Adverse pathologic features impact survival outcomes for small renal masses following nephrectomy.

PURPOSE: While most small renal masses (SRM) < 4 cm have an excellent prognosis following resection, the impact of adverse T3a pathologic features on oncologic outcomes of SRMs remains unclear. We sought to compare clinical outcomes for surgically resected pT3a versus pT1a SRMs at our institution. MATERIALS AND METHODS: We retrospectively reviewed records of patients who underwent radical or partial nephrectomy (RN, PN) for renal tumors <4 cm at our institution between 2010 and 2020. We compared features and outcomes of pT3a vs pT1a SRMs. Continuous and categorical variables were compared using Student's t and Pearson's chi-squared tests, respectively. Postoperative outcomes of interest including overall, cancer-specific, and recurrence-free survival (OS, CSS, and RFS) were analyzed using Kaplan-Meier method, Cox proportional hazard regression, and competing risk analysis. Analyses were performed using R statistical package (R Foundation, v4.0). RESULTS: We identified 1,837 patients with malignant SRMs. Predictors of postoperative pT3a upstaging included higher renal score, larger tumor size, and presence of radiologic features concerning for T3a disease (odds ratio [OR] = 5.45, 95% confidence interval [CI] 3.92-7.59, P < 0.001). On univariable modeling, pT3a SRMs had higher positive margin rates (9.6% vs 4.1%, P < 0.001), worse OS (hazard ratio [HR] = 2.9, 95% CI 1.6-5.3, P = 0.002), RFS (HR 9.32, 95% CI 2-40.1, P = 0.003), and CSS (HR = 3.6, 95% CI 1.5-8.2, P = 0.003). On multivariable modeling, pT3a status remained associated with worse RFS (HR = 2.7, 95% CI 1.04-7, P = 0.04), but not OS (HR 1.6, 95% CI = 0.83-3.1, P = 0.2); multivariable modeling was deferred for CSS due to low event rates. CONCLUSIONS: Adverse T3a pathologic features portend worse outcomes for SRMs, highlighting the crucial role of pre-operative planning and case selection. These patients have relatively poor prognosis, and should be monitored more closely and counseled for consideration of adjuvant therapy or clinical trials.

T cell immunotherapies engage neutrophils to eliminate tumor antigen escape variants.

Cancer immunotherapies, including adoptive T cell transfer, can be ineffective because tumors evolve to display antigen-loss-variant clones. Therapies that activate multiple branches of the immune system may eliminate escape variants. Here, we show that melanoma-specific CD4+ T cell therapy in combination with OX40 co-stimulation or CTLA-4 blockade can eradicate melanomas containing antigen escape variants. As expected, early on-target recognition of melanoma antigens by tumor-specific CD4+ T cells was required. Surprisingly, complete tumor eradication was dependent on neutrophils and partly dependent on inducible nitric oxide synthase. In support of these findings, extensive neutrophil activation was observed in mouse tumors and in biopsies of melanoma patients treated with immune checkpoint blockade. Transcriptomic and flow cytometry analyses revealed a distinct anti-tumorigenic neutrophil subset present in treated mice. Our findings uncover an interplay between T cells mediating the initial anti-tumor immune response and neutrophils mediating the destruction of tumor antigen loss variants.

Pathway Alterations in Stage II/III Primary Melanoma.

PURPOSE: Genomic classification of melanoma has thus far focused on the mutational status of BRAF, NRAS, and NF1. The clinical utility of this classification remains limited, and the landscape of alterations in other oncogenic signaling pathways is underexplored. METHODS: Using primary samples from the InterMEL study, a retrospective cohort of cases with specimens collected from an international consortium with participating institutions throughout the United States and Australia, with oversampling of cases who ultimately died of melanoma, we examined mutual exclusivity and co-occurrence of genomic alterations in 495 stage II/III primary melanomas across 11 cancer pathways. Somatic mutation and copy number alterations were analyzed from next-generation sequencing using a clinical sequencing panel. RESULTS: Mutations in the RTK-RAS pathway were observed in 81% of cases. Other frequently occurring pathways were TP53 (31%), Cell Cycle (30%), and PI3K (18%). These frequencies are generally lower than was observed in The Cancer Genome Atlas, where the specimens analyzed were predominantly obtained from metastases. Overall, 81% of the cases had at least one targetable mutation. The RTK-RAS pathway was the only pathway that demonstrated strong and statistically significant mutual exclusivity. However, this strong mutual exclusivity signal was evident only for the three common genes in the pathway (BRAF, NRAS, and NF1). Analysis of co-occurrence of different pathways exhibited no positive significant trends. However, interestingly, a high frequency of cases with none of these pathways represented was observed, 8.4% of cases versus 4.0% expected (P < .001). A higher frequency of RTK-RAS singletons (with no other pathway alteration) was observed compared with The Cancer Genome Atlas. Clonality analyses suggest strongly that both the cell cycle and RTK-RAS pathways represent early events in melanogenesis. CONCLUSION: Our results confirm the dominance of mutations in the RTK-RAS pathway. The presence of many mutations in several well-known, actionable pathways suggests potential avenues for targeted therapy in these early-stage cases.

