Abstract Introduction: Anaplastic Thyroid Cancer (ATC) is characterized by rapid progression and unclear dissemination mechanisms. Tumor evolution is not solely defined by the selective pressure acting on pre-existing subclones, but is intricately intertwined with the rapid, environmentally mediated acquisition of adaptive phenotypes. Metabolic plasticity is a critical process that lies at the intersection of these complementary evolutionary paradigms, actively fueling malignant progression and conferring metastatic competence. Elucidating how metabolic rewiring contributes to the emergence and expansion of highly invasive ATC clones is critical to counteract TC progression Experimental procedures: We established a TC tumorigenesis model by leveraging human embryonic stem cells and CRISPR/Cas9 genome engineering to generate distinct TC progenitor cells, harbouring specific mutations. We developed highly invasive in vitro TC cells to identify the metabolic signatures linked to cellular aggressiveness. The data were corroborated in orthotopic TC mouse models, which recapitulated the disease progression. The metabolic profile was characterized by measuring oxygen consumption rate (OCR), extracellular acidification rate (ECAR). RNA-seq data were analyzed to obtain transcriptomic and metabolism-related signatures associated with specific genetic background. Cells were treated with MitoQ, Treatment effects were assessed on primary tumor growth and metastatic dissemination. New, unpublished data: We observed that BRAF V600E single/double-mutated cells cluster based on their metabolic profile and undergo a similar metabolic shift during the selection of super-invasive subpopulations. BRAFV600E-mutated ATC-derived aggressive clones experience a reprogramming toward oxidative phosphorylation (OXPHOS). ATC superoxide clones exhibit heightened mitochondrial respiration, increased mitochondrial membrane potential, and accumulation of mitochondrial reactive oxygen species, in line with their enhanced invasive capacity. Leveraging this metabolic dependency uncovered a therapeutic opportunity: treatment with the mitochondria-targeted antioxidant MitoQ significantly reduced cellular invasiveness in vitro and suppressed lung metastasis formation in vivo in mouse models. This defined metabolic vulnerability provides a distinct signature that may aid in stratifying relevant thyroid cancer patient subsets. Conclusions: Our study demonstrates that mitochondrial metabolic rewiring is not a universal feature of ATC but is instead tightly dictated by the tumor’s genetic background. These findings underscore the critical interplay between genetic context and metabolic adaptation, providing a refined framework for developing targeted therapeutic strategies aimed at pharmacologically restraining the metastatic progression of BRAFV600E-mutated ATC Citation Format: Vincenzo Davide Pantina, Chiara Modica, Francesco Verona, Giulia Bozzari, Roberta Drago, Caterina D'accardo, Gaetana Porcelli, Sebastiano Di Bella, Rosario Brancato, Pierre Sonveaux, Matilde Todaro, Giorgio Stassi. Genetic background shapes mitochondrial metabolic adaptations underlying thyroid cancer progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4722.

Abstract Topic Esophageal Cancer: Molecular Biology/Pathology Background Resistance to perioperative FLOT chemotherapy remains a major determinant of poor outcome in esophageal adenocarcinoma. Epithelial–mesenchymal plasticity (EMP) enables dynamic cell state transitions that may promote adaptive chemoresistance, yet its functional contribution to chemoresistance in esophageal adenocarcinoma remains insufficiently characterized. Methods Esophageal adenocarcinoma cell models were engineered to stably express a dual-fluorescent reporter system driven by E-cadherin and vimentin promoters, allowing real-time visualization of epithelial, mesenchymal, and hybrid epithelial/mesenchymal (E/M) states. Fluorescence-Activated Cell Sorting was used to isolate phenotypically distinct subpopulations. Sensitivity to FLOT chemotherapy was assessed using cell viability and clonogenic survival. Dynamic state transitions were evaluated following chemotherapy exposure. RNA sequencing on sorted populations will enable the identification of transcriptional programs associated with chemoresistance and EMP. Results Distinct epithelial–mesenchymal subpopulations were identified across several cellular models, with marked heterogeneity. One model, FLO1, exhibited all three phenotypic states, including a hybrid E/M population indicative of high plasticity. FLOT chemotherapy exposure induced significant phenotypic shifts toward hybrid states, accompanied by increased survival and persistence of this cell subset. These findings suggest a dynamic, reversible model of chemoresistance driven by EMP rather than fixed cell identity. Conclusion Epithelial–mesenchymal plasticity promotes adaptive resistance to FLOT chemotherapy in esophageal adenocarcinoma by enabling dynamic transitions toward therapy-tolerant states. Defining molecular programs underlying these transitions may support the development of treatment strategies that limit resistance and improve patient response to perioperative chemotherapy.

