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PubMed2026

Development and internal validation of a six-gene prognostic model based on galactose metabolism for overall survival in lung adenocarcinoma.

BACKGROUND: Lung cancer remains a leading cause of cancer incidence and mortality globally. Metabolic reprogramming promotes tumor progression and shapes an immunosuppressive tumor microenvironment. Galactose metabolism is involved in multiple malignancies, but its prognostic value in lung adenocarcinoma (LUAD) remains unclear. This study aimed to develop and internally validate a galactose metabolism-related multigene prognostic model for LUAD. METHODS: A retrospective prognostic model development and internal validation study was performed using RNA sequencing (RNA-seq) and clinical data from 585 LUAD patients in The Cancer Genome Atlas (TCGA). Differential expression, functional enrichment, univariate and multivariate Cox regression were applied to construct a prognostic gene signature. Internal validation was performed using bootstrap resampling. Model performance was evaluated by time-dependent receiver operating characteristic (ROC), C-index, calibration, and Kaplan-Meier analysis. Associations between the model and immune infiltration, immunotherapy responsiveness, and tumor stemness were also analyzed. RESULTS: A six-gene prognostic model (GALT, GANC, PGM1, GALM, B4GALT1, PGM2) was developed. The model showed good discrimination with 1-, 3-, and 5-year area under the curve (AUC) values of 0.719, 0.693, and 0.684, respectively. The low-risk group exhibited significantly longer survival, increased antitumor immune infiltration (CD8+ T cells, M1 macrophages, activated CD4+ memory T cells), higher expression of T cell proliferation-related genes, lower immune checkpoint expression, better predicted immunotherapy response, and lower tumor stemness compared with the high-risk group. CONCLUSIONS: We developed and internally validated a six-gene prognostic model for LUAD based on galactose metabolism. The model shows moderate prognostic performance and is associated with antitumor immunity and tumor stemness. It may be used for prognostic risk stratification and to guide personalized immunotherapy in LUAD.

Galactose metabolism↗

PubMed2026

Predictive biomarkers in cancer immunotherapy for genitourinary malignancies.

Immunotherapy has transformed the management of genitourinary cancers, offering durable responses in selected patient groups. However, the clinical benefit of immune checkpoint inhibitors varies significantly across renal cell carcinoma, urothelial carcinoma, and prostate cancer, underscoring the need for reliable predictive biomarkers. This review summarizes current knowledge on established and emerging biomarkers, including PD L1 expression, tumor mutational burden, molecular subtypes, genomic alterations, tumor microenvironment characteristics, circulating biomarkers, microbiome influences, and multi omic integrative approaches. We discuss their potential clinical relevance, limitations, and applicability across different tumor types. Future directions emphasize the development of composite biomarkers, standardization of testing platforms, real time monitoring strategies, and the integration of advanced technologies such as artificial intelligence and spatial profiling. Understanding and validating these biomarkers will be essential for optimizing personalized immunotherapy in genitourinary cancers.

Circulating tumor DNA↗

PubMed2025

Comprehensive proteomic and pathological profiling identifies PRAS40 as a novel biomarker and mediator of primary immune checkpoint blockade resistance in non-small cell lung cancer.

BACKGROUND: Immune checkpoint blockade (ICB) has revolutionized the treatment landscape of non-small cell lung cancer (NSCLC), yet primary resistance remains a significant clinical challenge. Recent evidence implicates PRAS40 (AKT1S1) in regulating cellular survival and immune responses, but its role in immunotherapy resistance is not fully understood. METHODS: Transcriptomic data from TCGA and GTEx cohorts were analyzed to assess PRAS40 expression. Prognostic value was evaluated using Cox regression. Immune microenvironment features were characterized with CIBERSORT and TIMER. Predictive efficacy for ICB response was examined using TIDE and IPS. Plasma PRAS40 levels in 66 NSCLC patients receiving ICB were quantified by proximity extension assay (PEA), and multiplex immunohistochemistry assessed associations among PRAS40, PD-L1, and CD8+ T cells in tumor tissues. RESULTS: High PRAS40 expression was associated with poor prognosis, reduced CD8+ T cell infiltration, and downregulation of immune checkpoint genes. Elevated circulating PRAS40 predicted primary ICB resistance and shorter progression-free survival, independent of PD-L1 or CD8+ T cell status. CONCLUSION: PRAS40 is strongly associated with primary ICB resistance in NSCLC and may serve as a novel predictive biomarker. These findings support its potential to guide personalized immunotherapy in lung cancer.

