Cancer patient management: Current use of next-generation sequencing in the EU TOP4.

BACKGROUND: Next-generation sequencing (NGS) is recognised by a growing audience of medical professionals as a functional diagnostic tool in oncology. However, adoption in clinical routine proceeds haphazardly in Europe. METHODS: A semi-structured interview survey was administered to 68 cancer care professionals in four EU countries between June-August and November-December 2021. Pre-screening questionnaires assessed sufficient NGS expertise, diverse geographical distribution, and professional roles. RESULTS: Our findings provide a better understanding of current clinical, regulatory, and reimbursement practices for NGS in four EU countries. CONCLUSIONS: Despite the impending European In-vitro Diagnostic Medical Devices Regulation (IVDR), tortuous national guidelines implementations and limping reimbursement policies are common traits across surveyed countries and produce disparity in access to advanced healthcare services amid regional distinctions. POLICY SUMMARY: The evident information gap between involved parties and demand for consistent national guidelines could be filled by health economics analyses tailored to local specifics to provide factual leverage for a structured adoption of NGS testing.

Multiple instance learning for lung pathophysiological findings detection using CT scans.

Lung diseases affect the lives of billions of people worldwide, and 4 million people, each year, die prematurely due to this condition. These pathologies are characterized by specific imagiological findings in CT scans. The traditional Computer-Aided Diagnosis (CAD) approaches have been showing promising results to help clinicians; however, CADs normally consider a small part of the medical image for analysis, excluding possible relevant information for clinical evaluation. Multiple Instance Learning (MIL) approach takes into consideration different small pieces that are relevant for the final classification and creates a comprehensive analysis of pathophysiological changes. This study uses MIL-based approaches to identify the presence of lung pathophysiological findings in CT scans for the characterization of lung disease development. This work was focus on the detection of the following: Fibrosis, Emphysema, Satellite Nodules in Primary Lesion Lobe, Nodules in Contralateral Lung and Ground Glass, being Fibrosis and Emphysema the ones with more outstanding results, reaching an Area Under the Curve (AUC) of 0.89 and 0.72, respectively. Additionally, the MIL-based approach was used for EGFR mutation status prediction - the most relevant oncogene on lung cancer, with an AUC of 0.69. The results showed that this comprehensive approach can be a useful tool for lung pathophysiological characterization.

Towards Machine Learning-Aided Lung Cancer Clinical Routines: Approaches and Open Challenges.

Advancements in the development of computer-aided decision (CAD) systems for clinical routines provide unquestionable benefits in connecting human medical expertise with machine intelligence, to achieve better quality healthcare. Considering the large number of incidences and mortality numbers associated with lung cancer, there is a need for the most accurate clinical procedures; thus, the possibility of using artificial intelligence (AI) tools for decision support is becoming a closer reality. At any stage of the lung cancer clinical pathway, specific obstacles are identified and "motivate" the application of innovative AI solutions. This work provides a comprehensive review of the most recent research dedicated toward the development of CAD tools using computed tomography images for lung cancer-related tasks. We discuss the major challenges and provide critical perspectives on future directions. Although we focus on lung cancer in this review, we also provide a more clear definition of the path used to integrate AI in healthcare, emphasizing fundamental research points that are crucial for overcoming current barriers.

Extracellular Vesicles from Pancreatic Cancer Stem Cells Lead an Intratumor Communication Network (EVNet) to fuel tumour progression.

