Search Results (942)

Background: Colorectal cancer (CRC) demonstrates substantial clinical and biological diversity across age groups, ancestral backgrounds, and treatment settings, alongside a rising incidence of early-onset disease (EOCRC). The mitogen-activated protein kinase (MAPK) pathway is a major driver of CRC development and therapy response; however, the distribution and prognostic value of MAPK alterations across distinct patient subgroups remain unclear. Methods: We analyzed 2515 CRC tumors with harmonized demographic, clinical, genomic, and treatment metadata. Patients were stratified by ancestry (Hispanic/Latino [H/L] vs. non-Hispanic White [NHW]), age at diagnosis (early-onset [EO] vs. late-onset [LO]), and FOLFOX chemotherapy exposure. MAPK pathway alterations were identified using a curated gene set encompassing canonical EGFR-RAS-RAF-MEK-ERK signaling components and regulatory nodes. Conversational artificial intelligence (AI-HOPE and AI-HOPE-MAPK) enabled natural language-driven cohort construction and exploratory analytics; findings were validated using Fisher’s exact testing, chi-square analyses, and Kaplan–Meier survival estimates. Results: MAPK pathway disruption demonstrated marked heterogeneity across ancestry and treatment contexts. Among EO H/L patients, FGFR3, NF1, and RPS6KA6 mutations were significantly enriched in tumors not receiving FOLFOX, whereas PDGFRB alterations were more frequent in FOLFOX-treated EO H/L tumors relative to EO NHW counterparts. In late-onset H/L disease, NTRK2 and PDGFRB mutations were more common in non-FOLFOX tumors. Distinct MAPK-associated alterations were also observed among NHW patients, particularly in non-FOLFOX settings, including AKT3, FGF4, RRAS2, CRKL, DUSP4, JUN, MAPK1, RRAS, and SOS1. Survival analyses provided borderline evidence that MAPK alterations may be linked to improved overall survival in treated EO NHW patients. Conversational AI markedly accelerated analytic throughput and multi-parameter discovery. Conclusions: Although MAPK alterations are pervasive in CRC, their distribution varies meaningfully by ancestry, age, and treatment exposure. These findings highlight NF1, MAPK3, RPS6KA4, and PDGFRB as potential biomarkers in EOCRC and H/L patients, supporting the need for ancestry-aware precision oncology approaches. Full article

Background: The prognostic value of treatment-induced necrosis in soft STS remains uncertain. This study evaluated whether MRI-based changes in necrosis (Δ necrosis) between pre- and post-neoadjuvant chemotherapy scans correlate with pathologic necrosis and clinical outcomes. Methods: In this retrospective cohort, 27 patients with STS who received neoadjuvant chemotherapy and underwent pre- and post-treatment MRI were analyzed. Necrosis was graded categorically (<5%, 5–25%, 25–50%, 50–75%, 75–95%, and >95%), and Δ necrosis was calculated as the change in estimated necrosis between scans. Correlations between MRI-derived and pathologic necrosis were assessed using Spearman’s rank coefficient. Survival analyses (progression-free, local recurrence-free, and disease-specific overall survival) were performed using Kaplan–Meier and log-rank tests. Results: Post-treatment MRI necrosis moderately correlated with pathologic necrosis (ρ = 0.44, p = 0.028), whereas Δ necrosis showed a weaker, nonsignificant correlation (ρ = 0.24, p = 0.24). Neither MRI-based nor pathologic necrosis thresholds were associated with survival outcomes. Conclusions: MRI-based Δ necrosis did not predict pathologic necrosis or oncologic outcomes in STS, suggesting that radiologic changes in necrosis may not serve as reliable markers of therapeutic response. Future studies integrating quantitative imaging and standardized pathology protocols together with future exploration of molecular tools such as ctDNA are needed to refine treatment assessment in STS. Full article