Landscape of mutations in early stage primary cutaneous melanoma: An InterMEL study.

It is unclear why some melanomas aggressively metastasize while others remain indolent. Available studies employing multi-omic profiling of melanomas are based on large primary or metastatic tumors. We examine the genomic landscape of early-stage melanomas diagnosed prior to the modern era of immunological treatments. Untreated cases with Stage II/III cutaneous melanoma were identified from institutions throughout the United States, Australia and Spain. FFPE tumor sections were profiled for mutation, methylation and microRNAs. Preliminary results from mutation profiling and clinical pathologic correlates show the distribution of four driver mutation sub-types: 31% BRAF; 18% NRAS; 21% NF1; 26% Triple Wild Type. BRAF mutant tumors had younger age at diagnosis, more associated nevi, more tumor infiltrating lymphocytes, and fewer thick tumors although at generally more advanced stage. NF1 mutant tumors were frequent on the head/neck in older patients with severe solar elastosis, thicker tumors but in earlier stages. Triple Wild Type tumors were predominantly male, frequently on the leg, with more perineural invasion. Mutations in TERT, TP53, CDKN2A and ARID2 were observed often, with TP53 mutations occurring particularly frequently in the NF1 sub-type. The InterMEL study will provide the most extensive multi-omic profiling of early-stage melanoma to date. Initial results demonstrate a nuanced understanding of the mutational and clinicopathological landscape of these early-stage tumors.

Long-term Outcomes of Local and Metastatic Small Cell Carcinoma of the Urinary Bladder and Genomic Analysis of Patients Treated With Neoadjuvant Chemotherapy.

INTRODUCTION: Small cell carcinoma of the bladder (SCCB) is a rare variant of bladder cancer with poor outcomes. We evaluated long-term outcomes of nonmetastatic (M0) and metastatic (M1) SCCB and correlated pathologic response with genomic alterations of patients treated with neoadjuvant chemotherapy (NAC). PATIENTS AND METHODS: Clinical history and pathology samples from SCCB patients diagnosed at our institution were reviewed. RESULTS: One hundred and ninety-nine SCCB patients were identified. (M0: 147 [74%]; M1: 52 [26%]). Among M0 patients, 108 underwent radical cystectomy (RC) (NAC: 71; RC only: 23; adjuvant chemotherapy: 14); 14 received chemoradiotherapy; the rest received chemotherapy alone or no cancer-directed therapy. RC-only patients had a median follow-up of 9.1 years, and median disease-free survival (DFS) and overall survival (OS) were 1.1 and 1.2 years, respectively. NAC patients had pathologic response (

FACETS: Fraction and Allele-Specific Copy Number Estimates from Tumor Sequencing.

Clinical sequencing studies routinely involve molecular profiling of patients for mutations and copy number alterations. However, detection of "actionable" aberrations to guide treatment decisions require accurate, tumor purity-, ploidy-, and clonal heterogeneity-adjusted integer copy number calls. In this chapter, we describe the FACETS algorithm, an Allele-Specific Copy Number (ASCN) analysis tool with a broad application to whole-genome, whole-exome, as well as targeted panel sequencing platforms to annotate the genome for the detection of copy number alterations including homozygous/heterozygous deletions, copy-neutral loss-of-heterozygosity (LOH) events, allele-specific gains/amplifications, and cellular fraction profiles.We will describe some methodological details on joint segmentation of total and allele-specific copy number, on the estimation of integer copy number calls adjusting for tumor purity, ploidy, and intratumor heterogeneity, along with comprehensive output and integrated visualization. We also provide a tutorial on the installation, application, and tips to run and interpret FACETS.