Humans↗

PubMed2026

Long-read sequencing reveals widespread novel splicing and neojunction-derived neoantigens in nasopharyngeal carcinoma.

The widespread transcriptomic diversity driven by alternative splicing (AS) contributes to all hallmarks of cancer and represents a critical source of neoantigens for personalized immunotherapy. However, unlike other major malignancies, the full repertoire of AS in nasopharyngeal carcinoma (NPC) remains underexplored. Here, we employ long-read sequencing (LR-seq) to generate a high-resolution, isoform-level transcriptomic atlas from a cohort of 14 NPC tumor samples and four immortalized nasopharyngeal epithelial cell lines. We identify a substantial number of full-length novel transcripts (22,687; ∼44.38%), which reveal diverse splicing patterns and previously unannotated splicing events. By integrating short-read RNA-seq data to quantify isoform expression, we discover a subset of novel transcripts that are differentially expressed between tumor samples and immortalized nasopharyngeal epithelial cell lines. Furthermore, LR-seq enables precise identification of chimeric readthrough fusion transcripts, such as CLDN15-FIS1 and FOXRED2-TXN2 Finally, we develop a computational framework, tumor-specific splicing neoantigen detection (TS-SNAD), to predict neoantigens originating from novel exon-exon junctions (neojunctions) in tumor-specific novel transcripts. Using this framework, we identify neojunction-derived neoantigens and experimentally validate the immunogenicity of selected HLA-B*40:01-restricted neoantigens. These neojunction-derived peptides constitute a new class of noncanonical neoantigens with significant potential for developing personalized cancer vaccines for NPC.

Humans↗

PubMed2026

Genetic insights into lung squamous cell carcinoma: how TP53 and CSMD3 co-mutations shape prognosis and immune response.

BACKGROUND: Lung squamous cell carcinoma (LUSC) accounts for a significant proportion of lung cancer cases and is often associated with smoking and various environmental factors. The prognostic and immunologic implications of TP53 and CSMD3 co-mutations in LUSC remain poorly understood. This study aimed to investigate the role of TP53/CSMD3 co-mutations in LUSC using comprehensive bioinformatics analyses. METHODS: Data from 487 LUSC patients were obtained from The Cancer Genome Atlas (TCGA) database, with external validation performed using the combined cohort. Patients were stratified into TP53/CSMD3 co-mutation, single-mutation, and wild-type (WT) groups. Prognostic analysis was conducted using Kaplan-Meier survival curves. Tumor mutational burden (TMB) was calculated, and immune cell infiltration was assessed using multiple algorithms. Differentially expressed genes (DEGs) between co-mutated and WT groups were identified, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. A nomogram incorporating mutation status, gender, age, and tumor stage (T stage) was developed for individualized prognostic prediction. RESULTS: The TP53/CSMD3 co-mutated group exhibited significantly better overall survival (OS) compared to single-mutation and WT groups. TMB scores were markedly higher in co-mutated patients, suggesting potential sensitivity to immune checkpoint inhibitors. Immune infiltration analysis revealed distinct profiles, including elevated CD8 T cells and reduced immunosuppressive components, in the co-mutation group. A total of 403 DEGs were identified between co-mutated and WT groups, with significant enrichment in immune-related pathways. Mechanistically, the co-mutation was associated with distinct downregulation of complement negative regulators (CFH/CFI), indicating complement hyperactivation independent of TMB. The constructed nomogram provided accurate individualized prognostic assessments. CONCLUSIONS: The co-mutation of TP53 and CSMD3 identifies a distinct LUSC subtype with favorable survival, marked by high TMB and an immune-activated microenvironment. Beyond TMB-driven neoantigen generation, the significant downregulation of complement negative regulators (CFH/CFI) reveals an independent complement hyperactivation pathway associated with CSMD3 loss. The constructed nomogram provides accurate individualized survival prediction. These findings establish TP53/CSMD3 co-mutation as a promising prognostic biomarker and offer mechanistic insights for personalized immunotherapy strategies. Future prospective cohorts are warranted to validate its predictive value.

Lung squamous cell carcinoma (LUSC)↗

PubMed2026

A Real-Time Image-Based Co-Culture Assay to Quantify Tumor-Infiltrating Lymphocyte-Mediated Apoptotic Killing of Patient-Derived Tumor Organoids.