Liver cancer, also known as hepatocellular carcinoma (HCC), remains a major global health concern, with high mortality driven by late-stage diagnosis, limited treatment efficacy, and frequent therapeutic resistance. Matrix metalloproteinases (MMPs), a large family of zinc-dependent endopeptidases, are central to the biological processes that drive liver tumor initiation and progression. By degrading and reorganizing extracellular matrix components, MMPs facilitate tumor expansion, tissue invasion, and metastatic dissemination. In addition, these enzymes regulate the availability of growth factors, cytokines, and chemokines, thereby influencing angiogenesis, inflammation, immune cell recruitment, and the development of an immunosuppressive tumor microenvironment. Aberrant expression or activity of multiple MMP family members is consistently associated with aggressive clinicopathologic features, including vascular invasion, increased metastatic potential, and reduced patient survival, highlighting their promise as prognostic markers and actionable therapeutic targets. Past attempts to modulate MMP activity were hindered by broad inhibition profiles and dose-limiting toxicities, underscoring the need for improved specificity and delivery strategies. Recent advances in molecular design, biologics engineering, and nanotechnology have revitalized interest in MMP targeting by enabling more selective, context-dependent modulation of proteolytic activity. Preclinical studies demonstrate that carefully tuned MMP inhibition can limit tumor invasion, enhance anti-angiogenic responses, and potentially improve the efficacy of existing systemic therapies, including immuno-oncology agents. This review synthesizes current knowledge on the multifaceted roles of MMPs in HCC pathobiology and evaluates emerging therapeutic strategies that may finally unlock the clinical potential of targeting these proteases. Full article

Background and Objectives: This study aimed to comparatively evaluate the association of commonly used comorbidity scores with survival, mortality, and recurrence in ovarian cancer patients aged 50 years and above. Materials and Methods: In this single-center, retrospective study, 130 female patients diagnosed between 2017 and 2024 who had received systemic therapy and had complete medical records were included. Comorbidity scores—including the Charlson Comorbidity Index (CCI), Cumulative Illness Rating Scale-Geriatric (CIRS-G), Adult Comorbidity Evaluation-27 (ACE-27), Elixhauser Comorbidity Index, Index of Coexistent Disease (ICED), and Functional Comorbidity Index (FCI)—were calculated for each patient. Survival analyses were conducted using the Kaplan–Meier method and Cox regression modeling. The prognostic accuracy of comorbidity scores was assessed via receiver operating characteristic (ROC) curve analysis. Results: Patients with higher CCI scores had significantly shorter survival, and CCI was identified as an independent prognostic factor in multivariate analysis. While other comorbidity scores were associated with overall survival in univariate analyses, they lost statistical significance in multivariate models. Patients with a higher comorbidity burden experienced more frequent disease recurrence and shorter time to recurrence. Conclusions: Comorbidity burden is a key clinical determinant of survival and disease trajectory in older patients with ovarian cancer. The CCI demonstrated the highest prognostic accuracy in this population and may serve as a valuable tool in individualized treatment planning. Integration of comorbidity-based assessments into standard decision-making processes is recommended in geriatric oncology practice. Full article

Esophageal cancer (EC), including esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC), remains a highly lethal disease because of its late diagnosis, significant biological heterogeneity, and frequent resistance to therapy. Growing evidence indicates that microRNAs (miRNAs) are key posttranscriptional regulators involved in tumor initiation, progression, metastasis, and response to treatment. This review provides a comprehensive and updated overview of miRNA dysregulation in both ESCC and EAC, with a specific focus on its emerging clinical relevance in early detection, prognostic assessment, and prediction of therapeutic response. Multiple tissue-based and circulating miRNA signatures, some capable of distinguishing between Barrett’s esophagus (BE), dysplasia, and EAC, demonstrate promising diagnostic performance. In parallel, several miRNAs, including miR-21, miR-23a, miR-455-3p, and miR-196b, have been consistently associated with chemoresistance and radioresistance. Moreover, distinct miRNA expression patterns are correlated with tumor aggressiveness, metastatic potential, and the risk of recurrence, supporting their integration with conventional histopathological and molecular parameters for improved patient stratification. Overall, miRNAs represent a powerful class of biomarkers and potential therapeutic targets in EC, with increasing translational relevance in precision oncology. Full article

