STX16 has been studied in various cancers, where it is suggested to regulate tumor cell proliferation, migration, and invasion by affecting vesicle trafficking and signal transduction pathways. However, its specific role in clear cell renal cell carcinoma (ccRCC) remains unclear. This study aims to systematically investigate the expression patterns, clinical significance, prognostic value and functional role of STX16 in ccRCC. Bioinformatics analyses using TCGA, CTPAC, TIMER, and UALCAN databases evaluated STX16 expression, clinical correlations, prognosis, and immune infiltration. Functional enrichment, co-expression, and PPI analyses explored STX16-associated pathways. Single-cell sequencing elucidated tumor microenvironment heterogeneity. Laboratory validation included Western blot, immunohistochemistry, and functional assays with siRNA-mediated STX16 knockdown in ccRCC cell lines. STX16 was significantly upregulated at mRNA and protein levels in ccRCC tissues. High STX16 expression correlated with advanced tumor stages, poor overall survival (OS), and disease-specific survival (DSS). Multivariable Cox regression identified STX16 as an independent prognostic factor. STX16 influenced immune infiltration, particularly involving CD4 + T cells, macrophages, and neutrophils, and was associated with immune pathways. Single-cell sequencing revealed heterogeneous STX16 expression across tumor microenvironment cell types. STX16 knockdown inhibited proliferation, migration, and invasion of ccRCC cell lines. STX16 is upregulated in ccRCC and acts as an independent prognostic factor associated with poor outcomes. Its role in promoting tumor progression and modulating immune infiltration highlights STX16 as a potential biomarker and therapeutic target in ccRCC.

Although it is the most common subtype of lung cancer in clinical practice, lung adenocarcinoma (LUAD) was proven to be associated with a poor prognosis. In recent years, lactate metabolism has been considered an important biological mechanism in lung cancer. However, the mechanisms of lactate-related genes in tumour microenvironment (TME) of LUAD are unknown. Lactate-related genes modification patterns in 701 LUAD samples from TCGA and GEO database were systematically assessed on the basis of 16 lactate-related genes (LRGs).We also identified the correlation of these clusters to the TME and immune cell infiltration in the TME. After unsupervised clustering analysis was performed, the LUAD samples were divided into three lactate-related gene phenotypes on the basis of 36 prognostic lactate-related genes (PLRGs). These molecular subtypes have different immune cell infiltration characteristics and pathway enrichment. Using LASSO, a 16-LRG risk signature was constructed. The lactate-related signature demonstrated a stable and accurate ability to predict the prognosis of LUAD in patients. Furthermore, the lactate-related signature demonstrated good predictive ability for immune infiltrating cells, tumour mutation burden, and response to immunotherapy. The 16-LRG risk signature was subsequently verified in the GSE50081 GEO cohort. This study revealed the significant clinical utility of the 16-LRG risk signature in the understanding the TME and prognosis of LUAD. The 16-LRG risk signature is conducive to understanding immune cell infiltration in the LUAD TME and contributes to the selection of more effective immunotherapy strategies.

Advances in high-throughput sequencing and decreasing costs have made cell-free DNA sequencing a promising approach for cancer detection. Sequencing assays require high read depth to detect low-frequency somatic mutations, so cell-free DNA panels must support deep sequencing while still assaying broadly enough to detect as many malignancies as possible. We developed OPTIC (Oncogene Panel Tester for Identifying Cancers), a pipeline employing a set cover algorithm, to identify the minimal set of genomic targets capturing the maximal proportion of tumours. Using three cohorts totalling 2,940 colorectal cancer samples, OPTIC was utilized to design a targeted sequencing panel spanning just 10,975 bases across APC, TP53, KRAS, BRAF, NRAS, PIK3CA, CTNNB1, RNF43, and ACVR2A. Collectively, these loci contain pathogenic mutations in 96.3% of cases. Our pipeline enables compact panel design without compromising sample coverage. This enables higher throughput, greater sequencing depth, and lower costs per-sample in early colorectal cancer detection from cell-free DNA.

