Fulzerasib, a KRASG12C inhibitor, has shown clinical activity in previously treated non-small-cell lung cancer (NSCLC). Clinical studies indicate that combining a KRASG12C inhibitor with an anti-EGFR antibody is effective in colorectal cancer; however, its benefit in NSCLC remains to be explored.

mRNA can be engineered to overcome cancer evolution.

Cell reprogramming can be used to short-circuit the cancer-immunity cycle.

Extrachromosomal circular DNA (eccDNA) are molecules that originate from chromosomal DNA but exist independently. While large eccDNA (ecDNA) contributes to tumorigenesis, the role of smaller eccDNA (<100,000 base pairs) in cancer remains unclear. Our analysis of 25 colorectal cancer (CRC) tumors and normal adjacent tissues revealed that eccDNA is significantly more abundant in tumor tissues, correlating strongly with chromosomal amplifications. The presence of whole intact genes on 1.29% of eccDNA was nonrandom. We identified 84 genes that recurred across tumors of multiple patients when present on eccDNA, with 19% of genes being cancer-associated. eccDNA-borne genes were often accompanied by increased expression, and their contribution to expression was much larger than that from linear amplifications and the larger ecDNA. The cytokine gene CXCL5 exemplified this phenomenon, showing substantial copy-number increase and upregulation when present on eccDNA. Functional validation in cell lines showed that CXCL5 eccDNA enhanced transcriptional output and immune cell recruitment function. The recurrence and overexpression of CRC-related genes on eccDNA indicate their selection in tumors, suggest that eccDNA can serve as an additional mechanism for dynamically influencing gene expression and is capable of conferring cancer phenotypes on cells. Analysis of chromatin landscapes revealed that eccDNA preferentially forms at sites of open chromatin and active transcription, with architectural boundaries marked by CTCF protein. Clinically, higher eccDNA levels correlated with poorer relapse-free survival in a small patient cohort. These findings suggest that circular DNA elements across the entire size spectrum participate in cancer evolution and warrant further investigation in larger cohorts.

Mutations in PIK3CA are one of several actionable mutations for patients with hormone receptor positive, human epidermal growth factor receptor 2 negative breast cancer. Alpelisib in combination with fulvestrant was the first approved PI3K inhibitor and was introduced in clinical practice in 2019. A lack of evidence for the use of alpelisib in the context of current treatment options like cyclin-dependent 4/6 inhibitor (CDK4/6i), highlights the importance of this analysis. We provide a real-world analysis of the use of alpelisib with the prospective German PRAEGNANT registry (NCT02338167).

Hepatocyte nuclear factor 4 alpha (HNF4α) is a conserved nuclear receptor that governs epithelial identity and metabolic homeostasis across endoderm-derived tissues. In cancer, HNF4α can function as either an oncogene or a tumor suppressor. In colorectal and hepatocellular carcinoma, reduced HNF4α activity accompanies loss of differentiation and tumor progression, consistent with tumor-suppressive functions. In contrast, in pancreatic ductal adenocarcinoma, invasive mucinous adenocarcinoma, and other lineage-defined epithelial tumors, HNF4α can also participate in transcriptional programs that sustain malignant identity, metabolic adaptation, and therapeutic resistance. However, these effects are highly context-dependent and do not imply a uniformly oncogenic role in these tumor types. These divergent functions are shaped by isoform usage, chromatin state, epigenetic regulation, metabolic cues, and transcription factor networks. Rather than acting as a classical oncogene or tumor suppressor in all settings, HNF4α is better understood as a context-dependent regulator of lineage state whose activity may either restrain tumor progression or support tumor maintenance. This mini review highlights the molecular mechanisms that shape HNF4α activity, including isoform biology and epigenetic control, and discusses emerging strategies for selectively inhibiting HNF4α in dependency states or restoring its differentiation-promoting functions in tumors where it is lost.

To evaluate whether 7-T susceptibility-weighted imaging (SWI) can predict glioma's histological grade, Ki-67 labeling index (LI), isocitrate dehydrogenase 1 (IDH1) mutation, 1p/19q co-deletion, telomerase reverse transcriptase (TERT) promoter mutation, and O-6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status of gliomas.