OBJECTIVE: Intratumor heterogeneity drives cancer progression and therapy resistance. However, it has yet to be determined whether and how subpopulations of cancer cells interact and how this interaction affects the tumour. DESIGN: We have studied the spontaneous flow of extracellular vesicles (EVs) between subpopulations of cancer cells: cancer stem cells (CSC) and non-stem cancer cells (NSCC). To determine the biological significance of the most frequent communication route, we used pancreatic ductal adenocarcinoma (PDAC) orthotopic models, patient-derived xenografts (PDXs) and genetically engineered mouse models (GEMMs). RESULTS: We demonstrate that PDAC tumours establish an organised communication network between subpopulations of cancer cells using EVs called the EVNet). The EVNet is plastic and reshapes in response to its environment. Communication within the EVNet occurs preferentially from CSC to NSCC. Inhibition of this communication route by impairing Rab27a function in orthotopic xenographs, GEMMs and PDXs is sufficient to hamper tumour growth and phenocopies the inhibition of communication in the whole tumour. Mechanistically, we provide evidence that CSC EVs use agrin protein to promote Yes1 associated transcriptional regulator (YAP) activation via LDL receptor related protein 4 (LRP-4). Ex vivo treatment of PDXs with antiagrin significantly impairs proliferation and decreases the levels of activated YAP.Patients with high levels of agrin and low inactive YAP show worse disease-free survival. In addition, patients with a higher number of circulating agrin+ EVs show a significant increased risk of disease progression. CONCLUSION: PDAC tumours establish a cooperation network mediated by EVs that is led by CSC and agrin, which allows tumours to adapt and thrive. Targeting agrin could make targeted therapy possible for patients with PDAC and has a significant impact on CSC that feeds the tumour and is at the centre of therapy resistance.

The value of cell-free circulating tumour DNA profiling in advanced non-small cell lung cancer (NSCLC) management.

Liquid biopsy (LB) has boosted a remarkable change in the management of cancer patients by contributing to tumour genomic profiling. Plasma circulating cell-free tumour DNA (ctDNA) is the most widely searched tumour-related element for clinical application. Specifically, for patients with lung cancer, LB has revealed valuable to detect the diversity of targetable genomic alterations and to detect and monitor the emergence of resistance mechanisms. Furthermore, its non-invasive nature helps to overcome the difficulty in obtaining tissue samples, offering a comprehensive view about tumour diversity. However, the use of the LB to support diagnostic and therapeutic decisions still needs further clarification. In this sense, this review aims to provide a critical view of the clinical importance of plasma ctDNA analysis, the most widely applied LB, and its limitations while anticipating concepts that will intersect the present and future of LB in non-small cell lung cancer patients.

An Interpretable Approach for Lung Cancer Prediction and Subtype Classification using Gene Expression.

Lung cancer is the deadliest form of cancer, accounting for 20% of total cancer deaths. It represents a group of histologically and molecularly heterogeneous diseases even within the same histological subtype. Moreover, accurate histological subtype diagnosis influences the specific subtype's target genes, which will help define the treatment plan to target those genes in therapy. Deep learning (DL) models seem to set the benchmarks for the tasks of cancer prediction and subtype classification when using gene expression data; however, these methods do not provide interpretability, which is great concern from the perspective of cancer biology since the identification of the cancer driver genes in an individual provides essential information for treatment and prognosis. In this work, we identify some limitations of previous work that showed efforts to build algorithms to extract feature weights from DL models, and we propose using tree-based learning algorithms that address these limitations. Preliminary results show that our methods outperform those of related research while providing model interpretability.Clinical Relevance: The machine learning methods used in this work are interpretable and provide biological insight. Two sets of genes were extracted: a set that differentiates normal tissue from cancerous tissue (cancer prediction), and a set of genes that distinguishes LUAD from LUSC samples (subtype classification).

Attention Based Deep Multiple Instance Learning Approach for Lung Cancer Prediction using Histopathological Images.

Deep Neural Networks using histopathological images as an input currently embody one of the gold standards in automated lung cancer diagnostic solutions, with Deep Convolutional Neural Networks achieving the state of the art values for tissue type classification. One of the main reasons for such results is the increasing availability of voluminous amounts of data, acquired through the efforts employed by extensive projects like The Cancer Genome Atlas. Nonetheless, whole slide images remain weakly annotated, as most common pathologist annotations refer to the entirety of the image and not to individual regions of interest in the patient's tissue sample. Recent works have demonstrated Multiple Instance Learning as a successful approach in classification tasks entangled with this lack of annotation, by representing images as a bag of instances where a single label is available for the whole bag. Thus, we propose a bag/embedding-level lung tissue type classifier using Multiple Instance Learning, where the automated inspection of lung biopsy whole slide images determines the presence of cancer in a given patient. Furthermore, we use a post-model interpretability algorithm to validate our model's predictions and highlight the regions of interest for such predictions.

The Adaptive Immune Landscape of the Colorectal Adenoma-Carcinoma Sequence.