Mitochondrial autophagy (mitophagy) in macrophages is crucial yet poorly understood within the lung adenocarcinoma (LUAD) tumor microenvironment. This study aimed to identify key macrophage mitophagy-related genes and develop a robust prognostic model for LUAD patients. By integrating single-cell transcriptomics with machine learning algorithms, including LASSO, SVM, and random forest, we identified TUBB6 and CAT as core prognostic genes. A novel risk model based on these genes (RiskScore = 0.225 × TUBB6 - 0.19 × CAT) was constructed and validated, demonstrating that patients in the high-risk group had significantly shorter overall survival (P < 0.001). The high-risk score also correlated with an altered immune microenvironment and increased sensitivity to chemotherapies like cisplatin and gemcitabine. Furthermore, in vitro experiments confirmed that macrophage-specific overexpression of TUBB6 significantly enhanced LUAD cell proliferation, migration, and invasion through secreted factors. Our findings establish a reliable, macrophage mitophagy-based prognostic model and highlight TUBB6 and CAT as novel biomarkers and potential therapeutic targets, offering new avenues for precision medicine in LUAD.

Immunotherapy has opened new avenues of treatment for patients with advanced non-small cell lung cancer (NSCLC) without previous hope of survival. Unfortunately, only a small percentage of patients benefit from it and there is not an effective biomarker to predict patients' response. Since T cells are key effectors of antitumor immunity, T cell receptor (TCR) has emerged as a potential predictive biomarker. Here, we evaluated the potential of baseline TCR repertoire, as a predictive biomarker in advanced NSCLC patients treated with pembrolizumab at first-line. After obtaining peripheral blood and tissue samples at baseline, next-generation sequencing targeting TCRβ/γ was performed. We found an uneven tumor-infiltrating TCRβ repertoire, and the use of various tumor-infiltrating and circulating TRBV/J genes were able of predicting the immunotherapy response. Our results support the potential of evaluating tissue and circulating TCRβ repertoire prior to pembrolizumab, revealing it as a promising immunotherapy response biomarker in NSCLC patients.

The International Cancer Genome Consortium Accelerating Research in Genomic Oncology (ICGC ARGO) project is an international initiative to sequence germline and tumour genomes from 100,000 cancer patients across 13 countries and 22 tumour types. By integrating genomic data with comprehensive clinical information including treatment outcomes, lifestyle, environmental exposures and family history, ICGC ARGO aims to accelerate the application of genomic insights in cancer diagnosis, treatment and prevention. However, a major challenge is harmonizing clinical data from diverse tumour types worldwide. To address this, the ICGC ARGO Data Dictionary was developed to ensure consistent high-quality clinical data collection by defining a minimal set of clinical fields within an event-based data model to capture clinical relationships and support longitudinal data collection. Grounded in international standardized terminology, it is interoperable with other data standards such as Minimal Common Oncology Data Elements (mCODE). Its adoption by global initiatives such as the European-Canadian Cancer Network (EUCANCan) and the Marathon of Hope Cancer Centres Network (MOHCCN) underscores its broad impact on advancing precision oncology research.

Prostate cancer (PrCa) incidence and severity vary across ancestries; men of African ancestry (AA) are more likely to be diagnosed and die from PrCa than those of European ancestry (EA). Current polygenic risk scores, even from multi-ancestry GWAS, do not fully capture population-specific genetic mechanisms, especially those mediated by non-coding regulatory single nucleotide polymorphisms (SNPs). Using a deep learning model of prostate enhancers, we identify ~ 2000 SNPs, potentially affecting enhancer function, with higher alternate allele frequency in AA men, that may affect PrCa risk. These SNPs may promote cancer via two mechanisms: increased enhancer activity leading to immune suppression and telomere elongation or decreased activity causing de-differentiation and apoptosis inhibition. Identified SNPs predominantly modulate binding of key transcription factors such as FOX, HOX, and AR - the first was experimentally validated. Incorporating these SNPs into a polygenic risk score improves PrCa risk assessment beyond existing GWAS-identified variants.

RNA G-quadruplexes (rG4s) are key regulatory elements in gene expression, yet the effects of genetic variants on rG4 formation remain underexplored. Here, we introduce G4mer, an RNA language model that predicts rG4 formation, classifies rG4 subtypes, and evaluates the effects of genetic variants across the transcriptome. G4mer significantly improves accuracy over existing methods and uncovers subtype-specific differences in mutational sensitivity and evolutionary constraint, highlighting sequence length and flanking motifs as important rG4 features. Applying G4mer to 5' untranslated region (UTR) variations, we identify variants in breast cancer-associated genes that alter rG4 formation and validate their impact on structure and gene expression. These results demonstrate the potential of integrating computational models with experimental approaches to study rG4 function, especially in diseases where non-coding variants are often overlooked. To support broader applications, G4mer is available as both a web tool and a downloadable model.