Understanding the functional capacity of tumor-infiltrating lymphocytes (TILs) to recognize and eliminate autologous tumor cells is central to advancing personalized immunotherapy. The goal of this method is to provide an image-based, live-cell imaging protocol that measures TIL-mediated, caspase-3-dependent apoptotic killing against patient-derived tumor organoids (PDTOs) in real time. This method integrates established procedures for isolation and expansion of PDTOs and TILs with a standardized three-dimensional co-culture system and automated fluorescence-based apoptosis detection. Tumor organoids are plated in imaging-compatible 96-well plates and labeled with a red tumor marker, while expanded TILs are added at defined effector-to-target ratios in the presence of a caspase-3 activated green fluorescent substrate. Co-cultures are imaged every 4 h using a live-cell analysis system to capture phase-contrast and dual-fluorescence channels. Quantitative image analysis identifies red-positive tumor structures and calculates the proportion of red/green double-positive apoptotic tumor objects over time. Appropriate technical and biological replicates are incorporated, along with baseline, spontaneous apoptosis, negative and positive killing controls to ensure assay rigor. By preserving tumor heterogeneity within the PDTOs' three-dimensional architecture while enabling longitudinal quantification, this protocol provides a physiologically relevant system for functionally profiling patient-specific tumor-TIL interactions and investigating immunomodulatory agents that augment anti-tumor immunity.

Humans↗

PubMed2026

Construction of a new predictive model in head and neck squamous cell carcinoma based on the investigation of extracellular matrix-associated genes.

A key aspect influencing immune cell infiltration is the composition of the extracellular matrix (ECM). Therefore, investigating the association between ECM-associated proteins and immune cell infiltration is key for the identification of new biomarkers to distinguish 'immune-hot' solid tumors and predict patient prognosis. A total of 513 head and neck squamous cell carcinoma (HNSCC) cases as training samples from The Cancer Genome Atlas and an additional 270 as testing samples from the Gene Expression Omnibus were obtained for use in the present study. Using a single-sample Gene Set Enrichment Analysis method, the 513 training samples were divided into Cluster 1 and Cluster 2. Subsequently, the present analysis uncovered 1,573 differentially expressed genes distinguishing the two clusters. After performing an intersection analysis with 751 ECM-associated genes, 103 differentially expressed ECM-associated genes were identified. Least absolute shrinkage and selection operator-Cox and multivariate Cox regression analyses were employed to identify candidate ECM risk genes (P<0.05) and to construct a predictive model. Finally, a nomogram and a three gene (cerebellin 2, galectin-10 and cathepsin G) predictive model were developed. Therefore, the present prognostic risk score model can evaluate the immune infiltration, predict the prognosis of HNSCC, and potentially guide more personalized immunotherapy interventions.

extracellular matrix↗

PubMed2025

A Programmable Nanovaccine Platform Based on M13 Bacteriophage for Personalized Cancer Vaccine and Therapy.

Nanovaccines co-assemble antigens and adjuvants to elicit robust immune responses but often require complex synthesis and post-modification procedures. Here, a programmable nanovaccine platform based on the M13 bacteriophage is developed for the scalable production of vaccines and single-step modular engineering of adjuvanticity, length, and antigen density. By reprogramming the sequence and size of the noncoding phage genome, the Toll-like receptor 9 activation and the length of the phage are precisely controlled. With a novel molecular engineering approach, the antigen density is tuned from 13.6% to 70.3%. A systematic modulation reveals an optimal adjuvanticity at a constant antigen density for maximum anti-tumor CD8+ T cell response, and vice versa, using the model antigen SIINFEKL. The M13 phage-based nanovaccine induces durable memory immunity lasting over a year. In addition, a 24-fold increase in neoantigen-specific CD8+ T cell frequency is achieved when increasing both the adjuvanticity and antigen density. Furthermore, when combined with anti-PD-1 therapy, the M13 phage-based personalized vaccine eradicates established MC-38 tumors in 75% of treated animals and they develop 100% resistance against tumor invasion when challenged 5 months after treatment. These findings establish M13 phage as a powerful and versatile nanovaccine platform with transformative potential for personalized cancer immunotherapy.

Cancer Vaccines↗

PubMed2025

Epigenetic orchestration of cancer-immune dynamics: mechanisms, technologies, and clinical advancements.

