Mutation status and postresection survival of patients with non-small cell lung cancer brain metastasis: implications of biomarker-driven therapy.

OBJECTIVE: Non-small cell lung cancer (NSCLC) is the most common primary tumor to develop brain metastasis. Prognostic markers are needed to better determine survival after neurosurgical resection of intracranial disease. Given the importance of mutation subtyping in determining systemic therapy and overall prognosis of NSCLC, the authors examined the prognostic value of mutation status for postresection survival of patients with NSCLC brain metastasis. METHODS: The authors retrospectively analyzed all cases of NSCLC brain metastasis with available molecular testing data that were resected by a single surgeon at a single academic center from January 2009 to February 2019. Mutation status, demographic characteristics, clinical factors, and treatments were analyzed. Association between predictive variables and overall survival after neurosurgery was determined with Cox regression. RESULTS: Of the included patients (n = 84), 40% were male, 76% were smokers, the mean ± SD Karnofsky Performance Status was 85 ± 14, and the mean ± SD age at surgery was 63 ± 11 years. In total, 23%, 26%, and 4% of patients had EGFR, KRAS, and ALK/ROS1 alterations, respectively. On multivariate analysis, survival of patients with EGFR (HR 0.495, p = 0.0672) and KRAS (HR 1.380, p = 0.3617) mutations were not significantly different from survival of patients with wild-type (WT) tumor. However, the subgroup of patients with EGFR mutation who also received tyrosine kinase inhibitor (TKI) therapy had significantly prolonged survival (HR 0.421, p = 0.0471). In addition, postoperative stereotactic radiosurgery (HR 0.409, p = 0.0177) and resected tumor diameter < 3 cm (HR 0.431, p = 0.0146) were also significantly associated with prolonged survival, but Graded Prognostic Assessment score ≤ 1.0 (HR 2.269, p = 0.0364) was significantly associated with shortened survival. CONCLUSIONS: Patients with EGFR mutation who receive TKI therapy may have better survival after resection of brain metastasis than patients with WT tumor. These results may inform counseling and decision-making regarding the appropriateness of resection of NSCLC brain metastasis.

Differential prioritization of therapies to subtypes of triple negative breast cancer using a systems medicine method.

Triple negative breast cancer (TNBC) is a group of cancers whose heterogeneity and shortage of effective drug therapies has prompted efforts to divide these cancers into molecular subtypes. Our computational platform, entitled GenEx-TNBC, applies concepts in systems biology and polypharmacology to prioritize thousands of approved and experimental drugs for therapeutic potential against each molecular subtype of TNBC. Using patient-based and cell line-based gene expression data, we constructed networks to describe the biological perturbation associated with each TNBC subtype at multiple levels of biological action. These networks were analyzed for statistical coincidence with drug action networks stemming from known drug-protein targets, while accounting for the direction of disease modulation for coinciding entities. GenEx-TNBC successfully designated drugs, and drug classes, that were previously shown to be broadly effective or subtype-specific against TNBC, as well as novel agents. We further performed biological validation of the platform by testing the relative sensitivities of three cell lines, representing three distinct TNBC subtypes, to several small molecules according to the degree of predicted biological coincidence with each subtype. GenEx-TNBC is the first computational platform to associate drugs to diseases based on inverse relationships with multi-scale disease mechanisms mapped from global gene expression of a disease. This method may be useful for directing current efforts in preclinical drug development surrounding TNBC, and may offer insights into the targetable mechanisms of each TNBC subtype.

Single and multivariate associations of MSR1, ELAC2, and RNASEL with prostate cancer in an ethnic diverse cohort of men.

Three genes, namely, ELAC2 (HPC2 locus) on chromosome 17p11, 2'-5'-oligoisoadenlyate-synthetase-dependent ribonuclease L (RNASEL, HPC1 locus), and macrophage scavenger receptor 1 (MSR1) within a region of linkage on chromosome 8p, have been identified as hereditary tumor suppressor genes in prostate cancer. We genotyped 41 tagged single nucleotide polymorphisms (SNPs) covering the three genes in a case-control cohort, which included 1,436 Caucasians, 648 Hispanics, and 270 African Americans. SNPs within MSR1, ELAC2, and RNASEL were significantly associated with risk of prostate cancer albeit with differences among the three ethnic groups (P = 0.043-1.0 x 10(-5)). In Caucasians, variants within MSR1 and ELAC2 are most likely to confer prostate cancer risk, and rs11545302 (ELAC2) showed a main effect independent of other significant SNPs (P = 2.03 x 10(-5)). A major haplotype G-A-C-G-C-G combining five SNPs within MSR1 was further shown to increase prostate cancer risk significantly in this study group. Variants in RNASEL had the strongest effects on prostate cancer risk estimates in Hispanics and also showed an interaction effect of family history. In African Americans, single SNPs within MSR1 were significantly associated with prostate cancer risk. A major risk haplotype C-G-G-C-G of five SNPs within ELAC2 was found in this group. Combining high-risk genotypes of MSR1 and ELAC2 in Caucasians and of RNASEL and MSR1 in Hispanics showed synergistic effects and suggest that an interaction between both genes in each ethnicity is likely to confer prostate cancer risk. Our findings corroborate the involvement of ELAC2, MSR1, and RNASEL in the etiology of prostate cancer even in individuals without a family history.

Single and multigenic analysis of the association between variants in 12 steroid hormone metabolism genes and risk of prostate cancer.

To estimate the prostate cancer risk conferred by individual single nucleotide polymorphisms (SNPs), SNP-SNP interactions, and/or cumulative SNP effects, we evaluated the association between prostate cancer risk and the genetic variants of 12 key genes within the steroid hormone pathway (CYP17, HSD17B3, ESR1, SRD5A2, HSD3B1, HSD3B2, CYP19, CYP1A1, CYP1B1, CYP3A4, CYP27B1, and CYP24A1). A total of 116 tagged SNPs covering the group of genes were analyzed in 2,452 samples (886 cases and 1,566 controls) in three ethnic/racial groups. Several SNPs within CYP19 were significantly associated with prostate cancer in all three ethnicities (P = 0.001-0.009). Genetic variants within HSD3B2 and CYP24A1 conferred increased risk of prostate cancer in non-Hispanic or Hispanic Caucasians. A significant gene-dosage effect for increasing numbers of potential high-risk genotypes was found in non-Hispanic and Hispanic Caucasians. Higher-order interactions showed a seven-SNP interaction involving HSD17B3, CYP19, and CYP24A1 in Hispanic Caucasians (P = 0.001). In African Americans, a 10-locus model, with SNPs located within SRD5A2, HSD17B3, CYP17, CYP27B1, CYP19, and CYP24A1, showed a significant interaction (P = 0.014). In non-Hispanic Caucasians, an interaction of four SNPs in HSD3B2, HSD17B3, and CYP19 was found (P < 0.001). These data are consistent with a polygenic model of prostate cancer, indicating that multiple interacting genes of the steroid hormone pathway confer increased risk of prostate cancer.