The current standard treatment for locally advanced squamous cell carcinoma of the head and neck (LASCCHN) comprises concurrent radiotherapy (CRT) alongside platinum-based chemotherapy. However, ...innovative therapeutic alternatives are being evaluated in phase II/III randomized trials. This study employed a Bayesian network meta-analysis (NMA) using fixed effects to provide both direct and indirect comparisons of all existing treatment modalities for unresectable LASCCHN.
We referenced randomized controlled trials (RCTs) from January 2000 to July 2023 by extensively reviewing PubMed, EMBASE, and Web of Science databases, adhering to the Cochrane methodology. Relevant data, including summary estimates of overall survival (OS) and progression-free survival (PFS), were extracted from these selected studies and recorded in a predefined database sheet. Subsequently, we conducted a random effects network meta-analysis using a Bayesian framework.
Based on the Surface Under the Cumulative Ranking (SUCRA) values, the league table organizes the various treatments for OS in the following order: IC + RT&MTT, MTT-CRT, IC + CRT&MTT, CRT, IC + CRT, MTT-RT, IC + MTT-RT, and RT. In a similar order, the treatments rank as follows according to the league table: IC + CRT&MTT, MTT-CRT, IC + CRT, IC + RT&MTT, CRT, IC + MTT-RT, MTT-RT, and RT. Notably, none of these treatments showed significant advantages over concurrent chemoradiotherapy.
Despite concurrent chemoradiotherapy being the prevailing treatment for LASCCHN, our findings suggest the potential for improved outcomes when concurrent chemoradiotherapy is combined with targeted therapy or induction chemotherapy.
is a recently discovered protein-coding gene. Here, pan-cancer analysis was conducted to determine the expression patterns of
and its impact on immune response, gene mutation, and possible molecular ...biological mechanisms in different tumors, together with investigating its potential usefulness for cancer prognosis.
Data on
expression and mutations were downloaded from TCGA and GTEx databases. Clinical survival data from TCGA were used to analyze the prognostic value of
. TIMER and ESTIMATE algorithms were used to assess correlations between
and tumor-infiltrating immune cells, immune cytokines, and immune scores.
BOLA2B was found to be highly expressed at both mRNA and protein levels in multiple tumors, where it was associated with worse overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in all cancers apart from ovarian cancer.
was also found to be positively correlated with copy number variation (CNV), and mutations in
, and
were found to influence
expression. Post-transcriptional modifications, including m5C, m1A, and m6A, were observed to regulate
expression in all cancers. Functional analysis showed that
was enriched in pathways associated with iron-sulfur cluster formation, mTOR-mediated autophagy, and cell cycle inhibition. Decreased
expression induced the proliferation of breast cancer cells and G2/M cell cycle arrest.
was found to be highly expressed in malignant tumors and could be used as a biomarker of poor prognosis in multiple cancers. Further investigation into
's role and molecular functions in cancer would provide new insights for cancer diagnosis and treatment.
Tumor residue after concurrent chemoradiotherapy (CCRT) in nasopharyngeal carcinoma (NPC) patients often predicts poor prognosis. Thus, the objective of this retrospective study is to develop a ...nomogram that combines magnetic resonance (MRI) radiomics features and clinical features to predict the early response of locally advanced nasopharyngeal carcinoma (LA-NPC).
A total of 91 patients with LA-NPC were included in this study. Patients were randomly divided into training and validation cohorts at a ratio of 3:1. Univariate and multivariate analyses were performed on the clinical parameters of the patients to select clinical features to build a clinical model. In the training cohort, the Least Absolute Shrinkage and Selection Operator (LASSO) regression model was used to select radiomics features for construction of a radiomics model. The logistic regression algorithm was then used to combine the clinical features with the radiomics features to construct the clinical radiomics nomogram. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were drawn to compare and verify the predictive performances of the clinical model, radiomics model, and clinical radiomics nomogram.
Platelet lymphocyte ratio (PLR) and nasopharyngeal tumor volume were identified as independent predictors of early response in patients with locally advanced nasopharyngeal carcinoma. A total of 5502 radiomics features were extracted, from which 25 radiomics features were selected to construct the radiomics model. The clinical radiomics nomogram demonstrated the highest AUC in both the training and validation cohorts (training cohort 0.975 vs 0.973 vs 0.713; validation cohort 0.968 vs 0.952 vs 0.706). The calibration curve and DCA indicated good predictive performance for the nomogram.
A clinical radiomics nomogram, which combines clinical features with radiomics features based on MRI, can predict early tumor regression in patients with LA-NPC. The performance of the nomogram is superior to that of either the clinical model or radiomics model alone. Therefore, it can be used to identify patients without CR at an early stage and provide guidance for personalized therapy.
Objective
Anlotinib is a multitarget anti-angiogenic drug that combined with temozolomide (TMZ) can effectively prolongs the overall survival (OS) of recurrent malignant glioma(rMG),but some patients ...do not respond to anlotinib combined with TMZ. These patients were associated with a worse prognosis and lack effective identification methods. Therefore, it is necessary to differentiate patients who may have good response to anlotinb in combination with TMZ from those who are not, in order to provide personalized targeted therapies.
Methods
Fifty three rMG patients (42 in training cohort and 11 in testing cohort) receiving anlotinib combined with TMZ were enrolled. A total of 3668 radiomics features were extracted from the recurrent MRI images. Radiomics features are reduced and filtered by hypothesis testing and Least Absolute Shrinkage And Selection (LASSO) regression. Eight machine learning models construct the radiomics model, and then screen out the optimal model. The performance of the model was assessed by its discrimination, calibration, and clinical usefulness with validation.
