Comprehensive Characterization of Cancer Driver Genes and Mutations.

Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify drivers now exist, but systematic attempts to combine and optimize them on large datasets are few. We report a PanCancer and PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) and using 26 computational tools to catalog driver genes and mutations. We identify 299 driver genes with implications regarding their anatomical sites and cancer/cell types. Sequence- and structure-based analyses identified >3,400 putative missense driver mutations supported by multiple lines of evidence. Experimental validation confirmed 60%-85% of predicted mutations as likely drivers. We found that >300 MSI tumors are associated with high PD-1/PD-L1, and 57% of tumors analyzed harbor putative clinically actionable events. Our study represents the most comprehensive discovery of cancer genes and mutations to date and will serve as a blueprint for future biological and clinical endeavors.

A single-cell tumor immune atlas for precision oncology.

The tumor immune microenvironment is a main contributor to cancer progression and a promising therapeutic target for oncology. However, immune microenvironments vary profoundly between patients, and biomarkers for prognosis and treatment response lack precision. A comprehensive compendium of tumor immune cells is required to pinpoint predictive cellular states and their spatial localization. We generated a single-cell tumor immune atlas, jointly analyzing published data sets of >500,000 cells from 217 patients and 13 cancer types, providing the basis for a patient stratification based on immune cell compositions. Projecting immune cells from external tumors onto the atlas facilitated an automated cell annotation system. To enable in situ mapping of immune populations for digital pathology, we applied SPOTlight, combining single-cell and spatial transcriptomics data and identifying colocalization patterns of immune, stromal, and cancer cells in tumor sections. We expect the tumor immune cell atlas, together with our versatile toolbox for precision oncology, to advance currently applied stratification approaches for prognosis and immunotherapy.

A CT-based Radiomics Signature Is Associated with Response to Immune Checkpoint Inhibitors in Advanced Solid Tumors.

Background Reliable predictive imaging markers of response to immune checkpoint inhibitors are needed. Purpose To develop and validate a pretreatment CT-based radiomics signature to predict response to immune checkpoint inhibitors in advanced solid tumors. Materials and Methods In this retrospective study, a radiomics signature was developed in patients with advanced solid tumors (including breast, cervix, gastrointestinal) treated with anti-programmed cell death-1 or programmed cell death ligand-1 monotherapy from August 2012 to May 2018 (cohort 1). This was tested in patients with bladder and lung cancer (cohorts 2 and 3). Radiomics variables were extracted from all metastases delineated at pretreatment CT and selected by using an elastic-net model. A regression model combined radiomics and clinical variables with response as the end point. Biologic validation of the radiomics score with RNA profiling of cytotoxic cells (cohort 4) was assessed with Mann-Whitney analysis. Results The radiomics signature was developed in 85 patients (cohort 1: mean age, 58 years ± 13 [standard deviation]; 43 men) and tested on 46 patients (cohort 2: mean age, 70 years ± 12; 37 men) and 47 patients (cohort 3: mean age, 64 years ± 11; 40 men). Biologic validation was performed in a further cohort of 20 patients (cohort 4: mean age, 60 years ± 13; 14 men). The radiomics signature was associated with clinical response to immune checkpoint inhibitors (area under the curve [AUC], 0.70; 95% CI: 0.64, 0.77; P < .001). In cohorts 2 and 3, the AUC was 0.67 (95% CI: 0.58, 0.76) and 0.67 (95% CI: 0.56, 0.77; P < .001), respectively. A radiomics-clinical signature (including baseline albumin level and lymphocyte count) improved on radiomics-only performance (AUC, 0.74 [95% CI: 0.63, 0.84; P < .001]; Akaike information criterion, 107.00 and 109.90, respectively). Conclusion A pretreatment CT-based radiomics signature is associated with response to immune checkpoint inhibitors, likely reflecting the tumor immunophenotype. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Summers in this issue.

Cell free circulating tumor DNA in cerebrospinal fluid detects and monitors central nervous system involvement of B-cell lymphomas.