Abstract Introduction: Papillary Thyroid Carcinoma (PTC) often exhibiting local invasion and the capacity for distant metastasis. While Galectin-3 (Gal-3) is a well-established diagnostic marker, absent in normal thyroid tissue and benign lesions, its intracellular functional role in thyroid cancer remains largely unknown. This study aimed to determine whether cell-autonomous Gal-3 in BRAFV600E mutated cells contributes directly to tumor aggressiveness by activating an invasive and metastatic program. Experimental procedures: We profiled Gal-3 expression in well-differentiated, poorly differentiated, and metastatic TC samples and used genetic modulation in TC cells to test its impact on proliferation, migration, invasion, and cell cycle. Transcriptomic and proteic profile characterization investigated the dormancy pathway and the interaction of Gal-3 with CD44v6 signaling axis to uncover intra and extra-cellular cooperative mechanisms in thyroid carcinoma progression. Synergistic anti-cancer effects of Gal-3 knockdown in combination with chemotherapy were tested both in vitro and in vivo trough ortothopic mouse models, to understand the intracellular Gal-3's impact on primary tumor growth, metastasis and chemosensitivity. New data: Our data establishes Gal-3 as a pivotal molecular character in PTC pathogenesis. Elevated Gal-3 expression is a hallmark of high-grade disease, showing a striking correlation with poorly differentiated and metastatic tumors compared to their well-differentiated counterparts, underscoring its prognostic significance. Mechanistically, the CD44v6 signaling cascade acts upstream, promoting the intracellular accumulation of Gal-3. This accumulation triggers a transcriptional program that simultaneously dictates cell cycle arrest, fuels enhanced migration and invasion, and crucially, activates a disseminated-dormant phenotype.Remarkably, disrupting Gal-3 via knockdown fundamentally destabilizes this dormant state, forcing dormant TC cells to exit quiescence and undergo outgrowth. This vulnerability translates directly into a therapeutic opportunity: combining Gal-3 silencing with standard chemotherapy profoundly sensitizes these slow-cycling, metastatic cells, achieving a synergistic enhancement of therapeutic efficacy. Conclusions: These findings unequivocally position Gal-3 as a functional driver of both invasive potential and the elusive dormant phenotype in TC. Furthermore, its modulation represents a highly promising strategy to re-sensitize slow-cycling, treatment-refractory metastatic TC cells, offering a novel avenue for treating patients with advanced disease. Citation Format: Chiara Modica, Vincenzo Davide Pantina, Francesco Verona, Roberta Drago, Giulia Bozzari, Matilde Todaro, Giorgio Stassi. Targeting intracellular Galectin-3 disrupts BRAFV600E mutated dormant cell dissemination and restores chemosensitivity in thyroid cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6106.

The green oncology paradigm emphasizes the use of natural products in cancer treatment to protect the environment while reducing the adverse effects associated with conventional therapies. In this context, humic substances (HSs), derived from the degradation of waste biomass, have emerged as promising candidates due to their diverse bioactive properties. Beyond their well-known antioxidant and antimicrobial effects, this study demonstrates the antitumor potential of HSs extracted from olive (HS-OL) and artichoke (HS-CYN). Our results reveal that HS-OL and HS-CYN significantly induce DNA damage by triggering apoptosis and reducing cell viability in cancer cells across various histotypes. When used in combination with standard therapies, these HSs enhance therapeutic efficacy, enabling the use of lower doses of chemotherapeutic agents while maintaining their effectiveness. The introduction of HSs into cancer treatment represents a sustainable and innovative approach that not only reduces the ecological footprint but also minimizes the side effects associated with traditional anticancer drugs, offering a dual benefit for both patients and the environment.

