Search Results (87)

Background: Colorectal cancer (CRC) is a leading cause of cancer death, and the incidence and mortality rates among young adults are rising. Although a subset of CRC cases presents with a family history, suggesting a hereditary component, the specific genetic underpinnings remain incompletely understood, particularly in early-onset CRC (EOCRC). This study aimed to discover novel risk genes for EOCRC using exome sequencing and gene-based rare variant burden testing. Methods: Our cohort consisted of 212 European-ancestry cases (174 diagnosed with CRC and 38 with significant polyps) from the South Australian Young Onset Colorectal Polyp and Cancer Study (SAYO) and 31,699 unaffected controls from the Simons Foundation Powering Autism Research for Knowledge (SPARK) cohort. After filtering for ancestry, relatedness, variant quality, and population allele frequency, we performed gene-set and individual-gene burden tests using predicted deleterious missense and loss-of-function variants. Statistical significance was assessed using permutation-corrected binomial testing. An independent validation was conducted in the UK Biobank. Results: Loss-of-function variants in known CRC tumor suppressor genes were significantly enriched in SAYO cases. Gene-level analyses identified MEIKIN as a novel EOCRC susceptibility candidate (p value = 1.0 × 10⁻⁷), with supporting enrichment of deleterious missense and loss-of-function variants in distal colon cancer cases from the UK Biobank. Additional genes (STK25, PGBD4, DIRAS3, ATG3, RPS6KA4, and DDX42) demonstrated borderline significance, implicating pathways related to kinetochore assembly, autophagy regulation, and immune signaling. Both predicted gain-of-function and loss-of-function variants contributed to the EOCRC risk, supporting heterogeneous mechanisms of CRC pathogenesis. Conclusions: This study identified novel candidate risk genes for EOCRC, underscoring the role of rare variants and expanding our understanding of the genetic architecture of CRC. Future studies should include functional validation and replication studies on other ancestries to confirm and extend these results. Full article

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies. An unmet need exists for reliable biomarkers and in vitro models capable of predicting patient drug response to advance personalized medicine. Traditional models fail to represent the tumor’s complexity and the role of the stromal environment in chemoresistance. Patient-derived organoids (PDOs) overcome these limitations, enabling multi-omics profiling and reliable drug testing for functional precision medicine. This review provides a comprehensive overview of PDAC PDO research, emphasizing the following major areas: (i) the genetic and phenotypic fidelity of PDOs, (ii) their predictive value for drug response and chemoresistance, (iii) the integration of the extracellular matrix and tumor microenvironment (TME) components, and (iv) emerging technologies. Studies confirm that PDOs faithfully represent the primary tumor’s specific genetic features and retain intratumoral heterogeneity. PDO-based platforms have demonstrated a strong correlation between in vitro drug sensitivity and in vivo efficacy in xenograft models, validating their utility for identifying drug candidates, repurposing existing drugs, and determining effective combinations. Efforts are ongoing to integrate crucial TME components, like cancer-associated fibroblasts, using innovative co-culture platforms such as fused PDOs and InterOMaX, to better model desmoplasia and chemoresistance mechanisms. Furthermore, PDO technology is converging with microphysiological systems and artificial intelligence tools to facilitate high-throughput drug screening and dynamic, real-time monitoring of therapeutic effects. The integration of PDOs into biobanks and advanced screening platforms holds the potential to accelerate drug discovery and improve therapeutic outcomes for PDAC patients, if challenges related to protocol standardization and regulatory acceptance are addressed. Full article

Whole-genome sequencing (WGS) is integral to precision oncology, yet most cancer biospecimens used for WGS are formalin-fixed paraffin-embedded (FFPE) due to their widespread availability in clinical practice. However, FFPE processing can degrade DNA quality. This study compares WGS outcomes from matched cryopreserved (CP) and FFPE tumor samples, hypothesizing that CP tissues yield superior sequencing quality and variant detection. Fifty matched pairs of CP and FFPE tumor samples spanning multiple cancer types were obtained from a biobank. DNA was extracted, and WGS was performed. We assessed sequencing quality metrics and variant analysis between the two preservation methods. Presequencing metrics favored CP tissue, with a significantly higher gDNA concentration, DIN, and DNA fragment size. The WGS results showed that the CP samples had a higher mean read depth and larger insert size. Although the mapping percentages were similar, FFPE exhibited higher tumor mutation burden (13.7 vs. 6.4 mutations/Mb) and lower concordance with CP in variant calls (43.5% overlap). CP samples detected more structural variants and enabled the improved identification of oncogenic driver mutations. Cryopreserved tissues consistently outperform FFPE in terms of DNA quality and WGS metrics, enabling the more accurate detection of clinically relevant mutations. These findings support prioritizing CP sample preservation for genomic profiling in cancer care. Full article