Background/Objectives: Early-onset colorectal cancer (EOCRC; diagnosed before age 50) is rising at an accelerated rate, with a disproportionate impact on underserved populations. While alterations in the receptor tyrosine kinase–RAS (RTK–RAS) signaling pathway play a fundamental role in colorectal cancer (CRC) biology, their prognostic significance in the setting of FOLFOX chemotherapy—particularly across different age groups and ancestral backgrounds—remains insufficiently characterized. We sought to characterize age-, ancestry-, and treatment-specific associations between RTK–RAS alterations and clinical outcomes using an AI-enabled precision oncology framework. Methods: We analyzed 2515 CRC cases, including 266 Hispanic/Latino (H/L) and 2249 non-Hispanic White (NHW) patients, stratified by age at onset, ancestry, and FOLFOX treatment status. Mutation frequencies were assessed using Fisher’s exact and chi-square tests, while overall survival was analyzed with Kaplan–Meier methods. The AI-HOPE and AI-HOPE–RTK–RAS conversational artificial intelligence platforms were used to integrate clinical, genomic, and treatment data via multi-parameter, natural language–based queries. Results: In early-onset Hispanic/Latino patients, ERBB2 and NF1 mutations occurred at significantly lower frequencies in FOLFOX-treated cases compared with untreated cases (p = 0.01 for both). In late-onset H/L patients, NTRK2 mutations were depleted in FOLFOX-treated tumors (p = 0.04). In untreated early-onset H/L patients, MAPK3 and NF1 mutations were enriched relative to NHW counterparts. Among early-onset NHW patients, IGF1R and ERRFI1 mutations were less frequent with FOLFOX exposure, while multiple RTK–RAS genes were reduced in FOLFOX-treated late-onset NHW patients. Survival analyses revealed worse overall survival in FOLFOX-untreated early-onset NHW patients with RTK–RAS alterations (p = 0.029), but improved survival in FOLFOX-treated late-onset NHW patients (p = 0.048). Conclusions: RTK–RAS pathway alterations demonstrate strong age-, ancestry-, and treatment-specific prognostic effects and may serve as precision biomarkers of differential chemotherapy response. AI-enabled analytics substantially accelerated integrative biomarker discovery, supporting their utility for advancing precision oncology in EOCRC. Full article

Residual microcalcifications after neoadjuvant chemotherapy (NAC) in breast cancer remain a complex diagnostic and therapeutic challenge. Although NAC has significantly improved pathologic complete response (pCR) rates and transformed surgical approaches, the persistence or evolution of microcalcifications may not accurately reflect residual disease. This discrepancy complicates radiologic interpretation, impacts surgical decision-making, and may lead to overtreatment or unnecessary mastectomies. This review synthesizes current evidence on the radiologic–pathologic correlation of post-NAC microcalcifications, their prognostic value, and their relevance to guiding surgical management in contemporary precision oncology. A narrative review of the literature was performed, focusing on imaging evolution after NAC, pathologic correlations, predictive and prognostic implications, and the role of microcalcifications in defining optimal surgical strategies, ranging from breast-conserving surgery to mastectomy. Emerging contributions from digital breast tomosynthesis, contrast-enhanced mammography (CEM), Magnetic Resonance (MR) and radiomics are also examined. Studies consistently demonstrate that residual microcalcifications are often poor predictors of viable tumor tissue after NAC. Up to half of cases with persistent calcifications may reflect minimal or absent residual invasive cancer, whereas calcifications may also persist in areas of treatment-induced necrosis or fibrosis. Reliance on calcifications alone may therefore lead to unnecessary extensive resections. Conversely, specific morphologic patterns, especially fine pleomorphic or branching calcifications, are more strongly associated with residual malignancy. Advanced imaging and radiomics show promise in improving predictive accuracy. Residual microcalcifications after NAC should not be interpreted as a direct surrogate of residual disease. A multimodal assessment integrating imaging evolution, tumor biology, and treatment response is essential to optimize surgical planning and avoid overtreatment. Precision surgery in the NAC era increasingly requires individualized decision-making supported by advanced imaging and robust radiologic–pathologic correlation. Full article