BACKGROUND: The tumor immune microenvironment exerts a pivotal influence in tumor initiation and progression. The aim of this study was to analyze the immune context of sporadic and familial adenomatous polyposis (FAP) lesions along the colorectal adenoma-carcinoma sequence (ACS). METHODS: We analyzed immune cell counts (CD3+, CD4+, CD8+, Foxp3+, and CD57+), tumor mutation burden (TMB), MHC-I expression and PD-L1 expression of 59 FAP and 74 sporadic colorectal lesions, encompassing adenomas with low-grade dysplasia (LGD) (30 FAP; 30 sporadic), adenomas with high-grade dysplasia (22 FAP; 30 sporadic), and invasive adenocarcinomas (7 FAP; 14 sporadic). RESULTS: The sporadic colorectal ACS was characterized by (1) a stepwise decrease in immune cell counts, (2) an increase in TMB and MHC-I expression, and (3) a lower PD-L1 expression. In FAP lesions, we observed the same patterns, except for an increase in TMB along the ACS. FAP LGD lesions harbored lower Foxp3+ T cell counts than sporadic LGD lesions. A decrease in PD-L1 expression occurred earlier in FAP lesions compared to sporadic ones. CONCLUSIONS: The colorectal ACS is characterized by a progressive loss of adaptive immune infiltrate and by the establishment of a progressively immune cold microenvironment. These changes do not appear to be related with the loss of immunogenicity of tumor cells, or to the onset of an immunosuppressive tumor microenvironment.

Liquid Biopsy for Disease Monitoring in Non-Small Cell Lung Cancer: The Link between Biology and the Clinic.

INTRODUCTION: Cell-free DNA (cfDNA) analysis offers a non-invasive method to identify sensitising and resistance mutations in advanced Non-Small Cell Lung Cancer (NSCLC) patients. Next-generation sequencing (NGS) of circulating free DNA (cfDNA) is a valuable tool for mutations detection and disease's clonal monitoring. MATERIAL AND METHODS: An amplicon-based targeted gene NGS panel was used to analyse 101 plasma samples of advanced non-small cell lung cancer (NSCLC) patients with known oncogenic mutations, mostly EGFR mutations, serially collected at different clinically relevant time points of the disease. RESULTS: The variant allelic frequency (VAF) monitoring in consecutive plasma samples demonstrated different molecular response and progression patterns. The decrease in or the clearance of the mutant alleles was associated with response and the increase in or the emergence of novel alterations with progression. At the best response, the median VAF was 0% (0.0% to 3.62%), lower than that at baseline, with a median of 0.53% (0.0% to 9.9%) (p = 0.004). At progression, the VAF was significantly higher (median 4.67; range: 0.0-36.9%) than that observed at the best response (p = 0.001) and baseline (p = 0.006). These variations anticipated radiographic changes in most cases, with a median time of 0.86 months. Overall, the VAF evolution of different oncogenic mutations predicts clinical outcomes. CONCLUSION: The targeted NGS of circulating tumour DNA (ctDNA) has clinical utility to monitor treatment response in patients with advanced lung adenocarcinoma.

Clinical Application of Next-Generation Sequencing of Plasma Cell-Free DNA for Genotyping Untreated Advanced Non-Small Cell Lung Cancer.

BACKGROUND: Analysis of circulating tumor DNA (ctDNA) has remarkable potential as a non-invasive lung cancer molecular diagnostic method. This prospective study addressed the clinical value of a targeted-gene amplicon-based plasma next-generation sequencing (NGS) assay to detect actionable mutations in ctDNA in patients with newly diagnosed advanced lung adenocarcinoma. METHODS: ctDNA test performance and concordance with tissue NGS were determined, and the correlation between ctDNA findings, clinical features, and clinical outcomes was evaluated in 115 patients with paired plasma and tissue samples. RESULTS: Targeted-gene NGS-based ctDNA and NGS-based tissue analysis detected 54 and 63 genomic alterations, respectively; 11 patients presented co-mutations, totalizing 66 hotspot mutations detected, 51 on both tissue and plasma, 12 exclusively on tissue, and 3 exclusively on plasma. NGS-based ctDNA revealed a diagnostic performance with 81.0% sensitivity, 95.3% specificity, 94.4% PPV, 83.6% NPV, test accuracy of 88.2%, and Cohen's Kappa 0.764. PFS and OS assessed by both assays did not significantly differ. Detection of ctDNA alterations was statistically associated with metastatic disease (p = 0.013), extra-thoracic metastasis (p = 0.004) and the number of organs involved (p = 0.010). CONCLUSIONS: This study highlights the potential use of ctDNA for mutation detection in newly diagnosed NSCLC patients due to its high accuracy and correlation with clinical outcomes.

