS gene expressions.

CONCLUSION

Our findings indicate that OS related-genes have a favorable prognostic value for HCC, which sheds new light on the relationship between oxidative stress and HCC, and suggests potential therapeutic strategies for HCC patients.

Bioinformatics analyses and experimental validation of the role of phagocytosis in low-grade glioma

BACKGROUND

Phagocytosis is of vital importance in tumor immune response. The alteration of phagocytosis in low-grade glioma (LGG) has not been investigated.

METHODS

The mRNA, copy number variation, single nucleotide variation, and methylation levels of phagocytosis-related genes were summarized in pan-cancer. Non-negative matrix factorization clustering was utilized to identify two LGG subtypes. LASSO regression analysis was performed to construct a phagocytosis-related prognostic signature (PRPS). Immune characteristics, immunotherapy response, and targeted-drug sensitivity were further explored. The phagocytosis activity in glioma was evaluated using scRNA-seq data. Multiplex immunohistochemical (m-IHC) technology was performed to identify the tumor-infiltrating immune cells in LGG.

RESULTS

The phagocytosis-related genes altered obviously in pan-cancer compared with corresponding normal tissues. Two LGG subtypes were obtained and the subtype with poor prognosis was combined with lower tumor purity, more active immune-related pathways, increasing infiltration of CD4+ T cells, CD8+ T cells, and natural killer (NK) cells, decreasing infiltration of macrophages, mast cells, and neutrophils, distinct pathway activity and cell death status, greater response to immunotherapy, and higher sensitivity to cyclophosphamide, erlotinib, gefitinib, lapatinib, and sorafenib. In addition, a PRPS involving 10 genes (i.e., SLC11A1, CAMK1D, PLA2G5, STAP1, ALOX15, PLCG2, SFTPD, AZU1, RAB27A, and LAMTOR2) was constructed to estimate the risk level of each LGG sample and high risk LGG patients had poor prognosis, upregulated infiltration of neutrophil, macrophage, Treg, and myeloid dendritic cell, down regulated infiltration of monocyte and NK cell, and increasing expression of large number of immune checkpoint genes. The phagocytosis activity is notably active in monocyte/macrophage. The m-IHC results confirmed increased infiltration of macrophages and neutrophils in LGG samples with high SLC11A1 expression.

CONCLUSION

The molecular characteristics of phagocytosis were revealed and the PRPS laid the foundation for personalized therapy in LGG.

Identification and validation of a novel anoikis-related prognostic model for prostate cancer

BACKGROUND

Anoikis resistance is a hallmark characteristic of oncogenic transformation, which is crucial for tumor progression and metastasis. The aim of this study was to identify and validate a novel anoikis-related prognostic model for prostate cancer (PCa).

METHODS

We collected a gene expression profile, single nucleotide polymorphism mutation and copy number variation (CNV) data of 495 PCa patients from the TCGA database and 140 PCa samples from the MSKCC dataset. We extracted 434 anoikis-related genes and unsupervised consensus cluster analysis was used to identify molecular subtypes. The immune infiltration, molecular function, and genome alteration of subtypes were evaluated. A risk signature was developed using Cox regression analysis and validated with the MSKCC dataset. We also identify potential drugs for high-risk group patients.

RESULTS

Two subtypes were identified. C1 exhibited a higher level of CNV amplification, immune score, stromal score, aneuploidy score, homologous recombination deficiency, intratumor heterogeneity, single-nucleotide variant neoantigens, and tumor mutational burden compared to C2. C2 showed a better survival outcome and had a high level of gamma delta T cell and activated B cell infiltration. The risk signature consisting of four genes (HELLS, ZWINT, ABCC5, and TPSB2) was developed (area under the curve = 0.780) and was found to be an independent prognostic factor for overall survival in PCa patients. Four CTRP-derived and four PRISM-derived compounds were identified for high-risk patients.

CONCLUSIONS

The anoikis-related prognostic model developed in this study could be a useful tool for clinical decision-making. This study may provide a new perspective for the treatment of anoikis-related PCa.

The m6A methyltransferase METTL5 promotes neutrophil extracellular trap network release to regulate hepatocellular carcinoma progression

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide, it has a poor prognosis due to its highly invasive and metastatic nature. Consequently, identifying effective prognostic markers and potential therapeutic targets has been extensively investigated. METTL5, an 18S rRNA methyltransferase, is abnormally high in HCC. But its biological function and prognostic significance in HCC remain largely unelucidated. This study aimed to investigate the role of METTL5 in HCC progression, and elucidate its possible molecular mechanisms in HCC via transcriptome sequencing, providing new insights for identifying new HCC prognostic markers and therapeutic targets.

METHODS

The METTL5 expression in HCC and paracancerous tissues was analyzed using HCC immunohistochemical microarrays and bioinformatic retrieval methods to correlate METTL5 with clinicopathological features and survival prognosis. We constructed a METTL5 knockdown hepatocellular carcinoma cell line model and an animal model to determine the effect of METTL5 on hepatocellular carcinoma progression. Subsequently, RNA sequencing was performed to analyze the molecular mechanism of METTL5 in HCC based on the sequencing results, and relevant experiments were performed to verify it.

RESULTS

We found that METTL5 expression was elevated in hepatocellular carcinoma tissues and correlated with poor patient prognosis, and in the analysis of clinicopathological features showed a correlation with TNM staging. In hepatocellular carcinoma cell lines with knockdown of METTL5, the malignant biological behavior was significantly reduced both in vitro and in vivo. Based on the sequencing results as well as the results of GO functional enrichment analysis and KEGG pathway enrichment analysis, we found that METTL5 could promote the generation and release of neutrophil extracellular capture network (NETs) and might further accelerate the progression of HCC.

CONCLUSION

The m6A methyltransferase METTL5 is overexpressed in hepatocellular carcinoma (HCC) and correlates with poor prognosis. METTL5 accelerates malignant progression of HCC by promoting generation and release of the neutrophil extracellular traps (NETs) network, providing new insights for clinical biomarkers and immunotherapeutic targets in HCC prognosis.

Proposal of a nutrition screening algorithm for patients with incurable cancer receiving palliative care: Data from a prospective cohort

OBJECTIVE

To propose and evaluate the clinical utility of a new nutrition screening algorithm, NutriPal, to detect the degree of nutritional risk in patients with incurable cancer receiving palliative care.

METHODS

It is a prospective cohort conducted in an oncology palliative care unit. The NutriPal algorithm was used in a three-step process: (i) administration of the Patient-Generated Subjective Global Assessment short form; (ii) calculation of the Glasgow Prognostic Score; and (iii) application of the algorithm to classify patients into four degrees of nutritional risk. The higher the degrees of NutriPal, the worse the nutritional risk, comparing nutritional measures, laboratory data, and overall survival (OS).

RESULTS

The study included 451 patients that were classified using the NutriPal. They were allocated to the degrees: 1 (31.26%), 2 (27.49%), 3 (21.73%), and 4 (19.71%). Statistically significant differences were found in most of the nutritional and laboratory parameters and in OS with each increment in the NutriPal degrees, and OS was reduced (log-rank <0.001). In addition, NutriPal was able to predict a 120-day mortality: there was a significantly higher risk of death in the patients classified as degrees 4 (hazard ratio [HR], 3.03; 95% confidence interval [95% CI], 2.18-4.19), 3 (HR, 2.01; 95% CI, 1.46-2.78), and 2 (HR, 1.42; 95% CI; 1.04-1.95) than in those classified as degree 1. It also showed good predictive accuracy (concordance statistic, 0.76).

CONCLUSION

The NutriPal is associated to nutritional and laboratory parameters and can predict survival. It could therefore be incorporated into clinical practice for patients with incurable cancer receiving palliative care.

A pyroptosis-related lncRNA-based prognostic index for hepatocellular carcinoma by relative expression orderings

Background

Hepatocellular carcinoma (HCC) is an invasive malignant tumor, and pyroptosis makes an important contribution to the pathology and progression of liver cancer. Many prognostic models have been proposed for HCC based on the quantitative expression level of candidate genes, which are unsuitable for clinical application due to their vulnerability against experimental batch effects. The aim of this study was to develop a novel pyroptosis-related long non-coding RNA (lncRNA)-based prognostic index (PLPI) for HCC based on relative expression orderings (REOs).