BackgroundObesity is a recognized risk factor for numerous cancers. Although several biological mechanisms have been proposed to explain obesity-associated carcinogenesis, the extent to which excess adiposity influences tumor genomic profiles remains incompletely understood. In particular, whether obesity-related selective pressures shape cancer-specific mutational landscapes is still underexplored.MethodsA pan-cancer analysis of non-synonymous somatic mutations across 14 tumor types using data from The Cancer Genome Atlas (TCGA) has been conducted. Body mass index (BMI) at diagnosis was analyzed as a continuous variable. Associations between gene mutations and BMI were assessed using logistic regression models adjusted for age, sex, and tumor mutational burden, with false discovery rate correction. Genes were prioritized using a two-step ranking strategy based on mutation frequency and regression strength. Functional inactivation, exon-level mutation distribution, and Gene Ontology enrichment analyses were performed for significantly BMI-associated genes.ResultsIn particular, bladder urothelial cancer (BLCA) resulted as the most frequently mutated neoplasia in association with higher body mass index. Among Eighty-six genes significantly associated with BMI in BLCA, a prioritized set of ten genes (BRCA2, DNAH9, GRIA4, PLXNA4, UNC13C, FCGBP, SF3B1, ELP1, NES, TRERF1) has been selected for further analyses. Overweight and obese patients exhibited distinct BMI-specific exon-level mutational patterns and concurrent deleterious mutations across multiple candidate genes. Functional inactivation analysis suggested loss-of-function mechanisms in most top-ranked genes, while Gene Ontology (GO) analysis highlighted deregulation of extracellular matrix-related pathways.DiscussionThese findings support a role for obesity in shaping the genomic landscape of tumors, highlighting the importance of integrating clinical parameters such as BMI into genomic studies to determine the potential impact of obesity on tumor evolution, heterogeneity, and treatment response.

MicroRNAs (miRNAs) are among the most studied molecules in recent years, and since their discovery, many miRNAs have been identified across various species. As members of the non-coding RNA family, miRNAs are key players in post-transcriptional gene regulation. These molecules can inhibit translation or promote degradation of messenger RNA (mRNA) by binding to the 3' untranslated region (UTR) of mRNA, thereby influencing almost all biological processes. To identify a miRNA's biological role, it is essential to predict the target sites to which it binds, a goal made possible through bioinformatics tools. This chapter discusses the bioinformatics tools commonly used for this purpose. Also, it analyzes the main factors considered in target prediction, such as seed match, free energy, conservation, site accessibility, multiple binding site contribution, and machine learning and deep learning approaches. Understanding the principles underlying these predictive methodologies is crucial for advancing one's biological research on miRNAs.

Abstract The epidemiological surge of early-onset colorectal cancer (EOCRC) is characterized by accelerated biological kinetics and disproportionately high rates of systemic relapse following curative-intent surgery. Because standard anatomical staging (TNM) lacks the resolution to accurately capture the intrinsic regenerative capacity of microscopic residual disease, we investigated the transcriptomic architecture of post-surgical failure in a strictly defined, curative-intent clinical pan-cohort. Unbiased transcriptomic profiling of the localized (M0) discovery sub-cohort identified IGF2 as the most significantly upregulated correlate of metachronous relapse. High-resolution isoform analysis revealed that this transcriptional output is predominantly driven by the embryonic (P4) and placental (P5) promoters. Systematic allele-specific expression (ASE) analysis supported widespread biallelic IGF2 expression consistent with relaxation of imprinting-domain control. This signal was not restricted to relapsing tumors, suggesting a recurrence-independent oncofetal baseline across the EOCRC spectrum. Because this foundational epigenetic unlocking is functionally insufficient on its own to execute systemic metastasis, we distilled the additional transcriptional plasticity required for dissemination into an internally derived and bootstrap-stabilized 5-gene recurrence-risk module Multivariable analysis across the combined pan-cohort supported an independent association between the high-risk module and systemic relapse (p < 0.001), capturing prognostic dimensions completely unresolved by classical pathological covariates and baseline staging. Ultimately, our findings reframe EOCRC aggressiveness as the product of a dual-hit architecture. This framework resolves the clinical paradox of widespread IGF2 LOI co-existing with heterogeneous outcomes, offering a biologically grounded basis for molecular risk stratification beyond anatomical boundaries.

