Principles in the Management of Glioblastoma.

Glioblastoma, the most aggressive and common malignant primary brain tumour, is characterized by infiltrative growth, abundant vascularization, and aggressive clinical evolution. Patients with glioblastoma often face poor prognoses, with a median survival of approximately 15 months. Technological progress and the subsequent improvement in understanding the pathophysiology of these tumours have not translated into significant achievements in therapies or survival outcomes for patients. Progress in molecular profiling has yielded new omics data for a more refined classification of glioblastoma. Several typical genetic and epigenetic alterations in glioblastoma include mutations in genes regulating receptor tyrosine kinase (RTK)/rat sarcoma (RAS)/phosphoinositide 3-kinase (PI3K), p53, and retinoblastoma protein (RB) signalling, as well as mutation of isocitrate dehydrogenase (IDH), methylation of O6-methylguanine-DNA methyltransferase (MGMT), amplification of epidermal growth factor receptor vIII, and codeletion of 1p/19q. Certain microRNAs, such as miR-10b and miR-21, have also been identified as prognostic biomarkers. Effective treatment options for glioblastoma are limited. Surgery, radiotherapy, and alkylating agent chemotherapy remain the primary pillars of treatment. Only promoter methylation of the gene MGMT predicts the benefit from alkylating chemotherapy with temozolomide and it guides the choice of first-line treatment in elderly patients. Several targeted strategies based on tumour-intrinsic dominant signalling pathways and antigenic tumour profiles are under investigation in clinical trials. This review explores the potential genetic and epigenetic biomarkers that could be deployed as analytical tools in the diagnosis and prognostication of glioblastoma. Recent clinical advancements in treating glioblastoma are also discussed, along with the potential of liquid biopsies to advance personalized medicine in the field of glioblastoma, highlighting the challenges and promises for the future.

Identification of Novel Molecular and Clinical Biomarkers of Survival in Glioblastoma Multiforme Patients: A Study Based on The Cancer Genome Atlas Data.

Glioblastoma multiforme (GBM) is the most prevalent type of brain tumour; although advancements in treatment have been made, the median survival time for GBM patients has persisted at 15 months. This study is aimed at investigating the genetic alterations and clinical features of GBM patients to find predictors of survival. GBM patients' methylation and gene expression data along with clinical information from TCGA were retrieved. The most overrepresented pathways were identified independently for each omics dataset. From the genes found in at least 30% of these pathways, one gene that was identified in both sets was further examined using the Kaplan-Meier method for survival analysis. Additionally, three groups of patients who started radio and chemotherapy at different times were identified, and the influence of these variations in treatment modality on patient survival was evaluated. Four pathways that seemed to negatively impact survival and two with the opposite effect were identified. The methylation status of PRKCB was highlighted as a potential novel biomarker for patient survival. The study also found that treatment with chemotherapy prior to radiotherapy can have a significant impact on patient survival, which could lead to improvements in clinical management and therapeutic approaches for GBM patients.

Current Applications and Challenges of Next-Generation Sequencing in Plasma Circulating Tumour DNA of Ovarian Cancer.