Methods

Firstly, the pyroptosis-related lncRNAs were identified through the Wilcoxon rank-sum test and gene co-expression analyses. Then, the novel prognostic model PLPI was constructed by pyroptosis-related lncRNA pairs, which were identified by multiple machine learning algorithms. Gene set enrichment, somatic mutation, and drug sensitivity analyses were conducted to measure the differences between high- and low-risk patients. Multiple immune analyses were used to explore the association between PLPI and the immunological microenvironment.

Results

In this study, a novel prognostic model PLPI based on 10 pyroptosis-related lncRNA pairs was constructed, which was proven to be an independent prognostic risk factor. The receiver operating characteristic (ROC) curves showed that the model had a good prognostic ability in the training, testing, and external set, respectively [5-year area under the curve (AUC) =0.73, 5-year AUC =0.81, 4-year AUC =0.79]. The results of survival, somatic mutation, and immune analyses showed that the patients in the low-risk group had a better prognosis, lower rates of somatic mutation, and better immune cell infiltration. Personalized chemotherapeutic drugs were also identified for the patients with HCC.

Conclusions

The novel PLPI not only greatly predicted the prognosis of patients with HCC but could also offer novel ideas and approaches for the therapeutic management of HCC.

A novel risk signature based on liquid-liquid phase separation-related genes reveals prognostic and tumour microenvironmental features in clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma(ccRCC) is one of the most common malignancies. However, there are still many barriers to its underlying causes, early diagnostic techniques and therapeutic approaches.

MATERIALS AND METHODS

The Cancer Genome Atlas (TCGA)- Kidney renal clear cell (KIRC) cohort differentially analysed liquid-liquid phase separation (LLPS)-related genes from the DrLLPS website. Univariate and multivariate Cox regression analyses and LASSO regression analyses were used to construct prognostic models. The E-MTAB-1980 cohort was used for external validation. Then, potential functions, immune infiltration analysis, and mutational landscapes were analysed for the high-risk and low-risk groups. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) experiments as well as single-cell analyses validated the genes key to the model.

RESULTS

We screened 174 LLPS-related genes in ccRCC and constructed a risk signature consisting of five genes (CLIC5, MXD3, NUF2, PABPC1L, PLK1). The high-risk group was found to be associated with worse prognosis in different subgroups. A nomogram constructed by combining age and tumour stage had a strong predictive power for the prognosis of ccRCC patients. In addition, there were differences in pathway enrichment, immune cell infiltration, and mutational landscapes between the two groups. The results of qRT-PCR in renal cancer cell lines and renal cancer tissues were consistent with the biosignature prediction. Three single-cell data of GSE159115, GSE139555, and GSE121636 were analysed for differences in the presence of these five genes in different cells.

CONCLUSIONS

We developed a risk signature constructed based on the five LLPS-related genes and can have a high ability to predict the prognosis of ccRCC patients, further providing a strong support for clinical decision-making.

Prognostic factors of chronic postsurgical pain following gastrointestinal surgery: A systematic review protocol

BACKGROUND

Chronic postsurgical pain (CPSP) presents a considerable healthcare challenge, impacting patients, and healthcare providers, particularly in the context of gastrointestinal surgery. The notable incidence of CPSP in this specific surgical domain emphasizes the need to identify patients with a high risk of developing this condition. Despite various studies exploring this topic, a comprehensive systematic review focusing on prognostic factors of CPSP following gastrointestinal surgery is currently lacking. Therefore, the aim of this systematic review is, through systematically examination of existing literature, to assess both established and potentially novel prognostic factors, associated with CPSP following gastrointestinal surgery.

METHODS

Adhering to the Cochrane Handbook and the Preferred Reporting Items for Systematic review and Meta-Analysis Protocols (PRISMA-P) checklist, we will use pre-established criteria based on Population, Intervention, Comparator, Outcome, Timing, and Setting (PICOT-S), to determine eligibility for inclusion. Essentially, this entails studies reporting on prognostic factors of CPSP following gastrointestinal surgery. Relevant studies will be identified through systematic searches in medical databases, examination of reference lists from included studies, and screening of Clinicaltrials.gov. No restrictions will be imposed regarding language, publication time or source, and both randomized trials and observational studies will be included. Data extraction will follow the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of prognostic factor studies (CHARMS-PF) and for quality assessment, we will use the Quality in Prognosis Studies (QUIPS) tool.

RESULTS

The aim for the systematic review is to identify and assess the prognostic value of potential factors for the development of CPSP following gastrointestinal surgery.

CONCLUSION

By creating a comprehensive overview of important prognostic factors for the development of CPSP following gastrointestinal surgery, the findings of this systematic review have the potential to guide future research and to enhance patient information resources.

Constructing lactylation-related genes prognostic model to effectively predict the disease-free survival and treatment responsiveness in prostate cancer based on machine learning

Background: Prostate cancer (PCa) is one of the most common malignancies in men with a poor prognosis. It is therefore of great clinical importance to find reliable prognostic indicators for PCa. Many studies have revealed the pivotal role of protein lactylation in tumor development and progression. This research aims to analyze the effect of lactylation-related genes on PCa prognosis. Methods: By downloading mRNA-Seq data of TCGA PCa, we obtained the differential genes related to lactylation in PCa. Five machine learning algorithms were used to screen for lactylation-related key genes for PCa, then the five overlapping key genes were used to construct a survival prognostic model by lasso cox regression analysis. Furthermore, the relationships between the model and related pathways, tumor mutation and immune cell subpopulations, and drug sensitivity were explored. Moreover, two risk groups were established according to the risk score calculated by the five lactylation-related genes (LRGs). Subsequently, a nomogram scoring system was established to predict disease-free survival (DFS) of patients by combining clinicopathological features and lactylation-related risk scores. In addition, the mRNA expression levels of five genes were verified in PCa cell lines by qPCR. Results: We identified 5 key LRGs (ALDOA, DDX39A, H2AX, KIF2C, RACGAP1) and constructed the LRGs prognostic model. The AUC values for 1 -, 3 -, and 5-year DFS in the TCGA dataset were 0.762, 0.745, and 0.709, respectively. The risk score was found a better predictor of DFS than traditional clinicopathological features in PCa. A nomogram that combined the risk score with clinical variables accurately predicted the outcome of the patients. The PCa patients in the high-risk group have a higher proportion of regulatory T cells and M2 macrophage, a higher tumor mutation burden, and a worse prognosis than those in the low-risk group. The high-risk group had a lower IC50 for certain chemotherapeutic drugs, such as Docetaxel, and Paclitaxel than the low-risk group. Furthermore, five key LRGs were found to be highly expressed in castration-resistant PCa cells. Conclusion: The lactylation-related genes prognostic model can effectively predict the DFS and therapeutic responses in patients with PCa.

Comparing the Perspectives of Generative AI, Mental Health Experts, and the General Public on Schizophrenia Recovery: Case Vignette Study

Background

The current paradigm in mental health care focuses on clinical recovery and symptom remission. This model's efficacy is influenced by therapist trust in patient recovery potential and the depth of the therapeutic relationship. Schizophrenia is a chronic illness with severe symptoms where the possibility of recovery is a matter of debate. As artificial intelligence (AI) becomes integrated into the health care field, it is important to examine its ability to assess recovery potential in major psychiatric disorders such as schizophrenia.

Objective

This study aimed to evaluate the ability of large language models (LLMs) in comparison to mental health professionals to assess the prognosis of schizophrenia with and without professional treatment and the long-term positive and negative outcomes.

Methods

Vignettes were inputted into LLMs interfaces and assessed 10 times by 4 AI platforms: ChatGPT-3.5, ChatGPT-4, Google Bard, and Claude. A total of 80 evaluations were collected and benchmarked against existing norms to analyze what mental health professionals (general practitioners, psychiatrists, clinical psychologists, and mental health nurses) and the general public think about schizophrenia prognosis with and without professional treatment and the positive and negative long-term outcomes of schizophrenia interventions.

Results

For the prognosis of schizophrenia with professional treatment, ChatGPT-3.5 was notably pessimistic, whereas ChatGPT-4, Claude, and Bard aligned with professional views but differed from the general public. All LLMs believed untreated schizophrenia would remain static or worsen without professional treatment. For long-term outcomes, ChatGPT-4 and Claude predicted more negative outcomes than Bard and ChatGPT-3.5. For positive outcomes, ChatGPT-3.5 and Claude were more pessimistic than Bard and ChatGPT-4.

