Search Results (3,690)

Neoadjuvant therapy (NAT) is a standard component of breast cancer treatment, yet response rates vary substantially across patients. Accurate prediction of pathological complete response remains an unmet clinical need to improve patient selection for NAT. This review summarizes current approaches of using computer vision to predict breast cancer response to NAT from histopathological slides. We examined studies employing computer vision and machine learning models on hematoxylin and eosin and immunohistochemically stained whole-slide images, focusing on morphological features of tumor cells, stroma and tumor-infiltrating lymphocytes associated with pathological complete response. Key morphological predictors of therapy resistance included low tumor cell density with cord-like patterns, necrosis, predominance of collagenous and fibroblast-rich stroma and tumor vascularization, while therapy sensitivity was associated with high nuclear staining intensity, high tumor cell density and lymphocyte infiltration. We highlighted the advantages of incorporating multimodal data to enhance predictive performance. Our analysis demonstrates that computer vision models can detect subtle morphological patterns that may be difficult for pathologists to evaluate, providing valuable insights for personalized therapy planning in breast cancer. Further development of cross-modal, interpretable artificial intelligence solutions may improve prediction accuracy and deepen our understanding of tumor biology relevant to NAT response. Full article

The mechanosensitive PIEZO family channels, PIEZO1 and PIEZO2, are essential for mechanotransduction and play roles in many cellular processes, including cell volume regulation, tissue development, touch sensation, and proprioception. Emerging evidence suggests roles for PIEZO channels in cancer biology; however, direct mechanistic evidence in breast cancer remains limited. They have been shown to promote proliferation, epithelial-to-mesenchymal transition (EMT), and migration; however, these roles are varied and context-dependent. In breast cancer specifically, the two PIEZO channels may play opposing and complex roles in tumor progression, the tumor microenvironment (TME), and the tumor immune microenvironment (TIME), potentially impacting therapeutic response and prognosis. Where breast cancer-specific mechanistic data are lacking, we integrate findings from other tumor types to generate testable hypotheses relevant to breast cancer. In this review, we will explore the importance of PIEZO channels in breast cancer development, progression, and therapeutic response, and explore therapeutics and potential strategies to improve patient outcomes. Full article

Background: Given the challenges in early detection and diagnosis, understanding the molecular underpinnings of endometrioid ovarian cancer (EOC) is crucial for improving patient outcomes. This multi-level study provides a new perspective on EOC, focusing on the expression of ARID1a (BAF250a) and RIF1. Methods: This study evaluates patient cohorts with EOC through semi-quantitative immunohistochemical staining of BAF250a (protein encoded by ARID1a) and RIF1 proteins alongside mutations that influence the gene expression of ARID1a and RIF1. Besides survival analyses, platinum- and taxane-based treatment responsiveness with regard to ARID1a and RIF1 expression has been analyzed using an online available database. Results: Histological and immunohistochemical analysis of clinical samples revealed a significant reciprocal alteration in protein expression, characterized by a marked reduction in the tumor suppressor BAF250a (p < 0.0001) and a concomitant elevation of RIF1 (p < 0.0001) in EOC compared to controls. Tumors harboring mutations in BRCA1 exhibited significantly (p = 2.82 × 10⁻⁴) lower ARID1a expression levels compared with corresponding wild-type tumors, whereas LAMB3-mutant tumors showed a significant (p = 5.16 × 10⁻³) upregulation of RIF1 mRNA expression. Conclusions: In conclusion, our study offers a new perspective, emphasizing that EOC is a distinct clinical and molecular entity. We demonstrated the expression patterns of ARID1a/BAF250a and RIF1 in EOC, establishing their potential relevance in the context of tumor biology and malignant transformation. Full article