Biobanks are essential for precision oncology, providing high-quality materials for biomedical research. Liquid biopsy has become a key tool for non-invasive detection of tumor-derived biomarkers, including circulating tumor DNA, proteins, and extracellular vesicles. However, the reliability of these assays critically depends on standardized preanalytical procedures. In this study, we evaluated the impact of two plasma isolation methods—direct centrifugation (DC) and density gradient centrifugation (DGC)—on the overall quality of breast cancer samples collected at the Bruno Boerci Biobank (Maugeri, Italy). Plasma obtained with the two methods was analyzed by spectrometry for hemolysis and lipemia, biochemical analysis for protein and lipoprotein composition, flow cytometry for cellular debris and platelet contamination. Preanalytical nonconformities due to hemolysis, icterus, and lipemia were comparable between methods. However, DGC was associated with a higher platelet contamination and reduced albumin and cholesterol levels. Inter-individual variability was preserved, supporting the robustness of patient-specific molecular signatures, despite absolute discrepancies. This study highlights the pivotal role of the isolation techniques in shaping the quality and overall composition of plasma samples. Harmonized, “fit-for-purpose” biobanking protocols are required to ensure reproducibility of downstream analyses, support biomarker discovery, and ultimately advance the identification of novel therapeutic targets in cancer. Full article

Hormonal alterations associated with polycystic ovary syndrome (PCOS) also impact bone metabolism, though it is unclear if this is bone-protective or not. Bone marker dysfunction has been reported in PCOS and appears to be associated with obesity. This study sought to determine whether a panel of bone marker proteins (BMPs) would be dysregulated in PCOS stratified by BMI as a potential biomarker for bone in PCOS. In this exploratory cross-sectional study, plasma was collected from 234 women (137 with PCOS and 97 controls) from a biobank cohort and compared to a nonobese, non-insulin resistant population (24 with PCOS and 24 controls). Slow Off-rate Modified Aptamer (SOMA)-scan plasma protein measurement was undertaken for the following BMPs: sclerostin; Dickkopf-related protein-1; glycogen synthase kinase-3 alpha/beta; periostin; tumor necrosis factor ligand superfamily member 11; fibroblast growth factor 23; sphingosine kinase 1; sphingosine kinase 2; cathepsins A, B, D, E, G, L2, S and Z; parathyroid hormone; osteocalcin; tumor necrosis factor ligand superfamily member 11 (sRANKL) and interleukin-1 beta. Four BMPs differed in the PCOS cohort (whole set without matching for body mass index (BMI) or insulin resistance (IR)): periostin (p = 0.05), cathepsin L (p = 0.05) and osteocalcin (p = 0.02) decreased in PCOS, whilst cathepsin D (p = 0.02) increased; however, linear regression showed that only cathepsins D and L and osteocalcin differed. None of the BMPs differed in the nonobese women with and without PCOS, nor in obese PCOS and controls stratified by BMI greater than 30 kg/m². In subgroup analysis, periostin (p = 0.001), sphingosine kinase 2 (p = 0.01) and cathepsin L (p = 0.001) were higher in obese versus nonobese PCOS (p = 0.01). Cathepsin Z (p = 0.02), sphingosine kinase 2 (p = 0.04) and lysosomal protective protein (p = 0.05) were lower in obese versus nonobese controls. Changes in BMPs indicative of impaired bone physiology were associated with BMI in both controls and PCOS, but did not differ between women with and without PCOS when BMI was matched. Hyperandrogenemia in PCOS did not affect BMP levels. Full article

The inherent complexity and heterogeneity of tumors pose substantial challenges for the development of effective oncology therapeutics. Organoids, three-dimensional (3D) in vitro models, have become essential tools for predicting therapeutic responses and advancing precision oncology, with established correlations to clinical outcomes in patient-derived models. These systems have transformed preclinical drug screening by bridging the gap between conventional two-dimensional (2D) cultures and in vivo models, preserving tumor histopathology, cellular heterogeneity, and patient-specific molecular profiles. Despite their potential, limitations in tumor organoid biology, including inter-batch variability and microenvironmental simplification, can undermine their reliability and scalability in large-scale drug screening. To overcome these challenges, the integration of advanced technologies such as artificial intelligence (AI), automated biomanufacturing, multi-omics analytics, and vascularization strategies has been explored. This review highlights the “Organoid plus and minus” framework, which combines technological augmentation with culture system refinement to improve screening accuracy, throughput, and physiological relevance. We are convinced that the future of drug development hinges on the convergence of these multidisciplinary technologies with standardized biobanking and co-clinical validation frameworks. This integration will position organoids as a cornerstone for personalized drug discovery and therapeutic optimization, ultimately advancing the development of efficacy in oncology. Full article