Conclusions

The finding that 3 out of the 4 LLMs aligned closely with the predictions of mental health professionals when considering the "with treatment" condition is a demonstration of the potential of this technology in providing professional clinical prognosis. The pessimistic assessment of ChatGPT-3.5 is a disturbing finding since it may reduce the motivation of patients to start or persist with treatment for schizophrenia. Overall, although LLMs hold promise in augmenting health care, their application necessitates rigorous validation and a harmonious blend with human expertise.

PEC-PRO: A new prognostic score from a series of 87 patients with localized perivascular epithelioid cell neoplasms (PEComas) treated with curative intent

BACKGROUND

Perivascular epithelioid cell neoplasms (PEComas) encompass a heterogeneous family of mesenchymal tumors. Previously described clinicopathologic features aimed at distinguishing benign from malignant variants but lacked prognostic value.

METHODS

This retrospective analysis examined clinicopathologic data from patients who had localized PEComa across French Sarcoma Network centers. The authors analyzed 12 clinicopathologic features in a Cox proportional hazard framework to derive a multivariate prognostic risk model for event-free survival (EFS). They built the PEComa prognostic score (PEC-PRO), in which scores ranged from 0 to 5, based on the coefficients of the multivariate model. Three groups were identified: low risk (score = 0), intermediate risk (score = 1), and high risk (score ≥ 2).

RESULTS

Analyzing 87 patients who had a median 46-month follow-up (interquartile range, 20-74 months), the median EFS was 96.5 months (95% confidence interval [CI], 47.1 months to not applicable), with 2-year and 5-year EFS rates of 64.7% and 58%, respectively. The median overall survival was unreached, with 2-year and 5-year overall survival rates of 82.3% and 69.3%, respectively. The simplified Folpe classification did not correlate with EFS. Multivariate analysis identified three factors affecting EFS: positive surgical margins (hazard ratio [HR], 5.17; 95% CI, 1.65-16.24; p = .008), necrosis (HR, 3.94; 95% CI, 1.16-13.43; p = .030), and male sex (HR, 3.13; 95% CI, 1.19-8.27; p = 0.023). Four variables were retained in the prognostic model. Patients with low-risk PEC-PRO scores had a 2-year EFS rate of 93.7% (95% CI, 83.8%-100.0%), those with intermediate-risk PEC-PRO scores had a 2-year EFS rate of 67.4% (95% CI, 53.9%-80.9%), and those with high-risk PEC-PRO scores had a 2-year EFS rate of 2.3% (95% CI, 0.0%-18.3%).

CONCLUSIONS

The PEC-PRO score reliably predicts the risk of postoperative recurrence in patients with localized PEComa. It has the potential to improve follow-up strategies but requires validation in a prospective trial.

Identification of hub genes within the CCL18 signaling pathway in hepatocellular carcinoma through bioinformatics analysis

Introduction

Hepatocellular carcinoma (HCC) is an aggressive malignancy, and CCL18, a marker of M2 macrophage activation, is often associated with tumor immune suppression. However, the role of CCL18 and its signaling pathway in HCC is still limited. Our study focuses on investigating the prognostic impact of CCL18 and its signaling pathway in HCC patients and biological functions in vitro.

Methods

HCC-related RNA-seq data were obtained from TCGA, ICGC, and GEO. The 6 hub genes with the highest correlation to prognosis were identified using univariate Cox and LASSO regression analysis. Multivariate Cox regression analysis was performed to assess their independent prognostic potential and a nomogram was constructed. In vitro experiments, including CCK8, EdU, RT-qPCR, western blot, and transwell assays, were conducted to investigate the biological effects of exogenous CCL18 and 6 hub genes. A core network of highly expressed proteins in the high-risk group of tumors was constructed. Immune cell infiltration was evaluated using the ESTIMATE and CIBERSORT packages. Finally, potential treatments were explored using the OncoPredict package and CAMP database.

Results

We identified 6 survival-related genes (BMI1, CCR3, CDC25C, CFL1, LDHA, RAC1) within the CCL18 signaling pathway in HCC patients. A nomogram was constructed using the TCGA_LIHC cohort to predict patient survival probability. Exogenous CCL18, as well as overexpression of BMI1, CCR3, CDC25C, CFL1, LDHA, and RAC1, can promote proliferation, migration, invasion, stemness, and increased expression of PD-L1 protein in LM3 and MHCC-97H cell lines. In the high-risk group of patients from the TCGA_LIHC cohort, immune suppression was observed, with a strong correlation to 21 immune-related genes and suppressive immune cells.

Conclusion

Exogenous CCL18 promotes LM3 and MHCC-97H cells proliferation, migration, invasion, stemness, and immune evasion. The high expression of BMI1, CCR3, CDC25C, CFL1, LDHA, and RAC1 can serve as a biomarkers for immune evasion in HCC.

Single-cell RNA combined with bulk RNA analysis to explore oxidative stress and energy metabolism factors and found a new prostate cancer oncogene MXRA8

BACKGROUND

Prostate cancer is the most common malignancy among men worldwide, and its diagnosis and treatment are challenging due to its heterogeneity.

METHODS

Integrating single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data, we identified two molecular subtypes of prostate cancer based on dysregulated genes involved in oxidative stress and energy metabolism. We constructed a risk score model (OMR) using common differentially expressed genes, which effectively evaluated prostate cancer prognosis.

RESULTS

Our analysis demonstrated a significant correlation between the risk score model and various factors, including tumor immune microenvironment, genomic variations, chemotherapy resistance, and immune response. Notably, patients with low-risk scores exhibited increased sensitivity to chemotherapy and immunotherapy compared to those with high-risk scores, indicating the model's potential to predict patient response to treatment. Additionally, our investigation of MXRA8 in prostate cancer showed significant upregulation of this gene in the disease as confirmed by PCR and immunohistochemistry. Functional assays including CCK-8, transwell, plate cloning, and ROS generation assay demonstrated that depletion of MXRA8 reduced the proliferative, invasive, migratory capabilities of PC-3 cells, as well as their ROS generation capacity.

CONCLUSIONS

Our study highlights the potential of oxidative stress and energy metabolism-related genes as prognostic markers and therapeutic targets in prostate cancer. The integration of scRNA-seq and bulk RNA-seq data enables a better understanding of prostate cancer heterogeneity and promotes personalized treatment development. Additionally, we identified a novel oncogene MXRA8 in prostate cancer.

Predictive and prognostic molecular biomarkers in lymphomas

Recent advances in molecular diagnostics have markedly expanded our understanding of the genetic underpinnings of lymphomas and catalysed a transformation in not just how we classify lymphomas, but also how we treat, target, and monitor affected patients. Reflecting these advances, the World Health Organization Classification, International Consensus Classification, and National Comprehensive Cancer Network guidelines were recently updated to better integrate these molecular insights into clinical practice. We summarise here the molecular biomarkers of lymphomas with an emphasis on biomarkers that have well-supported prognostic and predictive utility, as well as emerging biomarkers that show promise for clinical practice. These biomarkers include: (1) diagnostic entity-defining genetic abnormalities [e.g., B-cell acute lymphoblastic leukaemia (B-ALL) with KMT2A rearrangement]; (2) molecular alterations that guide patients' prognoses (e.g., TP53 loss frequently conferring worse prognosis); (3) mutations that serve as the targets of, and often a source of acquired resistance to, small molecular inhibitors (e.g., ABL1 tyrosine kinase inhibitors for B-ALL BCR::ABL1, hindered by ABL1 kinase domain resistance mutations); (4) the growing incorporation of molecular measurable residual disease (MRD) in the management of lymphoma patients (e.g., molecular complete response and sequencing MRD-negative criteria in multiple myeloma). Altogether, our review spans the spectrum of lymphoma types, from the genetically defined subclasses of precursor B-cell lymphomas to the highly heterogeneous categories of small and large cell mature B-cell lymphomas, Hodgkin lymphomas, plasma cell neoplasms, and T/NK-cell lymphomas, and provides an expansive summary of our current understanding of their molecular pathology.

