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Objectives While the gastrointestinal symptom cluster (GISC) is common in patients receiving chemotherapy, limited information is available on its underlying mechanism(s). Emerging evidence suggests a role for inflammatory processes through the actions of the nuclear factor kappa B (NF-κB) signaling pathway. This study evaluated for associations between a GISC and levels of DNA methylation for genes within this pathway. Methods Prior to their second or third cycle of chemotherapy, 1071 outpatients reported symptom occurrence using the Memorial Symptom Assessment Scale. A GISC was identified using exploratory factor analysis. Differential methylation analyses were performed in two independent samples using EPIC ( n = 925) and 450K ( n = 146) microarrays. Trans expression-associated CpG (eCpG) loci for 56 NF-κB signaling pathway genes were evaluated. Loci significance were assessed using an exploratory false discovery rate (FDR) of 25% for the EPIC sample. For the validation assessment using the 450K sample, significance was assessed at an unadjusted p-value of 0.05. Results For the EPIC sample, the GISC was associated with increased expression of lymphotoxin beta ( LTB) at one differentially methylated trans eCpG locus (cg03171795; FDR = 0.168). This association was not validated in the 450K sample. Conclusions This study is the first to identify an association between a GISC and epigenetic regulation of a gene that is involved in the initiation of gastrointestinal immune responses. Findings suggest that increased LTB expression by hypermethylation of a trans eCpG locus is involved in the occurrence of this cluster in patients receiving chemotherapy. LTB may be a potential therapeutic target for this common cluster.

Background: Breast cancer incidence in the United States is lower in Hispanic/Latina (H/L) compared with African American/Black or Non-Hispanic White women. An Indigenous American breast cancer–protective germline variant (rs140068132) has been reported near the estrogen receptor 1 gene. This study tests the association of rs140068132 and other polymorphisms in the 6q25 region with subtype-specific breast cancer risk in H/Ls of high Indigenous American ancestry. Methods: Genotypes were obtained for 5,094 Peruvian women with (1,755) and without (3,337) breast cancer. Associations between genotype and overall and subtype-specific risk for the protective variant were tested using logistic regression models and conditional analyses, including other risk-associated polymorphisms in the region. Results: We replicated the reported association between rs140068132 and breast cancer risk overall [odds ratio (OR), 0.53; 95% confidence interval (CI), 0.47–0.59], as well as the lower odds of developing hormone receptor negative (HR−) versus HR+ disease (OR, 0.77; 95% CI, 0.61–0.97). Models, including HER2, showed further heterogeneity with reduced odds for HR+HER2+ (OR, 0.68; 95% CI, 0.51–0.92), HR−HER2+ (OR, 0.63; 95% CI, 0.44–0.90) and HR−HER2− (OR, 0.77; 95% CI, 0.56–1.05) compared with HR+HER2−. Inclusion of other risk-associated variants did not change these observations. Conclusions: The rs140068132 polymorphism is associated with decreased risk of breast cancer in Peruvians and is more protective against HR− and HER2+ diseases independently of other breast cancer-associated variants in the 6q25 region. Impact: These results could inform functional analyses to understand the mechanism by which rs140068132-G reduces risk of breast cancer development in a subtype-specific manner. They also illustrate the importance of including diverse individuals in genetic studies.

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Supplementary Figures S1-S2; Supplementary Table S1.

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Purpose: Problems in management of oral cancers or precancers include identification of patients at risk for metastasis, tumor recurrence, and second primary tumors or risk for progression of precancers (dysplasia) to cancer. Thus, the objective of this study was to clarify the role of genomic aberrations in oral cancer progression and metastasis.Experimental Design: The spectrum of copy number alterations in oral dysplasia and squamous cell carcinomas (SCC) was determined by array comparative genomic hybridization. Associations with clinical characteristics were studied and results confirmed in an independent cohort.Results: The presence of one or more of the chromosomal aberrations +3q24-qter, -8pter-p23.1, +8q12-q24.2, and +20 distinguishes a major subgroup (70%–80% of lesions, termed 3q8pq20 subtype) from the remainder (20%–30% of lesions, non-3q8pq20). The 3q8pq20 subtype is associated with chromosomal instability and differential methylation in the most chromosomally unstable tumors. The two subtypes differ significantly in clinical outcome with risk for cervical (neck) lymph node metastasis almost exclusively associated with the 3q8pq20 subtype in two independent oral SCC cohorts.Conclusions: Two subtypes of oral lesions indicative of at least two pathways for oral cancer development were distinguished that differ in chromosomal instability and risk for metastasis, suggesting that +3q,–8p, +8q, and +20 constitute a biomarker with clinical utility for identifying patients at risk for metastasis. Moreover, although increased numbers of genomic alterations can be harbingers of progression to cancer, dysplastic lesions lacking copy number changes cannot be considered benign as they are potential precursors to non-3q8pq20 locally invasive, yet not metastatic oral SCC. Clin Cancer Res; 17(22); 7024–34. ©2011 AACR.

