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BACKGROUND: Interpreting the clinical consequences of genetic variants is the central problem in modern clinical genomics, for both hereditary diseases and oncology. However, clinical validation lags behind the pace of discovery, leading to distressing uncertainty for patients, physicians and researchers. This "interpretation gap" changes over time as evidence accumulates, and variants initially deemed of uncertain (VUS) significance may be subsequently reclassified in pathogenic/benign. We previously developed RENOVO, a random forest-based tool able to predict variant pathogenicity based on publicly available information from GnomAD and dbNFSP, and tested on variants that have changed their classification status over time. Here, we comprehensively evaluated the accuracy of RENOVO predictions on variants that have been reclassified over the last four years. METHODS: we retrieved 16 retrospective instances of the ClinVar database, every 3 months since March 2020 to March 2024, and analyzed time trends of variant classifications. We identified variants that changed their status over time and compared RENOVO predictions generated in 2020 with the actual reclassifications. RESULTS: VUS have become the most represented class in ClinVar (44.97% vs. 9.75% (likely) pathogenic and 40,33% (likely) benign). The rate of VUS reclassification is linear and slow compared to the rate of VUS reporting, exponential and currently ~ 30x faster, creating a growing divide between what can be sequenced vs. what can be interpreted. Out of 10,196 VUS variants in January 2020 that have undergone a clinically meaningful reclassification to march 2024, RENOVO correctly classified 82.6% in 2020. In addition, RENOVO correctly identified the majority of the few variants that switched clinically meaningful classes (e.g., from benign to pathogenic and vice versa). We highlight variant classes and clinically relevant genes for which RENOVO provides particularly accurate estimates. In particularly, genes characterized by large prevalence of high- or low-impact variants (e.g., POLE, NOTCH1, FANCM etc.). Suboptimal RENOVO predictions mostly concern genes validated through dedicated consortia (e.g., BRCA1/2), in which RENOVO would anyway have a limited impact. CONCLUSIONS: Time trend analysis demonstrates that the current model of variant interpretation cannot keep up with variant discovery. Machine learning-based tools like RENOVO confirm high accuracy that can aid in clinical practice and research.
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Bases de Dados Genéticas , Variação Genética , Humanos , Fatores de Tempo , Reprodutibilidade dos Testes , Genômica/métodosRESUMO
Intratumor morphological heterogeneity of pancreatic ductal adenocarcinoma (PDAC) predicts clinical outcomes but is only partially understood at the molecular level. To elucidate the gene expression programs underpinning intratumor morphological variation in PDAC, we investigated and deconvoluted at single cell level the molecular profiles of histologically distinct clusters of PDAC cells. We identified three major morphological and functional variants that co-exist in varying proportions in all PDACs, display limited genetic diversity, and are associated with a distinct organization of the extracellular matrix: a glandular variant with classical ductal features; a transitional variant displaying abortive ductal structures and mixed endodermal and myofibroblast-like gene expression; and a poorly differentiated variant lacking ductal features and basement membrane, and showing neuronal lineage priming. Ex vivo and in vitro evidence supports the occurrence of dynamic transitions among these variants in part influenced by extracellular matrix composition and stiffness and associated with local, specifically neural, invasion.