Approximately 30% of all human cancers are driven by mutations in RAS genes, KRAS, HRAS, and NRAS, resulting in the constitutive activation of RAS proteins and stimulation of MAPK/AKT signaling. Non-mutant, i.e., wild-type (WT) RAS can also become activated through mechanisms such as gene amplification or excessive stimulation by mutated or overexpressed receptor tyrosine kinases (e.g., EGFR), thereby promoting cancer progression. Mutant or activated RAS contributes to multiple hallmarks of cancer, including unchecked cellular proliferation, reprogrammed cellular metabolism, immunosuppression, and metastasis. Hence, RAS is of immense clinical importance, with hundreds of laboratories studying various aspects of RAS biology or developing RAS inhibitors. There is perhaps no greater unmet medical need in oncology than the need for a broadly efficacious but safe inhibitor of mutant and activated RAS. Mutant-specific KRAS G12C inhibitors have shown promising therapeutic efficacy, leading to FDA approval of sotorasib and adagrasib, although their use is limited to patients with the relatively rare G12C KRAS mutation. Mutant-specific KRAS inhibitors are also susceptible to adaptive resistance, in part, due to secondary RAS mutations, and compensatory signaling from WT RAS isozymes. A pan-RAS inhibitor capable of blocking all RAS isozymes, regardless of the underlying mutation, offers the potential for broader efficacy and capacity to avert resistance. While just a few years ago, pan-RAS inhibitors were predicted to be severely toxic or even fatal, the apparent safety profile of RMC-6236 (daraxonrasib), a pan-RAS inhibitor currently in clinical trials, suggests otherwise. Indeed, pan-RAS inhibitors are now considered by many in the RAS field to be the most promising class in development. In this review, we summarize the evolution and current status of pan-RAS and pan-KRAS inhibitors in preclinical and clinical development and highlight emerging human-relevant tumor models that are advancing preclinical evaluation. Full article

Cancer remains a major global health challenge, with persistent limitations in early diagnosis, metastatic disease control, and the achievement of durable therapeutic responses with acceptable toxicity. These challenges highlight the need for more precise biomarkers and more effective therapeutic strategies. Increasing evidence implicates dysregulated lipid metabolism as a central contributor to tumor development and progression. In recent years, proprotein convertase subtilisin/kexin type 9 (PCSK9), angiopoietin-like protein 3 (ANGPTL3), and cholesteryl ester transfer protein (CETP) have gained particular attention due to their roles in cholesterol homeostasis, oncogenic signaling, and immune modulation within the tumor microenvironment (TME). This narrative review evaluates the potential of these lipid-regulatory mediators as diagnostic biomarkers and therapeutic targets in oncology. The majority of available evidence derives from preclinical and epidemiological studies, with PCSK9 representing the most extensively investigated target. Findings are sometimes contradictory and strongly influenced by tumor type, disease stage, and biological context, which currently precludes the clinical applicability of these molecules as reliable biomarkers. Similar limitations apply to their translational potential as actionable therapeutic targets. Nevertheless, emerging preclinical evidence suggests that modulation of these glycoproteins may enhance the efficacy of chemotherapy, targeted therapies, and immunotherapy, including nanomedicine-based approaches. Of note, clinical research investigating the role of PCSK9 inhibition in oncology is currently ongoing, whereas comparable studies focusing on ANGPTL3 and CETP remain scarce. Overall, further mechanistic, translational, and prospective clinical investigations are warranted to elucidate the involvement of these lipid-regulatory proteins in cancer biology and to define their potential integration into future oncologic diagnostic and therapeutic strategies. Full article

Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) dysfunction is increasingly recognized as a key contributor to a broad spectrum of human diseases beyond classical cystic fibrosis (CF). CFTR is a cAMP-regulated chloride and bicarbonate ion channel expressed in both epithelial and non-epithelial tissues, where it regulates ion homeostasis, mucosal hydration, and cellular signaling. Both inherited CFTR mutations and acquired dysfunction resulting from environmental or inflammatory factors can disrupt these physiological processes and drive disease progression. Current evidence linking CFTR dysregulation to respiratory diseases, such as cystic fibrosis, chronic obstructive pulmonary disease (COPD), asthma, and HIV-associated airway disease, as well as cardiovascular, renal, neurological diseases, and cancer, is comprehensively discussed. Mechanistically, impaired CFTR function promotes oxidative stress, chronic inflammation, epithelial barrier dysfunction, altered mucociliary clearance, and dysregulation of signaling pathways, including NF-κB, TGF-β, PI3K/Akt, MAPK, and Wnt/β-catenin. In the context of HIV infection and cigarette smoke exposure, CFTR suppression is mediated in part by TGF-β signaling and miRNA-dependent mechanisms, resulting in compromised airway defense and increased susceptibility to pulmonary complications. Recent studies further demonstrate that CFTR dysregulation alters the expression of genes involved in fibrosis, inflammation, angiogenesis, and epithelial–mesenchymal transition (EMT). Notably, CFTR may act as either a tumor suppressor or a context-dependent oncogene, depending on tissue type and signaling milieu, highlighting its complex role in cancer biology. Advances in CFTR-targeted therapies, including potentiators, correctors, gene therapy, and combination approaches, have markedly improved outcomes in CF and may offer therapeutic potential for diseases associated with acquired CFTR dysfunction. We summarize the systemic consequences of CFTR dysregulation and the need for further mechanistic and translational research to clarify its role across diverse human diseases. Full article

Background and Objectives: Head and neck cancers are heterogeneous malignancies with variable biological behavior and treatment response, contributing to high morbidity and mortality. Conventional imaging techniques are limited in their ability to capture tumor biology, highlighting the need for advanced functional imaging. This review aims to evaluate the role of multiparametric magnetic resonance imaging (MRI) in characterizing the tumor microenvironment. Materials and Methods: A narrative review was conducted based on a targeted literature search of databases, including PubMed and Google Scholar. Studies addressing advanced MRI techniques for assessing tumor cellularity, vascularity, molecular features, and oxygenation were selected and analyzed. Results: Perfusion techniques, such as dynamic contrast-enhanced MRI (DCE-MRI) and arterial spin labeling (ASL), provide a quantitative assessment of tumor vascularity and show value in predicting treatment response. Diffusion-based methods, including diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI), enable evaluation of tissue cellularity and heterogeneity. Molecular approaches, such as chemical exchange saturation transfer (CEST) and amide proton transfer (APT), offer insights into protein content and proliferation. Oxygenation-sensitive techniques, such as blood oxygenation level dependent MRI (BOLD MRI) and oxygen-enhanced MRI (OE-MRI), allow non-invasive assessment of tumor hypoxia. Conclusions: Multiparametric MRI provides a comprehensive and biologically relevant evaluation of the tumor microenvironment in head and neck cancer, with potential to improve treatment prediction and support personalized therapeutic strategies. Full article

Cancer research has undergone a fundamental transformation in recent decades due to the integration of artificial intelligence (AI) models into the study of tumor biology. However, tumor evolution, driven by genetic and phenotypic alterations leading to heterogeneity, resistance and metastasis, remains a major challenge in oncology. To understand these processes is crucial for developing effective therapeutic strategies and improving patient outcomes. Conventional methods often fail to capture the complexity and dynamics of these processes. In contrast, AI tools have the ability to integrate and analyze large-scale multi-omics, imaging and clinical data, offering the capability to decode tumor complexity. AI-driven methods facilitate multi-modal data integration, enabling the recognition of patterns that connect molecular alterations with phenotypic outcomes. In functional genomics, AI tools predict the effects of genetic variants, identify regulatory elements and map dysregulated pathways, thus clarifying mechanisms underlying tumor development and resistance. In the imaging field, deep learning techniques improve tumor segmentation, characterization and longitudinal monitoring, providing more accurate insights into tumor progression and treatment response. Predictive modeling could allow the anticipation of tumor evolution and drug response, supporting adaptive therapeutic plans and real-time treatment adjustments. Moreover, AI supports biomarker discovery, patient stratification and decision support systems that can improve clinical trial design and accelerate the development of personalized therapies. However, these advances raise important ethical challenges, including data privacy, algorithmic bias and the preservation of patient autonomy. Addressing these concerns is essential to ensure the responsible deployment of AI in oncology. Full article