Immunotherapy has revolutionized cancer treatment, yet characterizing the spatial complexity of the tumor immune microenvironment remains a challenge. In this study, we established a comprehensive computational framework integrating multi-omics profiling across 27 cancer types to decode immune-related non-coding RNA regulatory networks. Moving beyond traditional bulk analysis, we utilized spatial transcriptomics to dissect the spatial localization of these regulators. We identified the SNHG6-BIRC5 axis as a critical driver of the "immune-cold" phenotype in lung adenocarcinoma. We provide visual evidence that this axis localizes to tumor nests and negatively correlates with T- cell infiltration, elucidating a mechanism of spatial immune exclusion. Validating the clinical relevance of these findings, genome-scale CRISPR-Cas9 screening data confirmed the functional essentiality of these targets for cancer cell survival. Furthermore, pharmacogenomic analysis revealed that high expression of this axis correlates with sensitivity to chemotherapy agents like Vinblastine, suggesting a potential stratification strategy for patients with immune-excluded tumors. To expand the clinical utility to immunotherapy prediction, we developed a pan-cancer XGBoost machine learning model incorporating 14 high-performance regulatory features. This model achieved robust performance in distinguishing immunotherapy responders from non-responders with an AUC of 0.771, outperforming traditional markers such as PD-L1. Collectively, this study highlights spatial determinants of immune exclusion and chemotherapy sensitivity- and presents a generalized machine- learning tool for precision immunotherapy stratification. The developed online resource is freely available to facilitate community-wide biomarker discovery.

The Muscleblind-like (MBNL) family comprises evolutionarily conserved RNA-binding proteins that interact with target RNAs via zinc finger domains. MBNLs orchestrate RNA processing, particularly alternative splicing, driving the developmental fetal-to-adult isoform switch across numerous target transcripts. This transition is a cornerstone in the process of MBNL-maintained cellular homeostasis and fails in many pathological conditions associated with deregulated expression or function of specific MBNL paralogs. This review provides current insights into the roles of MBNL genes and proteins in both health and disease. We examine their genomic architecture and protein organization and synthesize key insights from animal models to delineate the selective and compensatory functions of individual MBNL paralogs in physiology. To illustrate the roles of MBNLs in disease, we outline nucleotide repeat expansion disorders marked by their functional depletion, with a primary focus on myotonic dystrophy (DM). We also highlight selected cancer studies that have demonstrated the dual roles of MBNLs in tumorigenesis, encompassing both pro-oncogenic and tumor suppressive functions. Finally, using DM as a model, we review evidence for the therapeutic potential of endogenous MBNL gene modulation and argue that analogous strategies could be adapted and tailored to restore MBNL homeostasis in other disorders involving their dysregulation.

DNA microarray is a transformative technique in genomics, enabling simultaneous examination of thousands of gene expression levels. However, noise, high dimensionality (typically 12,000-22,000 genes), small sample sizes (155-1097 samples) and class imbalance complicate the extraction of meaningful diagnostic patterns. This paper presents MICRO-AI (Microarray Classification and Recognition using Artificial Intelligence), a comprehensive machine learning framework for DNA microarray analysis and automated disease diagnosis. The framework integrates advanced preprocessing (quantile normalisation, ComBat batch correction, KNN imputation), attention-weighted adaptive feature selection using recursive feature elimination with cross-validation, and heterogeneous ensemble classification combining gradient boosting machines, random forests and support vector machines with adaptive weight optimisation. A novel attention-based feature fusion mechanism dynamically prioritises discriminative gene expression signatures, reducing dimensionality by over 99% (from ∼20,000 to ∼127 genes) without loss of biological significance. MICRO-AI is validated on six benchmark datasets from three repositories: Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and ArrayExpress, spanning breast cancer, gastric cancer, ovarian cancer and leukaemia across 2321 total samples. Experimental results demonstrate average classification accuracy of 96.8%, sensitivity of 95.2%, specificity of 97.4%, F1-score of 96.0%, Matthews correlation coefficient of 0.928, and area under the receiver operating characteristic curve of 0.983. Comparative benchmarking against 10 state-of-the-art methods shows that MICRO-AI achieves 1.2-7.5% higher accuracy with an average training time of 52.3 s, representing 2.4-6.0× faster execution than deep learning alternatives. The modular architecture enables seamless integration with medical informatics systems for scalable clinical diagnostic deployment.

Non-small cell lung cancer (NSCLC) is a malignant tumor characterized by high morbidity and mortality, as well as metabolic reprogramming. Enhanced serine synthesis plays a crucial role in the aberrant metabolism of NSCLC. Among the three key enzymes involved in serine synthesis, phosphoserine aminotransferase 1 (PSAT1) requires further investigation to elucidate its regulatory mechanisms in NSCLC.

