Nucleolar-spindle-associated protein 1 (NUSAP1) participates in the assembly of microtubules and the mitotic spindle. Mitotic spindles are microtubule-based structures that segregate chromosomes during mitosis. Its overexpression and knockdown caused alterations in gene expression programs linked to tumor progression. It was also identified as one of the potential hub genes in various cancers, including the mediation of hepatocellular carcinoma. The present research addresses the NUSAP1 protein structure refinement and its targeting by the lead molecules identified using various computational approaches. The initial structure of NUSAP1 from the Alpha fold database is evaluated using the Ramachandran plot and subjected to multiple energy minimization steps through the YASARA program. The best-optimized structure of NUSAP1 is obtained and subjected to binding site analysis and virtual screening studies using I-TASSER and Mcule webservers, respectively. From the binding site analysis, His293 was considered the ligand binding site for docking ligands by AutoDock Vina. Selected ligands from the Mcule chemical library were chosen through various filters, and 50 hits were identified for further studies. Among the 50 hits, 27 were identified as non-toxic molecules using a toxicity checker. Further, based on the RO5 violation check, 18 hits exhibited no RO5 violations. Further, for all 18 hits, LigPlot analysis was performed, and 11 hits exhibited hydrogen and hydrophobic interactions with the NUSAP1 protein. Among 11, three hits showed promising hydrogen and hydrophobic interactions near the potential binding site His293. For the promising three hits with Mcule IDs 9300000909-0-6, 9753624331-0-3, and 1764527053-0-4, ADMET properties were predicted using the PreADMET server. The comparative studies of drug-likeness properties found that all three hits do not violate Lipinski's rule of 5. The comparative studies of ADME properties of three hits found that the 9753624331-0-3 compound exhibits non-inhibiting properties in liver enzymes and p-glycoprotein inhibition. Furthermore, 9753624331-0-3 is computed as the lowest solvation-free energy of -18.1300000 and found to be non-mutagenic, negative for all toxicity studies, including the Ames test, fishes, rats, mice, and daphnia. Based on the drug-likeness, ADME, and toxicity predictions, the 9753624331-0-3 presented favorable properties and hence may be considered the potential lead targeting the NUSAP1 protein.

Immunogenic cell death (ICD) is a regulated form of cell death that elicits an adaptive immune response, recognized as a promising strategy in cancer immunotherapy. Its therapeutic efficacy, however, can be influenced by tumor-intrinsic factors, particularly in heterogeneous diseases like breast cancer (BC). This study investigated the ICD-related gene expression signature in BC using the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) cohorts. Analysis revealed significantly elevated expression of HSP90AA1, CXCR3, MYD88, FOXP3, PDIA3, XBP1, and IFNB1, and reduced expression of P2RX7 in BC tissues compared with normal tissues. Furthermore, the expression of these genes varied significantly across distinct BC subtypes, patient ages, and tumor stages. Concurrently, an investigation into the UPR pathway, known to intersect with ICD, highlighted Binding immunoglobulin Protein (BiP/GRP78/HSPA5) as a molecule of interest. To explore potential modulators of this pathway, in silico docking studies were performed, which predicted favorable binding interactions of quercetin and taxifolin with BiP. These findings suggest that characterizing the expression patterns of these ICD-related genes and UPR components could inform the development of personalized immunotherapeutic strategies for BC, tailored to specific tumor subtypes, stages, and patient demographics. Further exploration of BiP's role and its potential for therapeutic manipulation may offer novel avenues to enhance anti-tumor immunity.

Key molecular pathways involved in colorectal cancer (CRC) progression include the activation of the heat shock protein 90 (HSP90) pathway, PI3K/AKT, TP53, and mismatch repair (MMR) pathways. In the current study, we identified that FKBP4 is overexpressed at the transcript and translational levels in CRC patient samples, suggesting it may be a predictive biomarker for diagnosis. Our STRING network data analysis identified a strong association (string score: 0.999) between FKBP4 and HSP90. HSP90 is involved in stability, transportation, and protein folding. TCGA CRC patient samples data revealed a strong positive correlation between FKBP4 and HSP90. Furthermore, molecular docking, dynamics simulations, and hydrogen bond analysis confirmed a strong interaction between FKBP4 and HSP90, suggesting its importance in CRC cell survival and progression. These findings highlight that disrupting the FKBP4-HSP90 complex could be a promising therapeutic approach for CRC.

The cyclic GMP-AMP synthase (cGAS)-stimulator of interferon (IFN) genes (STING) pathway emerges as a dual-functional role in urologic malignancies, exhibiting context-dependent tumor-suppressive and pro-tumorigenic activities. When this pathway is activated in urologic tumors, IFN transcription and CD8+ T cell infiltration are triggered, which has an anticancer effect. However, this pathway facilitates the development of prostate cancer through the up-regulation of regulatory B cells. STING palmitoylation triggers immune escape in renal cell carcinoma, and the STING/SLC14A1 axis also mediates chemoresistance in bladder cancer.