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Purpose: Heat shock protein-90 (HSP-90), a molecular chaperone required by numerous oncogenic kinases [e.g., HER-2, epidermal growth factor receptor (EGFR), Raf-1, v-Src, and AKT] for conformational stability, has attracted wide interest as a novel target for cancer therapy. HSP-90 inhibition induces degradation of HSP-90 client proteins, leading to a combinatorial inhibition of multiple oncogenic signaling pathways with consecutive growth arrest and apoptosis. MET, a tyrosine kinase that is constitutively active in tumor cells with MET oncogene amplification, has recently been identified as another HSP-90 client.Experimental Design: The aim of our study was to assess the efficacy of SNX-2112, a synthetic HSP-90 inhibitor, in 3 different MET-amplified tumor cell lines (GTL-16, MKN-45, and EBC-1) as well as PR-GTL-16 cells, a GTL-16 subline selected for resistance to the highly selective MET kinase inhibitor PHA-665752.Results: In all cell lines, SNX-2112 led to degradation of MET, HER-2, EGFR, and AKT, as well as abrogation of Ras/Raf/MEK/MAPK and PI3K/AKT signaling, followed by complete cell cycle arrest. SNX-5542, an orally bioavailable prodrug of SNX-2112, displayed significant antitumor efficacy in vivo in nude mice bearing MET-amplified tumor xenografts. Importantly, HSP-90 inhibition maintained its antitumor efficacy in PR-GTL-16 cells both in vitro and in vivo, suggesting that HSP-90 inhibition could be a particularly valuable strategy in MET-amplified tumors that have acquired resistance to MET kinase inhibition.Conclusions: Our study provides evidence for the efficacy of HSP-90 inhibition in MET-amplified cancer cells, particularly when MET kinase inhibitor resistance has emerged. Clin Cancer Res; 17(1); 122–33. ©2011 AACR.

Supplementary Figures 1-3 from Global Gene Expression Profiling of Pleural Mesotheliomas: Overexpression of Aurora Kinases and P16/CDKN2A Deletion as Prognostic Factors and Critical Evaluation of Microarray-Based Prognostic Prediction

Adult male germ cell tumors (GCTs) comprise distinct groups: seminomas and nonseminomas, which include pluripotent embryonal carcinomas as well as other histologic subtypes exhibiting various stages of differentiation. Almost all GCTs show 12p gain, but the target genes have not been clearly defined. To identify 12p target genes, we examined Affymetrix (Santa Clara, CA) U133A+B microarray (∼83% coverage of 12p genes) expression profiles of 17 seminomas, 84 nonseminoma GCTs, and 5 normal testis samples. Seventy-three genes on 12p were significantly overexpressed, including GLUT3 and REA (overexpressed in all GCTs) and CCND2 and FLJ22028 (overexpressed in all GCTs, except choriocarcinomas). We characterized a 200-kb gene cluster at 12p13.31 that exhibited coordinated overexpression in embryonal carcinomas and seminomas, which included the known stem cell genes NANOG, STELLA, and GDF3 and two previously uncharacterized genes. A search for other coordinately regulated genomic clusters of stem cell genes did not reveal any genomic regions similar to that at 12p13.31. Comparison of embryonal carcinoma with seminomas revealed relative overexpression of several stem cell–associated genes in embryonal carcinoma, including several core “stemness” genes (EBAF, TDGF1, and SOX2) and several downstream targets of WNT, NODAL, and FGF signaling (FGF4, NODAL, and ZFP42). Our results indicate that 12p gain is a functionally relevant change leading to activation of proliferation and reestablishment/maintenance of stem cell function through activation of key stem cell genes. Furthermore, the differential expression of core stem cell genes may explain the differences in pluripotency between embryonal carcinomas and seminomas. (Cancer Res 2006; 66(2): 820-7)