Clear cell renal cell carcinoma (ccRCC) is characterized by a complex molecular landscape driven by recurrent genetic alterations. While genomic and transcriptomic profiling have identified core drivers, they often fail to provide robust biomarkers due to the significant decoupling of mRNA and protein levels, as well as the critical role of post-translational modifications in tumor biology. This review synthesizes current evidence from landmark proteogenomic initiatives, such as the Clinical Proteomic Tumor Analysis Consortium (CPTAC), and independent multi-omic studies. It evaluates the integration of genomic, transcriptomic, and proteomic data to map metabolic reprogramming, signalling pathway activity, and chromatin-level alterations in ccRCC. Proteogenomic analyses reveal that protein-level data provide a functional perspective that is missing from sequencing alone, specifically identifying suppressed oxidative phosphorylation, enhanced glycolysis, and the activation of the PI3K/AKT/mTOR cascade, independent of genetic mutations. Furthermore, proteogenomics has defined novel molecular subtypes and individual protein biomarkers, such as UCHL1 and p-mTOR, which correlate more accurately with clinical outcomes and therapeutic responses than their transcriptomic counterparts. Proteogenomics is a crucial tool for refining disease taxonomy and identifying novel therapeutic vulnerabilities in ccRCC. By bridging the gap between genotype and functional phenotype, this integrated approach facilitates more precise risk stratification and accelerates the development of personalized medicine through better-informed selection of targeted and immune-based therapies. Full article

Characterizing the m6A epigenetic landscape is essential for understanding glioma biology, yet transcriptome-wide mapping of these modifications at isoform resolution across specific tumor subtypes has remained limited. Conventional short-read approaches lack the capacity to resolve full-length transcript isoforms or assign m6A modifications to individual transcripts, representing a critical gap in glioma where alternative splicing is pervasive. Methods: We performed direct RNA nanopore sequencing and transcriptome-wide m6A analysis in 14 glioma tumor tissues, including IDH1-mutant astrocytoma, oligodendroglioma, and IDH1 wild-type glioblastoma, enabling isoform-resolved profiling not accessible by conventional short-read approaches. m6A sites were predicted computationally using the m6Anet deep learning framework, which has been independently benchmarked against MeRIP-seq-derived sites, and high-confidence calls were defined at a probability threshold of ≥0.9 and required detection across multiple patients within each subtype. Results: IDH1-mutant gliomas showed a higher overall burden of computationally inferred m6A-modified sites, transcripts, and genes than IDH1 wild-type glioblastoma, along with variation in transcript biotypes, regional distribution of m6A sites, and extent of isoform methylation. Differential methylation analysis identified subtype-specific patterns of m6A localization, many of which were observed without corresponding changes in gene-level expression, indicating that m6A variation represents a post-transcriptional regulatory layer not captured by gene-level analysis alone. Integration of gene expression, isoform usage, and m6A status further identified variation in isoform composition and transcript features between astrocytoma and glioblastoma. Analysis of m6A regulators showed subtype-associated expression patterns among readers, writers, and erasers, and exploratory analyses identified isoform-level associations with survival that were not apparent at the gene level. Conclusions: Overall, these data describe subtype-specific patterns of m6A marking and isoform architecture across glioma tissues, derived from computational inference using direct RNA sequencing in a modestly sized cohort and warrant validation by orthogonal methods in larger studies. These findings are consistent with concurrent independent evidence that isoform-specific m6A deposition is evolutionarily conserved across mammals and that long-read isoform resolution reveals transcript diversity in glioma not captured by gene-level analysis. While cohort size and the absence of orthogonal site-level validation suggest that the data require cautious interpretation, this work provides a hypothesis-generating resource and methodological framework for future mechanistic and translational investigation of the glioma epitranscriptome. Full article