Epigenetic alterations in urothelial bladder cancer associated with disease outcomes

OBJECTIVES

Bladder cancer (BLCA) is a molecular heterogeneous disease with known genetic distinctive signatures. However, DNA methylation is highly prevalent across a wide range of tumors, suggesting its potential in oncogenesis. Here, we aimed to interrogate the role of nine epigenetic alterations as diagnostic and prognostic markers in BLCA.

METHODS

DNA methylation, gene expression, and clinicopathological information were retrieved from The Cancer Genome Atlas data portal. Methylation values and gene expression were assessed to determine their association with normal and malignant tissue. Additionally, we studied the association between methylation values and clinicopathological variables. For the prognostic model, Kaplan-Meier Survival curves were generated. Lastly, univariate and multivariate analysis were performed to evaluate the simultaneous impact of methylation and clinicopathological variables on the risk of tumor progression and survival.

RESULTS

Nine CpG sites' methylation β -values involved in our study demonstrated different methylation signatures between normal and malignant urothelium. Hypermethylated CpGs were overrepresented in tumor tissue (p < 0.0001). Opposingly, 4 CpG sites showed lower methylation values in tumor samples (p < 0.0001). Cg12743248high and cg17192862low are risk factors for progression-free survival, whereas cg12374721high (HR:3.003 (1.283-7.030)) also demonstrated to be the most valuable independent risk factor for disease progression and a risk factor for overall survival.

CONCLUSIONS

We have identified that methylated cg12374721 shows promise as a diagnostic and independent prognostic marker in BLCA progression.

Predictive and prognostic biomarkers in gastrointestinal tract tumours

Tumours of the gastrointestinal tract represent nearly a quarter of all newly diagnosed tumours diagnosed in 2019. Various treatment modalities for gastrointestinal cancers exist, some of which may be guided by biomarkers. Biomarkers act as gauges of either normal or pathogenic processes or responses to an exposure or intervention. They come in many forms. This review explores established and potential molecular/immunohistochemical (IHC) predictive and prognostic biomarkers of the gastrointestinal tract.

In-hospital Prognostic Value of TAPSE/sPAP in Patients Hospitalized for Acute Heart Failure

AIMS

TAPSE/sPAP (tricuspid annular plane systolic excursion over systolic pulmonary artery pressure) assessed by echocardiography appears to be a good noninvasive approach for right ventricular to pulmonary artery coupling assessment. We aimed to assess the in-hospital prognostic value of TAPSE/sPAP among patients hospitalized for acute heart failure (AHF).

METHODS AND RESULTS

333 consecutive patients (mean age 68 ± 14 years, 70% of male, mean LVEF 44 ± 16%) hospitalized for AHF across 39 French cardiology department, with TAPSE/sPAP measured by echocardiography within the 24 first hours of hospitalization were included in this prospective study. The primary outcome was in-hospital major adverse cardiovascular events (MACEs) defined as all-cause death, resuscitated cardiac arrest or cardiogenic shock and occurred in 50 (15%) patients. Using receiver operating characteristics curves analysis, the best TAPSE/sPAP threshold for in-hospital MACEs was 0.40 mm/mmHg. TAPSE/sPAP <0.40 mm/mmHg was independently associated with in-hospital MACEs, even after adjustment with comorbidities (OR:3.75, 95%CI[1.87-7.93], p < 0.001), clinical severity (OR:2.80, 95%CI[1.36-5.95], p = 0.006). Using a 1:1 propensity-matched population, TAPSE/sPAP ratio <0.40 was associated with a higher rate of in-hospital MACEs (OR:2.98, 95%CI[1.53-6.12], p = 0.002). After adjustment, TAPSE/sPAP <0.40 showed the best improvement in model discrimination and reclassification above traditional prognostic factors (C-statistic improvement: 0.05; Chi-2 improvement: 14.4; LR-test p < 0.001). These results were consistent in an external validation cohort of 133 patients.

CONCLUSION

TAPSE/sPAP < 0.40 mm/mmHg assessed by an early echocardiography during an AHF episode is independently associated with in-hospital MACEs suggesting enhanced close monitoring and strengthened HF-specific care in these patients.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT05063097.

Risk factors and prognosis of sentinel lymph node metastasis in breast-conserving breast cancer: A retrospective study based on the SEER database

At present, the risk factors and prognosis of sentinel lymph node metastasis (SLNM) are analyzed based on the study of axillary lymph node metastasis, but whether there is a difference between the two is unclear. Therefore, an accurate and appropriate predictive model needs to be proposed to evaluate patients undergoing sentinel lymph node biopsy (SLNB) for breast cancer. We selected 16983 women with breast cancer from the Surveillance Epidemiology and End Results (SEER) database. They were randomly assigned to two cohorts, one for development (n = 11891) and one for validation (n = 5092). multi-factor logistics regression was used to distinguish risk factors affecting SLNM. The potential prognostic factors were identified using the COX regression analysis. The hazard ratio (HR) and 95% confidence interval (95%CI) were calculated for all results. Multiple Cox models are included in the nomogram, with a critical P value of .05. In order to evaluate the model's performance, Concordance index and receiver operating characteristic curves were used. Six independent risk factors affecting SLNM were screened out from the Logistic regression, including tumor location, number of regional lymph nodes (2-5), ER positive, PR positive, tumor size (T2-3), and histological grade (Grade II-III) are independent risk factors for SLNM in patients (P < .05). Eight prognostic factors were screened out in the multivariate COX regression analysis (P < .05): Age: Age 60 to 79 years, Age ≥ 80 years; Race; Histological grading: Grade II, Grade III; No radiotherapy; Tumor size: T2, T3; ER positive:, sentinel lymph node positive, married. Histological grade, tumor location, T stage, ER status, PR status and the number of SLNB are significantly correlated with axillary SLNM. Age, ethnicity, histological grade, radiotherapy, tumor size, ER status, SLN status, and marital status were independent risk factors for Breast cancer specific survival (BCSS). Moreover, the survival rate of patients with 3 positive SLNs was not significantly different from that with one or two positive SLNs, We concluded that patients with stage N1 breast cancer were exempt from axillary lymph node dissection, which is worthy of further study.

Age is just a number: can proteomic analysis provide insight into the aging body?

Recent proteomic studies have increased our understanding of the molecular process of aging, potentially enabling age-related diseases to be treated before the appearance of symptoms. [Formula: see text].

Surgical resection for hepatocellular carcinoma: a single-centre's one decade of experience

Background and aims

Liver cancer is the third leading cause of global cancer deaths, and hepatocellular carcinoma is its most common type. Liver resection is one of the treatment options for hepatocellular carcinoma (HCC). This study aims to explore our hospital's more than a decade of experience in liver resection for HCC patients.

Methods

This is a retrospective cohort study on HCC patients undergoing resection from 2010 to 2021 in a tertiary-level hospital in Jakarta, Indonesia. Mortality rates were explored as the primary outcome of this study. Statistical analysis was done on possible predictive factors using Pearson's χ2. Survival analysis was done using the Log-Rank test and Cox Regression.

Results

Ninety-one patients were included in this study. The authors found that the postoperative mortality rates were 8.8% (in hospital), 11.5% (30 days), and 24.1% (90 days). Excluding postoperative mortalities, the long-term mortality rates were 44.4% (first year), 58.7% (3 years), and 69.7% (5 years). Cumulatively, the mortality rates were 46.4% (1 year), 68.9% (3 years), 77.8% (5 years), and 67.0% (all time). Significant predictive factors for cumulative 1-year mortality include large tumour diameter [odds ratio (OR) 14.06; 95% CI: 2.59-76.35; comparing <3 cm and >10 cm tumours; P<0.01], positive resection margin (OR 2.86; 1.17-77.0; P=0.02), and tumour differentiation (P=0.01). Multivariate analysis found hazard ratios of 6.35 (2.13-18.93; P<0.01) and 1.81 (1.04-3.14; P=0.04) for tumour diameter and resection margin, respectively.

Conclusion

The mortality rate of HCC patients undergoing resection is still very high. Significant predictive factors for mortality found in this study benefit from earlier diagnosis and treatment; thus, highlighting the importance of HCC surveillance programs.

Construction of an oxidative stress-associated genes signature in breast cancer by machine learning algorithms

OBJECTIVE

To construct a prognostic model of a breast cancer-related oxidative stress-related gene (OSRG) signature using machine learning algorithms.