Cancer progression is an evolutionary process shaped by clonal dynamics within a complex tumor ecosystem. Deciphering tumor evolution solely as the gradual accumulation of mutations that confer selective advantages and promote the expansion of selected cellular clones does not fully capture the complexity and dynamics of cancer development. Emerging evidence increasingly underscores the critical contribution of non-genetic regulatory mechanisms in shaping cellular behavior, revealing a remarkable degree of cellular plasticity that enables cells to dynamically adapt their phenotype and functional state in response to intrinsic and extrinsic cues. In this review, we discuss how tumor evolution is propelled not only by stable genetic mutations, which initiate malignant transformation and confer proliferative advantages, but also by dynamic adaptive programs. These mechanisms, including the epithelial–mesenchymal transition, cellular dormancy and metabolic reprogramming, enable tumor cells to survive microenvironmental stress and facilitate metastatic dissemination. Herein, we conceptualize tumor progression as the evolutionary selection of highly adaptable clonal populations, governed by a synergistic interplay between genetic fitness and cellular plasticity. We propose that understanding the convergence of stable genetic alterations and reversible epigenetic states is critical for developing novel therapeutic strategies to effectively target metastatic disease.

Cancer stem cells (CSCs) drive tumour initiation, progression, metastasis, and therapy resistance through their remarkable plasticity, enabling dynamic transitions between stem-like and differentiated states. A pivotal mechanism underlying this plasticity is epithelial-mesenchymal plasticity (EMP), which encompasses epithelial-mesenchymal transition (EMT), partial or hybrid EMT (E/M) states, and mesenchymal-epithelial transition (MET), allowing cancer cells to acquire invasive, stem-like properties while maintaining proliferative potential. Unlike the traditional binary view of EMT, recent evidence reveals a spectrum of intermediate E/M phenotypes that exhibit increased tumorigenicity, metastatic potential, and therapy resistance. This plasticity is orchestrated by intricate regulatory networks involving EMT-inducing transcription factors, signalling pathways, and non-coding RNAs. The tumour microenvironment (TME), with its cellular and non-cellular components, provides critical extrinsic cues that stabilize E/M states. Notably, metabolic reprogramming cooperates with EMP. Indeed, E/M flexibly shifts between glycolysis, oxidative phosphorylation, and lipid metabolism alterations to fuel invasion, buffer oxidative stress, and evade ferroptosis. Advanced and recently developed in vitro and in vivo models have illuminated these dynamics: dual-fluorescent reporters, microfluidic tumour-on-a-chip, genetically engineered mouse models, bioluminescence imaging, and intravital microscopy enable real-time tracking of EMP during progression and therapy response. On the other side, in silico tools, single-cell/spatial transcriptomics, network inference, machine learning, and agent-based modelling, map hybrid states, predict trajectories, and help identify biomarkers, revealing EMP’s role in evolutionary fitness. Therapeutically, targeting EMP holds promise to target resistant cancer cells and prevent relapse, though challenges arise from redundancy and plasticity. Strategies include pathway inhibitors, metabolic disruptors, epigenetic agents, TME modulators, and differentiation inducers. Combination therapies, guided by EMP biomarkers and rational models, act in combination with standard treatments to lock cells in epithelial states, disrupt hybrid phenotypes, and overcome resistance. This review highlights EMP as the main driver of tumour evolution, offering a unified framework for understanding tumour heterogeneity and heterogeneity-driven failures in therapy. By elucidating molecular mechanisms and vulnerabilities, it paves the way for precision interventions that could transform outcomes in aggressive malignancies, ultimately restraining metastasis and recurrence.