The levels of cell free circulating tumor DNA (ctDNA) in plasma correlated with treatment response and outcome in systemic lymphomas. Notably, in brain tumors, the levels of ctDNA in the cerebrospinal fluid (CSF) are higher than in plasma. Nevertheless, their role in central nervous system (CNS) lymphomas remains elusive. We evaluated the CSF and plasma from 19 patients: 6 restricted CNS lymphomas, 1 systemic and CNS lymphoma, and 12 systemic lymphomas. We performed whole exome sequencing or targeted sequencing to identify somatic mutations of the primary tumor, then variant-specific droplet digital PCR was designed for each mutation. At time of enrolment, we found ctDNA in the CSF of all patients with restricted CNS lymphoma but not in patients with systemic lymphoma without CNS involvement. Conversely, plasma ctDNA was detected in only 2/6 patients with restricted CNS lymphoma with lower variant allele frequencies than CSF ctDNA. Moreover, we detected CSF ctDNA in 1 patient with CNS lymphoma in complete remission and in 1 patient with systemic lymphoma, 3 and 8 months before CNS relapse was confirmed; indicating CSF ctDNA might detect CNS relapse earlier than conventional methods. Finally, in 2 cases with CNS lymphoma, CSF ctDNA was still detected after treatment even though a complete decrease in CSF tumor cells was observed by flow cytometry (FC), indicating CSF ctDNA better detected residual disease than FC. In conclusion, CSF ctDNA can better detect CNS lesions than plasma ctDNA and FC. In addition, CSF ctDNA predicted CNS relapse in CNS and systemic lymphomas.

Non-coding recurrent mutations in chronic lymphocytic leukaemia.

Chronic lymphocytic leukaemia (CLL) is a frequent disease in which the genetic alterations determining the clinicobiological behaviour are not fully understood. Here we describe a comprehensive evaluation of the genomic landscape of 452 CLL cases and 54 patients with monoclonal B-lymphocytosis, a precursor disorder. We extend the number of CLL driver alterations, including changes in ZNF292, ZMYM3, ARID1A and PTPN11. We also identify novel recurrent mutations in non-coding regions, including the 3' region of NOTCH1, which cause aberrant splicing events, increase NOTCH1 activity and result in a more aggressive disease. In addition, mutations in an enhancer located on chromosome 9p13 result in reduced expression of the B-cell-specific transcription factor PAX5. The accumulative number of driver alterations (0 to ≥4) discriminated between patients with differences in clinical behaviour. This study provides an integrated portrait of the CLL genomic landscape, identifies new recurrent driver mutations of the disease, and suggests clinical interventions that may improve the management of this neoplasia.

OncodriveROLE classifies cancer driver genes in loss of function and activating mode of action.

MOTIVATION: Several computational methods have been developed to identify cancer drivers genes-genes responsible for cancer development upon specific alterations. These alterations can cause the loss of function (LoF) of the gene product, for instance, in tumor suppressors, or increase or change its activity or function, if it is an oncogene. Distinguishing between these two classes is important to understand tumorigenesis in patients and has implications for therapy decision making. Here, we assess the capacity of multiple gene features related to the pattern of genomic alterations across tumors to distinguish between activating and LoF cancer genes, and we present an automated approach to aid the classification of novel cancer drivers according to their role. RESULT: OncodriveROLE is a machine learning-based approach that classifies driver genes according to their role, using several properties related to the pattern of alterations across tumors. The method shows an accuracy of 0.93 and Matthew's correlation coefficient of 0.84 classifying genes in the Cancer Gene Census. The OncodriveROLE classifier, its results when applied to two lists of predicted cancer drivers and TCGA-derived mutation and copy number features used by the classifier are available at http://bg.upf.edu/oncodrive-role. AVAILABILITY AND IMPLEMENTATION: The R implementation of the OncodriveROLE classifier is available at http://bg.upf.edu/oncodrive-role. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Severe SARS-CoV-2 placenta infection can impact neonatal outcome in the absence of vertical transmission.