The Role of Liquid Biopsy in Early Diagnosis of Lung Cancer.

Liquid biopsy is an emerging technology with a potential role in the screening and early detection of lung cancer. Several liquid biopsy-derived biomarkers have been identified and are currently under ongoing investigation. In this article, we review the available data on the use of circulating biomarkers for the early detection of lung cancer, focusing on the circulating tumor cells, circulating cell-free DNA, circulating micro-RNAs, tumor-derived exosomes, and tumor-educated platelets, providing an overview of future potential applicability in the clinical practice. While several biomarkers have shown exciting results, diagnostic performance and clinical applicability is still limited. The combination of different biomarkers, as well as their combination with other diagnostic tools show great promise, although further research is still required to define and validate the role of liquid biopsies in clinical practice.

Validation of a Targeted Next-Generation Sequencing Panel for Tumor Mutation Burden Analysis: Results from the Onconetwork Immuno-Oncology Consortium.

Tumor mutation burden (TMB) is evaluated as a biomarker of response to immunotherapy. We present the efforts of the Onconetwork Immuno-Oncology Consortium to validate a commercial targeted sequencing test for TMB calculation. A three-phase study was designed to validate the Oncomine Tumor Mutational Load (OTML) assay at nine European laboratories. Phase 1 evaluated reproducibility and accuracy on seven control samples. In phase 2, six formalin-fixed, paraffin-embedded samples tested with FoundationOne were reanalyzed with the OTML panel to evaluate concordance and reproducibility. Phase 3 involved analysis of 90 colorectal cancer samples with known microsatellite instability (MSI) status to evaluate TMB and MSI association. High reproducibility of TMB was demonstrated among the sites in the first and second phases. Strong correlation was also detected between mean and expected TMB in phase 1 (r2 = 0.998) and phase 2 (r2 = 0.96). Detection of actionable mutations was also confirmed. In colorectal cancer samples, the expected pattern of MSI-high/high-TMB and microsatellite stability/low-TMB was present, and gene signatures produced by the panel suggested the presence of a POLE mutation in two samples. The OTML panel demonstrated robustness and reproducibility for TMB evaluation. Results also suggest the possibility of using the panel for mutational signatures and variant detection. Collaborative efforts between academia and companies are crucial to accelerate the translation of new biomarkers into clinical research.

BBIT20 inhibits homologous DNA repair with disruption of the BRCA1-BARD1 interaction in breast and ovarian cancer.

BACKGROUND AND PURPOSE: Advances in the treatment of triple-negative breast and ovarian cancer remain challenging. In particular, resistance to the available therapy, by restoring or overexpressing the DNA repair machinery, has often been reported. New strategies to improve the therapeutic outcomes of these cancers are needed. Herein, we disclose the dregamine 5-bromo-pyridin-2-ylhydrazone (BBIT20), a natural monoterpene indole alkaloid derivative, as an inhibitor of homologous DNA repair. EXPERIMENTAL APPROACH: To unveil BBIT20 antitumour activity and underlying molecular mechanism of action, two-dimensional (2D) and three-dimensional (3D) cell cultures, patient-derived cell lines and xenograft mouse models were used. KEY RESULTS: BBIT20 disrupted the BRCA1-BARD1 interaction, triggering nuclear-to-cytoplasmic BRCA1 translocation, cell cycle arrest and downregulation of homologous DNA repair-related genes and proteins, with subsequent enhancement of DNA damage, reactive oxygen species generation and apoptosis, in triple-negative breast and ovarian cancer cells. BBIT20 also displayed pronounced antitumour activity in patient-derived cells and xenograft mouse models of ovarian cancer, with low toxicity in non-malignant cells and undetectable side effects in mice. Additionally, it did not induce resistance in triple-negative breast and ovarian cancer and displayed marked synergistic effects with cisplatin and olaparib (a poly [ADP-ribose] polymerase inhibitor), on 2D and 3D models of these cancer cells. CONCLUSION AND IMPLICATIONS: These findings add an inhibitor of the BRCA1-BARD1 interaction to the list of DNA-damaging agents. Importantly, either as a single agent or in combination therapy, BBIT20 reveals great potential in the personalized treatment of aggressive and resistant cancers, particularly triple-negative breast and advanced ovarian cancer.