Supplementary Tables 3A-6A from Global Gene Expression Profiling of Pleural Mesotheliomas: Overexpression of Aurora Kinases and P16/CDKN2A Deletion as Prognostic Factors and Critical Evaluation of Microarray-Based Prognostic Prediction

Most gene expression profiling studies of mesothelioma have been based on relatively small sample numbers, limiting their statistical power. We did Affymetrix U133A microarray analysis on 99 pleural mesotheliomas, in which multivariate analysis showed advanced-stage, sarcomatous histology and P16/CDKN2A homozygous deletion to be significant independent adverse prognostic factors. Comparison of the expression profiles of epithelioid versus sarcomatous mesotheliomas identified many genes significantly overexpressed among the former, including previously unrecognized ones, such as uroplakins and kallikrein 11, both confirmed by immunohistochemistry. Examination of the gene expression correlates of survival showed that more aggressive mesotheliomas expressed higher levels of Aurora kinases A and B and functionally related genes involved in mitosis and cell cycle control. Independent confirmation of the negative effect of Aurora kinase B was obtained by immunohistochemistry in a separate patient cohort. A role for Aurora kinases in the aggressive behavior of mesotheliomas is of potential clinical interest because of the recent development of small-molecule inhibitors. We then used our data to develop microarray-based predictors of 1 year survival; these achieved a maximal accuracy of 68% in cross-validation. However, this was inferior to prognostic prediction based on standard clinicopathologic variables and P16/CDNK2A status (accuracy, 73%), and adding the microarray model to the latter did not improve overall accuracy. Finally, we evaluated three recently published microarray-based outcome prediction models, but their accuracies ranged from 63% to 67%, consistently lower than reported. Gene expression profiling of mesotheliomas is an important discovery tool, but its power in clinical prognostication has been overestimated. (Cancer Res 2006; 66(6): 2970-9)

Supplementary Figures 1-4 from Down-Regulation of Stem Cell Genes, Including Those in a 200-kb Gene Cluster at 12p13.31, Is Associated with In vivo Differentiation of Human Male Germ Cell Tumors

Supplementary Table 1 from Microfluidic-Based Multiplex qRT-PCR Identifies Diagnostic and Prognostic microRNA Signatures in the Sera of Prostate Cancer Patients

Supplementary Figures 1-7 from Microfluidic-Based Multiplex qRT-PCR Identifies Diagnostic and Prognostic microRNA Signatures in the Sera of Prostate Cancer Patients

Supplementary Table 1-5 from Down-Regulation of Stem Cell Genes, Including Those in a 200-kb Gene Cluster at 12p13.31, Is Associated with In vivo Differentiation of Human Male Germ Cell Tumors

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Background: Fatigue is the most common and debilitating symptom experienced by oncology patients undergoing chemotherapy. Little is known about patient characteristics that predict changes in fatigue severity over time. Purpose: To predict the severity of evening fatigue in the week following the administration of chemotherapy using machine learning approaches. Methods: Outpatients with breast, gastrointestinal, gynecological, or lung cancer (N = 1217) completed questionnaires one week prior to and one week following administration of chemotherapy. Evening fatigue was measured with the Lee Fatigue Scale (LFS). Separate prediction models for evening fatigue severity were created using clinical, symptom, and psychosocial adjustment characteristics and either evening fatigue scores or individual fatigue item scores. Prediction models were created using two regression and three machine learning approaches. Results: Random forest (RF) models provided the best fit across all models. For the RF model using individual LFS item scores, two of the 13 individual LFS items (i.e. ‘worn out’, ‘exhausted’) were the strongest predictors. Conclusion: This study is the first to use machine learning techniques to predict evening fatigue severity in the week following chemotherapy from fatigue scores obtained in the week prior to chemotherapy. Our findings suggest that the language used to assess clinical fatigue in oncology patients is important and that two simple questions may be used to predict evening fatigue severity.