The discovery of microRNAs (miRNAs), small non-coding RNAs approximately 22 nucleotides in length, revolutionized our understanding of post-transcriptional gene regulation in the early part of the twenty-first century. Since then, non-coding RNAs (ncRNAs) have become a major focus of scientific research, revealing their critical roles in cellular processes. Advances in high-throughput sequencing technologies have brought long non-coding RNAs (lncRNAs)-transcripts longer than 200 nucleotides-into the spotlight. While their functions are still being unraveled, lncRNAs have been identified as important regulators within the RNA interference (RNAi) pathway. They contain multiple miRNA response elements (MREs), allowing them to compete with other RNAs for miRNA binding. This competition, known as the competing endogenous RNA (ceRNA) or "sponge RNA" mechanism, has provided new insights into the complexity of gene regulation. This chapter explores the biomedical significance of ceRNAs, highlighting their role in modulating gene expression and their potential implications in disease. The chapter also summarizes available tools, resources, and practical examples for studying lncRNA-miRNA interactions to aid researchers in navigating this sophisticated regulatory network. It aims to support further advancements in this rapidly evolving field by bridging theoretical knowledge with practical applications.

Cancer stem cells (CSCs) are a small subset within the tumor mass significantly contributing to cancer progression through dysregulation of various oncogenic pathways, driving tumor growth, chemoresistance and metastasis formation. The aggressive behavior of CSCs is guided by several intracellular signaling pathways such as WNT, NF-kappa-B, NOTCH, Hedgehog, JAK-STAT, PI3K/AKT1/MTOR, TGF/SMAD, PPAR and MAPK kinases, as well as extracellular vesicles such as exosomes, and extracellular signaling molecules such as cytokines, chemokines, pro-angiogenetic and growth factors, which finely regulate CSC phenotype. In this scenario, tumor microenvironment (TME) is a key player in the establishment of a permissive tumor niche, where CSCs engage in intricate communications with diverse immune cells. The “oncogenic” immune cells are mainly represented by B and T lymphocytes, NK cells, and dendritic cells. Among immune cells, macrophages exhibit a more plastic and adaptable phenotype due to their different subpopulations, which are characterized by both immunosuppressive and inflammatory phenotypes. Specifically, tumor-associated macrophages (TAMs) create an immunosuppressive milieu through the production of a plethora of paracrine factors (IL-6, IL-12, TNF-alpha, TGF-beta, CCL1, CCL18) promoting the acquisition by CSCs of a stem-like, invasive and metastatic phenotype. TAMs have demonstrated the ability to communicate with CSCs via direct ligand/receptor (such as CD90/CD11b, LSECtin/BTN3A3, EPHA4/Ephrin) interaction. On the other hand, CSCs exhibited their capacity to influence immune cells, creating a favorable microenvironment for cancer progression. Interestingly, the bidirectional influence of CSCs and TME leads to an epigenetic reprogramming which sustains malignant transformation. Nowadays, the integration of biological and computational data obtained by cutting-edge technologies (single-cell RNA sequencing, spatial transcriptomics, trajectory analysis) has significantly improved the comprehension of the biunivocal multicellular dialogue, providing a comprehensive view of the heterogeneity and dynamics of CSCs, and uncovering alternative mechanisms of immune evasion and therapeutic resistance. Moreover, the combination of biology and computational data will lead to the development of innovative target therapies dampening CSC-TME interaction. Here, we aim to elucidate the most recent insights on CSCs biology and their complex interactions with TME immune cells, specifically TAMs, tracing an exhaustive scenario from the primary tumor to metastasis formation.