Pancreatic ductal adenocarcinoma (PDAC) is the most complex and aggressive disease with the worst rates of unresectable or metastatic disease at diagnosis, resistance to systemic therapy, and case fatality rate (CFR) among leading cancers. In non-metastatic disease, neoadjuvant treatment with modern chemotherapeutic regimens followed by surgical resection and/or adjuvant mFOLFIRINOX has significantly improved oncological outcomes. However, recurrence rates remain alarmingly high, while immune checkpoint inhibitors (ICIs) or molecularly targeted therapy have not yet demonstrated clinical benefits. Comprehensive genomic profiling through NGS-based approved assays such as TruSight Oncology 500 (TSO500) could guide targeted therapy. Rapidly evolving mRNA cancer vaccines and circulating tumor DNA (ctDNA)-based prediction of minimal residual disease (MRD) and recurrence risk hold great promise towards the realization of rational combination therapy to improve recurrence-free survival (RFS) and overall survival (OS). More recently, single-cell multiomics (SC MO), spatial proteomics and transcriptomics (SPT), artificial intelligence (AI), and systems biology have revolutionized cancer research, enabling holistic tumor microenvironment (TME) analysis. In this comprehensive review, we describe the latest advances and unmet needs in the standard of care of PDAC. Moreover, we discuss the expectations of ongoing randomized clinical trials of adjuvant mRNA vaccine-based therapy and ctDNA MRD testing as prognostic biomarkers, towards personalized treatment to improve RFS and OS in a medium-term perspective. With a longer perspective, we explore how harnessing SC MO, SPT, AI, and systems biology can reveal the 3D spatial organization of interacting cancer, immune, and stromal cells. Multi-dimensional TME-, TSO500- and ctDNA-based framework of dynamic biomarkers are of paramount importance to achieve an optimal patient-specific perioperative multimodal treatment combining precision immunotherapy, targeted drugs, and modern chemotherapy, translated into future practice-changing clinical trials, that could eliminate MRD towards recurrence prevention. Full article

Pancreatic cancer remains one of the most lethal malignancies worldwide, with pancreatic ductal adenocarcinoma accounting for the vast majority of cases and characterized by extensive desmoplasia, immune exclusion, and resistance to systemic therapies. Increasing evidence implicates lysosomal cathepsins as important regulators of these defining features of pancreatic tumor biology. Cathepsin-dependent proteolysis and lysosome-associated signaling pathways contribute to extracellular matrix remodeling, regulate immune cell trafficking, and influence antigen processing and presentation. Beyond their classical degradative functions, cathepsins participate in stress-adaptive cellular programs linked to autophagy, metabolic regulation, and proteostasis, supporting tumor cell survival under hypoxic, nutrient-limited, and therapy-induced stress conditions. Within the tumor microenvironment, dysregulated cathepsin activity promotes immune evasion by reshaping cytokine networks, impairing effective antigen presentation, and reinforcing physical and functional barriers to cytotoxic T-cell infiltration. Collectively, these mechanisms position the lysosome–cathepsin system as a central regulator of proteolytic remodeling, immune exclusion, and adaptive therapy resistance in pancreatic cancer, highlighting its potential relevance for emerging combinatorial therapeutic strategies. Full article