Purpose: Known clinical and genetic markers have limitations in predicting disease course and outcome in juvenile myelomonocytic leukemia (JMML). DNA methylation patterns in JMML have correlated with outcome across multiple studies, suggesting it as a biomarker to improve patient stratification. However, standardized approaches to classify JMML on the basis of DNA methylation patterns are lacking. We, therefore, sought to define an international consensus for DNA methylation subgroups in JMML and develop classification methods for clinical implementation. Experimental Design: Published DNA methylation data from 255 patients with JMML were used to develop and internally validate a classifier model. Accuracy across platforms (EPIC-arrays and MethylSeq) was tested using a technical validation cohort (32 patients). The suitability of both methods for single-patient classification was demonstrated using an independent cohort (47 patients). Results: Analysis of pooled, published data established three DNA methylation subgroups as a de facto standard. Unfavorable prognostic parameters (PTPN11 mutation, elevated fetal hemoglobin, and older age) were significantly enriched in the high methylation (HM) subgroup. A classifier was then developed that predicted subgroups with 98% accuracy across different technological platforms. Applying the classifier to an independent validation cohort confirmed an association of HM with secondary mutations, high relapse incidence, and inferior overall survival (OS), while the low methylation subgroup was associated with a favorable disease course. Multivariable analysis established DNA methylation subgroups as the only significant factor predicting OS. Conclusions: This study provides an international consensus definition for DNA methylation subgroups in JMML. We developed and validated methods which will facilitate the design of risk-stratified clinical trials in JMML.

Mutations in the CBL gene were first identified in adults with various myeloid malignancies. Some patients with juvenile myelomonocytic leukemia (JMML) were also noted to harbor mutations in CBL, but were found to have generally less aggressive disease courses compared to patients with other forms of Ras pathway-mutant JMML. Importantly, and in contrast to most reports in adults, the majority of CBL mutations in JMML patients are germline with acquired uniparental disomy occurring in affected marrow cells. Here, we systematically studied a large cohort of 33 JMML patients with CBL mutations and found that this disease is highly diverse in presentation and overall outcome. Moreover, we discovered somatically acquired CBL mutations in 15% of pediatric patients who presented with more aggressive disease. Neither clinical features nor methylation profiling were able to distinguish patients with somatic CBL mutations from those with germline CBL mutations, highlighting the need for germline testing. Overall, we demonstrate that disease courses are quite heterogeneous even among patients with germline CBL mutations. Prospective clinical trials are warranted to find ideal treatment strategies for this diverse cohort of patients.

Cancers display significant heterogeneity with respect to tissue of origin, driver mutations, and other features of the surrounding tissue. It is likely that individual tumors engage common patterns of the immune system-here "archetypes"-creating prototypical non-destructive tumor immune microenvironments (TMEs) and modulating tumor-targeting. To discover the dominant immune system archetypes, the University of California, San Francisco (UCSF) Immunoprofiler Initiative (IPI) processed 364 individual tumors across 12 cancer types using standardized protocols. Computational clustering of flow cytometry and transcriptomic data obtained from cell sub-compartments uncovered dominant patterns of immune composition across cancers. These archetypes were profound insofar as they also differentiated tumors based upon unique immune and tumor gene-expression patterns. They also partitioned well-established classifications of tumor biology. The IPI resource provides a template for understanding cancer immunity as a collection of dominant patterns of immune organization and provides a rational path forward to learn how to modulate these to improve therapy.

1AbstractCOVID-19 has caused tremendous death and suffering since it first emerged in 2019. In response, models were developed to help predict the course of various disease metrics, and these models have been relied upon to help guide public health policy. Here we present a method called COVIDNearTerm to “forecast” hospitalizations in the short term, two to four weeks from the time of prediction. COVIDNearTerm is based on an autoregressive model and utilizes a parametric bootstrap approach to make predictions. We evaluated COVIDNearTerm on San Francisco Bay Area hospitalizations and compared it to models from the California COVID Assessment Tool (CalCAT). We found that that COVIDNearTerm pre-dictions were more accurate than the CalCAT ensemble predictions for all comparisons and any CalCAT component for a majority of comparisons. For instance, at the county level our 14-day hospitalization median absolute percentage errors ranged from 16% to 36%. For those same comparisons the CalCAT ensemble errors were between 30% and 59%. COVIDNearT-erm is also easier to use than some other methods. It requires only previous hospitalization data and there is an open source R package that implements the algorithm.