Comparative genomics of primary prostate cancer and paired metastases: insights from 12 molecular case studies.

Primary prostate cancer (PCa) can show marked molecular heterogeneity. However, systematic analyses comparing primary PCa and matched metastases in individual patients are lacking. We aimed to address the molecular aspects of metastatic progression while accounting for the heterogeneity of primary PCa. In this pilot study, we collected 12 radical prostatectomy (RP) specimens from men who subsequently developed metastatic castration-resistant prostate cancer (mCRPC). We used histomorphology (Gleason grade, focus size, stage) and immunohistochemistry (IHC) (ERG and p53) to identify independent tumors and/or distinct subclones of primary PCa. We then compared molecular profiles of these primary PCa areas to matched metastatic samples using whole-exome sequencing (WES) and amplicon-based DNA and RNA sequencing. Based on combined pathology and molecular analysis, seven (58%) RP specimens harbored monoclonal and topographically continuous disease, albeit with some degree of intratumor heterogeneity; four (33%) specimens showed true multifocal disease; and one displayed monoclonal disease with discontinuous topography. Early (truncal) events in primary PCa included SPOP p.F133V (one patient), BRAF p.K601E (one patient), and TMPRSS2:ETS rearrangements (eight patients). Activating AR alterations were seen in nine (75%) mCRPC patients, but not in matched primary PCa. Hotspot TP53 mutations, found in metastases from three patients, were readily present in matched primary disease. Alterations in genes encoding epigenetic modifiers were observed in several patients (either shared between primary foci and metastases or in metastatic samples only). WES-based phylogenetic reconstruction and/or clonality scores were consistent with the index focus designated by pathology review in six out of nine (67%) cases. The three instances of discordance pertained to monoclonal, topographically continuous tumors, which would have been considered as unique disease in routine practice. Overall, our results emphasize pathologic and molecular heterogeneity of primary PCa, and suggest that comprehensive IHC-assisted pathology review and genomic analysis are highly concordant in nominating the 'index' primary PCa area. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

LAG-3 expression on peripheral blood cells identifies patients with poorer outcomes after immune checkpoint blockade.

Immune checkpoint blocking antibodies are a cornerstone in cancer treatment; however, they benefit only a subset of patients and biomarkers to guide immune checkpoint blockade (ICB) treatment choices are lacking. We designed this study to identify blood-based correlates of clinical outcome in ICB-treated patients. We performed immune profiling of 188 ICB-treated patients with melanoma using multiparametric flow cytometry to characterize immune cells in pretreatment peripheral blood. A supervised statistical learning approach was applied to a discovery cohort to classify phenotypes and determine their association with survival and treatment response. We identified three distinct immune phenotypes (immunotypes), defined in part by the presence of a LAG-3+CD8+ T cell population. Patients with melanoma with a LAG+ immunotype had poorer outcomes after ICB with a median survival of 22.2 months compared to 75.8 months for those with the LAG- immunotype (P = 0.031). An independent cohort of 94 ICB-treated patients with urothelial carcinoma was used for validation where LAG+ immunotype was significantly associated with response (P = 0.007), survival (P < 0.001), and progression-free survival (P = 0.004). Multivariate Cox regression and stratified analyses further showed that the LAG+ immunotype was an independent marker of outcome when compared to known clinical prognostic markers and previously described markers for the clinical activity of ICB, PD-L1, and tumor mutation burden. The pretreatment peripheral blood LAG+ immunotype detects patients who are less likely to benefit from ICB and suggests a strategy for identifying actionable immune targets for further investigation.

Therapeutic Implications of Detecting MAPK-Activating Alterations in Cutaneous and Unknown Primary Melanomas.