Background: Medication-related osteonecrosis of the jaw (MRONJ) is a serious adverse effect of bone-modifying agents. The aim of this study was to elucidate the pathogenesis of MRONJ through a comprehensive comparison of bone-metabolism-related factors in sera from patients with MRONJ and healthy controls. Methods: This study was a retrospective cross-sectional biobank analysis in which 31 patients in a non-MRONJ group and 10 patients in an MRONJ group were screened. Serum levels of 13 proteins (i.e., hormones, growth factors, and cytokines) related to bone metabolism were measured by simultaneous multi-parameter analysis using bead-based immunoassays. Results: The MRONJ group displayed suppressed bone metabolism with a background of chronic inflammation. In addition, a significant decrease in the expression of alkaline phosphatase liver/bone/kidney (p < 0.05, effect size of 0.46 (95% CI: 0.08 to 0.73)) and a significant increase (p < 0.05, effect size was −0.42 (95%CI: −0.72 to 0.01)) in the expression of tumor necrosis factor α were observed in the MRONJ group. Conclusions: These results may contribute to a better understanding of the etiology, pathophysiology, and progression of MRONJ. Full article

The search for markers applicable for efficient differential diagnosis and personalized therapy is a priority task of experimental neuro-oncology. Modern molecular methods allow us to analyze human biopsy material; however, further actions with this extracted tumor tissue are limited. Relevant and sophisticated CNS tumor models are required for precise therapy development. Although it is possible to use human biomaterial to create 2D and 3D cultures and implant them into xenograft animals, the data generated from such models is limited. Due to changes in the classification of the CNS tumors in 2021, a representative model should have not only morphological similarity to human tumors but also key genetic aberrations for studying the mechanisms of carcinogenesis and personalized therapy (such as PDGFRa, Olig1/2, Sox2, and Mki67) for different glioma models such as astrocytoma, oligodendroglioma, and glioblastoma. On the basis of a unique scientific facility “The Collection of experimental tumors of the nervous system and neural tumor cell lines” (Avtsyn Research Institute of Human Morphology of “Petrovsky National Research Center of Surgery”), there is a biobank of chemically induced transplantable tumors of laboratory animals. Their properties, mechanisms, and progression closely correlate with malignant CNS neoplasms in humans. These are potentially useful for identifying novel signaling pathways associated with oncogenesis in the nervous system and personalizing therapeutic approaches. In our work, we characterized a tissue-transplantable brain tumor strain of rat glioma101.8 using MRI, IHC, scRNA-seq, and qPCR-RT methods. According to this study, the cellular composition of the tissue-transplantable rat glioma 101.8 strain was determined, as well as the major genetic signature characteristics of each cell population of this tissue-transplantable strain and its microenvironment. Full article

Over the past decade, patient-derived organoids (PDOs) have emerged as powerful in vitro models that closely recapitulate the histological, genetic, and functional features of their parental primary tissues, representing a ground-breaking tool for cancer research and precision medicine. This advancement has led to the development of living PDO biobanks, collections of organoids derived from a wide range of tumor types and patient populations, which serve as essential platforms for drug screening, biomarker discovery, and functional genomics. The classification and global distribution of these biobanks reflect a growing international effort to standardize protocols and broaden accessibility, supporting both basic and translational research. While their relevance to personalized medicine is increasingly recognized, the establishment and maintenance of PDO biobanks remain technically demanding, particularly in terms of optimizing long-term culture conditions, preserving sample viability, and mimicking the tumor microenvironment. In this context, this review provides an overview of the classification and worldwide distribution of tumor and paired healthy tissue-specific PDO biobanks, explores their translational applications, highlights recent advances in culture systems and media formulations, and discusses current challenges and future perspectives for their integration into clinical practice. Full article

