Moving tumor-agnostic therapy to the big stage - translational and molecular oncology highlights from the ESMO Congress 2025.

From laboratory bench to surgical room: Molecular profiling and single-cell technologies in precision surgery for colorectal cancer patients.

Domestic cats are among the most popular companion animals worldwide, with steadily increasing ownership and life expectancy. Paradoxically, despite their high prevalence and shared environmental exposures with humans, cats remain markedly underrepresented in molecular oncology research. Cancer is a leading cause of feline mortality, and alimentary lymphoma (AL) has emerged as one of the most common feline malignancies, yet its molecular landscape remains poorly characterized. This review summarizes current knowledge on feline AL, including epidemiology, risk factors, classification schemes, diagnostic challenges, treatment outcomes, and survival, with particular emphasis on low-grade alimentary lymphoma (LGAL), the most prevalent subtype. We discuss the complex relationship between chronic inflammatory enteropathies and lymphoma, highlighting diagnostic ambiguities and the inflammatory-neoplastic continuum. Importantly, we provide a critical overview of existing genomic, transcriptomic, epigenomic, proteomic, and metabolomic studies in feline AL, revealing a striking paucity of high-throughput, multi-omics analyses based on clinical material. Recent advances in feline genome assembly and annotation offer new opportunities to address these gaps. Furthermore, we compare feline AL with its human gastrointestinal T-cell lymphoma counterparts, demonstrating substantial molecular homology across key oncogenic pathways, including JAK/STAT signaling. This comparative perspective underscores the potential of feline AL as a naturally occurring model for the human disease. We conclude that comprehensive molecular characterization of feline AL is urgently needed to improve diagnostics, prognostication, and targeted therapies, with likely translational benefits for both veterinary and human oncology. Aim: The goal of this review is to summarize the current knowledge on feline alimentary lymphoma, including its origin, risk, classification, treatment approaches, and especially molecular landscape, which still remains poorly investigated with modern high-throughput techniques.

Sex differences play a crucial role in determining tumor incidence, treatment sensitivity, and prognosis among men and women. However, current clinical cancer treatment strategies fail to account for these differences. Furthermore, the underlying mechanisms of tumor disparities between sexes remain elusive. Sex differences in sex chromosomes, hormone levels, metabolism, and immunity synergistically contribute to tumor-related disparities. As the demand for precision medicine escalates, there is an urgent need to conduct further exploration and research to address the tumor differences between sexes. In this review, we discuss the impact of biological sex differences on tumor cells and the tumor microenvironment, aiming to identify more effective strategies for tumor prevention and treatment.

Transcriptome-wide RNA Stability Across Cancers Reveals Therapeutic Vulnerabilities.

Organoids as a new approach in advancing cancer therapies for hematologic malignancies.

Cancer-associated fever, localized tumour hyperthermia, iron accumulation, and solid mass formation are consistently observed clinical phenomena, yet they remain mechanistically fragmented across molecular, genetic, and inflammatory explanations. In this theory-forward article, we advance Intrinsic Gravitational Thermogenesis (IGT) as a unifying physical principle governing energy dissipation, mass clustering, and thermal retention across scales—from stellar evolution to embryogenesis and oncogenesis. Drawing on astrophysics, thermodynamics, bone–marrow physiology, and cancer biology, we propose that iron acts as a conserved thermophysical mediator linking gravitational compression in stars with metabolic–structural heat generation in tumours. This framework does not displace molecular oncology but embeds it within a deeper energetic and physical architecture, offering a scale-invariant theory of growth, fever, and pathological mass formation.

Transcriptomic profiling is a cornerstone of molecular biology and plays a central role in translational and molecular oncology, where reliable gene expression measurements are essential. Targeted RNA sequencing approaches offer several advantages over whole-transcriptome methods, including high sensitivity, reproducibility, and reduced turnaround time, particularly when working with formalin-fixed paraffin-embedded (FFPE) samples. HTG EdgeSeq HTP has previously addressed these needs; however, the recent discontinuation of this platform has created a technical gap for targeted transcriptome analysis in FFPE specimens. In this study, we perform a systematic technical comparison between HTG EdgeSeq HTP and an analogous targeted platform, TempO-Seq, to assess its suitability as an alternative for research applications in molecular oncology. We analyzed 21 FFPE endometrial cancer samples together with three RNA reference controls derived from cell lines and evaluated concordance across multiple levels of biomarkers, ranging from individual transcripts to complex multi-gene signatures comprising tens to thousands of genes. While single-gene measurements showed limited concordance between platforms, multi-gene biomarkers exhibited substantially higher agreement, indicating that aggregation across multiple probes mitigates platform-specific effects. Overall, our results demonstrate that TempO-Seq provides comparable performance to HTG EdgeSeq HTP at the level of multi-gene biomarkers, supporting its use as a robust alternative for targeted transcriptomic profiling of FFPE samples in molecular oncology research.

