Annabella Di Mauro

Gastric adenocarcinomas with yolk sac tumor (YST) differentiation represent an exceptionally rare and poorly understood phenotype, characterized by the emergence of extraembryonic features within an epithelial malignancy. Their histogenesis remains debated, with increasing evidence supporting somatic lineage plasticity rather than germ cell origin. Here, we performed an integrated histopathologic and genomic characterization of three gastric adenocarcinomas with YST differentiation surgically treated at a tertiary cancer center. Histologically, all tumors showed a predominant adenocarcinoma component associated with variable YST differentiation, displaying reticular/microcystic and papillary patterns and expression of oncofetal markers, including alpha-fetoprotein (AFP) and Glypican-3. Targeted next-generation sequencing using a 523-gene panel revealed microsatellite-stable profiles with intermediate tumor mutational burden and substantial intertumoral heterogeneity. Despite gene-level variability, the detected alterations involved signaling pathways commonly implicated in epithelial tumorigenesis, including PI3K-AKT and RTK/RAS-MAPK signaling. Several recurrent alterations were identified across cases, including CCND3 variants and MDM2 copy number gains; however, their biological significance requires validation in larger cohorts. Functional enrichment analysis identified alterations involving developmental and proliferative signaling programs. Overall, these findings suggest that YST differentiation may represent a phenotypic manifestation of epithelial tumor plasticity arising within gastric adenocarcinoma and is associated with epithelial-related oncogenic programs, although broader genomic and comparative studies are required to clarify its histogenesis. This study provides preliminary molecular and histopathologic insights into this rare entity and supports the integration of molecular profiling into its diagnostic and translational management.

Introduction: Thyroblastoma is a rare and highly aggressive embryonal thyroid malignancy typically associated with DICER1 alterations. However, DICER1-wildtype cases remain poorly characterized at the molecular level. Methods: We report a case of aggressive thyroblastoma in a 62-year-old male, negative for canonical DICER1 RNase IIIb mutations. Comprehensive genomic profiling was performed using Oxford Nanopore long-read sequencing, followed by integrative bioinformatic and pathway-level analyses. Results: Molecular analysis revealed an alternative oncogenic signature characterized by an EIF1AX p.Lys3_Lys5dup duplication, TERT alterations (promoter C228T and coding p.C42R), and an AGK–BRAF fusion predicted to drive constitutive MAPK/ERK signaling. Functional enrichment analyses highlighted dysregulation of translational initiation, telomere maintenance, and mitogenic pathways, alongside potential immune-escape mechanisms linked to DUX4 activation. Clinically, the tumor exhibited a triphasic morphology, extensive locoregional infiltration, pulmonary metastases, and only transient response to chemotherapy. Discussion: These findings expand the molecular spectrum of thyroblastoma beyond the canonical DICER1-driven paradigm and suggest that DICER1-wildtype cases may represent a distinct biological subgroup. The identification of alterations affecting TERT and MAPK pathways highlights potential therapeutic vulnerabilities and supports the clinical value of comprehensive genomic profiling in ultra-rare thyroid malignancies.

Neoadjuvant strategies in head and neck squamous cell carcinoma (HNSCC) are reshaping therapeutic paradigms by shifting emphasis from anatomical staging toward biology-driven response stratification. The transition from induction chemotherapy to immune checkpoint–based and combination regimens has transformed the perioperative setting into a translational platform that enables interrogation of tumor–immune interactions and clonal selection under therapeutic pressure prior to surgery. In this context, pathological response assessment has emerged as a robust surrogate endpoint, overcoming the limitations of radiologic evaluation, which often fails to capture immune-mediated pseudoprogression and spatially heterogeneous regression. Quantification of residual viable tumor (RVT) provides a reproducible metric of therapeutic efficacy, while characterization of immune-related regression beds, tertiary lymphoid structures, macrophage polarization states, and compartment-specific nodal responses offers mechanistic insight into tumor clearance and resistance evolution. Evidence from phase II trials, single-cell sequencing, spatial transcriptomics, and multiplex immune profiling supports the prognostic relevance of pathology-driven endpoints. Integration of digital pathology and artificial intelligence–assisted image analysis further enhances reproducibility and enables high-resolution mapping of residual disease and immune architecture. Within this modern oncologic framework, the neoadjuvant-treated specimen functions as a dynamic biomarker platform guiding response-adapted surgical strategies and biomarker-driven clinical trial design. This study was designed as a narrative review. A structured literature search was performed using PubMed and major oncology journals to identify relevant studies on pathology-driven response assessment in neoadjuvant-treated head and neck squamous cell carcinoma. The review focused on publications addressing histopathological response criteria, immune microenvironment remodeling, spatial profiling technologies, and computational pathology approaches.

Soft-tissue sarcomas (STSs) comprise a rare, heterogeneous group of mesenchymal malignancies in which histologic grade remains the strongest determinant of outcome, metastatic risk, and therapeutic strategy. Intermediate/high-grade STSs exhibit a pronounced propensity for early distant relapse, yet growing evidence indicates that metastatic behaviour is not uniform. Within this spectrum, an oligometastatic phenotype, characterised by a limited number of metastases, often confined to the lung, has emerged as a clinically and biologically distinct state associated with more indolent metastatic kinetics and improved survival when treated with aggressive local interventions. However, the criteria that define true oligometastatic STSs remain unsettled, and prospective evidence is lacking. Emerging molecular and immunological correlates provide a potential framework for biological triage. Low genomic complexity (low-risk CINSARC), a B-cell/TLS-rich tumour microenvironment, high immune-cytotoxic signatures, and persistently low or undetectable circulating tumour DNA (ctDNA) are each linked to reduced metastatic competence and may underpin oligometastatic trajectories. Conversely, high chromosomal instability, immunosuppressive microenvironments, and elevated ctDNA levels align with covertly polymetastatic biology despite limited radiographic disease. In this context, artificial intelligence and machinelearning approaches applied to computational genomics, immune profiling, imaging, and liquid-biopsy data offer a powerful strategy to integrate these multi-dimensional features and refine predictions of metastatic behaviour in STS. Oligometastatic STS therefore represents a biologically definable subset amenable to multimodal management integrating local ablative therapies, systemic agents, and immune-based strategies. Prospective, biomarker-stratified trials are needed to validate selection frameworks and optimise treatment sequencing in this evolving therapeutic space.