BACKGROUND: Epigenetic dysregulation plays a pivotal role in cancer immune evasion by orchestrating tumour antigen silencing, immune cell dysfunction, and the formation of an immunosuppressive microenvironment. By disrupting successive phases of the cancer-immunity cycle-from antigen presentation to T cell exhaustion-these aberrations facilitate immune escape and tumour progression, highlighting the need for targeted epigenetic intervention. AIM OF REVIEW: This review systematically dissects how epigenetic alterations impair anti-tumour immunity at each stage of the CI cycle. It not only integrates fragmented mechanistic evidence but also emphasizes underexplored crosstalk between specific epigenetic regulators and immune cell types. It further highlights emerging technologies-such as single-cell epigenomics, spatial multi-omics, and CRISPR-based screens-that are driving discovery of novel therapeutic targets and refining patient stratification. Key scientific concepts of review. We discuss how epigenetic interventions, alone or in combination with immunotherapies, can reinvigorate immune responses and overcome resistance to current treatments. A particular focus is given to how integrative high-resolution platforms are mapping immunoepigenetic landscapes, enabling mechanism-informed, precision immunotherapy strategies. By bridging epigenetic regulation with translational immuno-oncology, this review outlines a future where epigenetic reprogramming becomes central to overcoming immune evasion in cancer.

Humans↗

PubMed2026

Therapeutic melanoma vaccines: Platforms, neoantigen strategies, and emerging combination immunotherapies.

Melanoma has emerged as a major focus of cancer immunotherapy research because of its highly immunogenic nature and responsiveness to immune-based treatments. Therapeutic melanoma vaccines are designed to stimulate tumor-specific immune responses through the delivery of Tumor-Associated Antigens (TAAs), Tumor-Specific Antigens (TSAs), and personalized neoantigens. This narrative review provides an overview of current melanoma vaccine strategies, including peptide-based vaccines, dendritic cell vaccines, nucleic acid-based platforms such as mRNA, DNA, and viral vector vaccines. Recent advances in vaccine engineering and tumor genomics have accelerated the development of personalized neoantigen vaccines capable of targeting mutations unique to individual tumors. In parallel, Artificial Intelligence (AI) and Machine Learning (ML) are increasingly being incorporated into neoantigen identification pipelines to improve epitope prediction and optimize vaccine design. Combination strategies involving Immune Checkpoint Inhibitors (ICIs), particularly anti-PD-1 and anti-CTLA-4 therapies, have further enhanced interest in melanoma vaccines by helping overcome tumor-induced immune suppression and augment T-cell activation. In addition to reviewing vaccine mechanisms and emerging technologies, this manuscript examines the evolving clinical trial landscape through analysis of melanoma vaccine studies registered on ClinicalTrials.gov. Although many studies have reported encouraging safety and immunogenicity findings, challenges related to tumor heterogeneity, immune evasion, biomarker selection, and manufacturing complexity continue to limit widespread clinical implementation. Ongoing advances in computational immunology, biomaterial engineering, and precision oncology are expected to further refine melanoma vaccine development and improve therapeutic efficacy. Collectively, these innovations may help establish melanoma vaccines as an increasingly important component of future personalized cancer immunotherapy strategies.

DNA vaccines↗

PubMed2026

Predictive Biomarkers for Immune Checkpoint Inhibitor Efficacy: Challenges, Innovations, and a Pathway to Precision Medicine in the Era of Cancer Immunotherapy.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have transformed oncology practice. However, treatment response remains heterogeneous, rendering predictive biomarkers critical for optimal patient care. The 3 established biomarkers, programmed death-ligand 1, tumor mutational burden (TMB), and microsatellite instability-high/deficient mismatch repair, are approved and clinically validated but are modest predictors of benefit. As a result, multiple novel predictive biomarkers remain under investigation. CONTENT: This review highlights established and investigational predictive ICI efficacy biomarkers. For established biomarkers, we describe biology, assay modalities, approved companion diagnostics, landmark studies, and notable limitations. Due to the multisystem nature of antitumor immune effects, investigational biomarkers span multiple domains, including tumor genomic biomarkers (e.g., mutational signatures, TMB, neoantigen clonality), tumor microenvironment (e.g., tumor-infiltrating lymphocytes [TILs], tertiary lymphoid structures), systemic immune biomarkers (e.g., cytokines, autoantibodies, glycoproteins, peripheral blood mononuclear cells), and the microbiome (e.g., gastrointestinal microbial diversity, responder-enriched taxa). SUMMARY: The established biomarkers PD-L1, TMB, and microsatellite instability-high/deficient mismatch repair inform ICI use in clinical practice but have important limitations. Multiple investigational biomarkers show promise in refining patient selection and optimizing therapy. Moving forward, increased assay harmonization, prospective validation, and standardized parameters may improve performance. Composite models integrating complementary signals across domains may further individualize treatment and lead to an era of personalized cancer immunotherapy.