Tacrolimus (TAC) is recommended for the patients with drug tolerance or respond poorly to other conventional immunosuppressants in myasthenia gravis (MG), but its effectiveness is influenced by dose and genetic polymorphism. Studies suggest that HLA polymorphisms are significantly associated with susceptibility to MG, but the relationship between HLA and TAC efficacy in MG has not been explored. In this paper, we investigated the correlation between TAC therapeutic efficacy and HLA in different MG subgroups. HLA-C*03 was associated with a better response to TAC in patients with early-onset MG, generalized MG, and those with a high concentration of TAC. While HLA-A*11:01 showed poor responsiveness to TAC in generalized MG. Furthermore, computational docking was used to demonstrate the binding situation of HLA-A with the TAC binding protein FKBP1A. It showed that HLA-A*11:01 had a higher binding strength with FKBP1A than HLA-C*03, indicating that the combination of different types of HLA and FKBP1A may be one of the reasons affecting its therapeutic efficacy. This study highlights the influence of HLA on the efficacy of TAC among different MG subgroups, providing clues for precise treatment of MG with TAC.

Thrombocytopenia-absent radius (TAR) syndrome is a rare congenital disorder characterized by bilateral radial aplasia with preserved thumbs and early-onset thrombocytopenia. While hematologic and skeletal abnormalities define the condition, its association with hematologic malignancies is extremely rare, with only a few reported cases of leukemia. Juvenile myelomonocytic leukemia (JMML) is an uncommon pediatric myelodysplastic/myeloproliferative neoplasm frequently linked to RAS pathway mutations. To our knowledge, JMML has not previously been reported in association with TAR syndrome.

The Hippo/YAP signaling pathway is a key regulatory network that governs organ size, tissue homeostasis, cell proliferation, and cell polarity. Aberrant Hippo/YAP signaling contributes to the initiation and progression of multiple cancers, making this pathway an attractive therapeutic target. Although several agents targeting Hippo/YAP have shown promise in preclinical models, clinical translation has been limited. These challenges likely stem from an incomplete understanding of the upstream regulators, downstream effectors, pathway crosstalk, and context-dependent roles of Hippo/YAP across different tumor types. Continued mechanistic investigation is required to clarify these complexities and reveal new therapeutic vulnerabilities. In this review, we summarize the current knowledge of the core components of the Hippo/YAP pathway, its regulatory mechanisms and interactions with other signaling cascades, its dysregulation in cancer, the involvement of microRNAs and lncRNAs in pathway modulation, and emerging therapeutic strategies targeting Hippo/YAP.

Background: From 2019 July 15 to 2022 February 14, the REZOR study enrolled 369 treatment-naïve patients with locally advanced or metastatic non-small cell lung cancer harboring EGFR mutations (exon 19 deletion or L858R mutation). Patients were randomly assigned 1:1 to receive either rezivertinib (180 mg/d) plus gefitinib placebo or gefitinib (250 mg/d) plus rezivertinib placebo. Previous results demonstrated significantly improved progression-free survival (PFS) with rezivertinib versus gefitinib and a favorable safety profile. Here, we update the analyses of central nervous system (CNS) outcomes in patients with baseline CNS metastases. Methods: All patients underwent brain magnetic resonance imaging at baseline and each subsequent efficacy evaluation until radiological disease progression or any other treatment discontinuation criteria were met. EGFR mutation status was determined by testing using tissue or plasma samples during screening. Patients with stable, asymptomatic CNS metastasis were eligible for enrollment. The CNS full analysis set (cFAS) comprised patients with baseline CNS metastasis identified on magnetic resonance imaging and evaluated by blinded independent central review according to the Response Assessment in Neuro-Oncology Brain Metastases criteria. Patients with measurable CNS target lesions formed the CNS evaluable-for-response set (cEFR). Results: As of the 2023 November 30 data cutoff, 159 patients had baseline CNS metastasis in the cFAS (rezivertinib: n = 81; gefitinib: n = 78) and 25 in the cEFR (rezivertinib: n = 12; gefitinib: n = 13) per blinded independent central review. In the cFAS, 59 CNS PFS events occurred (rezivertinib: n = 30; gefitinib: n = 29). Median CNS PFS was significantly longer with rezivertinib (24.9 months; 95% confidence interval [CI], 16.5 months-not estimable [NE]) than with gefitinib (15.2 months; 95% CI, 10.5 months-NE), with a hazard ratio of 0.58 (95% CI, 0.34 to 0.99; P = 0.047). In the cEFR, the CNS objective response rate was 83.3% (95% CI, 51.6% to 97.9%) with rezivertinib and 76.9% (95% CI, 46.2% to 95.0%) with gefitinib (odds ratio = 1.50; 95% CI, 0.20 to 11.0; P = 0.690). No new safety findings were observed. Conclusions: Rezivertinib demonstrated a statistically significant superior CNS efficacy over gefitinib as first-line treatment in advanced EGFR-mutated non-small cell lung cancer patients with baseline CNS metastases. The safety profile was consistent with previous analyses. Trial registration: NCT03866499 (ClinicalTrials.gov).