Results
Fifty three patients with rMG were enrolled in our study. Thirty four patients displayed effective treatment response, showed a higher survival benefits than non-response group, the median progression-free survival(PFS) was 8.53 months versus 5.33 months (
p
= 0.06) and the median OS was 19.9 months and 7.33 months (
p
= 0.029), respectively. Three radiomics features were incorporated into the model construction as final variables after LASSO regression analysis. In testing cohort, Logistic Regression (LR) model has the best performance with an Area Under the Curve (AUC) of 0.93 compared with other models, which can effectively predict the response of rMG patients to anlotinib in combination with TMZ. The calibration curve confirmed the agreement between the observed actual and prediction probability. Within the reasonable threshold probability range (0.38–0.88), the radiomics model shows good clinical utility.
Conclusions
The above-described radiomics model performed well, which can serve as a clinical tool for individualized prediction of the response to anlotinb combined with TMZ in rMG patients.
•This study analyzed IFI30 expression in breast cancer using multiple public database sources and methods.•IFI30 expression was elevated in breast cancer and correlated with tumor stage and ...prognosis.•IFI30 expression was associated with various immune-related pathways and T cell subsets in breast cancer.•IFI30 overexpression modulated PD-L1 expression and inhibitory efficacy in macrophages.•Targeting the IFI30-PD-L1 axis may be a novel strategy for breast cancer immunotherapy.
IFI30 is a lysosomal thiol reductase involved in antigen presentation and immune regulation in various cancers, including breast cancer. Despite its known involvement, the precise mechanism, function, and relationship with the PD-L1 axis and immune response remain unclear.
We conducted an extensive investigation into IFI30 mRNA expression in breast cancer utilizing data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Furthermore, we characterized IFI30 mRNA expression across various cell types using publicly available single-cell RNA sequencing datasets, and assessed protein expression through immunohistochemistry using an in-house breast cancer tissue microarray. Functional experiments were performed to elucidate the effects of IFI30 overexpression on PD-L1 expression and inhibitory efficacy in both macrophages and breast tumor cells.
Our study unveiled a marked upregulation of IFI30 expression in breast cancer tissues compared to their normal counterparts, with notable associations identified with tumor stage and prognosis. Additionally, IFI30 expression demonstrated significant correlations with various immune-related signaling pathways, encompassing peptide antigen binding, cytokine binding, and MHC class II presentation. Notably, breast cancer samples exhibiting high IFI30 expression in tumor cells displayed high PD-L1 expression on corresponding cells, alongside a diminished ratio of CD8 + T cell infiltration within the tumor microenvironment. Furthermore, ectopic knockdown of IFI30 in both tumor cells and macrophages resulted in a reduction of PD-L1 expression, while conversely, overexpression of IFI30 led to an increase in PD-L1 expression.
This study offers new insights into the involvement of IFI30 in breast cancer, elucidating its interplay with the PD-L1 axis and immune response dynamics. Our findings suggest that modulation of the IFI30-PD-L1 axis could serve as a promising strategy for regulating T cells infiltration in breast cancer thus treating breast cancer.
•Currently, nasopharyngeal carcinoma(NPC) stands as a significant cancer posing a threat to human health, with approximately three-quarters of cases being diagnosed at the locally advanced ...stage.•While multiple treatment options exist for locally advanced NPC, the determination of the most clinically beneficial and cost-effective approach remains unclear.•The objective of this study is to construct Network Meta-Analysis (NMA) and Cost-Effectiveness Analysis (CEA) models to assess which treatment strategy yields the maximum benefit.•Our research team specializes in clinical diagnosis, treatment, and efficacy prediction for NPC, with notable achievements in pharmacoeconomics.•Through this study, we aim to provide a therapeutic guidance for clinical practitioners by evaluating the comparative benefits of different treatment modalities. The ultimate goal is to contribute valuable insights for healthcare professionals in the field.
The aim of this study is to evaluate the efficacy and cost-effectiveness of various induction chemotherapy (IC) regimens as first-line treatment for Locoregionally advanced nasopharyngeal carcinoma (LA-NPC), aiming to provide clinicians and patients with informed insights to aid in treatment decision-making.
We conducted a network meta-analysis (NMA) and cost-effectiveness analysis (CEA) based on data from 10 clinical trials investigating IC regimens for the treatment of LA-NPC. A Bayesian NMA was performed, with the primary outcomes being hazard ratios (HRs) for disease-free survival (DFS) and overall survival (OS). To model the disease progression of LA-NPC, we developed a dynamic partitioned survival model consisting of three disease states: progression-free survival (PFS), progression disease (PD), and death. The model was run on a 3-week cycle for a research period of 10 years, with quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICERs) serving as outcome measures.
According to the surface under the cumulative ranking curve (SUCRA) estimates derived from the NMA, TPC and TP, as IC regimens, appear to exhibit superior efficacy compared to other treatment modalities. In terms of CEA, concurrent chemoradiotherapy (CCRT), TPF + CCRT, and GP + CCRT were found to be dominated (more costs and less QALYs). Comparatively, TPC + CCRT emerged as a cost-effective option with an ICER of $1260.57/QALY when compared to PF + CCRT. However, TP + CCRT demonstrated even greater cost-effectiveness than TPC + CCRT, with an associated increase in costs of $3300.83 and an increment of 0.1578 QALYs per patient compared to TPC + CCRT, resulting in an ICER of $20917.62/QALY.
Based on considerations of efficacy and cost-effectiveness, the TP + CCRT treatment regimen may emerge as the most favorable first-line therapeutic approach for patients with LA-NPC.