PURPOSE: Cutaneous and unknown primary melanomas frequently harbor alterations that activate the MAPK pathway. Whether MAPK driver detection beyond BRAF V600 is clinically relevant in the checkpoint inhibitor era is unknown. EXPERIMENTAL DESIGN: Patients with melanoma were prospectively offered tumor sequencing of 341-468 genes. Oncogenic alterations in 28 RTK-RAS-MAPK pathway genes were used to construct MAPK driver groups. Time to treatment failure (TTF) was determined for patients who received first-line programmed cell death protein 1 (PD-1) monotherapy, nivolumab plus ipilimumab, or subsequent genomically matched targeted therapies. A Cox proportional hazards model was constructed for TTF using driver group and clinical variables. RESULTS: A total of 670 of 696 sequenced melanomas (96%) harbored an oncogenic RTK-RAS-MAPK pathway alteration; 33% had ≥1 driver. Nine driver groups varied by clinical presentation and mutational burden. TTF of PD-1 monotherapy (N = 181) varied by driver, with worse outcomes for NRAS Q61 and BRAF V600 versus NF1 or other alterations (median 4.2, 7.5, 22, and not reached; P < 0.0001). Driver group remained significant, independent of tumor mutational burden and clinical features. TTF did not vary by driver for nivolumab plus ipilimumab (N = 141). Among 172 patients with BRAF V600 wild-type melanoma who progressed on checkpoint blockade, 27 were treated with genomically matched therapy, and eight (30%) derived clinical benefit lasting ≥6 months. CONCLUSIONS: Targeted capture multigene sequencing can detect oncogenic RTK-RAS-MAPK pathway alterations in almost all cutaneous and unknown primary melanomas. TTF of PD-1 monotherapy varies by mechanism of ERK activation. Oncogenic kinase fusions can be successfully targeted in immune checkpoint inhibitor-refractory melanoma.

Pan-cancer identification of clinically relevant genomic subtypes using outcome-weighted integrative clustering.

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 .

Using somatic variant richness to mine signals from rare variants in the cancer genome.

To date, the vast preponderance of somatic variants observed in the cancer genome have been rare variants, and it is common in practice to encounter in a new tumor variants that have not been observed previously. Here we focus on probability estimation for encountering such hitherto unseen variants. We draw upon statistical methodology that has been developed in other fields of study, notably in species estimation in ecology, and word frequency estimation in computational linguistics. Analysis of whole-exome and targeted panel sequencing data sets reveal substantial variability in variant "richness" between genes that could be harnessed for clinically relevant problems. We quantify the variant-tissue association and show a strong gene-specific, lineage-dependent pattern of encountering new variants. This variability is largely determined by the proportion of observed variants that are rare. Our findings suggest that variants that occur at very low frequencies can harbor important signals that are clinically consequential.

Radiogenomics of rectal adenocarcinoma in the era of precision medicine: A pilot study of associations between qualitative and quantitative MRI imaging features and genetic mutations.

OBJECTIVE: To investigate associations between genetic mutations and qualitative as well as quantitative features on MRI in rectal adenocarcinoma at primary staging. METHODS: In this retrospective study, patients with rectal adenocarcinoma, genome sequencing, and pretreatment rectal MRI were included. Statistical analysis was performed to evaluate associations between qualitative features obtained from subjective evaluation of rectal MRI and gene mutations as well as between quantitative textural features and gene mutations. For the qualitative evaluation, Fisher's Exact test was used to analyze categorical associations and Wilcoxon Rank Sum test was used for continuous clinical variables. For the quantitative evaluation, we performed manual segmentation of T2-weighted images for radiomics-based quantitative image analysis. Thirty-four texture features consisting of first order intensity histogram-based features (n = 4), second order Haralick textures (n = 5), and Gabor-edge based Haralick textures were computed at two different orientations. Consensus clustering was performed with 34 computed texture features using the K-means algorithm with Euclidean distance between the texture features. The clusters resulting from the algorithm were then used to enumerate the prevalence of gene mutations in those clusters. RESULTS: In 65 patients, 45 genes were mutated in more than 3/65 patients (5%) and were included in the statistical analysis. Regarding qualitative imaging features, on univariate analysis, tumor location was significantly associated with APC (p = 0.032) and RASA1 mutation (p = 0.032); CRM status was significantly associated with ATM mutation (p = 0.021); and lymph node metastasis was significantly associated with BRCA2 (p = 0.046) mutation. However, these associations were not significant after adjusting for multiple comparisons. Regarding quantitative imaging features, Cluster C1 had tumors with higher mean Gabor edge intensity compared with cluster C2 (θ = 0°, p = 0.018; θ = 45°, p = 0.047; θ = 90°, p = 0.037; cluster C3 (θ = 0°, p = 0.18; θ = 45°, p = 0.1; θ = 90°, p = 0.052), and cluster C4 (θ = 0°, p = 0.016; θ = 45°, p = 0.033; θ = 90°, p = 0.014) suggesting that the cluster C1 had tumors with more distinct edges or heterogeneous appearance compared with other clusters. CONCLUSIONS: Although this preliminary study showed promising associations between quantitative features and genetic mutations, it did not show any correlation between qualitative features and genetic mutations. Further studies with larger sample size are warranted to validate our preliminary data.