The effect of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on the pathophysiology of the placenta and its impact on pregnancy outcome has not yet been fully elucidated. Here, we present a comprehensive clinical, morphological, and molecular analysis of placental tissues from pregnant women with and without SARS-CoV-2 infection. SARS-CoV-2 could be detected in half of placental tissues from SARS-CoV-2-positive women. The presence of the virus was not associated with any distinctive pathological, maternal, or neonatal outcome features. SARS-CoV-2 tissue load was low in all but one patient who exhibited severe placental damage leading to neonatal neurological manifestations. The placental transcriptional response induced by high viral load of SARS-CoV-2 showed an immunopathology phenotype similar to autopsy lung tissues from patients with severe coronavirus disease 2019. This finding contrasted with the lack of inflammatory response in placental tissues from SARS-CoV-2-positive women with low viral tissue load and from SARS-CoV-2-negative women. Importantly, no evidence of vertical transmission of SARS-CoV-2 was found in any newborns, suggesting that the placenta may be an effective maternal-neonatal barrier against the virus even in the presence of severe infection. Our observations suggest that severe placental damage induced by the virus may be detrimental for the neonate independently of vertical transmission.

Immune cell profiling of the cerebrospinal fluid enables the characterization of the brain metastasis microenvironment.

Brain metastases are the most common tumor of the brain with a dismal prognosis. A fraction of patients with brain metastasis benefit from treatment with immune checkpoint inhibitors (ICI) and the degree and phenotype of the immune cell infiltration has been used to predict response to ICI. However, the anatomical location of brain lesions limits access to tumor material to characterize the immune phenotype. Here, we characterize immune cells present in brain lesions and matched cerebrospinal fluid (CSF) using single-cell RNA sequencing combined with T cell receptor genotyping. Tumor immune infiltration and specifically CD8+ T cell infiltration can be discerned through the analysis of the CSF. Consistently, identical T cell receptor clonotypes are detected in brain lesions and CSF, confirming cell exchange between these compartments. The analysis of immune cells of the CSF can provide a non-invasive alternative to predict the response to ICI, as well as identify the T cell receptor clonotypes present in brain metastasis.

Single-cell transcriptional changes associated with drug tolerance and response to combination therapies in cancer.

Tyrosine kinase inhibitors were found to be clinically effective for treatment of patients with certain subsets of cancers carrying somatic mutations in receptor tyrosine kinases. However, the duration of clinical response is often limited, and patients ultimately develop drug resistance. Here, we use single-cell RNA sequencing to demonstrate the existence of multiple cancer cell subpopulations within cell lines, xenograft tumors and patient tumors. These subpopulations exhibit epigenetic changes and differential therapeutic sensitivity. Recurrently overrepresented ontologies in genes that are differentially expressed between drug tolerant cell populations and drug sensitive cells include epithelial-to-mesenchymal transition, epithelium development, vesicle mediated transport, drug metabolism and cholesterol homeostasis. We show analysis of identified markers using the LINCS database to predict and functionally validate small molecules that target selected drug tolerant cell populations. In combination with EGFR inhibitors, crizotinib inhibits the emergence of a defined subset of EGFR inhibitor-tolerant clones. In this study, we describe the spectrum of changes associated with drug tolerance and inhibition of specific tolerant cell subpopulations with combination agents.

The DYRK Family of Kinases in Cancer: Molecular Functions and Therapeutic Opportunities.

DYRK (dual-specificity tyrosine-regulated kinases) are an evolutionary conserved family of protein kinases with members from yeast to humans. In humans, DYRKs are pleiotropic factors that phosphorylate a broad set of proteins involved in many different cellular processes. These include factors that have been associated with all the hallmarks of cancer, from genomic instability to increased proliferation and resistance, programmed cell death, or signaling pathways whose dysfunction is relevant to tumor onset and progression. In accordance with an involvement of DYRK kinases in the regulation of tumorigenic processes, an increasing number of research studies have been published in recent years showing either alterations of DYRK gene expression in tumor samples and/or providing evidence of DYRK-dependent mechanisms that contribute to tumor initiation and/or progression. In the present article, we will review the current understanding of the role of DYRK family members in cancer initiation and progression, providing an overview of the small molecules that act as DYRK inhibitors and discussing the clinical implications and therapeutic opportunities currently available.