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Carcinoma Ductal Pancreático , Neoplasias Pancreáticas , Humanos , Neoplasias Pancreáticas/patologia , Carcinoma Ductal Pancreático/patologia , Matriz Extracelular/genética , Matriz Extracelular/metabolismo , Matriz Extracelular/patologia , Membrana Basal/metabolismo , Sistema NervosoRESUMO
Caloric Restriction (CR) has established anti-cancer effects, but its clinical relevance and molecular mechanism remain largely undefined. Here, we investigate CR's impact on several mouse models of Acute Myeloid Leukemias, including Acute Promyelocytic Leukemia, a subtype strongly affected by obesity. After an initial marked anti-tumor effect, lethal disease invariably re-emerges. Initially, CR leads to cell-cycle restriction, apoptosis, and inhibition of TOR and insulin/IGF1 signaling. The relapse, instead, is associated with the non-genetic selection of Leukemia Initiating Cells and the downregulation of double-stranded RNA (dsRNA) sensing and Interferon (IFN) signaling genes. The CR-induced adaptive phenotype is highly sensitive to pharmacological or genetic ablation of LSD1, a lysine demethylase regulating both stem cells and dsRNA/ IFN signaling. CR + LSD1 inhibition leads to the re-activation of dsRNA/IFN signaling, massive RNASEL-dependent apoptosis, and complete leukemia eradication in ~90% of mice. Importantly, CR-LSD1 interaction can be modeled in vivo and in vitro by combining LSD1 ablation with pharmacological inhibitors of insulin/IGF1 or dual PI3K/MEK blockade. Mechanistically, insulin/IGF1 inhibition sensitizes blasts to LSD1-induced death by inhibiting the anti-apoptotic factor CFLAR. CR and LSD1 inhibition also synergize in patient-derived AML and triple-negative breast cancer xenografts. Our data provide a rationale for epi-metabolic pharmacologic combinations across multiple tumors.
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Insulinas , Leucemia Mieloide Aguda , Humanos , Animais , Camundongos , Restrição Calórica , Leucemia Mieloide Aguda/patologia , Histona Desmetilases/genética , Células-Tronco Neoplásicas/patologia , Linhagem Celular TumoralRESUMO
BACKGROUND: The current therapeutic algorithm for Advanced Stage Melanoma comprises of alternating lines of Targeted and Immuno-therapy, mostly via Immune-Checkpoint blockade. While Comprehensive Genomic Profiling of solid tumours has been approved as a companion diagnostic, still no approved predictive biomarkers are available for Melanoma aside from BRAF mutations and the controversial Tumor Mutational Burden. This study presents the results of a Multi-Centre Observational Clinical Trial of Comprehensive Genomic Profiling on Target and Immuno-therapy treated advanced Melanoma. METHODS: 82 samples, collected from 7 Italian Cancer Centres of FFPE-archived Metastatic Melanoma and matched blood were sequenced via a custom-made 184-gene amplicon-based NGS panel. Sequencing and bioinformatics analysis was performed at a central hub. Primary analysis was carried out via the Ion Reporter framework. Secondary analysis and Machine Learning modelling comprising of uni and multivariate, COX/Lasso combination, and Random Forest, was implemented via custom R/Python scripting. RESULTS: The genomics landscape of the ACC-mela cohort is comparable at the somatic level for Single Nucleotide Variants and INDELs aside a few gene targets. All the clinically relevant targets such as BRAF and NRAS have a comparable distribution thus suggesting the value of larger scale sequencing in melanoma. No comparability is reached at the CNV level due to biotechnological biases and cohort numerosity. Tumour Mutational Burden is slightly higher in median for Complete Responders but fails to achieve statistical significance in Kaplan-Meier survival analysis via several thresholding strategies. Mutations on PDGFRB, NOTCH3 and RET were shown to have a positive effect on Immune-checkpoint treatment Overall and Disease-Free Survival, while variants in NOTCH4 were found to be detrimental for both endpoints. CONCLUSIONS: The results presented in this study show the value and the challenge of a genomics-driven network trial. The data can be also a valuable resource as a validation cohort for Immunotherapy and Target therapy genomic biomarker research.