Circulating tumour DNA (ctDNA) facilitates longitudinal study of the tumour genome, which, unlike tumour tissue biopsies, globally reflects intratumor and intermetastatis heterogeneity. Despite its costs, next-generation sequencing (NGS) has revolutionised the study of ctDNA, ensuring a more comprehensive and multimodal approach, increasing data collection, and introducing new variables that can be correlated with clinical outcomes. Current NGS strategies can comprise a tumour-informed set of genes or the entire genome and detect a tumour fraction as low as 10-5. Despite some conflicting studies, there is evidence that ctDNA levels can predict the worse outcomes of ovarian cancer (OC) in both early and advanced disease. Changes in those levels can also be informative regarding treatment efficacy and tumour recurrence, capable of outperforming CA-125, currently the only universally utilised plasma biomarker in high-grade serous OC (HGSOC). Qualitative evaluation of sequencing shows that increasing copy number alterations and gene variants during treatment may correlate with a worse prognosis in HGSOC. However, following tumour clonality and emerging variants during treatment poses a more unique opportunity to define treatment response, select patients based on their emerging resistance mechanisms, like BRCA secondary mutations, and discover potential targetable variants. Sequencing of tumour biopsies and ctDNA is not always concordant, likely as a result of clonal heterogeneity, which is better captured in the plasma samples than it is in a large number of biopsies. These incoherences may reflect tumour clonality and reveal the acquired alterations that cause treatment resistance. Cell-free DNA methylation profiles can be used to distinguish OC from healthy individuals, and NGS methylation panels have been shown to have excellent diagnostic capabilities. Also, methylation signatures showed promise in explaining treatment responses, including BRCA dysfunction. ctDNA is evolving as a promising new biomarker to track tumour evolution and clonality through the treatment of early and advanced ovarian cancer, with potential applicability in prognostic prediction and treatment selection. While its role in HGSOC paves the way to clinical applicability, its potential interest in other histological subtypes of OC remains unknown.

The Challenge of Somatic Variants in Focal Cortical Dysplasia.

Objective: The advent of next-generation sequencing (NGS) enabled the detection of low-level brain somatic variants in postsurgical tissue of focal cortical dysplasia (FCD). The genetic background of FCD Type I remains elusive, while the mammalian target of rapamycin (mTOR) pathway seems to have a relevant role in the pathogenesis of FCD Type II. Our goal was to uncover information on the molecular basis of FCD, performing whole genome sequencing (WGS) in postsurgical tissue to detect candidate brain-specific somatic variants, and evaluate their clinical significance. Design: WGS was performed using paired peripheral venous blood and postsurgical pathological brain deoxyribonucleic acid (DNA) samples. Libraries were prepared using the Roche KAPA HyperPrep polymerase chain reaction (PCR) free library preparation kit. Paired-end 150bp reads were generated on the Illumina NovaSeq platform. The FASTQ files were processed using the nf-core sarek pipeline (version 3.0) to call somatic variants, which were then annotated with ANNOVAR. A screening strategy was applied to obtain relevant variants. Results: Two female patients with drug-resistant epilepsy due to FCD who underwent surgical treatment were included. Regarding neuropathological diagnosis, one patient had FCD Type Ia and the other had FCD Type IIa. Five somatic nonsynonymous single nucleotide variants (SNVs) were detected using WGS, three in FCD Ia tissue (WDR24 p.Trp259Gly; MICAL1 p.Lys1036Arg; and KATNB1 p.Leu566Ile) and two in FCD IIa tissue (MATN4 p.Phe91Val and ANKRD6 p.His386Gln). All variants were predicted to be potentially pathogenic by at least two different tools. However, they were classified as variants of uncertain significance (VUS) according to the American College of Medical Genetics and Genomics (ACMG) criteria. Conclusion: Brain-specific somatic missense variants were identified by NGS in new candidate genes (WDR24, MICAL1, KATNB1, MATN4, and ANKRD6) using postsurgical FCD tissue, which may contribute to further understanding of the genetic background of FCD. All the reported genes were previously related to epilepsy and/or malformations of central nervous system (CNS) and cortical development. However, the pathogenicity assessment of these variants and, consequently, their impact on clinical practice still poses an important challenge.

Integrated Multi-Omics Signature Predicts Survival in Head and Neck Cancer.

Head and Neck Cancer (HNC) is characterized by phenotypic, biological, and clinical heterogeneity. Despite treatment modalities, approximately half of all patients will die of the disease. Several molecular biomarkers have been investigated, but until now, without clinical translation. Here, we identified an integrative nine-gene multi-omics signature correlated with HNC patients' survival independently of relapses or metastasis development. This prognosis multi-omic signature comprises genes mapped in the chromosomes 1q, 3p, 8q, 17q, 19p, and 19q and encompasses alterations at copy number, gene expression, and methylation. Copy number alterations in LMCD1-A1S and GRM7, the methylation status of CEACAM19, KRT17, and ST18, and the expression profile of RPL29, UBA7, FCGR2C, and RPSAP58 can predict the HNC patients' survival. The difference higher than two years observed in the survival of HNC patients that harbor this nine-gene multi-omics signature can represent a significant step forward to improve patients' management and guide new therapeutic targets development.