Recent progress in machine learning (ML) has fueled the emergence of intelligent clinical decision support systems (CDSSs) designed to optimize diagnostic and prognostic accuracy through the analysis of complex and heterogeneous medical data. The analysis provides a comprehensive perspective on the use of machine learning in the medical field by integrating a bibliometric assessment of the recent literature and a detailed examination of the algorithms used in current studies. The bibliometric component highlights the evolution of publications, the thematic distribution of research and emerging directions within various medical specialties. In addition, the evaluation of selected articles sheds light on the concrete ways of applying ML algorithms, as well as the methodological limitations encountered in clinical practice. Random forest and gradient boosting are commonly used in internal medicine and cardiology, while convolutional neural networks (CNNs) dominate neuroimaging in neurology and image-based analyses in oncology and radiology. Full article

Colorectal cancer (CRC) remains one of the leading causes of cancer-related morbidity and mortality worldwide. Despite advances in screening and therapeutic strategies, early detection and individualized treatment remain major challenges. In recent years, an expanding repertoire of biomarkers has emerged, spanning genomic, transcriptomic, proteomic, and metabolomic signatures. Epigenetic features, such as DNA methylation panels, as well as non-coding RNAs and the gut microbiome, hold potential not only for improving early diagnosis but also for refining prognosis and predicting therapeutic responses within the framework of precision oncology. This narrative review provides an updated, integrative overview of CRC diagnostic, prognostic, and predictive biomarkers. We distinguish established markers already in clinical practice, such as RAS and BRAF mutations, HER2 amplification, microsatellite instability/mismatch repair deficiency (MSI/dMMR), and widely investigated molecular alterations including TP53 mutations and immune-checkpoint-related markers, from novel biomarkers with growing translational potential. We also discuss the implementation challenges of these biomarkers in clinical practice, including issues related to validation, standardization, and cost-effectiveness, as well as the multi-modal approach for the development of composite diagnostic panels. Full article

Introduction: In rectal cancer, the choice of treatment strategy depends on the tumor stage and the response to neoadjuvant therapy. Accurate assessment of tumor regression through magnetic resonance imaging (MRI) may help to guide personalized approaches, including delayed or nonoperative management. This study aimed to assess the correlations between pathological complete response (pCR) and clinical staging before and after neoadjuvant treatment in rectal cancer patients. Methods: We conducted a retrospective analysis of rectal cancer patients treated with neoadjuvant therapy followed by radical resection in our oncological surgery department between July 2012 and December 2024. Clinical staging and tumor response were assessed using MRI, focusing on T- and N-stage evaluation. Pathological complete response (pCR) was defined as the absence of tumor cells on histopathological examination. Associations between pCR and clinical variables were explored. Results: Out of a total of 1693 rectal cancer patients, 783 (46.25%) received neoadjuvant therapy, with 62 patients (7.92%) presenting pCR. The majority had tumor stage cT3 (n = 45, 72.6%) and lymph node stage cN2b (n = 25, 40.3%) before treatment. Post-treatment MRI showed complete tumor response (T0) in 20 patients (32.3%) and nodal downstaging to N0 in 34 patients (54.8%). MRI provided imaging findings that indicate a limited correlation between clinical assessment of tumor response and pathological outcome. Six patients (9.6%) developed distant metastases, and there were no local recurrences. Conclusions: While MRI provides valuable preoperative information, its accuracy in predicting pCR remains limited. Achieving pCR is a favorable prognostic indicator, but it does not eliminate the risk of distant metastasis; therefore, continued surveillance and individualized management strategies remain essential to optimize outcomes in rectal cancer patients. Full article