Pancreatic ductal adenocarcinoma (PDAC) is among the most lethal solid malignancies, characterized by aggressive biology and a paucity of effective treatments. Activating mutations in KRAS occur in more than 90% of cases and are fundamental to tumor initiation, progression, therapeutic resistance, and immune exclusion, establishing KRAS as the dominant oncogenic driver in PDAC. Long considered undruggable, KRAS has recently become a viable therapeutic target with the development of allele-specific inhibitors as well as pan-RAS(ON) agents capable of broadly suppressing mutant RAS signaling. Preclinical models and early-phase clinical trials demonstrate meaningful antitumor activity, with emerging evidence of tumor microenvironment remodeling and delayed resistance. Combination strategies integrating KRAS-directed therapies with chemotherapy, vertical pathway inhibition, immunotherapy, and emerging approaches such as KRAS degradation and RNA-targeted approaches are being explored to improve the depth and durability of response. Together, these advances signal a paradigm shift toward molecularly guided treatment strategies in PDAC and offer a promising path forward in a disease with substantial unmet clinical need.

Hsa-miR-99a has been linked to the advancement of several malignancies, including colorectal cancer (CRC). This investigation seeks to elucidate its function and regulatory network in CRC.

Gastric carcinoma poses a significant global health challenge, often diagnosed late due to its similarity to chronic gastric conditions. Helicobacter pylori (Hp) infection plays a crucial role in gastric carcinogenesis through inflammation and the release of virulent products.

T cell dysfunction (TCD) plays a critical role in cancer progression and significantly impacts patient outcomes. Despite its importance, the exact molecular mechanisms underlying TCD remain poorly understood. To address this, we constructed a comprehensive pan-cancer landscape of TCD, with a particular focus on identifying miRNA biomarkers that define and predict TCD severity. Our analysis revealed six key miRNAs (miR-203b, miR-214, miR-4772, miR-141, miR-200a, and miR-200b) that were closely associated with varying degrees of TCD. These prognostic miRNAs not only exhibited distinct expression patterns across four identified TCD subtypes (from low to high TCD severity) but also demonstrated strong predictive performance in classifying patients with different levels of TCD. The identified miRNA signatures serve as reliable biomarkers for stratifying patients into high-risk and low-risk groups, with higher TCD levels correlating to poorer overall survival. In addition to miRNA biomarkers, we observed that patients with severe TCD exhibited increased infiltration of immune cells and macrophages and dysregulation of DNA methylation patterns. Patients with higher degrees of TCD displayed low methylation levels, which further contributed to the progression of T cell dysfunction. In summary, our study highlights the pivotal role of miRNA biomarkers in shaping the landscape of T cell dysfunction across cancers. These miRNAs serve as both prognostic indicators and predictive tools, enabling accurate classification of TCD severity and offering new avenues for therapeutic exploration and patient stratification in cancer immunotherapy.

Although some patients with cervical cancer respond well to therapy, others show minimal response and develop recurrence after treatment. A better understanding of the molecular features that distinguish and drive the variable responses to therapy is needed to improve patient stratification and treatment. In this issue of Cancer Research, Sandoval and colleagues conduct integrated multiomic analyses of longitudinal patient cohorts to characterize the molecular and cellular reprogramming induced by chemoradiation therapy (CRT). The analyses show that treatment fundamentally reshapes the tumor microenvironment, inducing a shift from lymphoid-dominant to myeloid-dominant immune infiltration. The authors also identify the induction of MDM2-dependent DNA damage response specifically in tumor cells. Leveraging both treatment-naïve and CRT-exposed patient-derived xenografts, they demonstrate that MDM2 inhibition enhances radiation response, with the greatest efficacy in therapy-resistant tumors. These findings identify MDM2 as a rational, therapy-induced target emerging from unbiased analysis. As the field moves toward integrating targeted therapies and immunotherapy with standard chemoradiation, this study underscores the importance of understanding when, where, and in whom to intervene. See related article by Sandoval et al., p. 1639.