Circulating tumour DNA from the cerebrospinal fluid allows the characterisation and monitoring of medulloblastoma.

The molecular characterisation of medulloblastoma, the most common paediatric brain tumour, is crucial for the correct management and treatment of this heterogenous disease. However, insufficient tissue sample, the presence of tumour heterogeneity, or disseminated disease can challenge its diagnosis and monitoring. Here, we report that the cerebrospinal fluid (CSF) circulating tumour DNA (ctDNA) recapitulates the genomic alterations of the tumour and facilitates subgrouping and risk stratification, providing valuable information about diagnosis and prognosis. CSF ctDNA also characterises the intra-tumour genomic heterogeneity identifying small subclones. ctDNA is abundant in the CSF but barely present in plasma and longitudinal analysis of CSF ctDNA allows the study of minimal residual disease, genomic evolution and the characterisation of tumours at recurrence. Ultimately, CSF ctDNA analysis could facilitate the clinical management of medulloblastoma patients and help the design of tailored therapeutic strategies, increasing treatment efficacy while reducing excessive treatment to prevent long-term secondary effects.

NK Cell Infiltrates and HLA Class I Expression in Primary HER2+ Breast Cancer Predict and Uncouple Pathological Response and Disease-free Survival.

PURPOSE: We investigated the value of tumor-infiltrating NK (TI-NK) cells and HLA class I tumor expression as biomarkers of response to neoadjuvant anti-HER2 antibody-based treatment in breast cancer. EXPERIMENTAL DESIGN: TI-NK cells and HLA-I were determined by IHC in pretreatment tumor biopsies from two cohorts of patients with HER2-positive breast cancer [discovery cohort (n = 42) and validation cohort (n = 71)]. Tumor-infiltrating lymphocytes (TIL) were scored according to international guidelines. Biomarker association with pathologic complete response (pCR) and disease-free survival (DFS) was adjusted for prognostic factors. Gene set variation analysis was used for determining immune cell populations concomitant to NK-cell enrichment in HER2-positive tumors from the Cancer Genome Atlas (n = 190). RESULTS: TI-NK cells were significantly associated with pCR in the discovery cohort as well as in the validation cohort (P < 0.0001), independently of clinicopathologic factors. A ≥3 TI-NK cells/50x high-power field (HPF) cutoff predicted pCR in the discovery and validation cohort [OR, 188 (11-3154); OR, 19.5 (5.3-71.8)]. Presence of TI-NK cells associated with prolonged DFS in both patient cohorts [HR, 0.07 (0.01-0.6); P = 0.01; HR, 0.3 (0.08-1.3); P = 0.1]. NK-, activated dendritic- and CD8 T-cell gene expression signatures positively correlated in HER2-positive tumors, supporting the value of NK cells as surrogates of effective antitumor immunity. Stratification of patients by tumor HLA-I expression identified patients with low and high relapse risk independently of pCR. CONCLUSIONS: This study identifies baseline TI-NK cells as an independent biomarker with great predictive value for pCR to anti-HER2 antibody-based treatment and points to the complementary value of tumor HLA-I status for defining patient prognosis independently of pCR.

LIF regulates CXCL9 in tumor-associated macrophages and prevents CD8+ T cell tumor-infiltration impairing anti-PD1 therapy.

Cancer response to immunotherapy depends on the infiltration of CD8+ T cells and the presence of tumor-associated macrophages within tumors. Still, little is known about the determinants of these factors. We show that LIF assumes a crucial role in the regulation of CD8+ T cell tumor infiltration, while promoting the presence of protumoral tumor-associated macrophages. We observe that the blockade of LIF in tumors expressing high levels of LIF decreases CD206, CD163 and CCL2 and induces CXCL9 expression in tumor-associated macrophages. The blockade of LIF releases the epigenetic silencing of CXCL9 triggering CD8+ T cell tumor infiltration. The combination of LIF neutralizing antibodies with the inhibition of the PD1 immune checkpoint promotes tumor regression, immunological memory and an increase in overall survival.