METHODS

The OSRGs of breast cancer were constructed by least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis. The Cancer Genome Atlas (TCGA) was used to analyse the gene expression and prognostic value. The Human Protein Atlas was used to analyse the protein expression of hub genes. Receiver operating characteristic analysis, calibration curve and decision curve analysis were used to predict the stability of this model.

RESULTS

The area under the curve of 1-, 3- and 5-year overall survival were 0.751, 0.707 and 0.645 in the TCGA training dataset; and 0.692, 0.678 and 0.602 in the TCGA testing dataset, respectively. Calibration plot showed good agreement between predicted probabilities and observed outcomes. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) pathway analysis indicated that multiple cancer-related pathways were highly enriched in the high-risk group. Immune infiltration analysis showed immune cells and their functions may play a key role in the development and mechanism of breast cancer.

CONCLUSIONS

This new OSRG signature was associated with the immune infiltration and it might be useful in predicting the prognosis in patients with breast cancer.

The prognostic value of preoperative D-dimer to albumin ratio for overall survival and progression-free survival in colorectal cancer

Introduction: This study aimed to explore the predictive value of the D-dimer-to-albumin ratio (DAR) for progression-free survival (PFS) and overall survival (OS) in patients with colorectal cancer (CRC). Methods: The Kaplan-Meier method was used to plot survival curves for PFS and OS. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive efficacy of the DAR for PFS and OS in patients with CRC. Cox proportional hazards regression analysis was used to analyze prognostic factors influencing outcomes. A nomogram based on the DAR was constructed to predict 1-, 3-, and 5-year prognoses of patients with CRC; its predictive ability was evaluated using the concordance index (C-index) and calibration curves. Additionally, the clinical utility of the DAR-based nomogram was validated using an internal randomized validation cohort. Results: A total of 1,339 patients with CRC who underwent surgery were enrolled. The optimal cut-off value for DAR was determined to be 3.320, dividing patients into low (<3.320 [n = 470]) and high (≥3.320 [n = 869]) DAR groups. Compared with other composite immune inflammatory markers, DAR exhibited superior prognostic predictive efficacy. Patients with a high DAR had a significantly worse prognosis than those with a low DAR (PFS, 50.9% versus [vs.] 69.4%, p < 0.001; OS, 52.9% vs. 73.8%, p < 0.001). DAR also demonstrated significant prognostic stratification for most tumor subgroups, particularly in the stage III-IV subgroup and normal carcinoembryonic antigen subgroup. DAR has been identified as an independent predictive indicator of PFS/OS in patients with CRC. For every standard deviation increase in DAR, the risk for PFS/OS in patients with CRC was reduced by 9.5% (hazard ratio [HR] 1.095 [95% confidence interval (CI) 1.013-1.185]; p = 0.022) and 9.3% (HR 1.093 [95% CI 1.012-1.180]; p = 0.024), respectively. The DAR-based nomogram was confirmed to demonstrate good prognostic prediction accuracy and achieved high evaluation in the internal validation cohort. Conclusion: Preoperative DAR is a promising biomarker for predicting PFS and OS among patients with CRC. The DAR-based prognostic prediction nomogram may serve as an effective tool for the comprehensive assessment of prognosis in patients with CRC.

Effect of CHRDL1 on angiogenesis and metastasis of colorectal cancer cells via TGF-β/VEGF pathway

Colorectal cancer (CRC) is a common digestive tract tumor with the third incidence and death in the world. There is still an urgent need for effective therapeutic targets and prognostic markers for CRC. Herein, we report a novel potential target and marker, Chordin like-1 (CHRDL1). The function of CHRDL1 has been reported in gastric cancer, breast cancer, and oral squamous cell carcinoma. However, the biological effect of CHRDL1 in CRC remains unrevealed. Transwell and tube formation experiments were used to determine the biological function of CHRDL1. Western blot and rescue experiments were used to determine the specific mechanisms of CHRDL1. Results showed CHRDL1 is significantly downregulated in CRC cell lines and tissues. In vitro, experiments confirmed that CHRDL1 can inhibit cell growth, migration, invasion, angiogenesis and reverse epithelial-mesenchymal transformation. In vivo, experiments proved that it can inhibit tumor growth and metastasis. Mechanistically, we newly find that CHRDL1 exerts biological functions through the transforming growth factor-beta (TGF-β)/vascular endothelial growth factor signaling axis in vitro and in vivo. Therefore, we concluded that CHRDL1 reduces the growth, migration, and angiogenesis of CRC cells by downregulating TGF-β signaling. Our new findings on CHRDL1 may provide a basis for clinical antiangiogenesis therapy and the prognosis of CRC.

Current progress and prospects for G protein-coupled estrogen receptor in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a biologically and clinically heterogeneous disease. The G protein-coupled estrogen receptor (GPER) plays a crucial role in mediating the effect of estrogen and estrogen-like compounds in TNBC cells. Compared with other subtypes, GPER has a higher expression in TNBC. The GPER mechanisms have been thoroughly characterized and analyzed in estrogen receptor α (ERα) positive breast cancer, but not in TNBC. Our previous work revealed that a higher expression of GPER mRNA indicates a better prognosis for ERα-positive breast cancer; however, its effects in TNBC differ. Whether GPER could serve as a predictive prognostic marker or therapeutic target for TNBC remains unclear. In this review, we provide a detailed introduction to the subcellular localization of GPER, the different effects of various ligands, and the interactions between GPER and closely associated factors in TNBC. We focused on the internal molecular mechanisms specific to TNBC and thoroughly explored the role of GPER in promoting tumor development. We also discussed the interaction of GPER with specific cytokines and chemokines, and the relationship between GPER and immune evasion. Additionally, we discussed the feasibility of using GPER as a therapeutic target in the context of existing studies. This comprehensive review highlights the effects of GPER on TNBC, providing a framework and directions for future research.

Better chance of survival is associated with higher neutrophil CD16 expression in patients with complicated intra-abdominal infections

Aim

The ability of neutrophil CD16 (nCD16) expression to predict outcome in complicated intra-abdominal infections (cIAIs) has not yet been studied; therefore we aimed to evaluate its potential prognostic value in such patients.

Methods

Between November 2018 and August 2021 a single-center prospective study was performed in the Department of Surgical Diseases at a University Hospital Stara Zagora. A flow cytometry was used to measure the levels of nCD16 before surgery and on the 3rd postoperative day (POD) in 62 patients with cIAIs.

Results

We observed a mortality rate of 14.5% during hospitalization. Survivors had significantly higher perioperative expression of nCD16 than non-survivors (P = 0.02 preoperatively and P = 0.006 postoperatively). As predictor of favorable outcome we found a good predictive performance of preoperative nCD16 (AUROC = 0.745) and a very good predictive performance of postoperative levels (AUROC = 0.846). An optimal preoperative threshold nCD16 = 34.75 MFI permitted prediction of survival with sensitivity and specificity of 66.7% and 77.8%, respectively. A better sensitivity of 72.5% and specificity of 85.7% were observed for threshold = 54.8 MFI on the 3rd POD.

Conclusion

Perioperative neutrophil CD16 expression shows a great potential as a predictor of favorable outcome in patients with cIAIs.

Predictive Model for Prognosis of Sudden Sensorineural Hearing Loss by Nomogram

Objective: To explore the prognostic factors of patients with sudden sensorineural hearing loss (SSNHL), analyze the possible influencing factors, and construct a nomogram for personalized evaluation of their prognosis. Methods: A retrospective study was conducted on 269 patients with SSNHL. The prognostic factors were analyzed by univariate analysis and multivariate logistic regression analysis. The nomogram was constructed based on the results of multivariate logistic regression analysis, and the model was verified by receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results: Among the 269 patients hospitalized, 136 cases were improved (44 cases were cured, 28 cases were markedly effective, 64 cases were effective) and 133 cases were ineffective. After univariate analysis, it was found that age, duration from onset to treatment, audiometric configuration, serum albumin (ALB), and neutrophil-to-lymphocyte ratio (NLR) were associated with hearing outcomes. Duration from onset to treatment and audiometric configuration were independent risk factors when the treatment outcome was divided into ineffective, effective, significant improvement, and complete recovery groups or divided into improvement and ineffective groups after multivariate logistic regression analysis. The factors according to univariate analysis and multivariate logistic regression analysis results were included in the nomogram to construct the prediction models. The area under the ROC curve of model discrimination was 0.752 [95% confidence interval (CI): 0.695-0.808] when the treatment outcome was divided into 2 groups. The calibration curve showed the consistency of the results, and the DCA prediction curve showed good clinical efficacy. The C-index was 0.756 (95% CI: 0.710-0.802) when the treatment outcome was divided into 4 groups. Conclusion: Age, duration from onset to treatment, audiometric configuration, ALB, and NLR are influencing factors for SSNHL. Duration from onset to treatment and audiometric configuration are independent risk factors for SSNHL. The nomogram presents the prognosis of patients with SSNHL in an intuitive, visual, and readable graph, providing clinicians with a personalized assessment.

