Detecting Reconnaissance and Discovery Tactics from the MITRE ATT&CK Framework in Zeek Conn Logs Using Spark's Machine Learning in the Big Data Framework.

While computer networks and the massive amount of communication taking place on these networks grow, the amount of damage that can be done by network intrusions grows in tandem. The need is for an effective and scalable intrusion detection system (IDS) to address these potential damages that come with the growth of these networks. A great deal of contemporary research on near real-time IDS focuses on applying machine learning classifiers to labeled network intrusion datasets, but these datasets need be relevant pertaining to the currency of the network intrusions. This paper focuses on a newly created dataset, UWF-ZeekData22, that analyzes data from Zeek's Connection Logs collected using Security Onion 2 network security monitor and labelled using the MITRE ATT&CK framework TTPs. Due to the volume of data, Spark, in the big data framework, was used to run many of the well-known classifiers (naïve Bayes, random forest, decision tree, support vector classifier, gradient boosted trees, and logistic regression) to classify the reconnaissance and discovery tactics from this dataset. In addition to looking at the performance of these classifiers using Spark, scalability and response time were also analyzed.

Germline mutations in Black patients with ovarian, fallopian tube and primary peritoneal carcinomas.

OBJECTIVE: Routine genetic testing for ovarian cancer and identification of germline mutations can help improve early detection of cancer as well as guide treatment. Knowledge of genetic counseling and referral rates for genetic testing has been lower for Black patients, compared to White patients. We aimed to describe the demographics and presence of germline mutations in Black individuals with ovarian, fallopian tube or peritoneal carcinoma at two large academic institutions. METHODS: Fifty-one Black patients with invasive epithelial ovarian, fallopian tube, or primary peritoneal carcinoma were identified via institutional tissue banks over a 20-year time-period. Germline DNA was sequenced using BROCA, a targeted capture and parallel sequencing assay that identified pathogenic germline mutations in ovarian carcinoma susceptibility genes. RESULTS: Germline mutations in ovarian cancer susceptibility genes were found in 25.5% of women, most commonly BRCA1 and BRCA2. This mutation frequency mirrors those previously described among predominantly White populations. Our data suggests there may be an advantage in survival among those with germline mutations, although this was not statistically significant. CONCLUSIONS: Given similar frequencies of germline mutations between Black and White patients with ovarian cancer, we conclude that there are not major differences in the genetic predisposition to ovarian carcinoma. Equitable access to genomic advancements including germline and tumor sequencing would facilitate equal access to PARP inhibitors, the standard of care for patients with BRCA mutated advanced ovarian cancer.

Characterizing TP53 mutations in ovarian carcinomas with and without concurrent BRCA1 or BRCA2 mutations.

OBJECTIVES: Mutations in the TP53 tumor suppressor gene are common in ovarian carcinoma (OC) but their impact on outcomes is controversial. We sought to define the relationship of TP53 mutations to cancer outcomes and their interactions with co-occurrent BRCA1 or BRCA2 (BRCA) mutations, comparing three different TP53 mutation classification schemes. METHODS: We performed next generation sequencing on 393 cases of OC prospectively followed for survival. TP53 mutations were classified according to three schemes termed Structural, Functional, and Hotspot. Mutation distribution was compared between cases with and without BRCA mutations. In a subset of 281 cases of high grade serous carcinoma (HGSC), overall survival was compared using Kaplan-Meier curves, logrank testing, and multivariate Cox regression analysis, both stratified and adjusted for BRCA mutation status. Multivariate logistic regression was used to analyze the effects of TP53 mutation type on platinum resistance. RESULTS: TP53 mutations were identified in 76.8% of the total cohort (n = 302/393) and 87.9% of HGSC (n = 247/281). Cases with BRCA mutations demonstrated significantly higher TP53 mutation frequency overall (n = 84/91, 92.3% vs. n = 218/302, 72.2%, p < 0.001). TP53 mutations were not associated with overall survival, even when stratified by BRCA mutation. TP53 mutations were associated with platinum sensitivity, even after adjusting for BRCA mutation status (OR 0.41, p = 0.048). The choice of TP53 mutation classification scheme was not found to alter any significant outcome. CONCLUSIONS: BRCA mutations significantly co-occur with TP53 mutations. After adjusting for BRCA mutations, TP53 mutations are associated with platinum sensitivity, and this effect is not dependent on TP53 mutation type.

Inherited mutations in fallopian tube, ovarian and primary peritoneal carcinoma: Changes in diagnoses and mutational frequency over 20 years.