A Pan-cancer Landscape of Interactions between Solid Tumors and Infiltrating Immune Cell Populations.

Purpose: Throughout their development, tumors are challenged by the immune system, and they acquire features to evade its surveillance. A systematic view of these traits, which shed light on how tumors respond to immunotherapies, is still lacking.Experimental Design: Here, we computed the relative abundance of an array of immune cell populations to measure the immune infiltration pattern of 9,174 tumors of 29 solid cancers. We then clustered tumors with similar infiltration pattern to define immunophenotypes. Finally, we identified genomic and transcriptomic traits associated to these immunophenotypes across cancer types.Results: In highly cytotoxic immunophenotypes, we found tumors with low clonal heterogeneity enriched for alterations of genes involved in epigenetic regulation, ubiquitin-mediated proteolysis, antigen presentation, and cell-cell communication, which may drive resistance in combination with the ectopic expression of negative immune checkpoints. Tumors with immunophenotypes of intermediate cytotoxicity are characterized by an upregulation of processes involved in neighboring tissue invasion and remodeling that may foster the recruitment of immunosuppressive cells. Tumors with poorly cytotoxic immunophenotype tend to be of more advanced stages and bear a greater burden of copy number alterations and frequent alterations of cell cycle, hedgehog, ß-catenin, and TGFß pathways, which may cause immune depletion.Conclusions: We provide a comprehensive landscape of the characteristics of solid tumors that may influence (or be influenced by) the characteristics of their immune infiltrate. These results may help interpret the response of solid tumors to immunotherapies and guide the development of novel drug combination strategies. Clin Cancer Res; 24(15); 3717-28. ©2018 AACR.

Cancer Genome Interpreter annotates the biological and clinical relevance of tumor alterations.

While tumor genome sequencing has become widely available in clinical and research settings, the interpretation of tumor somatic variants remains an important bottleneck. Here we present the Cancer Genome Interpreter, a versatile platform that automates the interpretation of newly sequenced cancer genomes, annotating the potential of alterations detected in tumors to act as drivers and their possible effect on treatment response. The results are organized in different levels of evidence according to current knowledge, which we envision can support a broad range of oncology use cases. The resource is publicly available at http://www.cancergenomeinterpreter.org .

Molecular Diagnosis of Diffuse Gliomas through Sequencing of Cell-Free Circulating Tumor DNA from Cerebrospinal Fluid.

Purpose: Diffuse gliomas are the most common primary tumor of the brain and include different subtypes with diverse prognosis. The genomic characterization of diffuse gliomas facilitates their molecular diagnosis. The anatomical localization of diffuse gliomas complicates access to tumor specimens for diagnosis, in some cases incurring high-risk surgical procedures and stereotactic biopsies. Recently, cell-free circulating tumor DNA (ctDNA) has been identified in the cerebrospinal fluid (CSF) of patients with brain malignancies.Experimental Design: We performed an analysis of IDH1, IDH2, TP53, TERT, ATRX, H3F3A, and HIST1H3B gene mutations in two tumor cohorts from The Cancer Genome Atlas (TCGA) including 648 diffuse gliomas. We also performed targeted exome sequencing and droplet digital PCR (ddPCR) analysis of these seven genes in 20 clinical tumor specimens and CSF from glioma patients and performed a histopathologic characterization of the tumors.Results: Analysis of the mutational status of the IDH1, IDH2, TP53, TERT, ATRX, H3F3A, and HIST1H3B genes allowed the classification of 79% of the 648 diffuse gliomas analyzed, into IDH-wild-type glioblastoma, IDH-mutant glioblastoma/diffuse astrocytoma and oligodendroglioma, each subtype exhibiting diverse median overall survival (1.1, 6.7, and 11.2 years, respectively). We developed a sequencing platform to simultaneously and rapidly genotype these seven genes in CSF ctDNA allowing the subclassification of diffuse gliomas.Conclusions: The genomic analysis of IDH1, IDH2, TP53, ATRX, TERT, H3F3A, and HIST1H3B gene mutations in CSF ctDNA facilitates the diagnosis of diffuse gliomas in a timely manner to support the surgical and clinical management of these patients. Clin Cancer Res; 24(12); 2812-9. ©2018 AACR.