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Detecção Precoce de Câncer , Melanoma , Humanos , Melanoma/genética , Proteínas Proto-Oncogênicas B-raf , Genômica , ItáliaRESUMO
The last decade has seen rapid progress in the use of genomic tests, including gene panels, whole-exome sequencing, and whole-genome sequencing, in research and clinical cancer care. These advances have created expansive opportunities to characterize the molecular attributes of cancer, revealing a subset of cancer-associated aberrations called driver mutations. The identification of these driver mutations can unearth vulnerabilities of cancer cells to targeted therapeutics, which has led to the development and approval of novel diagnostics and personalized interventions in various malignancies. The applications of this modern approach, often referred to as precision oncology or precision cancer medicine, are already becoming a staple in cancer care and will expand exponentially over the coming years. Although genomic tests can lead to better outcomes by informing cancer risk, prognosis, and therapeutic selection, they remain underutilized in routine cancer care. A contributing factor is a lack of understanding of their clinical utility and the difficulty of results interpretation by the broad oncology community. Practical guidelines on how to interpret and integrate genomic information in the clinical setting, addressed to clinicians without expertise in cancer genomics, are currently limited. Building upon the genomic foundations of cancer and the concept of precision oncology, the authors have developed practical guidance to aid the interpretation of genomic test results that help inform clinical decision making for patients with cancer. They also discuss the challenges that prevent the wider implementation of precision oncology.
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Testes Genéticos , Genômica , Neoplasias , Medicina de Precisão , Humanos , Neoplasias/genética , Neoplasias/terapia , Neoplasias/diagnóstico , Medicina de Precisão/métodos , Genômica/métodos , Testes Genéticos/métodos , Guias de Prática Clínica como Assunto , Biomarcadores Tumorais/genética , MutaçãoRESUMO
BACKGROUND: Immune-related adverse events (IRAE) pose a significant diagnostic and therapeutic challenge in patients treated with immune-oncology (IO) drugs. IRAEs have been suggested to correlate with better outcome, but studies are conflicting. Estimating the true incidence of IRAEs is particularly difficult in the early phase I/II trial setting. A key issue is the lack of IRAE diagnostic criteria, necessary to discriminate "pure" IRAEs from other treatment-related adverse events not sustained by an autoimmune process. METHODS: In patients treated with immune-oncology (IO) drugs in phases I-II trials at our institute, we identified high confidence (HC) or low confidence (LC) IRAEs by clinical consensus. We empirically developed an IRAE likelihood score (ILS) based on commonly available clinical data. Correlation with outcome was explored by multivariate Cox analysis. To mitigate immortal time-bias, analyses were conducted (1) at 2-month landmark and (2) modeling IRAEs as time-dependent covariate. RESULTS: Among 202 IO-treated patients, 29.2% developed >1 treatment-related adverse events (TRAE). Based on ILS >5, we classified patients in no IRAE (nâ =â 143), HC IRAE (nâ =â 24), or LC IRAE (nâ =â 35). hazard ratios (HR) for HC were significantly lower than LC patients (HR for PFS ranging 0.24-0.44, for OS 0.18-0.23, all Pâ <â .01). CONCLUSION: ILS provides a simple system to identify bona fide IRAEs, pruning for other treatment-related events likely due to different pathophysiology. Applying stringent criteria leads to lower and more reliable estimates of IRAE incidence and identifies events with significant impact on survival.
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BACKGROUND: Molecular-driven oncology allows oncologists to identify treatments that match a cancer's genomic profile. Clinical trials are promoted as an effective modality to deliver a molecularly matched treatment. We explore the role of geographical accessibility in Italy, and its impact on patient access to clinical trials. MATERIAL AND METHODS: We retrospectively reviewed molecular data from a single-institutional case series of patients receiving next-generation sequencing testing between March 2019 and July 2020. Actionable alterations were defined as the ones with at least one matched treatment on Clinicaltrials.gov at the time of genomic report signature. We then calculated the hypothetical distance to travel to reach the nearest assigned clinical trial. RESULTS: We identified 159 patients eligible for analysis. One hundred and one could be potentially assigned to a clinical trial in Italy, and the median distance that patients needed to travel to reach the closest location with a suitable clinical trial was 76 km (interquartile rangeâ =â 127.46 km). Geographical distribution of clinical trials in Italy found to be heterogeneous, with Milan and Naples being the areas with a higher concentration. We then found that the probability of having a clinical trial close to a patient's hometown increased over time, according to registered studies between 2015 and 2020. CONCLUSIONS: The median distance to be travelled to the nearest trial was generally acceptable for patients, and trials availability is increasing. Nevertheless, many areas are still lacking trials, so efforts are required to increase and homogenize the possibilities to be enrolled in clinical trials for Italian patients with cancer.