Background: In the past decade, the median overall survival for breast cancer has improved from 11 months to a 5-year survival rate of 17.8%. This is largely feasible solely thanks to molecular oncology. The metabolic characteristics of cancer cells contrast with those of normal cells. Signal transducer and activator of transcription 3 (STAT3) is an important breast cancer-related gene, which can promote the progress of breast cancer. It has been proved in clinical and basic research that over-expressed and constitutively activated STAT3 is involved in the progress, proliferation, metastasis and chemotherapy resistance of breast cancer. Flavonoids exhibit antioxidant, antiviral, anticancer, and anti-inflammatory properties. These inexpensive pharmaceutical compounds exhibit considerable biological activities and are advantageous for various chronic conditions, including cancer. Purpose: This study aimed to assess the novel herbal STAT 3 inhibitor targeting Breast cancer through in-silico molecular docking. Method: STAT 3 was chosen as the target proteins in the current investigation. The bond was found using the Auto Dock software using a grid-based docking method. Compounds' 2D structures were generated, converted to 3D, and subsequently energetically lowered up to an arms gradient of 0.01 using the Merck Molecular Force Field (MMFF). Result: Structural based flavones derivatives (Chrysin, Apigenin, Luteolin & Scultellarein) found to be effective anti-lung cancer component and effectively binds to be target protein STAT 3 with binding energy-5.89, -5.6, -5.96 &-5.96 kcal/mol for Chrysin, Apigenin, Luteolin & Scultellarein respectively and showed potent inhibitory action on STAT 3. Conclusion: The results of the current investigation demonstrated that the chosen lead molecules had significant inhibitory effects on the target STAT 3 enzyme, consequently disrupting mitosis and genomic integrity in cancer cells. The molecular docking analysis demonstrated significant binding energy.

Cancer is a leading cause of mortality worldwide and the focus of priority programs and strategies for scientific and technological development in public health and health promotion. Modern screening technologies are aimed at early cancer diagnosis to improve treatment outcomes; however most of them are characterized by invasiveness and low patient compliance. Therefore, non-invasive cancer diagnosis is a promising field in molecular biology and oncology. Advances in molecular genetics and bioinformatics have enabled the identification of a wide range of diagnostic, prognostic, and predictive biomarkers, which can be analyzed not only in tumor tissue samples but also in peripheral blood. the purpose of the study was to analyze and summarize current scientific and practical data in the field of non-invasive cancer screening using molecular biological analysis, development of innovative test systems and diagnostic kits, as well as issues of legal regulation and integration into medical and social insurance programs. Material and Methods . The study was based on Russian and international scientific databases, including the National Library of Medicine using the PubMed electronic resource, Elibrary, and Google scholar search results. Open internet resources were also searched using the keywords: cancer; malignant neoplasm; tumor; diagnostic; non-invasive; early; blood; Blood-based tests; test system; screening; pancancer; multi-cancer; sequencing; PCR; marker; DNA; cfDNA; multi-cancer early detection; MCED. The analytical review included clinical trial reports, meta-analyses, systematic reviews, and cohort randomized trials for the period 2008–2025. Results. There is a steady trend worldwide towards the widespread adoption of universal, non-invasive methods for early cancer diagnosis. Retrospective and prospective multicenter studies and meta-analyses conducted over the past 15 years have demonstrated advances in interdisciplinary multimodal analysis of diverse patient data (clinical, genomic, transcriptomic, epigenomic, etc.), emphasizing the cost-effectiveness of these methods. Conclusion . Currently, large-scale population-based studies considering race and ethnicity are vital for validating methodological approaches and evaluating the effectiveness of non-invasive cancer screening methods, especially in diverse nations like Russia.