Prevalence and prognostic implications of myocardial injury across different waves of COVID-19

Introduction

The prognostic ability of myocardial injury across different waves of the COVID-19 pandemic is not well established. The purpose of this study was to evaluate the prevalence and prognostic implications of myocardial injury in the first and sixth wave of COVID-19.

Methods

We conducted a retrospective observational study that included patients admitted to the emergency department with COVID-19 with data on concentrations of cardiac troponin during the first and sixth wave. We compared the prevalence of myocardial injury and its predictive capacity for 30-day all-cause death in both waves.

Results and discussion

A total of 346 patients were included (1st wave 199 and 6th wave 147 patients). The prevalence of myocardial injury was 21% with non-significant differences between waves. Myocardial injury was associated, in both waves, with a higher prevalence of comorbidities and with an increased risk of 30-day all-cause death [1st wave HR: 3.73 (1.84-7.55); p < 0.001 and 6th wave HR: 3.13 (1.23-7.92); p = 0.016], with non-significant differences in predictive capacity between groups after ROC curve analysis [AUC: 1st wave 0.829 (95% CI: 0.764-0.895) and 6th wave 0.794 (95% CI: 0.711-0.876)]. As limitations, this is a retrospective study with a relatively small simple size and troponin assay was performed at the discretion of the emergency physician so selection bias could be present. In conclusion, the prevalence of myocardial injury and its prognostic capacity was similar in both waves despite vaccination programs. Myocardial injury predicts short-term mortality in all COVID-19 patients, so they should be treated intensively.

Establishment of skin cutaneous melanoma prognosis model based on vascular mimicry risk score

Studies have indicated that Vascular mimicry (VM) could contribute to the unfavorable prognosis of skin cutaneous melanoma (SKCM). Thus, the objective of this study was to identify therapeutic targets associated with VM in SKCM and develop a novel prognostic model. Gene expression data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) were utilized to identify differentially expressed genes (DEGs). By intersecting these DEGs with VM genes, we acquired VM-related DEGs specific to SKCM, and then identified prognostic-related VM genes. A VM risk score system was established based on these prognosis-associated VM genes, and patients were then categorized into high- and low-score groups using the median score. Subsequently, differences in clinical characteristics, gene set enrichment analysis (GSEA), and other analyses were further presented between the 2 groups of patients. Finally, a novel prognostic model for SKCM was established using the VM score and clinical characteristics. 26 VM-related DEGs were identified in SKCM, among the identified DEGs associated with VM in SKCM, 5 genes were found to be prognostic-related. The VM risk score system, comprised of these genes, is an independent prognostic risk factor. There were significant differences between the 2 patient groups in terms of age, pathological stage, and T stage. VM risk scores are associated with epithelial biological processes, angiogenesis, regulation of the SKCM immune microenvironment, and sensitivity to targeted drugs. The novel prognostic model demonstrates excellent predictive ability. Our study identified VM-related prognostic markers and therapeutic targets for SKCM, providing novel insights for clinical diagnosis and treatment.

rural: colorectal cancer survival and prognostic disparities from 2000 to 2019

This study aimed to analyze the differences in colorectal cancer (CRC) survival between urban and rural areas over the past 20 years, as well as investigate potential prognostic factors for CRC survival in both populations. Using registry data from Surveillance, Epidemiology, and End Results (SEER) from 2000 to 2019, 463,827 CRC cases were identified, with 85.8% in urban and 14.2% in rural areas. The mortality of CRC surpassed its survival rate by the sixth year after diagnosis in urban areas and the fifth year in rural areas. Furthermore, the 5-year overall survival (OS) of CRC increased by 2.9-4.3 percentage points in urban and 0.6-1.5 percentage points in rural areas over the past two decades. Multivariable Cox regression models identified independent prognostic factors for OS and disease-specific survival (DSS) of CRC in urban and rural areas, including age over 40, Black ethnicity, and tumor size greater than 5 cm. In addition, household income below $75,000 was found to be an independent prognostic factor for OS and DSS of CRC in urban areas, while income below $55,000 was a significant factor for rural areas. In conclusion, this study found a notable difference in CRC survival between rural and urban areas. Independent prognostic factors shared among both rural and urban areas include age, tumor size, and race, while household income seem to be area-specific predictive variables. Collaboration between healthcare providers, patients, and communities to improve awareness and early detection of CRC may help to further advance survival rates.

An Accelerated Failure Time Model to Predict Cause-Specific Survival and Prognostic Factors of Lung and Bronchus Cancer Patients with at Least Bone or Brain Metastases: Development and Internal Validation Using a SEER-Based Study

BACKGROUND

This study addresses the significant challenge of low survival rates in patients with cause-specific lung cancer accompanied by bone or brain metastases. Recognizing the critical need for an effective predictive model, the research aims to establish survival prediction models using both parametric and non-parametric approaches.

METHODS

Clinical data from lung cancer patients with at least one bone or brain metastasis between 2000 and 2020 from the SEER database were utilized. Four models were constructed: Cox proportional hazard, Weibull accelerated failure time (AFT), log-normal AFT, and Zografos-Balakrishnan log-normal (ZBLN). Independent prognostic factors for cause-specific survival were identified, and model fit was evaluated using Akaike's and Bayesian information criteria. Internal validation assessed predictive accuracy and discriminability through the Harriel Concordance Index (C-index) and calibration plots.

RESULTS

A total of 20,412 patients were included, with 14,290 (70%) as the training cohort and 6122 (30%) validation. Independent prognostic factors selected for the study were age, race, sex, primary tumor site, disease grade, total malignant tumor in situ, metastases, treatment modality, and histology. Among the accelerated failure time (AFT) models considered, the ZBLN distribution exhibited the most robust model fit for the 3- and 5-year survival, as evidenced by the lowest values of Akaike's information criterion of 6322 and 79,396, and the Bayesian information criterion of 63,495 and 79,396, respectively. This outperformed other AFT and Cox models (AIC = [156,891, 211,125]; BIC = [158,848, 211,287]). Regarding predictive accuracy, the ZBLN AFT model achieved the highest concordance C-index (0.682, 0.667), a better performance than the Cox model (0.669, 0.643). The calibration curves of the ZBLN AFT model demonstrated a high degree of concordance between actual and predicted values. All variables considered in this study demonstrated significance at the 0.05 level for the ZBLN AFT model. However, differences emerged in the significant variations in survival times between subgroups. The study revealed that patients with only bone metastases have a higher chance of survival compared to only brain and those with bone and brain metastases.

CONCLUSIONS

The study highlights the underutilized but accurate nature of the accelerated failure time model in predicting lung cancer survival and identifying prognostic factors. These findings have implications for individualized clinical decisions, indicating the potential for screening and professional care of lung cancer patients with at least one bone or brain metastasis in the future.

Prognostic Value of Immunoscore in Colorectal Carcinomas

Aims. Immunoscore, based on the evaluation of CD3+ and CD8+ densities in the center of the tumor and its invasive margin, is currently considered as a potential prognostic factor, particularly in colorectal carcinomas. In the current study, we aimed to assess the prognostic value of immunoscore in colorectal cancer stage I to IV, through a survival study. Methods and Results. It was a descriptive and retrospective study involving 104 cases of colorectal cancer. Data were collected over 3 years (2014-2016). An immunohistochemical study (anti-CD3, anti-CD8) by the tissue microarray technique was carried out in the areas of "hot spot" in the tumor center and invasive margin. A percentage was assigned to each marker and within each region. Then, the density was classified as "low" or "high," according to a cutoff fixed at the median of percentages. immunoscore was calculated by the method described by Galon et al. The prognostic value of the immunoscore was assessed through a survival study. The mean age of patients was 61.6 years. immunoscore was low in 60.6% (n = 63). Our study had shown that low immunoscore significantly deteriorates survival and a high immunoscore enhances survival significantly (P < .001). We found a correlation between immunoscore and T stage (P = .026). A multivariate showed that the predictive factors for survival were immunoscore (P = .001) and age (P = .035). Conclusions. Our study highlights the potential role of immunoscore as a prognostic factor in colorectal cancer. Its reproducibility and reliability allow its introduction into daily practice for better therapeutic management.