Humans↗

PubMed2024

optiPRM: A Targeted Immunopeptidomics LC-MS Workflow With Ultra-High Sensitivity for the Detection of Mutation-Derived Tumor Neoepitopes From Limited Input Material.

Personalized cancer immunotherapies such as therapeutic vaccines and adoptive transfer of T cell receptor-transgenic T cells rely on the presentation of tumor-specific peptides by human leukocyte antigen class I molecules to cytotoxic T cells. Such neoepitopes can for example arise from somatic mutations and their identification is crucial for the rational design of new therapeutic interventions. Liquid chromatography mass spectrometry (LC-MS)-based immunopeptidomics is the only method to directly prove actual peptide presentation and we have developed a parameter optimization workflow to tune targeted assays for maximum detection sensitivity on a per peptide basis, termed optiPRM. Optimization of collision energy using optiPRM allows for the improved detection of low abundant peptides that are very hard to detect using standard parameters. Applying this to immunopeptidomics, we detected a neoepitope in a patient-derived xenograft from as little as 2.5 × 106 cells input. Application of the workflow on small patient tumor samples allowed for the detection of five mutation-derived neoepitopes in three patients. One neoepitope was confirmed to be recognized by patient T cells. In conclusion, optiPRM, a targeted MS workflow reaching ultra-high sensitivity by per peptide parameter optimization, makes the identification of actionable neoepitopes possible from sample sizes usually available in the clinic.

Humans↗

PubMed2026

Mass Spectrometry-Based Profiling of Personalized Immunopeptidomes in Thai Renal Cell Carcinoma.

This study profiles the personalized immunopeptidomes of 13 Thai patients with renal cell carcinoma (RCC), addressing a critical knowledge gap in Southeast Asian populations characterized by distinct HLA allele distributions. We combined whole-exome sequencing (WES)-based personalized proteome construction with liquid chromatography-tandem mass spectrometry (LC-MS/MS), using both database-driven searches and de novo peptide sequencing. HLA typing identified several class I allotypes that are underrepresented in publicly available immunopeptidome resources, including seven alleles not previously represented in the databases examined; HLA-A*11:01 was the most frequent allele in this cohort. Database-based analysis identified a single tumor-specific neoantigen derived from a mutant JADE2 peptide in the patient with the highest tumor mutational burden, which was validated by a mutant-specific ELISPOT response. In contrast, de novo sequencing revealed numerous noncanonical peptides, a subset of which were supported by proteogenomic validation using PepQuery and detected exclusively in cancer proteomes but not in normal tissue data sets, indicating their potential as tumor-associated antigen candidates. Together, these results establish an integrated and scalable framework for identifying HLA-presented tumor-derived peptides and provide a foundational immunopeptidome resource to support personalized cancer immunotherapy development in Southeast Asia.

Humans↗

PubMed2026

Splenic hilum nodal involvement in resected left-sided pancreatic cancer: meta-analysis.