The landscape of common genetic drivers and DNA methylation in low-grade (epilepsy-associated) neuroepithelial tumors: A review.

Low-grade neuroepithelial tumors (LNETs) represent an important group of central nervous system neoplasms, some of which may be associated to epilepsy. The concept of long-term epilepsy-associated tumors (LEATs) includes a heterogenous group of low-grade, cortically based tumors, associated to drug-resistant epilepsy, often requiring surgical treatment. LEATs entities can sometimes be poorly discriminated by histological features, precluding a confident classification in the absence of additional diagnostic tools. This study aimed to provide an updated review on the genomic findings and DNA methylation profiling advances in LNETs, including histological entities of LEATs. A comprehensive search strategy was conducted on PubMed, Embase, and Web of Science Core Collection. High-quality peer-reviewed original manuscripts and review articles with full-text in English, published between 2003 and 2022, were included. Results were screened based on titles and abstracts to determine suitability for inclusion, and when addressed the topic of the review was screened by full-text reading. Data extraction was performed through a qualitative content analysis approach. Most LNETs appear to be driven mainly by a single genomic abnormality and respective affected signaling pathway, including BRAF p.V600E mutations in ganglioglioma, FGFR1 abnormalities in dysembryoplastic neuroepithelial tumor, MYB alterations in angiocentric glioma, BRAF fusions in pilocytic astrocytoma, PRKCA fusions in papillary glioneuronal tumor, between others. However, these molecular alterations are not exclusive, with some overlap amongst different tumor histologies. Also, clustering analysis of DNA methylation profiles allowed the identification of biologically similar molecular groups that sometimes transcend conventional histopathological classification. The exciting developments on the molecular basis of these tumors reinforce the importance of an integrative histopathological and (epi)genetic classification, which can be translated into precision medicine approaches.

Cytogenomic Analysis of Long-Term Epilepsy-Associated Tumors Using an Array-Based CGH Strategy.

A palette of copy number changes in long-term epilepsy-associated tumors (LEATs) have been reported, but the data are heterogeneous. To better understand the molecular basis underlying the development of LEATs, we performed array-comparative genomic hybridization analysis to investigate chromosomal imbalances across the entire genome in 8 cases of LEATs. A high number of aberrations were found in 4 patients, among which deletions predominated. Both whole-chromosome and regional abnormalities were observed, including monosomy 19, deletion of 1p, deletions of 4p, 12p, and 22q, and gain of 20p. The common altered regions are located mainly on chromosomes 19 and 4p, identifying genes potentially involved in biological processes and cellular mechanisms related to tumorigenesis. Our study highlights new genomic alterations and reinforces others previously reported, offering new molecular insights that may help in diagnosis and therapeutic decision-making.

Development of a genomic predictive model for cholangiocarcinoma using copy number alteration data.

AIMS: Cholangiocarcinoma (CC) is a rare tumour arising from the biliary tract epithelium. The aim of this study was to perform a genomic characterisation of CC tumours and to implement a model to differentiate extrahepatic (ECC) and intrahepatic (ICC) cholangiocarcinoma. METHODS: DNA extracted from tumour samples of 23 patients with CC, namely 10 patients with ECC and 13 patients with ICC, was analysed by array comparative genomic hybridisation. A support vector machine algorithm for classification was applied to the genomic data to distinguish between ICC and ECC. A survival analysis comparing both groups of patients was also performed. RESULTS: With these whole genome results, we observed several common alterations between tumour samples of the same CC anatomical type, namely gain of Xp and loss of 3p, 11q11, 14q, 16q, Yp and Yq in ICC tumours, and gain of 16p25.3 and loss of 3q26.1, 6p25.3-22.3, 12p13.31, 17p, 18q and Yp in ECC tumours. Gain of 2q37.3 was observed in the samples of both tumour subtypes, ICC and ECC. The developed genomic model comprised four chromosomal regions that seem to enable the distinction between ICC and ECC, with an accuracy of 71.43% (95% CI 43% to 100%). Survival analysis revealed that in our cohort, patients with ECC survived on average 8 months less than patients with ICC. CONCLUSIONS: This genomic characterisation and the introduction of genomic models to clinical practice could be important for patient management and for the development of targeted therapies. The power of this genomic model should be evaluated in other CC populations.