Risk Factors Associated With Poor Outcomes After Quadriceps Tendon Repair

Background

Ruptures of the quadriceps tendon present most frequently in older adults and individuals with underlying medical conditions.

Purpose

To examine the relationship between patient-specific factors and tear characteristics with outcomes after quadriceps tendon repair.

Study Design

Case-control study; Level of evidence, 3.

Methods

A retrospective review was conducted on all patients who underwent quadriceps tendon repair between January 1, 2016, and January 1, 2021, at a single institution. Patients <18 years and those with chronic quadriceps tendon tears (>6 weeks to surgery) were excluded. Information was collected regarding patient characteristics, presenting symptoms, tear characteristics, physical examination findings, and postoperative outcomes. Poor outcome was defined as a need for revision surgery, complications, postoperative range of motion of (ROM) <110° of knee flexion, and extensor lag of >5°.

Results

A total of 191 patients met the inclusion criteria. Patients were aged 58.5 ± 13.2 years at the time of surgery, were predominantly men (90.6%), and had a mean body mass index (BMI) of 32.2 ± 6.3 kg/m2. Patients underwent repair with either suture anchors (15.2%) or transosseous tunnels (84.8%). Postoperatively, 18.5% of patients experienced knee flexion ROM of <110°, 11.3% experienced extensor lag of >5°, 8.5% had complications, and 3.2% underwent revision. Increasing age (odds ratio [OR], 1.03 [95% CI, 1.004-1.07]) and female sex (OR, 3.82 [95% CI, 1.25-11.28]) were significantly associated with postoperative knee flexion of <110°, and increasing age (OR, 1.08 [95% CI, 1.04-1.14]) and greater BMI (OR, 1.14 [95% CI, 1.05-1.23]) were significantly associated with postoperative extensor lag of >5°. Current smoking status (OR, 15.44 [95% CI, 3.97-65.90]) and concomitant retinacular tears (OR, 9.62 (95% CI, 1.67-184.14]) were associated with postoperative complications, and increasing age (OR, 1.05 [95% CI, 1.02-1.08]) and greater BMI (OR, 1.08 [95% CI, 1.02-1.14]) were associated with risk of acquiring any poor outcome criteria.

Conclusion

Patient-specific characteristics-such as increasing age, greater BMI, female sex, retinacular involvement, and current smoking status-were found to be risk factors for poor outcomes after quadriceps tendon repair. Further studies are needed to identify potentially modifiable risk factors that can be used to set patient expectations and improve outcomes.

Identification and validation of prognostic genes and immune landscape signatures based on a fatty acid oxidation‑related risk score model in glioma

Fatty acid oxidation (FAO) plays a crucial role in glioma metabolism and its interaction with the immune microenvironment. The aim of the present study was to investigate the relationship between FAO-related genes and glioma by constructing gene clusters using a glioma cohort. A total of 287 differentially expressed genes related to FAO were identified and the top 50 genes were selected based on their P-values. Subsequently, patients were classified into two distinct gene subtypes (A and B) based on these genes. Scores for each patient were calculated using the 50 genes and the patients were divided into the high and low-score groups accordingly. Patients in subtype B exhibited higher tumor grades and poor prognostic factors such as older age and worse survival rates. The high-score subgroup had unfavorable indicators, including isocitrate dehydrogenase 1 wild-type, high tumor grade and 1p19q non-codeleted, while immune checkpoint expression was generally higher in the high-score subgroup. The constructed scoring model was validated using an external dataset, and the tissue inhibitor of metalloproteinase 1 gene was identified through protein interaction analysis, suggesting its potential involvement in glioma malignancy and promotion of glioblastoma proliferation. In conclusion, FAO-related genes may contribute to tumor development through immune mechanisms and the present study may provide novel insights for potential therapeutic strategies in glioma treatment.

Evaluation of Circulating Tumor DNA as a Liquid Biomarker in Uveal Melanoma

Purpose

Uveal melanoma (UM) has a high propensity to metastasize. Prognosis is associated with specific driver mutations and copy number variations (CNVs), but limited primary tumor tissue is available for molecular characterization due to eye-sparing irradiation treatment. This study aimed to assess the rise in circulating tumor DNA (ctDNA) levels in UM and evaluate its efficacy for CNV-profiling of patients with UM.

Methods

In a pilot study, we assessed ctDNA levels in the blood of patients with UM (n = 18) at various time points, including the time of diagnosis (n = 13), during fractionated stereotactic radiotherapy (fSRT) treatment (n = 6), and upon detection of metastatic disease (n = 13). Shallow whole-genome sequencing (sWGS) combined with in silico size-selection was used to identify prognostically relevant CNVs in patients with UM (n = 26) from peripheral blood retrieved at the time of diagnosis (n = 9), during fSRT (n = 5), during post-treatment follow-up (n = 4), metastasis detection (n = 6), and metastasis follow-up (n = 4).

Results

A total of 34 patients had blood analyzed for ctDNA detection (n = 18) and/or CNV analysis (n = 26) at various time points. At the time of diagnosis, 5 of 13 patients (38%) had detectable ctDNA (median = 0 copies/mL). Upon detection of metastatic disease, ctDNA was detected in 10 of 13 patients (77%) and showed increased ctDNA levels (median = 24 copies/mL, P < 0.01). Among the six patients analyzed during fSRT, three (50%) patients had detectable ctDNA at baseline and three of six (50%) patients had undetectable levels of ctDNA. During the fSRT regimen, ctDNA levels remained unchanged (P > 0.05). The ctDNA fractions were undetectable to low in localized disease, and sWGS did not elucidate chromosome 3 status from blood samples. However, in 7 of 10 (70%) patients with metastases, the detection of chromosome 3 loss corresponded to the high metastatic-risk class.

Conclusions

The rise in ctDNA levels observed in patients with UM harboring metastases suggests its potential utility for CNV profiling. These findings highlight the potential of using ctDNA for metastasis detection and patient inclusion in therapeutic studies targeting metastatic UM.

The Clinical Significance and the Potential Regulatory Mechanism of the LncRNA OIP5-AS1 in Paediatric Severe Community-Acquired Pneumonia Blood Through the MiR-150-5p/PDCD4 Axis

BACKGROUND

This study aimed to elucidate the clinical significance and regulatory mechanism of the long non-coding RNA OIP5-AS1 in severe community-acquired pneumonia (SCAP) among paediatric patients.

METHODS

qRT-PCR was used to assess the mRNA levels of OIP5-AS1. ROC curve analysis was used to assess the diagnostic significance of OIP5-AS1. Short-term prognostic significance was evaluated through Kaplan-Meier survival. An in vitro cell model was developed using LPS-induced MRC-5 cells. CCK-8, flow cytometry, and ELISA were conducted to measure cell viability, apoptosis, and inflammatory factor levels. The association between miR-150-5p and PDCD4 was confirmed through DLR assays.

RESULTS

Elevated OIP5-AS1 were observed in paediatric patients with SCAP, which enabled effective differentiation from healthy individuals. High expression of OIP5-AS1 correlated with reduced survival rates. OIP5-AS1 knockdown attenuated cell viability suppression and the promotion of apoptosis and inflammatory factors induced by LPS. However, this attenuation was reversed by reduced levels of miR-150-5p. miR-150-5p was identified as a target of PDCD4 and OIP5-AS1.

CONCLUSION

Increased OIP5-AS1 levels show potential as a valuable diagnostic and prognostic biomarker for paediatric patients with SCAP. This study illustrates its role in regulating cell viability, apoptosis, and the inflammatory response via the miR-150-5p/PDCD4 axis, acting as a ceRNA.