BACKGROUND: Splenectomy is standard of care during left pancreatectomy for pancreatic ductal adenocarcinoma (PDAC) to obtain adequate lymphadenectomy. However, evidence supporting this approach is lacking. Splenic preservation would reduce short-term morbidity and is essential for emerging oncological adjunctive therapies, including immunotherapy and personalized cancer vaccines. This study reviewed the incidence of splenic hilum nodal involvement (SHNI) in left-sided PDAC. METHODS: A systematic review of the PubMed, Embase, and Cochrane databases was performed, identifying studies published from inception to July 2026. Outcomes of interest were the rate of SHNI (station 10), overall survival, and the rate of splenic artery nodal involvement (SANI; station 11). Meta-analyses were conducted using random-effects models. Subgroup analyses for SHNI were performed per tumour localization (pancreatic neck, body, tail). RESULTS: Among 2776 screened studies, 22 with 2260 patients undergoing left pancreatectomy for PDAC were included. The pooled prevalence of SHNI was 3.7% (95% confidence interval (c.i.) 2.2% to 6.2%); 1.1% for pancreatic body PDAC (95% c.i. 0.3% to 4.3%) and 9.7% for pancreatic tail PDAC (95% c.i. 3.5% to 24.0%). SHNI was not significantly associated with survival (pooled hazard ratio 2.05; 95% c.i. 0.89% to 4.72; P = 0.072). The pooled prevalence of SANI was 39.1% (95% c.i. 25.1% to 55.1%). CONCLUSION: In patients undergoing left pancreatectomy for PDAC, the presence of SHNI is rare, particularly in pancreatic body cancer (1.1%). These findings suggest that the relevance of routine splenectomy remains unclear, especially for pancreatic body PDAC. However, because the quality of current evidence is low, further investigation in prospective studies is required.

Humans↗

PubMed2026

Single-cell profiling reveals a novel CAF subpopulation linking stromal heterogeneity to immune suppression in breast cancer subtypes.

BACKGROUND: The tumor microenvironment critically influences breast cancer (BC) progression, immune surveillance, and therapeutic response. Cancer-associated fibroblasts (CAFs), a heterogeneous stromal population, are key regulators of these processes, yet their subtype-specific contributions in BC remain insufficiently defined. METHODS: We integrated three single-cell RNA sequencing datasets from 29 BC patients to characterize stromal populations. Bulk RNA-seq data from The Cancer Genome Atlas (TCGA) were analyzed to assess correlations between CAF subsets and immune infiltration. Gene signatures were derived to identify subtype-specific CAF-immune interactions, prognostic markers, and potential predictors of chemotherapy response. RESULTS: Three conserved stromal populations (iCAFs, myCAFs, and pericytes) were identified, along with a previously unrecognized subset, the cluster 3 (CL3) CAF-like cells, referred as metabolic stressed CAF (msCAF). msCAF cells displayed transcriptional programs associated with antigen presentation, stress response, glycolysis, and extracellular matrix remodeling. Their abundance was inversely correlated with T-cell infiltration and function, in a subtype-specific manner: triple negative breast cancer (TNBC) was enriched for msCAFs in immune-infiltrated but functionally constrained microenvironments, whereas Luminal A tumors exhibited weaker immune infiltration with heterogeneous CAF-immune associations. msCAFs were characterized by a conserved gene signature (HLA-A, HLA-C, IL32, EMP3) and subtype-specific genes related to T-cell exhaustion. Several genes demonstrated prognostic relevance with distinct patterns in Luminal A (IER3, TIMP1, TBX3, SEC61G) and TNBC (ADM, C4orf3, LDHA) tumors, as well as shared biomarkers (FN1, LOXL2, P4HA1). Multiple msCAF genes also predicted chemotherapy response, suggesting utility as treatment stratification biomarkers. CONCLUSION: msCAFs represent a clinically relevant CAF subset that drives immune suppression, impacts subtype-specific prognosis, and influences therapy response in BC. These findings highlight msCAFs as promising targets for enhancing immunotherapy and personalizing treatment strategies.

Humans↗

PubMed2025

Development and validation of a novel risk stratification signature derived from migrasome and tumor microenvironment-related genes for molecular subtyping and improving clinical outcomes in head and neck squamous cell carcinoma.

BACKGROUND: The tumor microenvironment (TME) and migrasomes released by tumor cells significantly influence carcinogenesis and immune evasion. However, our understanding of the prognostic and therapeutic implications of migrasome and tumor microenvironment-related genes (mtmRGs) in head and neck squamous cell carcinoma (HNSCC) remains limited. METHODS: We explored the relationship between mtmRGs and HNSCC prognosis by utilizing The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Subsequently, we developed an innovative prognostic signature, and assessed its prognostic significance using the Kaplan-Meier method, time-dependent receiver operating characteristic (ROC), and Cox regression analyses. To explore the underlying mechanisms, we conducted gene set variation analysis (GSVA), gene set enrichment analysis (GESA), and immune infiltration analysis. A nomogram was developed to estimate the overall survival (OS) rates for HNSCC patients. Lastly, we chose P4HA1, which was part of the signature, for additional experimental validation in vitro and in vivo. RESULTS: The mtmRGs signature effectively classifies HNSCC patients into two distinct risk subgroups, with the high-risk cohort demonstrating significantly poorer OS. The risk score serves as an independent prognostic factor for HNSCC patients; those with lower risk scores are more likely to exhibit favorable responses to immunotherapy, particularly with CTLA4 inhibitors. Furthermore, a lower risk score is significantly correlated with the sensitivity of HNSCC patients to cyclophosphamide, gemcitabine, and axitinib. CONCLUSION: This study presents an innovative gene signature associated with mtmRGs, which may be utilized both for predicting survival and directing personalized chemotherapy and immunotherapy regiments for patients with HNSCC.