Gliomas are notoriously difficult to treat owing to their pronounced heterogeneity and highly variable treatment responses. This reality drives the development of precise diagnostic and prognostic methods. This review explores the modern arsenal of bioinformatic tools aimed at refining diagnosis and stratifying glioma patients by different malignancy grades and types. We perform a comparative analysis of software solutions for processing whole-exome sequencing data, analyzing DNA methylation profiles, and interpreting transcriptomic data, highlighting their key advantages and limited applicability in routine clinical practice. Special emphasis is placed on the contribution of bioinformatics to fundamental oncology, as these tools aid in the discovery of new biomarker genes and potential targets for targeted therapy. The ninth section discusses the role of computational models in predicting immunotherapy efficacy. It demonstrates how integrative data analysis—including tumor mutational burden assessment, characterization of the tumor immune microenvironment, and neoantigen identification—can help identify patients who are most likely to respond to immune checkpoint inhibitors and other immunotherapeutic approaches. The obtained data provide compelling justification for including immunotherapy in standard glioma treatment protocols, provided that candidates are accurately selected based on comprehensive bioinformatic analysis. The tools discussed pave the way for transitioning from an empirical to a personalized approach in glioma patient management. However, we also note that this field remains largely in the preclinical research stage and has not yet revolutionized clinical practice. This review is intended for biological scientists and clinicians who find traditional bioinformatic tools difficult to use. Full article

Recently, extracellular vesicles (EVs) have emerged as pivotal mediators of intercellular communication that reflect physiological homeostasis and pathological alterations. By encapsulating diverse biomolecules, including proteins, nucleic acids, and lipids, EVs mirror the molecular signatures of their parent cells, thereby positioning EV-based biosensing as a transformative platform for noninvasive diagnostics, prognostic prediction, and therapeutic monitoring. This review provides a comprehensive overview of the current state and clinical translation of EV biosensing technologies. Herein, we have discussed ongoing efforts toward standardization and analytical validation (e.g., MISEV2023 and EV-TRACK) and evaluated advances in sensing modalities such as surface plasmon resonance (SPR), electrochemical, fluorescence, and magnetic detection systems, which have significantly improved analytical performance in terms of sensitivity and specificity. Furthermore, we highlight recent developments in multiplexed and multiomics integration at the single-EV level and the application of machine learning to enhance diagnostic accuracy and interpret biological heterogeneity. The clinical relevance of EV biosensing has been explored across multiple disease domains, including oncology, neurology, and cardiometabolic and infectious diseases, with an emphasis on translational progress toward standardized, regulatory-compliant, and scalable platforms. Finally, this review identifies key challenges in manufacturing scale-up, quality control, and point-of-care deployment and proposes a unified framework to accelerate the adoption of EV biosensing as a cornerstone of next-generation precision diagnostics and personalized medicine. Full article