Harnessing Clinical Sequencing Data for Survival Stratification of Patients with Metastatic Lung Adenocarcinomas.

PURPOSE: Broad panel sequencing of tumors facilitates routine care of people with cancer as well as clinical trial matching for novel genome-directed therapies. We sought to extend the use of broad panel sequencing results to survival stratification and clinical outcome prediction. PATIENTS AND METHODS: Using sequencing results from a cohort of 1,054 patients with advanced lung adenocarcinomas, we developed OncoCast, a machine learning tool for survival risk stratification and biomarker identification. RESULTS: With OncoCast, we stratified this patient cohort into four risk groups based on tumor genomic profile. Patients whose tumors harbored a high-risk profile had a median survival of 7.3 months (95% CI 5.5-10.9), compared to a low risk group with a median survival of 32.8 months (95% CI 26.3-38.5), with a hazard ratio of 4.6 (P<2e-16), far superior to any individual gene predictor or standard clinical characteristics. We found that co-mutations of both STK11 and KEAP1 are a strong determinant of unfavorable prognosis with currently available therapies. In patients with targetable oncogenes including EGFR/ALK/ROS1 and received targeted therapies, the tumor genetic background further differentiated survival with mutations in TP53 and ARID1A contributing to a higher risk score for shorter survival. CONCLUSION: Mutational profile derived from broad-panel sequencing presents an effective genomic stratification for patient survival in advanced lung adenocarcinoma. OncoCast is available as a public resource that facilitates the incorporation of mutational data to predict individual patient prognosis and compare risk characteristics of patient populations.

An IRAK1-PIN1 signalling axis drives intrinsic tumour resistance to radiation therapy.

Drug-based strategies to overcome tumour resistance to radiotherapy (R-RT) remain limited by the single-agent toxicity of traditional radiosensitizers (for example, platinums) and a lack of targeted alternatives. In a screen for compounds that restore radiosensitivity in p53 mutant zebrafish while tolerated in non-irradiated wild-type animals, we identified the benzimidazole anthelmintic oxfendazole. Surprisingly, oxfendazole acts via the inhibition of IRAK1, a kinase thus far implicated in interleukin-1 receptor (IL-1R) and Toll-like receptor (TLR) immune responses. IRAK1 drives R-RT in a pathway involving IRAK4 and TRAF6 but not the IL-1R/TLR-IRAK adaptor MyD88. Rather than stimulating nuclear factor-κB, radiation-activated IRAK1 prevented apoptosis mediated by the PIDDosome complex (comprising PIDD, RAIDD and caspase-2). Countering this pathway with IRAK1 inhibitors suppressed R-RT in tumour models derived from cancers in which TP53 mutations predict R-RT. Moreover, IRAK1 inhibitors synergized with inhibitors of PIN1, a prolyl isomerase essential for IRAK1 activation in response to pathogens and, as shown here, in response to ionizing radiation. These data identify an IRAK1 radiation-response pathway as a rational chemoradiation therapy target.

Adipocyte-Derived Lipids Mediate Melanoma Progression via FATP Proteins.