Glioblastoma is a highly aggressive, infiltrative brain tumor of the central nervous system (CNS). Its extensive molecular and biochemical heterogenicity hinders the identification of reliable biomarkers and therapeutic targets, thereby making prognosis and existing therapy ineffective. In recent years, breakthroughs in the use of proteomics on a range of biological samples, such as plasma, cerebrospinal fluid (CSF), tissues, brain cells, and exosomes, represent a potential improvement to GBM investigations. Mass spectrometry-based approaches represent an important technique in the characterization of the tumoral proteome, for the identification of differentially expressed proteins, and for studying altered molecular pathways involved in tumor stages. Proteomics studies advance our knowledge about GBM pathogenesis, the discovery of reliable diagnostic and prognostic markers, and therapeutic approaches, also. In this context, for the effective application of proteomics on GBM, it is mandatory to develop a translational network by integrating hospitals, biobanks, and research institutions into a single network, to enable a collaborative approach across disciplines, thereby enabling rapid translation to clinical application of new proteomic insights. Today, high-quality biobanks play a key role in enabling collaborative, ethically compliant research, supporting the effective application of proteomics in glioblastoma studies and the translation of discoveries into clinical practice. This review explores current trends in proteomics and GBM research, highlighting how leveraging biobank infrastructure and fostering institutional cooperation can drive the development of targeted pilot projects to enhance the impact and effectiveness of glioblastoma research. Full article

The increased workload in pathology laboratories today means automated tools such as artificial intelligence models can be useful, helping pathologists with their tasks. In this paper, we propose a segmentation model (DRU-Net) that can provide a delineation of human non-small cell lung carcinomas and an augmentation method that can improve classification results. The proposed model is a fused combination of truncated pre-trained DenseNet201 and ResNet101V2 as a patch-wise classifier, followed by a lightweight U-Net as a refinement model. Two datasets (Norwegian Lung Cancer Biobank and Haukeland University Lung Cancer cohort) were used to develop the model. The DRU-Net model achieved an average of 0.91 Dice similarity coefficient. The proposed spatial augmentation method (multi-lens distortion) improved the Dice similarity coefficient from 0.88 to 0.91. Our findings show that selecting image patches that specifically include regions of interest leads to better results for the patch-wise classifier compared to other sampling methods. A qualitative analysis by pathology experts showed that the DRU-Net model was generally successful in tumor detection. Results in the test set showed some areas of false-positive and false-negative segmentation in the periphery, particularly in tumors with inflammatory and reactive changes. In summary, the presented DRU-Net model demonstrated the best performance on the segmentation task, and the proposed augmentation technique proved to improve the results. Full article

Disease progression and treatment resistance in colorectal and other cancers are driven by a subset of cells within the tumor that have stem-cell-like properties and long-term tumorigenic potential. These stem-cell-like cells express the leucine-rich G repeat-containing protein-coupled receptor 5 (LGR5) and have characteristics similar to tissue-resident stem cells in normal adult tissues such as the colon. Organoid models of murine and human colorectal and other cancers contain LGR5-expressing (LGR5+) stem-cell-like cells and can be used to investigate the underlying mechanisms of cancer development, progression, therapy vulnerability, and resistance. A large biobank of organoids derived from colorectal cancer or adjacent normal tissue was developed. We performed a large-scale unbiased functional screen to identify bispecific antibodies (BsAbs) that preferentially inhibit the growth of colon tumor-derived, as compared to normal tissue-derived, organoids. We identified the most potent BsAb in the screen as petosemtamab, a Biclonics^® BsAb targeting both LGR5 and the epidermal growth factor receptor (EGFR). Petosemtamab employs three distinct mechanisms of action: EGFR ligand blocking, EGFR receptor internalization and degradation in LGR5+ cells, and Fc-mediated activation of the innate immune system by antibody-dependent cellular phagocytosis (ADCP) and enhanced antibody-dependent cellular cytotoxicity (ADCC) (see graphical abstract). Petosemtamab has demonstrated substantial clinical activity in recurrent/metastatic head and neck squamous cell carcinoma (r/m HNSCC). The safety profile is generally favorable, with low rates of skin and gastrointestinal toxicity. Phase 3 trials are ongoing in both first-line programmed death-ligand 1-positive (PD-L1+) and second/third-line r/m HNSCC. Full article