Targeting p53 for Melanoma Treatment: Counteracting Tumour Proliferation, Dissemination and Therapeutic Resistance.

Melanoma is the deadliest form of skin cancer, primarily due to its high metastatic propensity and therapeutic resistance in advanced stages. The frequent inactivation of the p53 tumour suppressor protein in melanomagenesis may predict promising outcomes for p53 activators in melanoma therapy. Herein, we aimed to investigate the antitumor potential of the p53-activating agent SLMP53-2 against melanoma. Two- and three-dimensional cell cultures and xenograft mouse models were used to unveil the antitumor activity and the underlying molecular mechanism of SLMP53-2 in melanoma. SLMP53-2 inhibited the growth of human melanoma cells in a p53-dependent manner through induction of cell cycle arrest and apoptosis. Notably, SLMP53-2 induced p53 stabilization by disrupting the p53-MDM2 interaction, enhancing p53 transcriptional activity. It also promoted the expression of p53-regulated microRNAs (miRNAs), including miR-145 and miR-23a. Moreover, it displayed anti-invasive and antimigratory properties in melanoma cells by inhibiting the epithelial-to-mesenchymal transition (EMT), angiogenesis and extracellular lactate production. Importantly, SLMP53-2 did not induce resistance in melanoma cells. Additionally, it synergized with vemurafenib, dacarbazine and cisplatin, and resensitized vemurafenib-resistant cells. SLMP53-2 also exhibited antitumor activity in human melanoma xenograft mouse models by repressing cell proliferation and EMT while stimulating apoptosis. This work discloses the p53-activating agent SLMP53-2 which has promising therapeutic potential in advanced melanoma, either as a single agent or in combination therapy. By targeting p53, SLMP53-2 may counteract major features of melanoma aggressiveness.

Next generation sequencing for liquid biopsy based testing in non-small cell lung cancer in 2021.

Lung cancer is the leading cause of cancer death worldwide, with non-small cell lung cancer (NSCLC) representing its most commonly diagnosed sub-type. Despite the significant improvements in lung cancer biomarkers knowledge, accompanied by substantial technological advances in molecular tumor profiling, a considerable fraction (up to 30 %) of advanced NSCLC patient presents with major testing challenges or tissue unavailability for molecular analysis. In this context, liquid biopsy is on the rise, currently gaining considerable interest within the molecular pathology and oncology community. Molecular profiling of liquid biopsy specimens using next generation molecular biology methodologies is a rapidly evolving field with promising applications not exclusively limited to advanced stages but also more recently expanding to early stages cancer patients. Here, we offer an overview of some of the most consolidated and emerging applications of next generation sequencing technologies for liquid biopsy testing in NSCLC.

Utility of Circulating Tumor DNA in Different Clinical Scenarios of Breast Cancer.

Breast cancer is a complex disease whose molecular mechanisms are not completely understood. Developing target therapies is a promising approach. Therefore, understanding the biological behavior of the tumor is a challenge. Tissue biopsy in the metastatic setting remains the standard method for diagnosis. Nevertheless, it has been associated with some disadvantages: It is an invasive procedure, it may not represent tumor heterogeneity, and it does not allow for treatment efficacy to be assessed or early recurrences to be detected. Analysis of circulating tumor DNA (ctDNA) may help to overcome this as it is a non-invasive method of monitoring the disease. In early-stage disease, it can detect early recurrences and monitor tumors' genomic profiles, identifying the emergence of new genetic alterations which can be related to tumor-acquired resistance. In the metastatic setting, the analysis of ctDNA may also allow for the anticipation of clinical and radiological progression of the disease, selection of targeted therapies, and for a photogram of tumor heterogeneity to be provided. It may also detect disease progression earlier in locally advanced tumors submitted to neoadjuvant treatment, and identify minimal residual disease. ctDNA analysis may guide clinical decision-making in different scenarios, in a precision medicine era, once it acts as a repository of genetic tumor material, allowing for a comprehensive mutation profiling analysis. In this review, we focused on recent advances towards the implementation of ctDNA in a clinical routine for breast cancer.