Emerging imaging spatial transcriptomics (iST) platforms and coupled analytical methods can recover cell-to-cell interactions, groups of spatially covarying genes, and gene signatures associated with pathological features, and are thus particularly well-suited for applications in formalin fixed paraffin embedded (FFPE) tissues. Here, we benchmark the performance of three commercial iST platforms-10X Xenium, Vizgen MERSCOPE, and Nanostring CosMx-on serial sections from tissue microarrays (TMAs) containing 17 tumor and 16 normal tissue types for both relative technical and biological performance. On matched genes, we find that Xenium consistently generates higher transcript counts per gene without sacrificing specificity. Xenium and CosMx measure RNA transcripts in concordance with orthogonal single-cell transcriptomics. All three platforms can perform spatially resolved cell typing with varying degrees of sub-clustering capabilities, with Xenium and CosMx finding slightly more clusters than MERSCOPE, albeit with different false discovery rates and cell segmentation error frequencies. Taken together, our analyses provide a comprehensive benchmark to guide the choice of iST method as researchers design studies with precious samples in this rapidly evolving field.

Despite advancements in several malignancies, the treatment atlas of natural killer (NK) cell therapy for pancreatic cancer remains inadequate, and the dynamic immune landscape underlying the various responses is still incompletely understood. This phase 1b/2 trial evaluated the safety and efficacy of allogeneic NK cell therapy combined with gemcitabine and S-1 as a first-line treatment for advanced pancreatic cancer (APC) and explored the dynamic responsive immune landscape (ChiCTR1900021764). The administration of 1 × 109 to 8 × 109 NK cells to 24 patients was well tolerated, with no graft-versus-host disease or dose-limiting toxicity. Among the 19 evaluable patients, the objective response rate was 31.6%, and the disease control rate was 73.7%. The median progression-free survival was 6.6 months, and the overall survival was 10.8 months. Further longitudinal single-cell RNA sequencing (scRNA-seq) of 19 paired-blood samples revealed an increased proportion of certain NK cell subsets (c4-ZEB2, c5-IL7, c6-IL15, c10-NCR3, and c11-TNFSF8) and T-cell subsets (CD8+ Teff and CD4+ Tem) in responders, characterized by increased expression of proinflammatory and effector molecules. Bulk T-cell receptor (TCR) Vβ repertoire sequencing of responders indicated potential T-cell clonal expansion, manifested as a greater abundance of large and hyperexpanded clonotypes. Our first-in-human trial demonstrated its safety and potentially preliminary efficacy, warranting further clinical evaluation. Multiomic profiling identified specific circulating NK and T-cell subsets potentially associated with clinical outcomes, providing novel insights into the dynamic transcriptional underpinnings of the immune landscape in response to NK cell-based therapy.

MicroRNA (miR)-425-5p is used as a molecular biomarker to identify cervical cancer (CxCa). However, few studies have examined the miR-425-5p-based modulation of the vital activities of CxCa cells. The levels of neural cell adhesion molecule 1 (NCAM1) and miR-425-5p in CxCa tissues and cells were tested using western blot and reverse transcription quantitative polymerase chain reaction (RT-qPCR) tests. CxCa cells' malignant phenotype was examined through clone formation tests, and transwell tests. CD8+T cells were co-cultured with CxCa cells and then analyzed for apoptosis rates and the expression of activation proteins (granzyme B (GZMB) and perforin) as well as immune factors (tumor necrosis factor-alpha (TNF-α) and interferon-gamma (IFN-γ)) using flow cytometry, western blot, and enzyme-linked immunosorbent assay (ELISA) methods. Finally, in nude mouse experiments, the tumor size was measured for subcutaneous tumors, and the expression of CD8+T cell-related factors was detected. The NCAM1 and miR-425-5p were down-regulated and up-regulated in CxCa tissue and cells, respectively. After silencing miR-425-5p, CxCa cells showed attenuation in vitality, clone formation rate, and their capacities to migrate, penetrate, and evade immune responses. NCAM1 was targeted and silenced by miR-425-5p. When NCAM1 was silenced, it partially counteracted miR-425-5p's inhibitory effects on the immune escape and proliferation. In nude mice, the tumor size and weight decreased after silencing miR-425-5p, and levels of CD8, IFN-γ, TNF-α, perforin, and GZMB were elevated. However, these changes were reversed when NCAM1 was silenced. In conclusion, miR-425-5p mediates the biological behavior and immune evasion of CxCa cells by regulating NCAM1.