Triple-negative breast cancer (TNBC) is an aggressive subtype requiring further knowledge of biomarkers to improve targeted therapy. A major resistance mechanism involves breast cancer stem cells (BCSCs) evading the immune system. Neoadjuvant or adjuvant chemotherapy may alter BCSCs and the patients’ immune response. We conducted a retrospective study including 29 early-stage TNBC patients resistant to chemotherapy diagnosed at the Catalan Institute of Oncology (Girona, Spain) in 2010–2019. We obtained 44 paired tumor samples (pre- and post-chemotherapy) from the Tumor Biobank, assessing BCSC biomarkers (CD44, CD24, and ALDH1), PD-L1, and percentages of stromal tumor-infiltrating lymphocytes (TILs). Clinicopathological characteristics were also collected. At baseline, 68% of tumors had high CD44 expression, 55% showed low CD24 expression, 9% had high ALDH1 expression, 91% were PD-L1-negative (<1%), and 64% had a low percentage of stromal TILs. PD-L1 expression significantly increased post-chemotherapy, with 50% of initially negative tumors becoming PD-L1 positive (≥1%) (p = 0.006). No significant changes were observed in BCSC markers or TILs. No association was found between baseline BCSCs and increased PD-L1 expression post-chemotherapy. At a median follow-up of 58.9 months, 48.3% of patients were alive, with non-significant favorable trends in time to progression, disease-free survival, and overall survival in the PD-L1 positivization cohort post-chemotherapy. In conclusion, high-risk early-stage TNBC tumors increased PD-L1 expression after chemotherapy, potentially affecting clinical outcomes. BCSCs remained stable and independent of the tumor immunogenicity post-chemotherapy. Further studies are needed to explore the relationship between BCSCs and the immunogenicity profile, for development of new combined therapeutic strategies. Full article

In 2023, at the Center for Biological Resources (CRB) at the Institute of Genetics and Biophysics (IGB, Naples, Italy) of the National Research Council (CNR), the Breast Cancer Tissues and Organoids Biobank (BCTO BioBank) was founded. This is a new generation Biobank, dedicated to the collection, characterization, storage, and distribution of tissues and their 3D ‘organoid’ patients-derived. Tumor and healthy tissues from breast cancer patients have been collected from surgeons at Monaldi Hospital (Naples, Italy) and used to generate the corresponding tumor and healthy organoids from the same patient. After their establishment in culture, both organoids were characterized for their receptor status on a microfluidic 2-lane OrganoPlate, by immunofluorescence. The resulting data were compared with the expression profile obtained by immunohistochemistry on respective parental tissues. These data allowed us to phenotypically validate the generated organoids and classify them in a dedicated database, where also the clinical data of the corresponding patients were collected. During the six months of activities, we collected and characterized 27 samples. The continuous BCTO BioBank activity is fundamental to generating a high number of samples, for a broader and efficiently elaborated patient stratification at molecular level, biomarker discovery investigations, and for tailored treatment protocols design. Full article

Objective: This study aimed to investigate potential specific molecular and neuroimaging biomarkers for stroke subtype recurrence to improve secondary stroke prevention. Methods: A retrospective analysis was conducted on a prospective stroke biobank. The main endpoint was to evaluate the association between different biomarkers and the recurrence of stroke subtypes. Serum levels of interleukin 6 (IL-6) and tumor necrosis factor-alpha (TNF-a) were analyzed as inflammation biomarkers; N-terminal pro-B-type natriuretic peptide (NT-pro-BNP) and microalbuminuria were used as atrial/endothelial dysfunction biomarkers, while leukoaraiosis (LA) and soluble TNF-like inducers of apoptosis (sTWEAK) were used as biomarkers for blood–brain barrier dysfunction. Demographic and clinical variables were also included. Results: A total of 5038 stroke patients were included, with a mean follow-up of 4.9 years (±3.3). Stroke recurrences were observed in 18.4% of patients (927 individuals). The main results found were as follows: LA was independently associated with lacunar stroke recurrence (adjusted OR 9.50; 95% CI: 3.12–28.93). NT-pro-BNP levels higher than >1000 pg/mL were independently associated with cardioembolic stroke recurrence (adjusted OR 1.80; 95% CI: 1.23–2.61). Persistently elevated TNF-a levels (>24 pg/mL) after stroke recurrence showed an adjusted OR of 21.26 (95% CI: 12.42–37.59) for atherothrombotic subtype, whereas persistently high sTWEAK levels (>7000 pg/mL) after a second hemorrhagic stroke showed an adjusted OR of 4.81 (95% CI: 2.86–8.07) for hemorrhagic subtype. Conclusions: The presence of LA and high levels of NT-pro-BNP, TNF-a, and sTWEAK were associated with an increased risk for lacunar, cardioembolic, atherothrombotic, and hemorrhagic stroke recurrences, respectively. Full article