OBJECTIVES: Women with fallopian tube carcinoma (FTC) are reported to have a higher frequency of inherited BRCA mutations than those with ovarian carcinoma (OC) or primary peritoneal carcinoma (PPC). We hypothesized that routine serial sectioning of fallopian tubes would increase the proportion of cases designated as FTC and change the frequency of inherited mutations between carcinoma types. METHODS: Eight hundred and sixty-seven women diagnosed from 1998 to 2018 were enrolled at diagnosis into an institutional tissue bank. Germline DNA, available from 700 women with FTC (N = 124), OC (N = 511) and PPC (N = 65), was assessed using targeted capture and massively parallel sequencing for mutations in ovarian carcinoma susceptibility genes. Cases were divided between those prior to routine serial sectioning (1998-2008) and after (2009-2019), and the frequency of FTC and inherited mutations was assessed. RESULTS: The proportion of carcinomas attributed as FTC after 2009 was 28% (128/465), significantly higher than before 2009 [5% (21/402), p < .0001, OR 6.9, 95% CI 4.3-11.2], with subsequent decreases in OC and PPC. In the sequenced group, overall inherited mutation frequency in FTC (24/124, 19%), OC (106/511, 21%, p = .42), and PPC (16/65, 25%, p = .25) were similar. Germline mutation rates in FTC were lower after 2009,16/107 cases (15%), compared to 8/17 cases (47.1%) before 2009 (p = .005, OR 0.20, 95% CI 0.06-0.64). CONCLUSIONS: The prevalence of inherited mutations is similar in FTC compared to OC or PPC when using modern pathological assignment. Complete serial sectioning of fallopian tubes has significantly increased the diagnosis of FTC, and subsequently decreased the frequency of inherited mutations within this group.

Diagnosis of Ovarian Carcinoma Homologous Recombination DNA Repair Deficiency From Targeted Gene Capture Oncology Assays.

PURPOSE: Homologous recombination DNA repair deficiency (HRD) is a therapeutic biomarker for sensitivity to platinum and poly(ADP-ribose) polymerase inhibitor therapies in breast and ovarian cancers. Several molecular phenotypes and diagnostic strategies have been developed to assess HRD; however, their clinical implementation remains both technically challenging and methodologically unstandardized. METHODS: We developed and validated an efficient and cost-effective strategy for HRD determination on the basis of calculation of a genome-wide loss of heterozygosity (LOH) score through targeted, hybridization capture and next-generation DNA sequencing augmented with 3,000 common, polymorphic single-nucleotide polymorphism (SNP) sites distributed genome-wide. This approach requires minimal sequence reads and can be readily integrated into targeted gene capture workflows already in use for molecular oncology. We interrogated 99 ovarian neoplasm-normal pairs using this method and compared results with patient mutational genotypes and orthologous predictors of HRD derived from whole-genome mutational signatures. RESULTS: LOH scores of ≥11% had >86% sensitivity for identifying tumors with HRD-causing mutations in an independent validation set (90.6% sensitivity for all specimens). We found strong agreement of our analytic approach with genome-wide mutational signature assays for determining HRD, yielding an estimated 96.7% sensitivity and 50% specificity. We observed poor concordance with mutational signatures inferred using only mutations detected by the targeted gene capture panel, suggesting inadequacy of the latter approach. LOH score did not significantly correlate with treatment outcomes. CONCLUSION: Targeted sequencing of genome-wide polymorphic SNP sites can be used to infer LOH events and subsequently diagnose HRD in ovarian tumors. The methods presented here are readily generalizable to other targeted gene oncology assays and could be adapted for HRD diagnosis in other tumor types.

KiRNet: Kinase-centered network propagation of pharmacological screen results.

The ever-increasing size and scale of biological information have popularized network-based approaches as a means to interpret these data. We develop a network propagation method that integrates kinase-inhibitor-focused functional screens with known protein-protein interactions (PPIs). This method, dubbed KiRNet, uses an a priori edge-weighting strategy based on node degree to establish a pipeline from a kinase inhibitor screen to the generation of a predictive PPI subnetwork. We apply KiRNet to uncover molecular regulators of mesenchymal cancer cells driven by overexpression of Frizzled 2 (FZD2). KiRNet produces a network model consisting of 166 high-value proteins. These proteins exhibit FZD2-dependent differential phosphorylation, and genetic knockdown studies validate their role in maintaining a mesenchymal cell state. Finally, analysis of clinical data shows that mesenchymal tumors exhibit significantly higher average expression of the 166 corresponding genes than epithelial tumors for nine different cancer types.