This study aimed to investigate the expression patterns of HOXB9, DLX5, NGR1, and GATA6 in endometrial cancer tissues compared to adjacent non-cancerous tissues. Using RT-qPCR and immunohistochemistry, the researchers found significant upregulation of HOXB9, DLX5, and NGR1, and downregulation of GATA6 in endometrial cancer samples. The biomarker expression levels correlated with clinicopathological features, and survival analysis revealed that high expression of HOXB9, DLX5, and NGR1 was associated with poorer prognosis, while high GATA6 expression indicated better outcomes. These findings suggest that these biomarkers may play crucial roles in endometrial cancer development and progression, highlighting their potential as diagnostic, prognostic, and therapeutic targets.

NUT carcinoma (NC) is an aggressive malignancy driven by BRD4::NUTM1 and other NUTM1 fusion oncogenes. BRD4::NUTM1 aberrantly activates transcription factors (TFs) associated with basal progenitor cells of stratified epithelium, resulting in a poorly differentiated squamous cell carcinoma (SCC) phenotypes. Among these TFs, SOX2 has been proposed as a critical driver. However, its role in NC initiation and progression has not been investigated in vivo. Using a genetically engineered mouse model that faithfully recapitulates human NC, we performed lineage-specific conditional deletion of Sox2 in both squamous and non-squamous tissues during NC oncogenesis. We found that SOX2 is dispensable for NC initiation and progression, and that tumors lacking SOX2 retain characteristic histological features and expression of key oncogenic drivers, including BRD4::NUTM1, MYC, and TP63. Bulk RNA sequencing revealed only modest transcriptional changes in SOX2-deficient tumors, primarily affecting metabolic and biosynthetic pathways, without disrupting core oncogenic programs. These findings challenge the assumption that SOX2 is universally required for NC oncogenesis and highlight the autonomy of BRD4::NUTM1 in establishing and maintaining the NC phenotype. Our results suggest that SOX2 is dispensable for NC and redirect therapeutic focus toward BRD4::NUTM1 and its chromatin remodeling dependencies.

Genetic testing is increasingly central to the management of localized prostate cancer (PCa). Advances in next-generation sequencing have revealed both germline and somatic alterations that influence disease risk, prognosis, and therapeutic response. Approximately 10% to 15% of men with PCa carry pathogenic germline variants, most commonly in BRCA2, ATM, CHEK2, HOXB13, and mismatch repair genes. Consensus recommendations and guidelines now endorse routine germline testing in men with high-risk localized disease, strong family history, or known familial mutations. Germline information, as well as somatic genomic classifiers, is increasingly being used to help guide screening and treatment recommendations.

This article examines the current landscape of molecular biomarkers for diagnosing localized prostate cancer (PCa), from the prostate-specific antigen (PSA) test to newer blood, urine, or tissue-based biomarkers which can improve the accuracy of PCa diagnosis compared with PSA alone. The article further examines how tissue-based biomarkers are being used for predicting outcomes and affecting treatment decisions. These biomarkers have the potential to transform the clinical management of PCa, but future studies are needed to optimize and standardize their use in combination with other tests, including modern imaging, to provide maximum benefit to PCa patients.

Neoadjuvant immune checkpoint inhibitors (nICIs) have demonstrated high response rates in deficient mismatch repair/microsatellite instability-high (dMMR/MSI-H) gastroesophageal adenocarcinoma (GEA). The NEONIPIGA and INFINITY trials demonstrated high rates of pathologic complete response (pCR) in this patient population. Furthermore, the INFINITY trial explored the feasibility of managing these patients nonoperatively, demonstrating promising results. This study aimed to evaluate clinical outcomes of nICIs in resectable dMMR/MSI-H GEA, with a focus on the feasibility of nonoperative management (NOM).

Prognostic assessment plays a crucial role in guiding clinical management and treatment decisions for gastric cancer patients. The enrichment characteristics of 5-hydroxymethylcytosine (5hmC) in circulating cell-free DNA (cfDNA) has emerged as potential prognostic epigenetic markers.