A crucial step in molecular oncology diagnostics is the acquisition of high-quality genomic DNA. However, DNA extracted from melanocytes frequently contains melanin a potent PCR inhibitor that co-purifies with nucleic acids. This contamination can significantly impair both research applications and molecular diagnostic assays essential for targeted therapies. To address the inhibitory impact of melanin on PCR amplification, particularly in DNA isolated from pigmented tissues such as melanoma lesions, we propose a rapid, efficient, and straightforward protocol for eliminating melanin contamination. PCR and Sanger sequencing were performed on 15 pigmented tissue specimens for which prior molecular testing and genotyping had yielded inconclusive results. Pre-treatment of sample lysates with phenol prior to DNA extraction significantly enhanced the removal of PCR inhibitors, improved DNA purity, and resulted in higher PCR amplification and genotyping success rates. This protocol enables simultaneous DNA extraction and purification, thereby enhancing the accuracy of genetic analyses, improving consistency in molecular biology and diagnostic research, and supporting more informed therapeutic strategies for patients with melanoma.

The diagnosis, management and potential eradication of cancer depend on tumour type, stage, extent and anatomical location. While surgery, chemotherapy and radiotherapy remain central, advances in molecular oncology have shifted treatment toward personalised approaches. Identification of tumour-specific molecular abnormalities and biomarkers has enabled targeted therapies that eliminate malignant cells while limiting damage to normal tissues. Cancer immunotherapy has emerged as a promising, non-invasive strategy that activates the immune system to recognise and attack tumour-specific antigens. Preventive vaccines based on weakened or inactivated viruses have achieved notable success in reducing virus-associated cancers. Therapeutic vaccines targeting tumour-associated antigens (TAAs) and patient-specific neoantigens aim to elicit strong cytotoxic and helper T-cell responses against established tumours. Advances in genomic sequencing, bioinformatics-driven neoantigen prediction and single-cell profiling now enable accurate identification of tumour-specific targets. This review highlights progress in cancer vaccine research, focusing on strategies targeting TAAs, neoantigens and delivery platforms such as dendritic cell-based systems, nucleic acid vaccines (DNA and mRNA), synthetic long peptides and viral or bacterial vectors. Clinical evidence shows that neoantigen vaccines induce potent tumour-specific T-cell responses with minimal autoimmunity and gain enhanced efficacy when combined with immune checkpoint inhibitors or adoptive T-cell transfer (ACT) using tumour-infiltrating lymphocytes (TILs). By reinvigorating anti-tumour T cells within the tumour microenvironment, these combination approaches support durable tumour regression and improved outcomes. Despite unresolved challenges, advances in AI-guided target discovery, nanotechnology-based delivery systems and scalable manufacturing offer promising solutions for achieving precise and durable cancer treatment.

Hematologic malignancies and an overview of emerging therapies for hematologic malignancies: a systematic review.

Precision Oncology in Pancreatic Cancer and Future Treatment Directions.

A context-augmented large language model for accurate precision oncology medicine recommendations.

BackgroundColon adenocarcinoma (COAD) remains a leading cause of cancer-related mortality worldwide. Although tumor deposits (TDs) are established prognostic indicators, their molecular characteristics and potential for improving risk stratification remain unexplored.MethodsWe performed an integrative analysis of transcriptomic and clinical data from TCGA and GEO databases to identify TD-associated molecular signatures. A hybrid ML framework combining random survival forest and stepwise Cox regression was developed to construct a risk stratification model. Model performance was validated through survival analysis, time-dependent ROC curves, and multivariate analyses. Gene set enrichment analysis explored underlying mechanisms and therapeutic implications.ResultsThe integrated molecular signature–based model demonstrated superior prognostic accuracy, effectively stratifying patients into risk groups with distinct survival outcomes (P < 0.001) and clinicopathological features. High-risk patients exhibited enhanced immune evasion mechanisms and differential drug sensitivity patterns. Pathway analysis revealed significant alterations in ECM receptor interaction, PPAR signaling, and neuroactive ligand-receptor interaction pathways.ConclusionsOur machine learning–based integration of TD molecular signatures establishes a robust risk stratification model for COAD patients, offering improved prognostic accuracy and valuable insights for personalized treatment strategies. Our findings highlight the potential of interpretable machine learning in molecular oncology risk modeling.Supplementary informationThe online version contains supplementary material available at 10.1007/s00384-025-05073-8.