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Neoplasias , Humanos , Estudos Retrospectivos , Neoplasias/terapia , Neoplasias/tratamento farmacológico , Oncologia , Itália , GenômicaRESUMO
Risk and outcome of acute promyelocytic leukemia (APL) are particularly worsened in obese-overweight individuals, but the underlying molecular mechanism is unknown. In established mouse APL models (Ctsg-PML::RARA), we confirmed that obesity induced by high-fat diet (HFD) enhances leukemogenesis by increasing penetrance and shortening latency, providing an ideal model to investigate obesity-induced molecular events in the preleukemic phase. Surprisingly, despite increasing DNA damage in hematopoietic stem cells (HSC), HFD only minimally increased mutational load, with no relevant impact on known cancer-driving genes. HFD expanded and enhanced self-renewal of hematopoietic progenitor cells (HPC), with concomitant reduction in long-term HSCs. Importantly, linoleic acid, abundant in HFD, fully recapitulates the effect of HFD on the self-renewal of PML::RARA HPCs through activation of peroxisome proliferator-activated receptor delta, a central regulator of fatty acid metabolism. Our findings inform dietary/pharmacologic interventions to counteract obesity-associated cancers and suggest that nongenetic factors play a key role. PREVENTION RELEVANCE: Our work informs interventions aimed at counteracting the cancer-promoting effect of obesity. On the basis of our study, individuals with a history of chronic obesity may still significantly reduce their risk by switching to a healthier lifestyle, a concept supported by evidence in solid tumors but not yet in hematologic malignancies. See related Spotlight, p. 47.
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Leucemia Promielocítica Aguda , PPAR delta , Animais , Camundongos , Catepsina G , Dieta Hiperlipídica/efeitos adversos , Leucemia Promielocítica Aguda/tratamento farmacológico , Leucemia Promielocítica Aguda/genética , Leucemia Promielocítica Aguda/patologia , Obesidade/complicações , Proteínas de Fusão Oncogênica/genética , PPAR delta/uso terapêuticoRESUMO
MOTIVATION: The steady increment of Whole Genome/Exome sequencing and the development of novel Next Generation Sequencing-based gene panels requires continuous testing and validation of variant calling (VC) pipelines and the detection of sequencing-related issues to be maintained up-to-date and feasible for the clinical settings. State of the art tools are reliable when used to compute standard performance metrics. However, the need for an automated software to discriminate between bioinformatic and sequencing issues and to optimize VC parameters remains unmet. RESULTS: The aim of the current work is to present RecallME, a bioinformatic suite that tracks down difficult-to-detect variants as insertions and deletions in highly repetitive regions, thus providing the maximum reachable recall for both single nucleotide variants and small insertion and deletions and to precisely guide the user in the pipeline optimization process. AVAILABILITY AND IMPLEMENTATION: Source code is freely available under MIT license at https://github.com/mazzalab-ieo/recallme. RecallME web application is available at https://translational-oncology-lab.shinyapps.io/recallme/. To use RecallME, users must obtain a license for ANNOVAR by themselves.