To investigate the effect of N-glycosylation on NANOG regulation of colon cancer stem cell characteristics. The GEPA database was used to screen and analyze the expression of N-glycosylase in colon cancer tissues. CD133 + stem cells were selected by magnetic bead sorting of colon cancer HCT116 cells and LoVo cells. Plasmid transfection of colon cancer stem cells was performed by Lipofectamine™ 3000. Cell activity was detected by MTT method. Microsphere formation test was used to detect the diameter and number of stem cell spheres. EdU flow cytometry was used to detect cell proliferation. Scratch assay was used to detect cell migration ability. Western Blot was used to detect the expression level of apoptosis-related proteins. Compared with the control group, colon cancer stem cells transfected with mutant expression vectors with N-glycosylation site deletion had reduced cell activity, decreased proliferation and migration ability; reduced tumor stem cell sphere formation ability; and increased intracellular apoptosis level. Conclusively, The seven N-glycans in the carboxyl terminus of human NANOG are involved in the molecular quality control of NANOG protein and the maintenance of the stem cell characteristics of colon cancer stem cells, further affecting the proliferation and migration ability of colon cancer stem cells.

Colorectal cancer (CRC) with liver-only metastases remains a significant clinical challenge owing to its high recurrence rate, even after curative hepatectomy. Despite advancements in surgical techniques and systemic therapies, identifying patients at elevated risk of recurrence is crucial for optimizing long-term outcomes. Circulating tumor DNA (ctDNA) is a biomarker for minimal residual disease and recurrence risk assessment. We hypothesize that plasma-only ctDNA assays using the Plasma-Safe-SeqS platform can enable early recurrence detection and guide postoperative management, including adjuvant chemotherapy. This single-center, prospective observational study will enroll 10 patients with histologically confirmed CRC and liver-only metastases undergoing curative hepatectomy. Plasma samples are collected preoperatively and at predefined intervals postoperatively (4, 12, 24, 36, and 48 weeks) to monitor ctDNA levels using a highly sensitive 14-gene panel designed to detect tumor-specific mutations. Mutant allele frequencies as low as 0.1% are detected using the Plasma-Safe-SeqS platform. The primary endpoint is the interval between ctDNA detection and clinically confirmed recurrence. The secondary endpoints include mutation concordance between pre- and postoperative samples, 3-year disease-free survival, 5-year overall survival, and correlations with clinicopathological features. Kaplan-Meier estimates and Cox proportional hazards models are used for statistical analyses. To our knowledge, this is the first study to utilize a 14-gene panel with Plasma-Safe-SeqS technology for ctDNA analysis in patients with CRC liver metastases following curative hepatectomy. By eliminating the need for tumor tissue, this plasma-only approach simplifies diagnostics and mitigates logistical barriers, including prolonged turnaround times associated with tumor-informed assays. We aim to validate ctDNA as a reliable biomarker for early recurrence detection. Furthermore, we may provide valuable insights into optimizing adjuvant chemotherapy strategies by identifying high-risk patients who may benefit from treatment while sparing low-risk patients from unnecessary toxicity. These findings may advance personalized postoperative care and enhance long-term outcomes in this patient population. Trial registration The study is registered in accordance with the International Committee of Medical Journal Editors (ICMJE) guidelines under the University Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR). The registry name is UMIN-CTR. The registration number is UMIN000057128. Trial details are available upon request.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, largely due to its highly immunosuppressive tumor microenvironment (TME), which fuels metastasis and resistance to immunotherapy. Through comprehensive analysis of single-cell RNA sequencing datasets, we identified multiple heterogeneous tumor-associated macrophage (TAMs) subpopulations as key regulators of PDAC progression, which coexpress MRC1 and exert their effects by actively suppressing antitumor immune responses. To overcome this barrier, we developed a spatiotemporal macrophage reprogramming platform that leverages STING phase separation to reprogram TAM plasticity and reshape the immune landscape. This system, MRC1-targeting peptide-M@BLZ945 (PMMB), integrates a colony-stimulating factor 1 receptor (CSF-1R) inhibitor and a STING agonist within a macrophage-mimetic nanostructure, enabling sequential, controlled reprogramming of TAMs. By leveraging STING phase separation, PMMB stabilizes TAMs in an antitumor CD80+ phenotype while preventing excessive inflammation, achieving durable immune activation. In preclinical models, PMMB not only suppresses both primary and metastatic PDAC but also enhances CD8+ T cell infiltration, reinvigorates anti-PD-1 therapy responses, and mitigates immune exhaustion. These findings establish spatiotemporal macrophage circuit engineering via STING phase separation as a cross-scale strategy to override PDAC's immune barriers and drive next-generation macrophage-targeted immunotherapy. This study paves the way for rationally designed, precision macrophage modulation strategies in solid tumors.