Despite significant improvements in the outcome of Estrogen Receptor (ER) α-positive breast cancer (BC) following the use of endocrine therapies, resistance remains a major challenge. Clinical studies proved that obesity, in addition to promote BC progression, is associated with a reduced efficacy to these treatments, but mechanisms remain unclear. We used co-culture systems followed by validation through an ‘ex vivo’ model of human mammary obese (Ob) adipocytes and obese endocrine-resistant metastatic Patient-Derived Organoids (PDOs). Transcriptomics with MixOmics-MINT and MetaCore Functional Tools along with lentiviral and pharmacological approaches provide insights into mechanisms. Clinical relevance was investigated using public datasets, transcriptome-based (n = 375), and immunohistochemistry-based (n = 65) evaluations. In a model of co-culture, we demonstrated that conditioned media (CM) released by 3T3-L1A adipocytes reduced the sensitivity of parental MCF-7 BC cells to the inhibitory effects of Tamoxifen (Tam) on growth, motility and invasion and significantly increased the proliferative, motile and invasive phenotype of Tam-resistant (TR) BC cells. Transcriptomics identified TXNIP (Thioredoxin-interacting protein), a known tumor suppressor gene, as a network central hub, that was significantly down-regulated in CM-treated MCF-7 and TR cells. Accordingly, TXNIP expression was negatively correlated with Body Mass Index (BMI) in BC patients. Lentiviral TXNIP overexpression and pharmacological induction of TXNIP (i.e. SAHA) or the blockade of insulin-like growth factor-I (IGF-1) signaling, an obesity hallmark able to affect TXNIP expression, reversed CM-mediated effects. TXNIP down-regulation, proliferation and motility in TR cells were exacerbated by CM derived from Ob 3T3-L1A, and combination of an IGF-1 inhibitor and SAHA abrogated Ob-CM activities. Results were also validated in aromatase inhibitor-resistant BC cells. The effectiveness of IGF-1/TXNIP axis inhibition was confirmed using an ‘ex vivo’ model of human mammary obese adipocytes and PDO models. Finally, retrospective analyses demonstrated that an IGF-1high/TXNIPlow signature was correlated with poorer survival in endocrine-treated BC patients. In conclusion, our study sheds new light on adipocyte/BC cell crosstalk, underscoring the potential of targeting IGF-1/TXNIP axis to block this harmful connection, especially in the context of obesity.

In many tumors, the tumor suppressor TP53 is not mutated, but functionally inactivated. However, mechanisms underlying p53 functional inactivation remain poorly understood. SETD8 is the sole enzyme known to mono-methylate p53 on lysine 382 (p53K382me1), resulting in the inhibition of its pro-apoptotic and growth-arresting functions. We analyzed SETD8 and p53K382me1 expression in clinical colorectal cancer (CRC) and inflammatory bowel disease (IBD) samples. Histopathological examinations, RNA sequencing, ChIP assay and preclinical in vivo CRC models, were used to assess the functional role of p53 inactivation in tumor cells and immune cell infiltration. By integrating bulk RNAseq and scRNAseq approaches in CRC patients, SETD8-mediated p53 regulation resulted the most significantly enriched pathway. p53K382me1 expression was confined to colorectal cancer stem cells (CR-CSCs) and C1Q+ TPP1+ tumor-associated macrophages (TAMs) in CRC patient tissues, with high levels predicting decreased survival probability. TAMs promote p53 functional inactivation in CR-CSCs through IL-6 and MCP-1 secretion and increased levels of CEBPD, which directly binds SETD8 promoter thus enhancing its transcription. The direct binding of C1Q present on macrophages and C1Q receptor (C1QR) present on cancer stem cells mediates the cross-talk between the two cell compartments. As monotherapy, SETD8 genetic and pharmacological (UNC0379) inhibition affects the tumor growth and metastasis formation in CRC mouse avatars, with enhanced effects observed when combined with IL-6 receptor targeting. These findings suggest that p53K382me1 may be an early step in tumor initiation, especially in inflammation-induced CRC, and could serve as a functional biomarker and therapeutic target in adjuvant setting for advanced CRCs.

Metastases represent one of the hardest obstacles in cancer treatment, accounting for many cancer-related deaths. Understanding the mechanisms that drive disease progression is essential to improve patient outcomes and develop more effective therapeutic strategies. This phenomenon appears to be elicited by dormant cancer cells (DCCs), which can persist undetected for extended periods of time, entering a non-proliferative, hibernation-like state that confers resistance to conventional therapies and facilitates immune evasion. Owing to their status as a rare and energy-restricted population, combined with the limitations of current medical imaging, DCCs often evade early detection, hindering timely intervention and effective clinical management. Consequently, a critical need exists to develop high-resolution detection systems and identify specific DCC targetable biomarkers. Here, a comprehensive overview of the current understanding of DCCs is reported, with a focus on recent advancements in experimental strategies for their identification and tracking, as well as therapeutic approaches currently under clinical investigation aimed at targeting these elusive cells.