The Influence of the Genetic and Immunologic Context in the Development of Colorectal Adenoma: A Case Series Report.

INTRODUCTION: Overcoming immunosurveillance is a major step in the progression of many types of tumors. Several immune escape strategies have been identified, including immunoediting and the establishment of an immune suppressive microenvironment. The aim of the present study was to determine whether the hereditary or sporadic context has any influence in the relationship between immune surveillance and tumor development, using sporadic and familial adenomatous polyposis related colorectal adenomas as a model. MATERIAL AND METHODS: The immune tumor-infiltrating cells of a total of 58 low-grade and 18 high-grade colorectal adenomas were examined and compared, using immunostaining for CD3, CD4, CD8, CD57, CD68 and FoxP3. RESULTS: FoxP3 and CD68 counts were significantly higher in sporadic low-grade dysplasia (p = 0.0003 and p = 0.0103, respectively),and FoxP3 and CD4 counts were found to be significantly higher in high-grade sporadic dysplasia (p = 0.0008 and p = 0.0018, respectively)when compared with corresponding lesions in patients with familial adenomatous polyposis. DISCUSSION: This study suggests that the immune microenvironment of sporadic and hereditary lesions is different. Sporadic lesions contain a higher number of immune suppressive Treg cells, which suggests a stronger immune selective pressure. In contrast, hereditarylesions seem to benefit from a more tolerant immune microenvironment, allowing for the development of lesions with lower immune cell infiltration. CONCLUSION: This study shows that sporadic lesions harbor higher tumor-infiltrating immune cell counts, which might reflect a higher immune tolerance towards hereditary lesions.

Introdução: A capacidade de contornar a imunovigilância é fundamental na progressão de muitos tumores. Já foram identificadas várias estratégias de escape imunológico, incluindo immunoediting e o estabelecimento de um microambiente imunológico supressivo. O objetivo do presente estudo passa por determinar se o contexto hereditário ou esporádico influencia a relação entre a imunovigilância e o desenvolvimento do tumor, usando adenomas coloretais esporádicos e hereditários, no contexto de polipose adenomatosa familiar, como modelos. Material e Métodos: Os infiltrados imunológicos tumorais de um total de 58 adenomas coloretais de baixo grau e de 18 de alto grau foram avaliados e comparados, usando imunohistoquímica com marcação para CD3, CD4, CD8, CD57, CD68 e FoxP3. Resultados: As contagens celulares com imunorreatividade para FoxP3 e CD68 foram significativamente mais elevadas na displasia esporádica de baixo grau (p = 0,0003 e p = 0,0103, respetivamente), enquanto que as contagens para FoxP3 e CD4 foram significativamente mais elevadas na displasia esporádica de alto grau (p = 0,0008 e p = 0,0018, respetivamente) quando comparadas com lesões correspondentes em doentes com polipose adenomatosa familiar. Discussão: O presente estudo sugere que o microambiente imunológico de lesões esporádicas e hereditárias é diferente. As lesões esporádicas contam com um número superior de células T reguladoras, supressoras da função imunológica, sugerindo-se uma pressão imune seletiva mais forte. Por seu turno, as lesões hereditárias parecem beneficiar de um microambiente imunológico mais tolerante, permitindo o desenvolvimento de lesões com menor infiltrado celular imune. Conclusão: Este estudo demonstra que as lesões esporádicas contam com contagens de infiltrados imunológicos tumorais superiores, o que poderá refletir uma maior tolerância imunológica face a lesões hereditárias.

Identifying relationships between imaging phenotypes and lung cancer-related mutation status: EGFR and KRAS.