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Benchmarking , Software , Biologia Computacional , Exoma , Sequenciamento de Nucleotídeos em Larga EscalaRESUMO
Innate immune responses to coronavirus infections are highly cell specific. Tissue-resident macrophages, which are infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in patients but are inconsistently infected in vitro, exert critical but conflicting effects by secreting both antiviral type I interferons (IFNs) and tissue-damaging inflammatory cytokines. Steroids, the only class of host-targeting drugs approved for the treatment of coronavirus disease 2019 (COVID-19), indiscriminately suppress both responses, possibly impairing viral clearance. Here, we established in vitro cell culture systems that enabled us to separately investigate the cell-intrinsic and cell-extrinsic proinflammatory and antiviral activities of mouse macrophages infected with the prototypical murine coronavirus MHV-A59. We showed that the nuclear factor κB-dependent inflammatory response to viral infection was selectively inhibited by loss of the lysine demethylase LSD1, which was previously implicated in innate immune responses to cancer, with negligible effects on the antiviral IFN response. LSD1 ablation also enhanced an IFN-independent antiviral response, blocking viral egress through the lysosomal pathway. The macrophage-intrinsic antiviral and anti-inflammatory activity of Lsd1 inhibition was confirmed in vitro and in a humanized mouse model of SARS-CoV-2 infection. These results suggest that LSD1 controls innate immune responses against coronaviruses at multiple levels and provide a mechanistic rationale for potentially repurposing LSD1 inhibitors for COVID-19 treatment.
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COVID-19 , Lisina , Animais , Humanos , Camundongos , Antivirais/farmacologia , Tratamento Farmacológico da COVID-19 , Citocinas/metabolismo , SARS-CoV-2/metabolismoRESUMO
Long-read sequencing allows analyses of single nucleic-acid molecules and produces sequences in the order of tens to hundreds kilobases. Its application to whole-genome analyses allows identification of complex genomic structural-variants (SVs) with unprecedented resolution. SV identification, however, requires complex computational methods, based on either read-depth or intra- and inter-alignment signatures approaches, which are limited by size or type of SVs. Moreover, most currently available tools only detect germline variants, thus requiring separate computation of sample pairs for comparative analyses. To overcome these limits, we developed a novel tool (Germline And SOmatic structuraL varIants detectioN and gEnotyping; GASOLINE) that groups SV signatures using a sophisticated clustering procedure based on a modified reciprocal overlap criterion, and is designed to identify germline SVs, from single samples, and somatic SVs from paired test and control samples. GASOLINE is a collection of Perl, R and Fortran codes, it analyzes aligned data in BAM format and produces VCF files with statistically significant somatic SVs. Germline or somatic analysis of 30[Formula: see text] sequencing coverage experiments requires 4-5 h with 20 threads. GASOLINE outperformed currently available methods in the detection of both germline and somatic SVs in synthetic and real long-reads datasets. Notably, when applied on a pair of metastatic melanoma and matched-normal sample, GASOLINE identified five genuine somatic SVs that were missed using five different sequencing technologies and state-of-the art SV calling approaches. Thus, GASOLINE identifies germline and somatic SVs with unprecedented accuracy and resolution, outperforming currently available state-of-the-art WGS long-reads computational methods.
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Gasolina , Software , Humanos , Análise de Sequência , Genoma , Células Germinativas , Sequenciamento de Nucleotídeos em Larga Escala , Genoma Humano , Análise de Sequência de DNA/métodosRESUMO
Metastatic breast cancer has a poor prognosis and is largely considered incurable. A better understanding of the molecular determinants of breast cancer metastasis could facilitate development of improved prevention and treatment strategies. We used lentiviral barcoding coupled to single-cell RNA sequencing to trace clonal and transcriptional evolution during breast cancer metastasis and showed that metastases derive from rare prometastatic clones that are underrepresented in primary tumors. Both low clonal fitness and high metastatic potential were independent of clonal origin. Differential expression and classification analyses revealed that the prometastatic phenotype was acquired by rare cells characterized by the concomitant hyperactivation of extracellular matrix remodeling and dsRNA-IFN signaling pathways. Notably, genetic silencing of key genes in these pathways (KCNQ1OT1 or IFI6, respectively) significantly impaired migration in vitro and metastasis in vivo, with marginal effects on cell proliferation and tumor growth. Gene expression signatures derived from the identified prometastatic genes predict metastatic progression in patients with breast cancer, independently of known prognostic factors. This study elucidates previously unknown mechanisms of breast cancer metastasis and provides prognostic predictors and therapeutic targets for metastasis prevention. SIGNIFICANCE: Transcriptional lineage tracing coupled with single-cell transcriptomics defined the transcriptional programs underlying metastatic progression in breast cancer, identifying prognostic signatures and prevention strategies.