Colorectal cancer (CRC) initiating cells (CICs) possess self-renewal capabilities and are pivotal in tumor recurrence and resistance to conventional therapies, including immunotherapy. The mechanisms underlying their interaction with immune cells remain unclear. We conducted a multi-omics analysis—encompassing DNA methylation, total RNA sequencing, and microRNAs (miRNAs; N = 800) profiling on primary CICs and differentiated tumor cell lines, including autologous pairs. Functional immunological assays were performed to assess the impact of miRNA modulation. CICs exhibited distinct methylation patterns, transcriptomic profiles, and miRNA expressions compared to differentiated tumor cells (p < 0.05 or 0.01). Notably, miRNA-15a and -196a were implicated in regulating tumorigenic pathways, such as epithelial-to-mesenchymal transition (EMT), TGF-β signaling, and immune modulation. The transfection of CICs with miRNA mimics led to the downregulation of oncogenic EMT markers (CRKL, lncRNA SOX2-OT, JUNB, SMAD3) and TGF-β pathway, resulting in a significant reduction of the in vitro proliferation and the tumorigenicity and migration in a zebrafish xenograft model. Additionally, miRNA-15a enhanced the expression of antigen processing machinery and decreased the expression of immune checkpoints (PD-L1, PD-L2, CTLA-4) and immunosuppressive cytokines (IL-4). The co-culture of HLA-matched lymphocytes with CICs overexpressing the miRNA-15a, elicited robust tumor-specific immune responses, characterized by a shift toward central and effector memory T cell phenotypes and prevented their terminal differentiation and exhaustion. The combination of miRNA modulation with Indoleamine 2,3-dioxygenase blockade and immunomodulating agents further potentiated these effects. Our study demonstrates that the modulation of miRNA-15a in CICs not only suppresses the tumorigenic properties but also enhances their visibility to the immune system by upregulating antigen presentation and reducing immunomodulatory molecules. These findings suggest that combining miRNA modulation with epigenetic or immunomodulatory agents holds significant promise for overcoming treatment resistance in CRC.

Despite advances in systemic therapeutic approaches, metastatic colorectal cancer (mCRC) patients harboring BRAF or RAS mutations have poor outcomes. Cancer stem cells (CSCs) play central roles in drug resistance and CRC recurrence. Therefore, targeting the epigenetic mechanisms that sustain CSC properties is a promising therapeutic approach. In this study, we report the efficacy of a treatment strategy with the potential to overcome chemotherapy resistance that involves administering the well-known antiepileptic drug and epigenetic agent valproic acid (VPA) and the standard chemotherapy regimen of oxaliplatin/fluoropyrimidine to wild-type CSCs and CSCs with BRAF and RAS mutations in enriched primary spheroid cultures. Notably, we demonstrated that VPA plus chemotherapy was more effective than other epigenetic drug-chemotherapy combinations by inhibiting cell proliferation and clonogenic growth and by inducing apoptosis and DNA damage. Mechanistically, proteomic analysis demonstrated that VPA induced CSC differentiation through the critical target of VPA, β-Catenin. Indeed, VPA promoted the proteasome-dependent degradation of β-Catenin by enhancing its binding to the E2 ubiquitin-conjugating enzyme UBE2a, leading to marked reductions in nuclear and cytoplasmic β-Catenin levels and subsequently decreasing β-Catenin/TCF-LEF target promoter activation. These effects were confirmed in three in vivo CRC xenograft models, including a syngeneic CT26 immunocompetent mouse model, where VPA combined with oxaliplatin/capecitabine chemotherapy and anti-VEGF therapy, a standard first-line treatment for mCRC, significantly suppressed tumor growth and prolonged survival with minimal toxicity. Proteomic analysis of tumor tissues from in vivo CRC models confirmed the VPA-mediated downregulation of CSC markers and β-Catenin.

Background: Despite advances in uveal melanoma (UM) diagnosis and treatment, about 50% of patients develop distant metastases, thereby displaying poor overall survival. Molecular profiling has identified several genetic alterations that can stratify patients with UM into different risk categories. However, these genetic alterations are currently dispersed over multiple studies and several methodologies, emphasizing the need for a defined workflow that will allow standardized and reproducible molecular analyses. Methods: Following the findings published by “The Cancer Genome Atlas–UM” (TCGA-UM) study, we developed an NGS-based gene panel (called the UMpanel) that classifies mutation sets in four categories: initiating alterations (CYSLTR2, GNA11, GNAQ and PLCB4), prognostic alterations (BAP1, EIF1AX, SF3B1 and SRSF2), emergent biomarkers (CDKN2A, CENPE, FOXO1, HIF1A, RPL5 and TP53) and chromosomal abnormalities (imbalances in chromosomes 1, 3 and 8). Results: Employing commercial gene panels, reference mutated DNAs and Sanger sequencing, we performed a comparative analysis and found that our methodological approach successfully predicted survival with great specificity and sensitivity compared to the TCGA-UM cohort that was used as a validation group. Conclusions: Our results demonstrate that a reproducible NGS-based workflow translates into a reliable tool for the clinical stratification of patients with UM.