Polyploid giant cancer cells (PGCCs) are characterized by abnormal enlargement and considerable polyploidy. Though the presence of giant cancer cells has been documented for decades, they remain not fully understood, especially in clinical practice, due to diagnostic challenges, and confusion regarding synonyms for PGCCs still exists. Thus, understanding PGCCs may be a key clue to overcoming them. This review offers a comprehensive overview of PGCCs, integrating insights from basic research and clinical studies to enhance understanding of their complex biology and clinical implications. In basic research, PGCCs are known to emerge under various stressors, including chemotherapy exposure, radiation, viral infection, and hypoxic environments. These cells play crucial roles in tumor progression through multiple mechanisms: enhancing genetic diversity, and facilitating metastatic spread via asymmetrical cell division and genomic instability. In clinical studies, PGCC-containing tumors have been shown to exhibit marked treatment resistance and are associated with a poor prognosis across multiple solid tumor types, including prostate, lung, and pancreatic cancers. Despite these therapeutic challenges, taxane-based chemotherapy has shown promising results in PGCC-containing tumors, such as pleomorphic carcinoma and undifferentiated carcinoma. Furthermore, emerging targeted therapies directed at specific pathways in PGCCs, particularly those involving TP53, represent potential strategies to improve clinical outcomes of patients with PGCC-containing tumors. Full article

Classic Hodgkin lymphoma (cHL) has traditionally been conceptualized as a malignancy confined to lymphoid tissues, with disease extent defined primarily by anatomical staging systems. While this framework has guided clinical management for decades, it incompletely captures the biological complexity of cHL. Emerging evidence from molecular, immunological, and translational studies supports a reinterpretation of cHL as a systemic immunobiological disease rather than a purely nodal malignancy. A defining feature of cHL is the rarity of malignant Hodgkin and Reed–Sternberg (HRS) cells, which orchestrate a highly structured tumor microenvironment through constitutive activation of signaling pathways, including NF-κB and JAK/STAT, and through expression of immune checkpoint ligands. Beyond local effects, HRS cells secrete cytokines, chemokines, and extracellular vesicles that enter the systemic circulation, promoting widespread immune reprogramming. This includes T-cell exhaustion, expansion of regulatory T cells, and activation of immunosuppressive myeloid populations, which collectively shape host immunity beyond the lymph node. Circulating tumor DNA (ctDNA) and soluble mediators such as thymus and activation-regulated chemokine (TARC/CCL17) provide measurable evidence of systemic disease activity and enable dynamic monitoring of tumor burden. These biological insights help explain key clinical features of cHL, including constitutional (“B”) symptoms, extranodal involvement, and heterogeneous patterns of treatment response and resistance. Importantly, integration of ctDNA kinetics, peripheral immune profiling, and functional imaging offers a multidimensional framework for disease assessment that overcomes the limitations of conventional staging systems. Therapeutically, the efficacy of immune checkpoint inhibitors underscores the central role of systemic immune dysregulation, while emerging biomarker-driven strategies support adaptive and personalized approaches to treatment. Collectively, these findings support a paradigm shift toward understanding cHL as a systemic immunobiological disease. This framework has important implications for disease monitoring, therapeutic decision-making, and future research, paving the way for biology-driven, precision medicine approaches in cHL. Full article

Background: Renal cell carcinoma (RCC) with venous tumor thrombus (VTT) represents a clinically challenging entity requiring complex surgical management. The prognostic significance of tumor thrombus level remains controversial, with conflicting evidence regarding its impact on perioperative and oncologic outcomes. Methods: This narrative review summarizes the current literature on the relationship between VTT level and surgical complexity, perioperative outcomes, and long-term oncologic results in patients undergoing radical nephrectomy with thrombectomy. Results: Higher levels of tumor thrombus are consistently associated with increased surgical complexity, including longer operative time, greater blood loss, and higher rates of perioperative complications. However, the impact of thrombus level on oncologic outcomes remains inconsistent across studies. Most contemporary evidence suggests that VTT level alone is not an independent predictor of survival, whereas tumor biology, nodal and distant metastatic staging, and histological features, plays a more significant role. Conclusions: While tumor thrombus level is a key determinant of surgical planning and technical difficulty, its prognostic value for long-term survival appears limited. Clinical decision-making should therefore integrate both anatomical and biological tumor characteristics to optimize patient outcomes. Full article