Genomic characterisation of multiple myeloma: study of a Portuguese cohort.

Multiple myeloma (MM) genomic complexity reflects in the variable patients' clinical presentation. Genome-wide studies seem to be a reasonable alternative to identify critical genomic lesions. In the current study, we have performed the genomic characterisation of a Portuguese cohort of patients with MM by array comparative genomic hybridisation. Overall, the most frequently detected alterations were 13q deletions, gains of 1q, 19p, 15q, 5p and 7p and trisomy 9. Even though some identified genomic alterations were previously associated with a prognostic value, other abnormalities remain with unknown, but putative significance for patients' clinical practice. These genomic alterations should be further assessed as possible biomarkers.

A seven-gene signature to predict the prognosis of oral squamous cell carcinoma.

The prognosis of oral squamous cell carcinoma (OSCC) patients remains poor without implemented biomarkers in the clinical routine practice to help in the patient's management. With this study we aimed to identify specific prognostic biomarkers for OSCC using a whole genome technology as well as to verify the clinical utility of a head and neck cancer-specific multiplex ligation-dependent probe amplification (MLPA) panel. A genomic characterization of tumor samples from 62 OSCC patients was performed using array comparative genomic hybridization (aCGH) and a more straightforward and cost-effective molecular technology, MLPA. The identification of a genomic signature and prognosis biomarkers was carried out by applying several statistical methods. With aCGH we observed that the chromosomes most commonly altered were 3p, 3q, 5q, 6p, 7q, 8p, 8q, 11q, 15q, 17q, and 18q. The MLPA results showed that the chromosomes with a higher frequency of alterations were 3p, 3q, 8p, 8q, and 11q. We identified a genomic signature with seven genes OCLN (3p21.31), CLDN16 (3q29), SCRIB (3q29), IKBKB (3q22.3), PAK2 (8q22.3), PIK3CB (3q28), and YWHAZ (8q24.3) that together allow to differentiate the patients that developed metastases or relapses after primary tumor treatment, with an overall accuracy of 79%. Amplification of PIK3CB as a predictor of metastases or relapses development was validated using TCGA data. This amplified gene showed a reduction in more than 5 years in the median survival of the patients. The identified biomarkers might have a significant impact in the patients' management and could leverage the OSCC precision medicine.

Liquid Biopsies: Applications for Cancer Diagnosis and Monitoring.

The minimally-or non-invasive detection of circulating tumor-derived components in biofluids, such as blood, liquid biopsy is a revolutionary approach with significant potential for the management of cancer. Genomic and transcriptomic alterations can be accurately detected through liquid biopsies, which provide a more comprehensive characterization of the heterogeneous tumor profile than tissue biopsies alone. Liquid biopsies could assist diagnosis, prognosis, and treatment selection, and hold great potential to complement current surveilling strategies to monitor disease evolution and treatment response in real-time. In particular, these are able to detect minimal residual disease, to predict progression, and to identify mechanisms of resistance, allowing to re-orient treatment strategies in a timelier manner. In this review we gathered current knowledge regarding the role and potential of liquid biopsies for the diagnosis and follow-up of cancer patients. The presented findings emphasize the strengths of liquid biopsies, revealing their chance of improving the diagnosis and monitoring of several tumor types in the near future. However, despite growing evidence supporting their value as a management tool in oncology, some limitations still need to be overcome for their implementation in the routine clinical setting.

Multiple Basal Cell Carcinomas of the Scalp After Radiotherapy: Genomic Study in a Case With Latency Period Over 80 Years.