Background: The clinical and oncologic significance of residual microcalcifications after neoadjuvant chemotherapy (NAC) in breast cancer remains poorly defined. While traditionally regarded as radiologic indicators of residual malignancy warranting complete surgical excision, accumulating evidence suggests that many post-treatment calcifications represent benign or in situ changes with limited prognostic relevance. This systematic review synthesizes current evidence to clarify the diagnostic, pathologic, and oncologic implications of persistent calcifications after NAC. Methods: Following PRISMA 2020 guidelines, we conducted a comprehensive search of PubMed, Embase, the Cochrane Library, Scopus, and Google Scholar for studies published between January 2000 and May 2025. Eligible studies included adult breast cancer patients treated with NAC who demonstrated residual calcifications on mammography or MRI with corresponding histopathologic or survival data. Two reviewers independently performed study selection, data extraction, and quality assessment using the Newcastle–Ottawa Scale and AMSTAR-2. Results: Twenty-four studies involving over 3000 patients were included. Across cohorts, 35–55% of residual calcifications were benign, and many others corresponded to ductal carcinoma in situ rather than invasive carcinoma. Calcifications frequently persisted despite pathologic complete response (pCR), particularly in HER2-positive and triple-negative subtypes. MRI demonstrated superior concordance with pathology compared with mammography. Persistent calcifications did not consistently correlate with worse disease-free or overall survival when pCR was achieved. Radiologic–pathologic discordance contributed to overtreatment in some cohorts, including unnecessary mastectomy or extensive resections. Conclusions: Residual calcifications after NAC should not be regarded as a definitive surrogate of residual invasive disease nor as an obligatory indication for complete surgical removal. Their frequent benign or in situ pathology and limited prognostic value support a more individualized approach to surgical planning, prioritizing pathologic response and margin status over radiographic calcifications alone. Full article

Immunohistochemistry (IHC) is essential for diagnostic, prognostic, and predictive biomarker assessment in oncology, but manual interpretation is limited by subjectivity and inter-observer variability. Machine learning (ML), a computational subset of AI that allows algorithms to recognise patterns and learn from annotated datasets to make predictions or decisions, has led to advancements in digital pathology by supporting automated quantification of biomarker expression on whole-slide images (WSIs). This review evaluates the role of ML-assisted IHC scoring in the transition from validated biomarkers to the discovery of emerging prognostic and predictive IHC biomarkers for genitourinary (GU) tumours. Current applications include ML-based scoring of routinely used biomarkers such as ER/PR, HER2, mismatch repair (MMR) proteins, PD-L1, and Ki-67, demonstrating improved consistency and scalability. Emerging studies in GU cancers show that algorithms can quantify markers including androgen receptor (AR), PTEN, cytokeratins, Uroplakin II, Nectin-4 and immune checkpoint proteins, with early evidence indicating associations between ML-derived metrics and clinical outcomes. Important limitations remain, including limited availability of training datasets, variability in staining protocols, and regulatory challenges. Overall, ML-assisted IHC scoring is a reproducible and evolving approach that may support biomarker discovery and enhance precision GU oncology. Full article

Background: Rising cancer incidence and mortality have increased the use of central venous catheters (CVCs), including peripherally inserted central catheters (PICCs) and port-a-cath systems (PCSs), which play an important role in treatment administration. However, CVCs are associated with mechanical, infectious, and thrombotic complications. This study evaluates PCS-related complications and their management in oncological patients at The Oncology Institute “Prof. Dr. Ion Chiricuță,” Cluj-Napoca, Romania. Methods: This non-randomized, observational, retrospective study included cancer patients who had a PCS implanted at The Oncology Institute “Prof. Dr. Ion Chiricuță,” Cluj-Napoca, between 1 January 2024 and 31 December 2024 and were enrolled in a follow-up protocol to monitor and manage PCS-related complications. This study evaluated the incidence of complications, their association with predefined prognostic factors, and their management. Results: In the study cohort (n = 124 patients), complications related to the PCS were observed in 20% of the patients, with a mean interval to complication onset of 47 days. Early-onset complications were observed in 40% of patients, while the remaining 60% developed late-onset complications. PCS infection was the most common complication (10 patients), followed by wound dehiscence and thrombosis (6 patients each). Bleeding, extravasation, catheter migration, port malfunction, and torsion were each documented in a single patient. No prognostic factors were significantly associated with early or late PCS complications, with thrombosis approaching significance (p = 0.051). Conclusions: PCSs are generally safe in oncology patients; infections and thrombosis predominate as PCS-related complications, but rarely require removal, and standardized care enables long-term use, improving patient quality of life. Full article