Genetic and functional characterization of disease associations explains comorbidity.

Understanding relationships between diseases, such as comorbidities, has important socio-economic implications, ranging from clinical study design to health care planning. Most studies characterize disease comorbidity using shared genetic origins, ignoring pathway-based commonalities between diseases. In this study, we define the disease pathways using an interactome-based extension of known disease-genes and introduce several measures of functional overlap. The analysis reveals 206 significant links among 94 diseases, giving rise to a highly clustered disease association network. We observe that around 95% of the links in the disease network, though not identified by genetic overlap, are discovered by functional overlap. This disease network portraits rheumatoid arthritis, asthma, atherosclerosis, pulmonary diseases and Crohn's disease as hubs and thus pointing to common inflammatory processes underlying disease pathophysiology. We identify several described associations such as the inverse comorbidity relationship between Alzheimer's disease and neoplasms. Furthermore, we investigate the disruptions in protein interactions by mapping mutations onto the domains involved in the interaction, suggesting hypotheses on the causal link between diseases. Finally, we provide several proof-of-principle examples in which we model the effect of the mutation and the change of the association strength, which could explain the observed comorbidity between diseases caused by the same genetic alterations.

Rational design of cancer gene panels with OncoPaD.

BACKGROUND: Profiling the somatic mutations of genes which may inform about tumor evolution, prognostics and treatment is becoming a standard tool in clinical oncology. Commercially available cancer gene panels rely on manually gathered cancer-related genes, in a "one-size-fits-many" solution. The design of new panels requires laborious search of literature and cancer genomics resources, with their performance on cohorts of patients difficult to estimate. RESULTS: We present OncoPaD, to our knowledge the first tool aimed at the rational design of cancer gene panels. OncoPaD estimates the cost-effectiveness of the designed panel on a cohort of tumors and provides reports on the importance of individual mutations for tumorigenesis or therapy. With a friendly interface and intuitive input, OncoPaD suggests researchers relevant sets of genes to be included in the panel, because prior knowledge or analyses indicate that their mutations either drive tumorigenesis or function as biomarkers of drug response. OncoPaD also provides reports on the importance of individual mutations for tumorigenesis or therapy that support the interpretation of the results obtained with the designed panel. We demonstrate in silico that OncoPaD designed panels are more cost-effective-i.e. detect a maximum fraction of tumors in the cohort by sequencing a minimum quantity of DNA-than available panels. CONCLUSIONS: With its unique features, OncoPaD will help clinicians and researchers design tailored next-generating sequencing (NGS) panels to detect circulating tumor DNA or biopsy specimens, thereby facilitating early and accurate detection of tumors, genomics informed therapeutic decisions, patient follow-up and timely identification of resistance mechanisms to targeted agents. OncoPaD may be accessed through http://www.intogen.org/oncopad.

In silico prescription of anticancer drugs to cohorts of 28 tumor types reveals targeting opportunities.

Large efforts dedicated to detect somatic alterations across tumor genomes/exomes are expected to produce significant improvements in precision cancer medicine. However, high inter-tumor heterogeneity is a major obstacle to developing and applying therapeutic targeted agents to treat most cancer patients. Here, we offer a comprehensive assessment of the scope of targeted therapeutic agents in a large pan-cancer cohort. We developed an in silico prescription strategy based on identification of the driver alterations in each tumor and their druggability options. Although relatively few tumors are tractable by approved agents following clinical guidelines (5.9%), up to 40.2% could benefit from different repurposing options, and up to 73.3% considering treatments currently under clinical investigation. We also identified 80 therapeutically targetable cancer genes.