ABSTRACT: Basal cell carcinoma (BCC) has been linked mostly to ultraviolet radiation exposure, but ionizing radiation has also been implicated in the genesis of a subset of BCCs occurring after radiotherapy. We present a 93-year-old woman with 4 BCCs of the scalp after radiotherapy for tinea capitis, diagnosed after a latency period of over 80 years. The largest lesion was located on the right temporal region and corresponded to a BCC of mixed type, with nodular, infiltrative, and micronodular components. We performed genomic study with array comparative genomic hybridization in samples from each BCC, which revealed more imbalances in the largest lesion than in the remaining ones, correlating with its higher histological complexity. Furthermore, this was the only lesion presenting loss at 2p22.3, where is mapped the BIRC6 gene associated with regulation of apoptosis, and loss at 16q24.3, where is mapped FANCA gene, responsible for DNA repair and maintenance of chromosome stability. Despite these differences, there were aberrations shared by all tumor samples, suggesting a common genetic signature. Our report describes, to the best of our knowledge, the longest latency period between exposure to radiotherapy and the diagnosis of BCC. The genomic study showed imbalances common to all tumor samples but also differences that could explain their heterogeneity in terms of histological subtype and biological potential. In addition, these differences could also be a consequence of different times in the evolution of the lesions at the moment of presentation, thus having a diverse combination of accumulated genomic imbalances.

Basal cell carcinomas of the scalp after radiotherapy for tinea capitis in childhood: A genetic and epigenetic study with comparison with basal cell carcinomas evolving in chronically sun-exposed areas.

BACKGROUND: Basal cell carcinoma (BCC) has been mostly associated with sun exposure, but ionizing radiation is also a known risk factor. It is not clear if the pathogenesis of BCC, namely at a genomic and epigenetic level, differs according to the underlying triggering factors. OBJECTIVE: The present study aims to compare genetic and epigenetic changes in BCCs related to ionizing radiation and chronic sun exposure. METHODS: Tumor samples from BCCs of the scalp in patients submitted to radiotherapy to treat tinea capitis in childhood and BCCs from sun-exposed areas were analysed through array comparative genomic hybridization (array-CGH) and methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) to detect copy number alterations and methylation status of specific genes. RESULTS: Genomic characterization of tumor samples revealed several copy number gains and losses in all chromosomes, with the most frequent gains observed at 2p, 6p, 12p, 14q, 15q, 18q, Xp and Yp, and the most frequent losses observed at 3q, 14q, 16p, 17q, 22q, Xp, Yp and Yq. We developed a statistical model, encompassing gains in 3p and 16p and losses in 14q and 20p, with potential to discriminate BCC samples with sporadic aetiology from BCC samples that evolve after radiotherapy in childhood for the treatment of tinea capitis, which presented statistical significance (P = 0.003). Few methylated genes were detected through MS-MLPA, most frequently RARB and CD44. CONCLUSIONS: Our study represents a step forward in the understanding of the genetic mechanisms underlying the pathogenesis of BCC and suggests potential differences according to the underlying ris k factors.

Probability distribution of copy number alterations along the genome: an algorithm to distinguish different tumour profiles.

Copy number alterations (CNAs) comprise deletions or amplifications of fragments of genomic material that are particularly common in cancer and play a major contribution in its development and progression. High resolution microarray-based genome-wide technologies have been widely used to detect CNAs, generating complex datasets that require further steps to allow for the determination of meaningful results. In this work, we propose a methodology to determine common regions of CNAs from these datasets, that in turn are used to infer the probability distribution of disease profiles in the population. This methodology was validated using simulated data and assessed using real data from Head and Neck Squamous Cell Carcinoma and Lung Adenocarcinoma, from the TCGA platform. Probability distribution profiles were produced allowing for the distinction between different phenotypic groups established within that cohort. This method may be used to distinguish between groups in the diseased population, within well-established degrees of confidence. The application of such methods may be of greater value in the clinical context both as a diagnostic or prognostic tool and, even as a useful way for helping to establish the most adequate treatment and care plans.