Advanced, metastatic melanomas frequently grow in subcutaneous tissues and portend a poor prognosis. Though subcutaneous tissues are largely composed of adipocytes, the mechanisms by which adipocytes influence melanoma are poorly understood. Using in vitro and in vivo models, we find that adipocytes increase proliferation and invasion of adjacent melanoma cells. Additionally, adipocytes directly transfer lipids to melanoma cells, which alters tumor cell metabolism. Adipocyte-derived lipids are transferred to melanoma cells through the FATP/SLC27A family of lipid transporters expressed on the tumor cell surface. Among the six FATP/SLC27A family members, melanomas significantly overexpress FATP1/SLC27A1. Melanocyte-specific FATP1 expression cooperates with BRAFV600E in transgenic zebrafish to accelerate melanoma development, an effect that is similarly seen in mouse xenograft studies. Pharmacologic blockade of FATPs with the small-molecule inhibitor Lipofermata abrogates lipid transport into melanoma cells and reduces melanoma growth and invasion. These data demonstrate that stromal adipocytes can drive melanoma progression through FATP lipid transporters and represent a new target aimed at interrupting adipocyte-melanoma cross-talk.Significance: We demonstrate that stromal adipocytes are donors of lipids that mediate melanoma progression. Adipocyte-derived lipids are taken up by FATP proteins that are aberrantly expressed in melanoma. Inhibition of FATPs decreases melanoma lipid uptake, invasion, and growth. We provide a mechanism for how stromal adipocytes drive tumor progression and demonstrate a novel microenvironmental therapeutic target. Cancer Discov; 8(8); 1006-25. ©2018 AACR.This article is highlighted in the In This Issue feature, p. 899.

Integrating Clinical and Multiple Omics Data for Prognostic Assessment across Human Cancers.

Multiple omic profiles have been generated for many cancer types; however, comprehensive assessment of their prognostic values across cancers is limited. We conducted a pan-cancer prognostic assessment and presented a multi-omic kernel machine learning method to systematically quantify the prognostic values of high-throughput genomic, epigenomic, and transcriptomic profiles individually, integratively, and in combination with clinical factors for 3,382 samples across 14 cancer types. We found that the prognostic performance varied substantially across cancer types. mRNA and miRNA expression profile frequently performed the best, followed by DNA methylation profile. Germline susceptibility variants displayed low prognostic performance consistently across cancer types. The integration of omic profiles with clinical variables can lead to substantially improved prognostic performance over the use of clinical variables alone in half of cancer types examined. Moreover, we showed that the kernel machine learning method consistently outperformed existing prognostic signatures, suggesting that including a large number of omic biomarkers may provide substantial improvement in prognostic assessment. Our study provides a comprehensive portrait of omic architecture for tumor prognosis across cancers, and highlights the prognostic value of genome-wide omic biomarker aggregation, which may facilitate refined prognostic assessment in the era of precision oncology.

BioNetGen 2.2: advances in rule-based modeling.

: BioNetGen is an open-source software package for rule-based modeling of complex biochemical systems. Version 2.2 of the software introduces numerous new features for both model specification and simulation. Here, we report on these additions, discussing how they facilitate the construction, simulation and analysis of larger and more complex models than previously possible. AVAILABILITY AND IMPLEMENTATION: Stable BioNetGen releases (Linux, Mac OS/X and Windows), with documentation, are available at http://bionetgen.org Source code is available at http://github.com/RuleWorld/bionetgen CONTACT: bionetgen.help@gmail.comSupplementary information: Supplementary data are available at Bioinformatics online.

COMT, BDNF, and DTNBP1 polymorphisms and cognitive functions in patients with brain tumors.

BACKGROUND: Cognitive dysfunction is common among patients with brain tumors and can be associated with the disease and treatment with radiotherapy and chemotherapy. However, little is known about genetic risk factors that may moderate the vulnerability for developing cognitive dysfunction. In this study, we examined the association of single nucleotide polymorphisms (SNPs) in the catechol-O-methyl transferase (COMT), brain-derived neurotrophic factor (BDNF), and dystrobrevin-binding protein 1 (DTNBP1) genes with cognitive functions and neuroimaging outcomes in patients with brain tumors. METHODS: One hundred and fifty patients with brain tumors completed neuropsychological tests of attention, executive functions, and memory and were genotyped for polymorphisms in the COMT, BDNF, and DTNBP1 genes. Ratings of white matter (WM) abnormalities on magnetic resonance imaging scans were performed. RESULTS: Multivariate regression shrinkage analyses, adjusted for age, education, treatment type, time since treatment completion, and tumor location, indicated a significant association between the COMT SNP rs4680 (Val158Met) and memory with lower scores in delayed recall (P < .01) among homozygotes (valine/valine). Additional COMT, BDNF and DTNBP1 SNPs were significantly associated with attention, executive functions, and memory scores. CONCLUSION: This is the first study to suggest that known and newly described polymorphisms in genes associated with executive and memory functions in healthy individuals and other clinical populations may modulate cognitive outcome in patients with brain tumors.