Recent advances in precision oncology have led to significant breakthroughs through the targeting of defined oncogenic drivers. However, the clinical efficacy of single-target therapies is increasingly constrained by the intrinsic complexity and adaptability of cancer. Solid tumors frequently arise from multifactorial oncogenic processes and adapt via diverse resistance mechanisms, ultimately limiting the durability of monotherapies. This review advocates for a paradigm shift toward multi-targeted, AI-enhanced strategies that harness high-throughput multi-omic data to inform the rational design of combination therapies. By leveraging artificial intelligence for drug discovery and repurposing, response prediction, and clinical trial optimization, the field of oncology is poised to transcend reductionist approaches and more fully address the biological intricacy of cancer.

Anthracyclines and human epidermal growth factor receptor 2 (HER-2) inhibitors are cornerstone therapies for breast cancer but are associated with significant cardiotoxicity. While sodium–glucose cotransporter 2 (SGLT2) inhibitors such as dapagliflozin have demonstrated cardio–renal protective effects during anthracycline treatment, their efficacy in preventing cardiotoxicity from sequential anthracycline and HER-2 blockade remains poorly understood. This study investigates the cardioprotective role of dapagliflozin in a preclinical model of chemotherapy-induced cardiotoxicity. Female C57Bl/6 mice were divided into four groups and treated for 10 days as follows: (1) a normal control group receiving saline (sham); (2) a model control group receiving doxorubicin (2.17 mg/kg/day for 5 days) followed by HER-2-blocking monoclonal antibody (2.25 mg/kg/day for 5 days); (3) a dapagliflozin-only group (10 mg/kg/day via oral gavage); and (4) a treatment group receiving the combination of doxorubicin, HER-2 inhibitor, and dapagliflozin. Cardiac function was assessed using echocardiography (VEVO 2100). Biomarkers of myocardial injury and inflammation (NLRP3, MyD88, CXCR4, H-FABP, troponin-T, and cytokines) were quantified via ELISA and immunohistochemistry. Circulating markers such as mitofusin-2, cardiac myosin light chain, malondialdehyde (MDA), and 4-hydroxy-2-nonenal (4-HNE) were also measured. Dapagliflozin significantly preserved the ejection fraction and reduced both radial and longitudinal strain impairment in mice treated with the doxorubicin–HER-2 inhibitor combination (p < 0.001). Levels of myocardial NLRP3, MyD88, CXCR4, H-FABP, interleukin-1β, and troponin-T were significantly lower in the dapagliflozin-treated group compared to the chemotherapy-only group. Serum markers of oxidative stress and cardiac injury, including mitofusin-2, MDA, 4-HNE, BNP, and high-sensitivity C-reactive protein (hs-CRP), were also reduced by dapagliflozin treatment. Our findings demonstrate that dapagliflozin effectively mitigates early cardiac dysfunction and injury in a preclinical model of sequential doxorubicin and HER-2 inhibitor therapy.

Pseudomyogenic haemangioendotheliomas (PMH) are exceedingly rare, mostly occurring in soft tissue, with malignant cases even more uncommon. In this report, we present a case of a 28-year-old male initially suspected of having a fibroblastic osteosarcoma of the right femur, which was then correctly diagnosed as a primary pseudomyogenic hemangioendothelioma of the bone with synchronous metastases to other skeletal segments. Molecular analysis through targeted RNA sequencing confirmed the correct diagnosis, revealing a fusion transcript ACTB::FOSB. To our knowledge, this is one of the few reported cases of suffering from multiple pathological fractures. The rapid skeletal progression and the onset of distant metastases in this case is highly unusual considering the typically indolent clinical course commonly reported in the literature for this tumor.

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality, with metastatic disease posing significant therapeutic challenges. While anti-EGFR therapy has improved outcomes for patients with RAS and BRAF wild-type tumors, resistance remains a major hurdle, limiting treatment efficacy. The concept of negative hyperselection has emerged as a refinement of molecular profiling, identifying additional genomic alterations—such as HER2 and MET amplificationsand MAP2K1 mutations—that predict resistance to anti-EGFR agents. Studies incorporating these expanded assessments have demonstrated that nearly half of patients with RAS/BRAF wild-type tumors harbor alternative resistance biomarkers, underscoring the need for expanded selection criteria. Liquid biopsies, particularly circulating tumor DNA (ctDNA) analysis, have revolutionized precision oncology by providing a minimally invasive, real-time assessment of tumor dynamics. ctDNA-based hyperselection enables the detection of resistance-associated alterations, guiding treatment decisions with greater accuracy than conventional tissue biopsies. Recent trials support the predictive value of ctDNA-defined negative hyperselection, revealing superior outcomes for patients stratified through liquid biopsy. This narrative review explores the evolving role of molecular hyperselection in first-line anti-EGFR therapy, emphasizing the integration of ctDNA to refine patient selection, enhance therapeutic efficacy, and pave the way for personalized treatment strategies in metastatic CRC.