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Perfilação da Expressão Gênica , Transdução de Sinais , Humanos , Linhagem Celular Tumoral , Transdução de Sinais/genética , Prognóstico , Matriz Extracelular/genética , Metástase Neoplásica , Regulação Neoplásica da Expressão GênicaRESUMO
Aberrant DNA methylation at CpG dinucleotides is a cancer hallmark that is associated with the emergence of resistance to anti cancer treatment, though molecular mechanisms and biological significance remain elusive. Genome scale methylation maps by currently used methods are based on chemical modification of DNA and are best suited for analyses of methylation at CpG rich regions (CpG islands). We report the first high coverage whole-genome map in cancer using the long read nanopore technology, which allows simultaneous DNA-sequence and -methylation analyses on native DNA. We analyzed clonal epigenomic/genomic evolution in Acute Myeloid Leukemias (AMLs) at diagnosis and relapse, after chemotherapy. Long read sequencing coupled to a novel computational method allowed definition of differential methylation at unprecedented resolution, and showed that the relapse methylome is characterized by hypermethylation at both CpG islands and sparse CpGs regions. Most differentially methylated genes, however, were not differentially expressed nor enriched for chemoresistance genes. A small fraction of under-expressed and hyper-methylated genes at sparse CpGs, in the gene body, was significantly enriched in transcription factors (TFs). Remarkably, these few TFs supported large gene-regulatory networks including 50% of all differentially expressed genes in the relapsed AMLs and highly-enriched in chemoresistance genes. Notably, hypermethylated regions at sparse CpGs were poorly conserved in the relapsed AMLs, under-represented at their genomic positions and showed higher methylation entropy, as compared to CpG islands. Analyses of available datasets confirmed TF binding to their target genes and conservation of the same gene-regulatory networks in large patient cohorts. Relapsed AMLs carried few patient specific structural variants and DNA mutations, apparently not involved in drug resistance. Thus, drug resistance in AMLs can be mainly ascribed to the selection of random epigenetic alterations at sparse CpGs of a few transcription factors, which then induce reprogramming of the relapsing phenotype, independently of clonal genomic evolution.
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Ilhas de CpG , Metilação de DNA , Resistencia a Medicamentos Antineoplásicos , Epigenoma , Leucemia Mieloide Aguda , Nanoporos , Humanos , Ilhas de CpG/genética , Ilhas de CpG/fisiologia , DNA/genética , DNA/metabolismo , Metilação de DNA/genética , Metilação de DNA/fisiologia , Resistencia a Medicamentos Antineoplásicos/genética , Resistencia a Medicamentos Antineoplásicos/fisiologia , Epigenoma/genética , Epigenoma/fisiologia , Leucemia Mieloide Aguda/tratamento farmacológico , Leucemia Mieloide Aguda/genética , Fatores de Transcrição/genética , Fatores de Transcrição/metabolismo , Redes Reguladoras de Genes/genética , Redes Reguladoras de Genes/fisiologia , Antineoplásicos/farmacologia , Antineoplásicos/uso terapêuticoRESUMO
iNKT cells account for a relevant fraction of effector T-cells in the intestine and are considered an attractive platform for cancer immunotherapy. Although iNKT cells are cytotoxic lymphocytes, their functional role in colorectal cancer (CRC) is still controversial, limiting their therapeutic use. Thus, we examined the immune cell composition and iNKT cell phenotype of CRC lesions in patients (n = 118) and different murine models. High-dimensional single-cell flow-cytometry, metagenomics, and RNA sequencing experiments revealed that iNKT cells are enriched in tumor lesions. The tumor-associated pathobiont Fusobacterium nucleatum induces IL-17 and Granulocyte-macrophage colony-stimulating factor (GM-CSF) expression in iNKT cells without affecting their cytotoxic capability but promoting iNKT-mediated recruitment of neutrophils with polymorphonuclear myeloid-derived suppressor cells-like phenotype and functions. The lack of iNKT cells reduced the tumor burden and recruitment of immune suppressive neutrophils. iNKT cells in-vivo activation with α-galactosylceramide restored their anti-tumor function, suggesting that iNKT cells can be modulated to overcome CRC-associated immune evasion. Tumor co-infiltration by iNKT cells and neutrophils correlates with negative clinical outcomes, highlighting the importance of iNKT cells in the pathophysiology of CRC. Our results reveal a functional plasticity of iNKT cells in CRC, suggesting a pivotal role of iNKT cells in shaping the tumor microenvironment, with relevant implications for treatment.