MRPS23 is a novel prognostic biomarker and promotes glioma progression

Mitochondrial ribosomal protein S23 (MRPS23), a component of the ribosome small subunit, has been reported to be overexpressed in various cancers and has been predicted to be involved in increased cell proliferation. It has been confirmed that MRPS23 was involved in the regulation of breast cancer and hepatocellular carcinoma cell proliferation. However, little is known about the function of MRPS23 in glioma. In this study, we found that MRPS23 expression was higher in gliomas than in adjacent normal tissues. Higher expression of MRPS23 in gliomas correlated with poorer prognosis, unfavorable histological features, absence of mutations in the isocitrate dehydrogenase gene (IDH), absence of chromosome 1p and 19q deletions, and responses to chemoradiotherapy. Univariate and multivariate Cox analysis demonstrated MRPS23 expression was independently prognostic of overall survival, disease-free survival, and progression-free survival in patients with glioma. KEGG enrichment analysis results indicated that high MRPS23 expression was associated with cell proliferation and immune response-related signaling pathways. We also confirmed that MRPS23 was highly expressed in glioma cells lines, and MRPS23 knockdown significantly reduced cell survival, proliferation, and migration of glioma cells lines. Collectively, these findings offer mechanistic insights into how MRPS23 during glioma progression, and identify MRPS23 as a potential therapeutic target in the future.

Association of cuproptosis-related signature with the prognosis of patients with head and neck squamous cell carcinoma

Patients with head and neck squamous cell carcinoma (HNSCC) have a poor prognosis because of their high recurrence and metastasis rates. Cuproptosis is a novel type of copper-dependent cell death that differs from apoptosis, necroptosis, and cytosolic scorch death. We designed and validated an individualized cuproptosis-related gene (CRG) signature for risk evaluation and prognostic prediction in HNSCC patients. Ninety differentially expressed CRGs were found in HNSCC. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analyses were performed to investigate the functional involvement of CRGs in the Cancer Genome Atlas (TCGA) HNSCC cohort. A CRG signature was created using 10 genes after univariate and multivariate analysis. Kaplan Meier (KM) analysis showed that the survival rate of the high-risk group was significantly lower than that of the low-risk group. Multivariate regression analysis identified risk scores based on prognostic characteristics as independent prognostic indicators of HNSCC. Moreover, risk models are related to tumor mutational burden (TMB), tumor-infiltrating immune cells (TICs), immune checkpoints, clinical characteristics, and antitumor drug susceptibility. Furthermore, we found that CuCl2 treatment promoted cuproptosis in HNSCC cells, and that the expression levels of cuproptosis-related genes were altered by different doses of CuCl2. In summary, understanding the detailed molecular mechanisms of cuproptosis and its impact on overall survival (OS), and identifying potential therapeutic targets for HNSCC will provide potential insights for treatment.Communicated by Ramaswamy H. Sarma.

Immature Sacrococcygeal Teratoma: A Case Report and Extensive Review of the Literature

Immature sacrococcygeal teratoma represents a histological form with rapid tumor growth, a risk of premature birth, an enhanced rate of complications, an increased risk of recurrence, and a higher mortality rate than the mature type. Thus, prenatal diagnosis of immature forms would significantly improve the prognosis of these cases. To this end, we performed an extensive literature review on the diagnosis, therapeutic management, and follow-up of immature teratomas. Regarding this medical conduct, we also presented our case. In conclusion, the early identification of immature sacrococcygeal teratomas with or without other associated structural abnormalities and their correct therapeutic approach are basic principles for a favorable evolution of these cases.

Blood eosinophils and fractional exhaled nitric oxide are prognostic and predictive biomarkers in childhood asthma

BACKGROUND

Blood eosinophils and fractional exhaled nitric oxide (Feno) are prognostic biomarkers for exacerbations and predict lung function responses to dupilumab in adolescents and adults with asthma.

OBJECTIVE

We evaluated the relationship between baseline blood eosinophils and Feno and response to dupilumab in children with asthma.

METHODS

Children aged 6 to 11 years with uncontrolled moderate-to-severe asthma (n = 408) were randomized to receive dupilumab 100/200 mg by body weight or volume-matched placebo every 2 weeks for 52 weeks. Annualized exacerbation rate (AER) reduction and least squares mean change in prebronchodilator percent predicted forced expiratory volume in 1 second (ppFEV1) at week 12 were assessed according to cutoff baseline levels for Feno (<20 ppb vs ≥20 ppb) and blood eosinophil count (<150, ≥150 to <300, ≥300 to <500, and ≥500 cells/μL). Quadrant analyses in populations defined by biomarker thresholds and spline models across continuous end points assessed the relationship with Feno and eosinophil count. Interaction testing evaluated the independent roles of Feno and blood eosinophils as predictive markers.

RESULTS

Exacerbation risk and magnitude of AER reduction increased in subgroups with higher baseline biomarker levels. Quadrant analyses revealed that disease of patients with either elevated Feno or eosinophil counts demonstrated a clinical response to dupilumab. Interaction testing indicated blood eosinophil counts or Feno independently added value as predictive biomarkers.

CONCLUSIONS

In children with uncontrolled moderate-to-severe asthma, blood eosinophil counts and Feno are clinically relevant biomarkers to identify those at risk for asthma exacerbations, as well as those with disease with clinical response to dupilumab.

TRIAL REGISTRATION

Liberty Asthma VOYAGE ClinicalTrials.gov NCT02948959.

Incorporating Novel Technologies in Precision Oncology for Colorectal Cancer: Advancing Personalized Medicine

Colorectal cancer (CRC) is one of the most heterogeneous and deadly diseases, with a global incidence of 1.5 million cases per year. Genomics has revolutionized the clinical management of CRC by enabling comprehensive molecular profiling of cancer. However, a deeper understanding of the molecular factors is needed to identify new prognostic and predictive markers that can assist in designing more effective therapeutic regimens for the improved management of CRC. Recent breakthroughs in single-cell analysis have identified new cell subtypes that play a critical role in tumor progression and could serve as potential therapeutic targets. Spatial analysis of the transcriptome and proteome holds the key to unlocking pathogenic cellular interactions, while liquid biopsy profiling of molecular variables from serum holds great potential for monitoring therapy resistance. Furthermore, gene expression signatures from various pathways have emerged as promising prognostic indicators in colorectal cancer and have the potential to enhance the development of equitable medicine. The advancement of these technologies for identifying new markers, particularly in the domain of predictive and personalized medicine, has the potential to improve the management of patients with CRC. Further investigations utilizing similar methods could uncover molecular subtypes specific to emerging therapies, potentially strengthening the development of personalized medicine for CRC patients.

Cuproptosis-Related lncRNAs Modulate the Prognosis of MIBC by Regulating the Expression Pattern of Immunosuppressive Molecules Within the Tumor Microenvironment

Background

Cuproptosis-related gene and long non-coding RNA (lncRNA) modulation of cancer regulation is well-established. This investigation aimed to elucidate the prognostic implications of cuproptosis-associated lncRNAs in muscle-invasive bladder cancer (MIBC).

Methods

Employing the Cancer Genome Atlas (TCGA) and IMvigor210 cohorts, bioinformatics and statistical analyses probed the prognostic relevance of cuproptosis-related lncRNAs.

Results

Co-expression analysis revealed tight associations between lncRNA expression and cuproptosis-linked genes, with 13 cuproptosis-related lncRNAs found to correlate with MIBC prognosis. Lasso regression identified a six-lncRNA prognostic signature, enabling patient stratification into high- and low-risk categories. Tissue validation substantiated differential expression of FAM13A-AS1, GHRLOS, LINC00456, OPA1-AS1, RAP2C-AS1, and UBE2Q1-AS1 between MIBC tumor and normal tissues. Comparative analyses of tumor microenvironments and immune profiles between risk groups disclosed elevated immunosuppressive molecule expression, including programmed cell death-1 (PD-L1) and T-cell immunoglobulin-3 (TIM-3), in high-risk individuals.

Conclusion

These findings suggest that cuproptosis-related lncRNAs may modulate the expression of immunosuppressive molecules, thereby influencing MIBC tumorigenesis and progression. Further exploration is warranted to unveil novel therapeutic targets for MIBC based on the expression patterns of cuproptosis-related lncRNAs and their impact on immune responses in the tumor microenvironment.