Tropomyosin 3 (TPM3), one of the four tropomyosin genes, is predominantly expressed in eukaryotic cells. As a crucial regulatory protein, TPM3 associates with actin within thin myofilaments, thereby playing an essential role in the regulation of muscle contraction. Beyond its fundamental function in muscle physiology, TPM3 is implicated in oncogenesis.

Pediatric diffuse low-grade gliomas (LGGs) are heterogeneous group of central nervous system tumors that typically exhibit a relatively benign clinical course. These tumors represent a unique classification in pediatric neuro-oncology, distinct from adult counterparts in terms of biological behavior, molecular pathways, and clinical presentation. The evolving World Health Organization classification system has increasingly relied on combination of histopathologic, genetic, and radiologic criteria to define and distinguish among pediatric glioma subtypes. This article aims to synthesize current knowledge regarding the clinical, molecular, and radiologic features of these pediatric diffuse LGGs and highlights the nuances in diagnosis, treatment approaches, and prognostic outlook.

The 5th edition of the WHO CNS tumor classification (2021) emphasizes molecular alterations, especially in pediatric tumors, integrating histology with molecular profiling for precise diagnosis. Advances like DNA methylation profiling and Next Generation Sequencing have refined tumor subtypes, influencing targeted therapies. Radiogenomics correlates imaging features with genetic profiles, enabling non-invasive tumor characterization, crucial in pediatric cases where biopsies are risky. Artificial intelligence, including machine learning and deep learning, enhances image analysis, segmentation, and prediction of molecular markers, supporting personalized treatment. Despite challenges like data variability and ethical concerns, these technologies promise to revolutionize pediatric neuro-oncology.

Tumor predisposition syndromes (TPS) are inherited cancer syndromes linked to approximately 10% of all cancers and up to 20% pediatric central nervous system (CNS) tumors. TPS manifest with characteristic patterns of neoplasms throughout the body and require targeted, region-specific imaging for surveillance. Advances in cancer genomics have allowed options for therapies targeting specific molecular pathways. This article highlights CNS imaging features of TPS, with additional insights into the underlying genomic alterations that lead to their development.

Afatinib, an irreversible ErbB family inhibitor, is approved for the treatment of non-small cell lung cancer (NSCLC) with both common and selected uncommon EGFR mutations. Evidence in end-stage renal disease (ESRD) patients undergoing hemodialysis (HD) is scarce, especially with pharmacokinetic (PK) data. Here, we report the case of a patient with metastatic NSCLC harboring an EGFR G719C mutation who was successfully treated with afatinib during regular hemodialysis. Afatinib was initiated at 20 mg once daily under fasting conditions and later escalated to 30 mg once daily. PK sampling was conducted on two consecutive HD days at each dose level. At 20 mg, the trough concentration (Ctrough) was 4.02 ng/mL, with peak concentrations (Cmax) of 6.09 and 8.75 ng/mL, both lower than reported values in patients with normal renal function. At 30 mg, Ctrough increased to 26.3 ng/mL, while Cmax values of 48.2 and 55.5 ng/mL were comparable to steady-state exposures in patients with preserved renal function. Notably, no adverse events were observed, and the patient has maintained a partial response for over eight months. This case suggests that afatinib can be administered without major dose modification in HD patients, with PK data indicating minimal impact of dialysis and underscoring the importance of accumulating real-world evidence in this underrepresented population.

"Lineage switch" is a term used to describe the phenomenon of change of lineage of acute leukemia to a different lineage. It is typically seen during therapy or at the time of relapse. More commonly, it is described in the pediatric population with an incidence of 6-9%. Lineage switches, though uncommon, can occur from acute myeloid leukemia (AML) to acute lymphoblastic leukemia (ALL (B/T)) and vice versa. The present scenario of AML to B-ALL switch is rare in an adult, with only a handful of cases described in literature. We report herein a case diagnosed as AML at 56 years of age, with NPM mutation who relapsed after 18 months post initial diagnosis. The clinicopathological features, flowcytometry, and molecular characteristics are discussed.

Succinate dehydrogenase (SDH) deficient gastrointestinal stromal tumor (GIST) is the most common type of wild type GIST characterized by lack of mutations in proto-oncogene receptor tyrosine kinase (KIT) or platelet-derived growth factor receptor alpha (PDFGR alpha) pathways. It has a unique predilection for females and young adults, with a relatively indolent prognosis and varied treatment modalities. Data regarding SDH GIST from the Indian subcontinent is sparse.