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Antineoplásicos , Neoplasias Colorretais , Células T Matadoras Naturais , Camundongos , Animais , Neutrófilos , Antineoplásicos/farmacologia , Imunoterapia , Neoplasias Colorretais/patologia , Microambiente TumoralRESUMO
We conducted a systematic review of studies that investigated whether quitting smoking at or around diagnosis improves survival of patients with hormone-dependent cancers (HDC). Nine studies published in 2013-2022 were included. Studies were very diverse in terms of design, definition of quitters and continued smokers, and prevalence of prognostic factors other than smoking cessation (e.g. patients' demographics, tumour characteristic, and treatments). For breast, ovarian, and endometrial cancer, all included studies found that quitters had better overall, disease specific, and disease-free survival than continued smokers. For prostate cancer, there was no evidence of an association of smoking cessation with improved survival. This literature review provided suggestive evidence that female smokers diagnosed with cancer of the breast, ovary, or endometrium may improve their chances of surviving by stopping smoking. Smoking cessation counselling should become part of standard oncological care for these patients and integrated into breast cancer screening programs.
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Neoplasias , Abandono do Hábito de Fumar , Masculino , Humanos , Feminino , Fumar/efeitos adversos , Fumar/epidemiologia , Fumar TabacoRESUMO
BACKGROUND: Precision oncology aims to improve clinical outcomes by personalising treatment options for patients with cancer. Exploiting vulnerabilities identified in a patient's cancer genome requires reliable interpretation of a huge mole of alterations and heterogeneous biomarkers. ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) allows evidence-based evaluation of genomic findings. Molecular tumour boards (MTBs) convey the required multi-disciplinary expertise to enable ESCAT evaluation and strategical treatment choice. MATERIALS AND METHOD: We retrospectively reviewed the records of 251 consecutive patients discussed by European Institute of Oncology MTB between June 2019 and June 2022. RESULTS: One-hundred eighty-eight (74.6%) patients had at least one actionable alteration. After MTB discussion, 76 patients received molecularly matched therapies (MMTs) while 76 patients received standard of care. Patients receiving MMT displayed higher overall response rate (37.3% versus 12.9%), median progression-free survival (mPFS 5.8 months, 95% confidence interval [CI] 4.1-7.5 versus 3.6 months, 95% CI 2.5-4.8, p = 0.041; hazard ratio 0.679, 95% CI 0.467-0.987) and median overall survival (mOS 35.1 months, 95% CI not evaluable versus 8.5 months, 95% CI 3.8-13.2; hazard ratio 0.431, 95% CI 0.250-0.744, p = 0.002). Superiority in OS and PFS persisted in multivariable models. Among 61 pretreated patients receiving MMT, 37.5% of patients had PFS2/PFS1 ratio ≥1.3. Patients with higher actionable targets (ESCAT tier I) had better OS (p = 0.001) and PFS (p = 0.049), while no difference was observed in lower evidence levels. CONCLUSIONS: Our experience shows that MTBs can yield valuable clinical benefit. Higher actionability ESCAT level appears to be associated with better outcomes for patients receiving MMT.