The epidermal growth factor receptor (EGFR) inhibitor cetuximab is the only FDA-approved oncogene-targeting therapy for head and neck squamous cell carcinoma (HNSCC). Despite variable treatment response, no biomarkers exist to stratify patients for cetuximab therapy in HNSCC. Here, we applied unbiased hierarchical clustering to reverse-phase protein array molecular profiles from patient-derived xenograft (PDX) tumors and revealed 2 PDX clusters defined by protein networks associated with EGFR inhibitor resistance. In vivo validation revealed unbiased clustering to classify PDX tumors according to cetuximab response with 88% accuracy. Next, a support vector machine classifier algorithm identified a minimalist biomarker signature consisting of 8 proteins - caveolin-1, Sox-2, AXL, STING, Brd4, claudin-7, connexin-43, and fibronectin - with expression that strongly predicted cetuximab response in PDXs using either protein or mRNA. A combination of caveolin-1 and Sox-2 protein levels was sufficient to maintain high predictive accuracy, which we validated in tumor samples from patients with HNSCC with known clinical response to cetuximab. These results support further investigation into the combined use of caveolin-1 and Sox-2 as predictive biomarkers for cetuximab response in the clinic.

HER2 and HER3 play key driving functions in the pathophysiology of HER2-amplified breast cancers, but this function is less well characterized in other cancers driven by HER2 amplification. This study aimed to explore the role of HER2 and HER3 signaling in other types of HER2-amplified cancer. The expression and signaling activity of HER2, HER3, and downstream pathway proteins were studied in cell panels representing HER2-amplified cancers of the breast, bladder, colon and rectal, stomach, esophagus, lung, tongue, and endometrium along with controls lacking HER2 amplification. We report that HER2-amplified cancers are addicted to HER2 across different cancer types and the depth of addiction is best linked with the expression level of HER2, but not with HER3 expression. We report that the expression and constitutive phosphorylation of HER3 are ubiquitous in HER2-amplified breast cancer cell lines, but much more variable in HER2-amplified cancer cells from other tissues. We observed the lapatinib-induced compensatory upregulation of HER3 signaling in many types of HER2-amplified cancers, although with much variability. We find that HER3 expression is essential for in vivo tumorigenic growth in some HER2-amplified tumors but not others. Importantly HER3 expression level does not correlate well with its functional importance. More biomarkers will be needed to guide the optimal use of HER3 inhibitors in HER2-amplified cancers from non-breast origin. Unlike oncogenes activated through mutational events, the activation of HER2 through overexpression represents a gradient of activities and depth of addiction and the response to inhibitors follows a similar gradient.

KRAS mutations drive a quarter of cancer mortality, and most are undruggable. Several inhibitors of the MAPK pathway are FDA approved but poorly tolerated at the doses needed to adequately extinguish RAS/RAF/MAPK signaling in the tumor cell. We found that oncogenic KRAS signaling induced ferrous iron (Fe2+) accumulation early in and throughout mutant KRAS-mediated transformation. We converted an FDA-approved MEK inhibitor into a ferrous iron–activatable drug conjugate (FeADC) and achieved potent MAPK blockade in tumor cells while sparing normal tissues. This innovation allowed sustainable, effective treatment of tumor-bearing animals, with tumor-selective drug activation, producing superior systemic tolerability. Ferrous iron accumulation is an exploitable feature of KRAS transformation, and FeADCs hold promise for improving the treatment of KRAS-driven solid tumors.

Acute lymphoblastic leukemia (ALL) is the most common cancer in children. Thirdhand smoke (THS) is the residual tobacco contamination that remains after the smoke clears. We investigated the effects of THS exposure in utero and during early life in a transgenic Cdkn2a knockout mouse model that is vulnerable to the development of leukemia/lymphoma. Female mice, and their offspring, were exposed from the first day of pregnancy to weaning. Plasma cytokines, body weight and hematologic parameters were measured in the offspring. To investigate THS exposure effects on the development of leukemia/lymphoma, bone marrow (BM) was collected from control and THS-exposed mice and transplanted into BM-ablated recipient mice, which were followed for tumor development for 1 year. We found that in utero and early-life THS exposure caused significant changes in plasma cytokine concentrations and in immune cell populations; changes appeared more pronounced in male mice. Spleen (SP) and BM B-cell populations were significantly lower in THS-exposed mice. We furthermore observed that THS exposure increased the leukemia/lymphoma-free survival in BM transplantation recipient mice, potentially caused by THS-induced B-cell toxicity. A trend towards increased solid tumors in irradiated mice reconstituted with THS-exposed BM stimulates the hypothesis that the immunosuppressive effects of in utero and early-life THS exposure might contribute to carcinogenesis by lowering the host defense to other toxic exposures. Our study adds to expanding evidence that THS exposure alters the immune system and that in utero and early-life developmental periods represent vulnerable windows of susceptibility for these effects.