Histone 3 lysine 27 (H3K27) demethylation is a key post-translational modification of chromatin and plays a fundamental role in gene activation. Demethylation of H3K27 is mediated by Jumonji C domain-containing lysine demethylase 6 A (KDM6A) and its paralog, KDM6B, both of which are responsible for homeostasis, autoimmune response, infectious diseases, and cancers. To date, mounting studies dedicate the roles of KDM6A/B on tumor promotion or suppression, and there are many reviews systematically summarize the relevant mechanisms of KDM6A/B in tumor development and therapy. KDM6A and KDM6B also contribute to the regulation of therapeutic insensitivity to chemotherapy, targeted response, radiotherapy and immunotherapy. Herein, we outline the current knowledge of KDM6A/B in regulation of therapeutic resistance, and suggest that KDM6A/B holds immense potential in recovering therapeutic resistance.

Von Hippel-Lindau (VHL) disease is a rare inherited tumor syndrome characterized by the development of multiple neoplasms. The broad variability in clinical manifestations makes this entity susceptible to being overlooked during clinicpathological diagnosis. A female patient in her late 20s presented with multiple adrenal masses during a routine health check-up, with associated dizziness and palpitations lasting 1 month. Laboratory studies revealed plasma-free normetanephrine level of 2894.9 pg/ml. Abdominal contrast-enhanced computed tomography showed multiple lesions consisting of bilateral adrenal masses and retroperitoneal nodules. Postoperative pathological examination demonstrated the diagnosis of bilateral adrenal pheochromocytomas, retroperitoneal paraganglioma, and pancreatic neuroendocrine tumor. Molecular genetic testing detected a pathogenic germline mutation in the VHL gene (c.499C > T: p.R167 W). Subsequent brain magnetic resonance imaging revealed a hypervascular cerebellar nodule. Genetic and clinical findings confirmed a definitive diagnosis of VHL syndrome type 2B. The diverse manifestations of VHL syndrome often cause diagnostic delays. Analyzing this case alongside the literature highlights the need to suspect VHL in young patients with multiple tumors, for whom genetic testing is crucial for definitive diagnosis. While a single case cannot capture the full disease spectrum, it provides valuable clinical insight.

Multi-omics strategies, integrating genomics, transcriptomics, proteomics, and metabolomics, have revolutionized biomarker discovery and enabled novel applications in personalized oncology. Despite rapid technological developments, a comprehensive synthesis addressing integration strategies, analytical workflows, and translational applications has been lacking. This review presents a comprehensive framework of multi-omics integration, encompassing workflows, analytical techniques, and computational tools for both horizontal and vertical integration strategies, with particular emphasis on machine learning and deep learning approaches for data interpretation. Recent applications of multi-omics have yielded promising biomarker panels at the single-molecule, multi-molecule, and cross-omics levels, supporting cancer diagnosis, prognosis, and therapeutic decision-making. However, major challenges persist, particularly in data heterogeneity, reproducibility, and the clinical validation of biomarkers across diverse patient populations. This review also highlights cutting-edge advances in single-cell multi-omics and spatial multi-omics technologies, which are expanding the scope of biomarker discovery and deepening our understanding of tumor heterogeneity. Finally, we discuss the integral role of multi-omics in personalized oncology, with a particular focus on predicting drug responses and optimizing individualized treatment strategies, supported by real-world clinical practice cases. By bridging technological innovations with translational applications, this review aims to provide a valuable resource for researchers and clinicians, offering insights into both current methodologies and future directions for implementing multi-omics data in biomarker discovery and personalized cancer care.

The transient receptor potential melastatin (TRPM) family consists of eight members (TRPM1-8), which play a pivotal role in regulating cation fluxes, including K+, Na+, Ca2+, and Mg2+. While these channels are integral to various physiological functions, emerging evidence links TRPM dysregulation to the pathogenesis of colorectal cancer (CRC), one of the most prevalent and deadly malignancies worldwide. This review highlights the multifaceted roles of TRPM channels in CRC pathogenesis, their potential as diagnostic and prognostic biomarkers, and their therapeutic applications. Recent research has revealed that certain types of TRPM channels and specific noncoding RNAs within TRPM loci are implicated in critical oncogenic processes such as proliferation, migration, invasion, and epithelial-mesenchymal transition. Specific members, including TRPM4, TRPM7, and TRPM8, exhibit diverse effects in CRC, ranging from modulating metastasis to influencing chemoresistance. Despite their significant role in CRC, conflicting findings on TRPM expression levels in patient tissues highlight the complexity of their involvement and necessitate further research. TRPM modulators show therapeutic potential as anticancer agents. However, challenges in specificity and off-target effects currently limit their clinical application. Advancing our understanding of TRPM function in CRC could hold promise for novel treatment strategies to improve patient outcomes.