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Neoplasias , Humanos , Neoplasias/terapia , Neoplasias/tratamento farmacológico , Estudos Retrospectivos , Medicina de Precisão , Oncologia , GenômicaRESUMO
The National Aeronautics and Space Administration's Deep Space Quantum Link mission concept enables a unique set of science experiments by establishing robust quantum optical links across extremely long baselines. Potential mission configurations include establishing a quantum link between the Lunar Gateway moon-orbiting space station and nodes on or near the Earth. This publication summarizes the principal experimental goals of the Deep Space Quantum Link. These goals, identified through a multi-year design study conducted by the authors, include long-range teleportation, tests of gravitational coupling to quantum states, and advanced tests of quantum nonlocality.
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The broad activity of agents blocking the programmed cell death protein 1 and its ligand (the PD-(L)1 axis) revolutionized oncology, offering long-term benefit to patients and even curative responses for tumors that were once associated with dismal prognosis. However, only a minority of patients experience durable clinical benefit with immune checkpoint inhibitor monotherapy in most disease settings. Spurred by preclinical and correlative studies to understand mechanisms of non-response to the PD-(L)1 antagonists and by combination studies in animal tumor models, many drug development programs were designed to combine anti-PD-(L)1 with a variety of approved and investigational chemotherapies, tumor-targeted therapies, antiangiogenic therapies, and other immunotherapies. Several immunotherapy combinations improved survival outcomes in a variety of indications including melanoma, lung, kidney, and liver cancer, among others. This immunotherapy renaissance, however, has led to many combinations being advanced to late-stage development without definitive predictive biomarkers, limited phase I and phase II data, or clinical trial designs that are not optimized for demonstrating the unique attributes of immune-related antitumor activity-for example, landmark progression-free survival and overall survival. The decision to activate a study at an individual site is investigator-driven, and generalized frameworks to evaluate the potential for phase III trials in immuno-oncology to yield positive data, particularly to increase the number of curative responses or otherwise advance the field have thus far been lacking. To assist in evaluating the potential value to patients and the immunotherapy field of phase III trials, the Society for Immunotherapy of Cancer (SITC) has developed a checklist for investigators, described in this manuscript. Although the checklist focuses on anti-PD-(L)1-based combinations, it may be applied to any regimen in which immune modulation is an important component of the antitumor effect.
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Ensaios Clínicos como Assunto , Imunoterapia , Neoplasias , Receptor de Morte Celular Programada 1 , Animais , Lista de Checagem , Inibidores de Checkpoint Imunológico , Fatores Imunológicos , Ligantes , Neoplasias/imunologia , Neoplasias/terapiaRESUMO
Considering the rapid improvement of cancer drugs' efficacy and the discovery of new molecular targets, the formulation of therapeutical indications based on the multidisciplinary approach of MTB is becoming increasingly important for attributing the correct salience to the targets identified in a single patient. Nevertheless, one of the biggest stumbling blocks faced by MTBs is not the bare indication, but its implementation in the clinical practice. Indeed, administering the drug suggested by MTB deals with some relevant difficulties: the economical affordability and geographical accessibility represent some of the major limits in the patient's view, while bureaucracy and regulatory procedures are often a disincentive for the physicians. In this review, we explore the current literature reporting MTB experiences and precision medicine clinical trials, focusing on the challenges that authors face in applying their therapeutical indications. Furthermore, we analyze and discuss some of the solutions devised to overcome these difficulties to support the MTBs in finding the most suitable solution for their specific situation. In conclusion, we strongly encourage regulatory agencies and pharmaceutical companies to develop effective strategies with medical centers implementing MTBs to facilitate access to innovative drugs and thereby allow broader therapeutical opportunities to patients.