Proteomics-based Predictive Model for the Early Detection of Metastasis and Recurrence in Head and Neck Cancer.

BACKGROUND/AIM: Head and neck squamous cell carcinoma (HNSCC) presents high morbidity, an overall poor prognosis and survival, and a compromised quality of life of the survivors. Early tumor detection, prediction of its behavior and prognosis as well as the development of novel therapeutic strategies are urgently needed for a more successful HNSCC management. MATERIALS AND METHODS: In this study, a proteomics analysis of HNSCC tumor and non-tumor samples was performed and a model to predict the risk of recurrence and metastasis development was built. RESULTS: This predictive model presented good accuracy (>80%) and comprises as variables the tumor staging along with DHB12, HMGB3 and COBA1 proteins. Differences at the intensity levels of these proteins were correlated with the development of metastasis and recurrence as well as with patient's survival. CONCLUSION: The translation of proteomic predictive models to routine clinical practice may contribute to a more precise and individualized clinical management of the HNSCC patients, reducing recurrences and improving patients' quality of life. The capability of generalization of this proteomic model to predict the recurrence and metastases development should be evaluated and validated in other HNSCC populations.

Upper aerodigestive tract carcinoma: Development of a (epi)genomic predictive model for recurrence and metastasis.

Despite the increased molecular knowledge and the diagnostic and therapeutic improvements, the survival of patients with upper aerodigestive tract carcinoma remains poor. The identification of early diagnostic and prognostic biomarkers and the development of molecular models to distinguish patients that will recur and/or develop metastasis after treatment as well as to benefit with target therapies can be important to decrease mortality, improve survival rates and improve the quality of life of these patients. The current study analyzed 21 upper aerodigestive tract carcinomas through array comparative genomic hybridization and methylation-specific multiplex ligation-dependent probe amplification techniques. A number of chromosomal regions and genes were observed with copy number alterations and methylation. A predictive (epi)genomic model that comprises the 3p chromosomal region and WT1, VHL and THBS1 genes was built, highlighting a molecular signature with possible clinical use. The current study may aid in the development of a more individualized patient management and targeted drug design. The power of this genomic and epigenetic model to predict the recurrence and metastasis development should be evaluated and validated in future larger cohort study.

Iodine­131 metabolic radiotherapy leads to cell death and genomic alterations through NIS overexpression on cholangiocarcinoma.

Cholangiocarcinoma (CC) is an aggressive liver tumor with limited therapeutic options. Natrium­iodide symporter (NIS) mediates the uptake of iodine by the thyroid, representing a key component in metabolic radiotherapy using iodine­131 (131I) for the treatment of thyroid cancer. NIS expression is increased in CC, providing the opportunity for a novel therapeutic approach for this type of tumor. Thus, in this study, we aimed to evaluate therapeutic efficacy of 131I in two human CC cell lines. Uptake experiments analyzed the 131I uptake profiles of the tumor cell lines under study. The cells were irradiated with various doses of 131I to evaluate and characterize the effects of metabolic radiotherapy. NIS protein expression was assessed by immunofluorescence methods. Cell survival was evaluated by clonogenic assay and flow cytometry was used to assess cell viability, and the type of death and alterations in the cell cycle. The genomic and epigenetic characterization of both CC cells was performed before and after irradiation. NIS gene expression was evaluated in the CC cells by RT­qPCR. The results revealed that CC cells had a higher expression of NIS. 131I induced a decrease in cell survival in a dose­dependent manner. With the increasing irradiation dose, a decrease in cell viability was observed, with a consequent increase in cell death by initial apoptosis. Karyotype and array comparative genomic hybridization (aCGH) analyses revealed that both CC cell lines were near­triploid with several numerical and structural chromosomal rearrangements. NIS gene expression was increased in the TFK­1 and HuCCT1 cells in a time­dependent manner. On the whole, the findings of this study demonstrate that the presence of NIS in cholangiocarcinoma cell lines is crucial for the decreased cell viability and survival observed following the exposure of cholangiocarcinoma cells to 131I.