Recent studies have indicated a potential link between immune-related gene expression and Bacillus Calmette-Guèrin (BCG) treatment response in non-muscle-invasive bladder cancer (NMIBC) patients, however, prognostic gene signatures have not significantly improved risk stratification beyond clinical characteristics. To identify predictive biomarkers in T1 high-risk (HR) bladder cancer (BC) patients responding to BCG treatment, a gene signature was derived from a discovery cohort of 73 BCG-naïve patients, both responders and non-responders, using the publicly available dataset GSE1542618. Among the identified genes, Indoleamine 2,3-dioxygenase (IDO1), an immunosuppressive enzyme, emerged as a crucial determinant of treatment outcomes. The association between IDO1 expression and worse prognosis was subsequently validated in a cohort of 75 BC patients using formalin-fixed paraffin-embedded (FFPE) BC specimens collected prior BCG treatment. This research revealed significant insights into the mechanisms underlying unsatisfactory responses to BCG treatment in HR patients, posing IDO1 as a promising prognostic biomarker and therapeutic target for NMIBC.

In light of the emerging breakthroughs in cancer biology, drug discovery, and personalized medicine, Tumor-on-Chip (ToC) platforms have become pivotal tools in current biomedical research. This study introduced a novel rapid prototyping approach for the fabrication of a ToC device using laser-patterned poly(methyl methacrylate) (PMMA) layers integrated with a polylactic acid (PLA) electrospun scaffold, enabling dynamic drug delivery and the assessment of therapeutic efficacy in cancer cells. Traditional drug screening methods, such as conventional cell cultures, mimic certain aspects of cancer progression but fail to capture critical features of the tumor microenvironment (TME). While animal models offer a closer approximation of tumor complexity, they are limited in their ability to predict human drug responses. Here, we evaluated the ability of our ToC device to recapitulate the interactions between cancer and TME cells and its efficacy in evaluating the drug response of breast cancer cells. The functional design of the proposed ToC system offered substantial potential for a wide range of applications in cancer research, significantly accelerating the preclinical assessment of new therapeutic agents.

Organoids, derived from primary donor or stem cells, closely replicate the composition and function of their in vivo counterparts. This quality makes them a reliable model for validating hypotheses on disease-related biological processes and mechanisms. To date, the classification of organoids is performed manually by microscope and, therefore, in a data-driven application, is time-consuming, inaccurate, and difficult to morphological analysis process. The use of deep learning (DL) in organoid image analysis becomes crucial to handle complexity, variability, and large amounts of data efficiently and accurately, overcoming the limitations of traditional image processing approaches. In this paper, five CNN-based DL models such as MobileNet, DenseNet, ResNet, Inception, VGG, and the very recent Vision Transformers (ViT) were analyzed using a publicly available dataset for the morphological classification of intestinal organoids. Additionally, traditional ML models, such as SVM and RF, were tested for comparison using a feature set similar to conventional image processing tools. The systematic performance evaluation is designed to guide users in choosing the most suitable model for processing organoid images. Among all models, ViT achieved the highest accuracy of 86.95%, demonstrating its effectiveness in organoid classification. Inception and DenseNet also exhibited strong performance, with accuracy values of 86.10% and 86.47%, respectively. Rather, SVM and RF performed significantly worse, showing an accuracy approximately 20% lower than the selected DL models. Considering efficiency, ViT had the highest accuracy but required more resources (0.0437 sec/image, 343 MB), while MobileNet, the lightest model (35.6 MB), had the fastest inference time (0.0063 sec/image). The findings highlight the potential of DL models in enhancing the accuracy of organoid classification while emphasizing the importance of balancing performance with computational efficiency for real-time applications.