Innovative Research Organization to Facilitate Clinical Trials Implementation in the Era of Molecular Oncology: The Spiderweb Model of the Oncodistinct Network.

The limiting dilution assay (LDA) is a key method to quantify clonogenic cells with self-renewing capacity in vitro, crucial for preclinical cancer research and therapy response assessment. It estimates the frequency of individual clonogenic, stem-like cells within a population based on their ability to form colonies with ≥50 cells at limiting cell numbers. Standard LDA analysis relies on linear, single-hit Poisson models, yet clonogenic growth under single-cell conditions often involves cooperative or competitive dynamics, violating this linearity assumption. Here, we present a modeling framework incorporating non-linear population dynamics into LDA analysis and introduce LDAcoop, an R-based tool for universal quantification of clonogenic cells in LDA formats. Across multiple cancer cell types, we benchmarked LDA against the colony formation assay (CFA) and show that LDA outperforms CFA, especially for patient-derived organoids, suspension cultures, and higher throughput applications. This renders the LDA format particularly suitable for larger-scale pharmacogenomic screening and drug sensitivity testing in complex models. Our results establish LDA and LDAcoop as versatile, scalable tools for robust quantification of clonogenic growth, supporting preclinical drug development and molecular precision oncology research.

Lung cancer is the leading cause of cancer-related mortality worldwide, with non-small cell lung carcinoma (NSCLC) comprising over 85% of cases. Advances in molecular diagnostics and precision oncology have shifted treatment toward mutation-driven strategies, resulting in significantly improved patient outcomes. This review synthesizes current evidence on the most clinically relevant genetic alterations in NSCLC and their corresponding targeted therapies, including epidermal growth factor receptor (EGFR) mutations, anaplastic lymphoma kinase (ALK) rearrangements, ROS1 fusions, BRAF V600E mutations, MET exon 14 skipping mutations, RET and NTRK fusions, HER2 alterations, and KRAS G12C mutations. We outline mechanisms of action, clinical efficacy, and limitations of FDA-approved tyrosine kinase inhibitors (TKIs) and emerging agents, with emphasis on resistance pathways, both on-target and bypass-mediated, observed during treatment with drugs such as osimertinib, crizotinib, sotorasib, and entrectinib. The role of next-generation sequencing (NGS), liquid biopsy, and comprehensive biomarker profiling in guiding personalized therapy selection is also discussed, along with strategies for sequential therapy and rational combination approaches.

Metastatic bladder cancer (mBC) continues to resist current treatment approaches, largely because aberrant microRNAs (miRNAs) simultaneously fuel epithelial-mesenchymal transition, enable immune system evasion, and promote resistance to therapies. Mounting evidence pinpoints miR-21 as a key oncomiR that amplifies PI3K/AKT signaling, while miR-200c plays a counterbalancing role by maintaining epithelial traits and promoting apoptosis. This makes the combined strategy of suppressing miR-21 while restoring miR-200c an especially compelling, though technically intricate, therapeutic target. Recently, two-dimensional transition-metal carbides and nitrides-known as MXenes-have emerged as promising tools, thanks to their exceptionally high surface area, excellent conductivity, and customizable surface chemistry, all of which make them ideal for shielding miRNAs, delivering them selectively to tumors, and enabling real-time photothermal monitoring. In this review, we weave together insights from epidemiology, molecular oncology, and nanotechnology to chart a translational pathway for applying MXene-based theranostic systems in mBC. We compile mechanistic data regarding miR-21 and miR-200c, detail the MXene physicochemical traits crucial for RNA loading and biosensing, and critically assess polymer-, ligand-, and ion-intercalation methods that improve biocompatibility without compromising electrical performance. Notably, preclinical studies show that MXene scaffolds can co-deliver anti-miR-21 and miR-200c mimics, destroy tumors via near-infrared photothermal therapy, and allow for electrochemical tracking of miRNA activity inside tumors-together achieving a potent, combined blockade of metastatic processes. Persistent challenges, including oxidative degradation, dose-dependent toxicity, and large-scale manufacturing, are addressed alongside promising innovations such as biodegradable surface coatings and machine-learning-assisted material design. Altogether, dual-miRNA theranostics using MXenes hold immense promise as transformative tools for precision treatment of metastatic bladder cancer.