Circulating tumor DNA (ctDNA) enables early detection of ESR1 mutations in hormone receptor-positive, HER2-negative metastatic breast cancer. Building on the PADA-1, the SERENA-6 trial demonstrated significant progression-free survival and quality-of-life benefits from ctDNA-guided early endocrine switching before radiologic progression.

Non‑small cell lung cancer (NSCLC), accounting for >85% of LC cases, remains a therapeutic challenge due to its low 5‑year survival rate, tumor heterogeneity and drug resistance. The SRY‑related high‑mobility group‑box (SOX) family comprises transcription factors involved in the initiation and progression of NSCLC. These factors regulate epithelial‑mesenchymal transition and angiogenesis, interact with epidermal growth factor receptor/KRAS pathways to influence tumor invasion and promote chemotherapy resistance by sustaining tumor stemness. The present review aimed to summarize the expression patterns, molecular mechanisms and clinical relevance of SOX family members (such as SOX2, SOX4 and SOX9) in NSCLC, as well as their potential as diagnostic biomarkers and therapeutic targets, and the application of emerging technology in elucidating their functions. The present review aimed to provide a theoretical foundation for precision diagnostics and therapeutics to foster more effective NSCLC treatment.

Small cell lung cancer (SCLC) is challenging to manage due to its high malignancy and early metastatic spread. Although initial chemoradiotherapy responses are common, resistance rapidly develops, and long-term efficacy remains limited. Immune checkpoint inhibitors (ICIs) overcome previous survival barriers, extending overall survival (OS) and progression-free survival (PFS) in extensive-stage SCLC. Nevertheless, absolute clinical benefits remain modest. To address efficacy limitations, current research focuses on optimizing first-line strategies by exploring multimodal regimens (e.g., adding targeted therapy or radiotherapy to chemoimmunotherapy) and advancing molecular subtyping for precision oncology. Furthermore, emerging therapies such as DLL3-targeted agents, bispecific antibodies (bsAbs), antibody-drug conjugates (ADCs), and chimeric antigen receptor T-cell (CAR-T) therapy continue to demonstrate clinical progress. This review synthesizes advances in SCLC management, focusing on mechanisms and clinical applications of multimodal strategies and novel therapies. It provides guidance for clinical decisions, research directions, and survival improvement.

Cell death is a fundamental process essential to all living organisms, with apoptosis serving as one of the most crucial pathways across various stages of life. Dysregulation of apoptosis is closely associated with numerous diseases, particularly cancer. PUMA (p53 upregulated modulator of apoptosis) is a key mediator of apoptotic cell death. It is activated in response to a wide range of internal and external signals. Beyond its established role in apoptosis, PUMA also regulates other forms of cell death, including necroptosis, autophagy, and ferroptosis, underscoring its critical role in cancer cell death, especially during chemotherapy. However, PUMA activation is frequently impaired in many cancers, leading to resistance to cell death and treatment failure. This review highlights recent advancements in understanding the regulation of PUMA expression at multiple levels, including epigenetic, transcriptional, post-transcriptional, and post-translational mechanisms. It also examines the influence of diverse cellular regulators, such as epigenetic modifiers, transcription factors, non-coding RNAs, kinases, and ubiquitin ligases in modulating PUMA activity. Additionally, we discuss PUMA's role in cancer progression, its impact on the effectiveness of anti-cancer therapies, and its potential as a prognostic biomarker for therapeutic resistance. Finally, we propose critical questions to inspire future research, aiming to deepen the understanding of PUMA regulation and its significance in cancer therapy.

Cancer's staggering molecular heterogeneity demands innovative approaches beyond traditional single-omics methods. The integration of multi-omics data, spanning genomics, transcriptomics, proteomics, metabolomics and radiomics, can improve diagnostic and prognostic accuracy when accompanied by rigorous preprocessing and external validation; for example, recent integrated classifiers report AUCs around 0.81-0.87 for difficult early-detection tasks. This review synthesizes how artificial intelligence (AI), particularly deep learning and machine learning, bridges this gap by enabling scalable, non-linear integration of disparate omics layers into clinically actionable insights. We explore cutting-edge AI methodologies, including graph neural networks for biological network modeling, transformers for cross-modal fusion, and explainable AI (XAI) for transparent clinical decision support. Critical applications are highlighted, such as AI-driven therapy selection (e.g., predicting targeted therapy resistance), proteogenomic early detection, and radiogenomic non-invasive diagnostics. We further address translational challenges: data harmonization, batch correction, missing data imputation, and computational scalability. Emerging trends, federated learning for privacy-preserving collaboration, spatial/single-cell omics for microenvironment decoding, quantum computing, and patient-centric "N-of-1" models, signal a paradigm shift toward dynamic, personalized cancer management. Despite persistent hurdles in model generalizability, ethical equity, and regulatory alignment, AI-powered multi-omics integration promises to transform precision oncology from reactive population-based approaches to proactive, individualized care.