EGFR and KRAS are the most frequently mutated genes in lung cancer, being active research topics in targeted therapy. The biopsy is the traditional method to genetically characterise a tumour. However, it is a risky procedure, painful for the patient, and, occasionally, the tumour might be inaccessible. This work aims to study and debate the nature of the relationships between imaging phenotypes and lung cancer-related mutation status. Until now, the literature has failed to point to new research directions, mainly consisting of results-oriented works in a field where there is still not enough available data to train clinically viable models. We intend to open a discussion about critical points and to present new possibilities for future radiogenomics studies. We conducted high-dimensional data visualisation and developed classifiers, which allowed us to analyse the results for EGFR and KRAS biological markers according to different combinations of input features. We show that EGFR mutation status might be correlated to CT scans imaging phenotypes; however, the same does not seem to hold for KRAS mutation status. Also, the experiments suggest that the best way to approach this problem is by combining nodule-related features with features from other lung structures.

Comprehensive Perspective for Lung Cancer Characterisation Based on AI Solutions Using CT Images.

Lung cancer is still the leading cause of cancer death in the world. For this reason, novel approaches for early and more accurate diagnosis are needed. Computer-aided decision (CAD) can be an interesting option for a noninvasive tumour characterisation based on thoracic computed tomography (CT) image analysis. Until now, radiomics have been focused on tumour features analysis, and have not considered the information on other lung structures that can have relevant features for tumour genotype classification, especially for epidermal growth factor receptor (EGFR), which is the mutation with the most successful targeted therapies. With this perspective paper, we aim to explore a comprehensive analysis of the need to combine the information from tumours with other lung structures for the next generation of CADs, which could create a high impact on targeted therapies and personalised medicine. The forthcoming artificial intelligence (AI)-based approaches for lung cancer assessment should be able to make a holistic analysis, capturing information from pathological processes involved in cancer development. The powerful and interpretable AI models allow us to identify novel biomarkers of cancer development, contributing to new insights about the pathological processes, and making a more accurate diagnosis to help in the treatment plan selection.

Targeted Gene Next-Generation Sequencing Panel in Patients with Advanced Lung Adenocarcinoma: Paving the Way for Clinical Implementation.

Identification of targetable molecular changes is essential for selecting appropriate treatment in patients with advanced lung adenocarcinoma. Methods: In this study, a Sanger sequencing plus Fluorescence In Situ Hybridization (FISH) sequential approach was compared with a Next-Generation Sequencing (NGS)-based approach for the detection of actionable genomic mutations in an experimental cohort (EC) of 117 patients with advanced lung adenocarcinoma. Its applicability was assessed in small biopsies and cytology specimens previously tested for epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) mutational status, comparing the molecular changes identified and the impact on clinical outcomes. Subsequently, an NGS-based approach was applied and tested in an implementation cohort (IC) in clinical practice. Using Sanger and FISH, patients were classified as EGFR-mutated (n = 22, 18.8%), ALK-mutated (n = 9, 7.7%), and unclassifiable (UC) (n = 86, 73.5%). Retesting the EC with NGS led to the identification of at least one gene variant in 56 (47.9%) patients, totaling 68 variants among all samples. Still, in the EC, combining NGS plus FISH for ALK, patients were classified as 23 (19.7%) EGFR; 20 (17.1%) KRAS; five (4.3%) B-Raf proto-oncogene (BRAF); one (0.9%) Erb-B2 Receptor Tyrosine Kinase 2 (ERBB2); one (0.9%) STK11; one (0.9%) TP53, and nine (7.7%) ALK mutated. Only 57 (48.7%) remained genomically UC, reducing the UC rate by 24.8%. Fourteen (12.0%) patients presented synchronous alterations. Concordance between NGS and Sanger for EGFR status was very high (κ = 0.972; 99.1%). In the IC, a combined DNA and RNA NGS panel was used in 123 patients. Genomic variants were found in 79 (64.2%). In addition, eight (6.3%) EML4-ALK, four (3.1%), KIF5B-RET, four (3.1%) CD74-ROS1, one (0.8%) TPM3-NTRK translocations and three (2.4%) exon 14 skipping MET Proto-Oncogene (MET) mutations were detected, and 36% were treatable alterations. Conclusions: This study supports the use of NGS as the first-line test for genomic profiling of patients with advanced lung adenocarcinoma.