Humans↗

PubMed2026

Age-stratified mutation patterns in early-onset colorectal cancer reveal distinct molecular features and therapeutic implications.

BACKGROUND: Colorectal cancer (CRC) is increasingly diagnosed in younger adults, with evidence that early-onset cases (age <50 years) differ in the spectrum of prevalent gene mutations compared with older individuals. To evaluate how these age-related differences may inform testing guidelines and therapeutic development, we examined mutation rates of the most prevalent gene mutations across four age-stratified cohorts. PATIENTS AND METHODS: Clinicogenomic data were obtained from Memorial Sloan Kettering Center for Harmonized Onco-genomic Research Dataset and China Pan-Cancer cohorts available in cBioPortal. A total of 6762 samples were analyzed. Mutation frequencies for a comprehensive panel of the 100 most prevalent CRC genes were compared across four age groups: 18-29 (n = 79), 30-39 (n = 402), 40-49 (n = 1064), and ≥50 (n = 5217) using chi-square analysis. False discovery rate (FDR) correction for multiple comparisons was carried out using Benjamini-Hochberg procedure. RESULTS: Statistically significant variation in mutation frequency across age groups was seen in 22 key genes. APC mutations increased with age and were seen in 49.4% of patients in the 18-29 group, 69.7% in 30-39, 73.3% in 40-49, and 75.25% of patients ≥50 (P < 0.001, FDR < 0.001). The oldest cohort was more than three times more likely to have an APC mutation than the youngest [odds ratio (OR) = 3.74, 95% confidence interval (CI) 2.44-5.74, P < 0.001]. In contrast, SMAD4 mutations were twice as common in the youngest age group at 31.6% compared with those over 40, with a prevalence of 17.29% in patients 40-49, and 18.84% in patients over 50 (OR = 2.03, 95% CI 1.26-3.27, P < 0.001, FDR < 0.001). POLE mutations peaked in the 30-39 age group with a prevalence of 10.7% compared with 6.3% in patients aged 18-29, 4.9% in patients aged 40-49, and 5.9% in patients aged ≥50 (P < 0.001, FDR < 0.001). Individuals in the 30-39 group were nearly twice as likely to carry a POLE mutation compared with those over 40 (OR = 1.96, 95% CI 1.41-2.74, P < 0.001). CONCLUSIONS: Differences in mutations of key genes including a lower prevalence of APC mutations and increased SMAD4 mutations in younger individuals provides further supporting evidence that early-onset CRC may represent a distinct biological subtype of CRC. Enrichment of POLE mutations in younger patients highlights the importance of expanded molecular profiling in early-onset CRC, which could help identify patients most likely to benefit from immunotherapy and advance personalized treatment strategies in CRC. Together, these findings reinforce the need to approach early-onset CRC as a distinct biological entity and ensure that appropriate molecular assays are incorporated to guide care.

APC↗

PubMed1976

Alternaria IgG precipitins and adverse reactions.

Late reactions consisting of fever, malaise, and swelling at the site, 4 to 6 hr after injections of Alternaria extract occurred in several patients receiving immunotherapy with Alternaria. These patients had in common serum IgG precipitins and exquisite leukocyte histamine release sensitivity to Alternaria. Such precipitins were 3 times more frequent in patients receiving Alternaria immunotherapy than a control group of patients receiving immunotherapy with other antigens. A prospective study revealed that 5 of 23 Alternaria-sensitive persons had precipitins before immunotherapy and another 6 developed precipitins during therapy. Only one of the 23 experienced a late Alternaria reaction. Thus, precipitins to Alternaria are common and do not seem to be the basis for the late reactions we observed. The finding of precipitins does not contraindicate immunotherapy.

Alternaria↗