Background Comprehensive molecular profiling has revealed somatic variations in cancer at genomic, epigenomic, transcriptomic, and proteomic levels. The accumulating data has shown clearly that molecular phenotypes of cancer are complex and influenced by a multitude of factors. Conventional unsupervised clustering applied to a large patient population is inevitably driven by the dominant variation from major factors such as cell-of-origin or histology. Translation of these data into clinical relevance requires more effective extraction of information directly associated with patient outcome. Methods Drawing from ideas in supervised text classification, we developed survClust, an outcome-weighted clustering algorithm for integrative molecular stratification focusing on patient survival. survClust was performed on 18 cancer types across multiple data modalities including somatic mutation, DNA copy number, DNA methylation, and mRNA, miRNA, and protein expression from the Cancer Genome Atlas study to identify novel prognostic subtypes. Results Our analysis identified the prognostic role of high tumor mutation burden with concurrently high CD8 T cell immune marker expression and the aggressive clinical behavior associated with CDKN2A deletion across cancer types. Visualization of somatic alterations, at a genome-wide scale (total mutation burden, mutational signature, fraction genome altered) and at the individual gene level, using circomap further revealed indolent versus aggressive subgroups in a pan-cancer setting. Conclusions Our analysis has revealed prognostic molecular subtypes not previously identified by unsupervised clustering. The algorithm and tools we developed have direct utility toward patient stratification based on tumor genomics to inform clinical decision-making. The survClust software tool is available at https://github.com/arorarshi/survClust.

Autophagy promotes protein degradation, and therefore has been proposed to maintain amino acid pools to sustain protein synthesis during metabolic stress. To date, how autophagy influences the protein synthesis landscape in mammalian cells remains unclear. Here, we utilize ribosome profiling to delineate the effects of genetic ablation of the autophagy regulator, ATG12, on translational control. In mammalian cells, genetic loss of autophagy does not impact global rates of cap dependent translation, even under starvation conditions. Instead, autophagy supports the translation of a subset of mRNAs enriched for cell cycle control and DNA damage repair. In particular, we demonstrate that autophagy enables the translation of the DNA damage repair protein BRCA2, which is functionally required to attenuate DNA damage and promote cell survival in response to PARP inhibition. Overall, our findings illuminate that autophagy impacts protein translation and shapes the protein landscape., Goldsmith et al. employ ribosome profiling to dissect how deletion of the essential autophagy component Atg12 impacts mRNA translation. They detect changes in the translation of mRNAs involved in DNA repair, centrosome clustering and cell cycle control and specifically focus on how loss of autophagy causes reduced production of BRCA2 and increased DNA damage.

Purpose To determine the usefulness of a comprehensive, targeted-capture next-generation sequencing (NGS) assay for the clinical management of children undergoing enucleation for retinoblastoma. Design Cohort study. Participants Thirty-two children with retinoblastoma. Methods We performed targeted NGS using the UCSF500 Cancer Panel (University of California, San Francisco, San Francisco, CA) on formalin-fixed, paraffin-embedded tumor tissue along with constitutional DNA isolated from peripheral blood, buccal swab, or uninvolved optic nerve. Peripheral blood samples were also sent to a commercial laboratory for germline RB1 mutation testing. Main Outcome Measures Presence or absence of germline RB1 mutation or deletion, tumor genetic profile, and association of genetic alterations with clinicopathologic features. Results Germline mutation or deletion of the RB1 gene was identified in all children with bilateral retinoblastoma (n = 12), and these NGS results were 100% concordant with commercial germline RB1 mutation analysis. In tumor tissue tested with NGS, biallelic inactivation of RB1 was identified in 28 tumors and focal MYCN amplification was identified in 4 tumors (2 with wild-type RB1 and 2 with biallelic RB1 inactivation). Additional likely pathogenic alterations beyond RB1 were identified in 13 tumors (41%), several of which have not been reported previously in retinoblastoma. These included focal amplifications of MDM4 and RAF1, as well as damaging mutations involving BCOR, ARID1A, MGA, FAT1, and ATRX. The presence of additional likely pathogenetic mutations beyond RB1 inactivation was associated with aggressive histopathologic features, including higher histologic grade and anaplasia, and also with both unilateral and sporadic disease. Conclusions Comprehensive NGS analysis reliably detects relevant mutations, amplifications, and chromosomal copy number changes in retinoblastoma. The presence of genetic alterations beyond RB1 inactivation correlates with aggressive histopathologic features.