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Robust pathway sampling in phenotype prediction. Application to triple negative breast cancer.

ABSTRACT: BACKGROUND:Phenotype prediction problems are usually considered ill-posed, as the amount of samples is very limited with respect to the scrutinized genetic probes. This fact complicates the sampling of the defective genetic pathways due to the high number of possible discriminatory genetic networks involved. In this research, we outline three novel sampling algorithms utilized to identify, classify and characterize the defective pathways in phenotype prediction problems, such as the Fisher's ratio sampler, the Holdout sampler and the Random sampler, and apply each one to the analysis of genetic pathways involved in tumor behavior and outcomes of triple negative breast cancers (TNBC). Altered biological pathways are identified using the most frequently sampled genes and are compared to those obtained via Bayesian Networks (BNs). RESULTS:Random, Fisher's ratio and Holdout samplers were more accurate and robust than BNs, while providing comparable insights about disease genomics. CONCLUSIONS:The three samplers tested are good alternatives to Bayesian Networks since they are less computationally demanding algorithms. Importantly, this analysis confirms the concept of "biological invariance" since the altered pathways should be independent of the sampling methodology and the classifier used for their inference. Nevertheless, still some modifications are needed in the Bayesian networks to be able to sample correctly the uncertainty space in phenotype prediction problems, since the probabilistic parameterization of the uncertainty space is not unique and the use of the optimum network might falsify the pathways analysis.

SUBMITTER: Cernea A

PROVIDER: S-EPMC7068866 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Robust pathway sampling in phenotype prediction. Application to triple negative breast cancer.

Cernea Ana A Fernández-Martínez Juan Luis JL deAndrés-Galiana Enrique J EJ Fernández-Ovies Francisco Javier FJ Alvarez-Machancoses Oscar O Fernández-Muñiz Zulima Z Saligan Leorey N LN Sonis Stephen T ST

BMC bioinformatics 20200311 Suppl 2

<h4>Background</h4>Phenotype prediction problems are usually considered ill-posed, as the amount of samples is very limited with respect to the scrutinized genetic probes. This fact complicates the sampling of the defective genetic pathways due to the high number of possible discriminatory genetic networks involved. In this research, we outline three novel sampling algorithms utilized to identify, classify and characterize the defective pathways in phenotype prediction problems, such as the Fish ...[more]

PMID: 32164540

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Project description:IntroductionTriple-negative breast cancer (TNBC) is a heterogeneous disease with no definitive prognostic markers. As a major component of tight junctions, claudins (CLDNs) presumably play an important role in carcinogenesis and progression of breast cancer. This study was aimed at determining the relationship between the expression of CLDNs and the clinical outcomes of TNBCs.Materials and methodsThe surgical specimens of primary breast tumors from a consecutive cohort of 173 TNBC patients were retrospectively collected. The membranous expression of CLDN1, CLDN2, CLDN4, and CLDN7 was measured by immunohistochemistry. Then, the associations between CLDN expression, clinicopathological features, and clinical outcomes were assessed.ResultsPositive CLDN1, CLDN2, CLDN4, and CLDN7 membrane expression was detected in 44.5%, 54.9%, 76.9%, and 73.4% of the cohort specimens, respectively. A lack of CLDN1 expression was related to only lymph node metastasis (P?=?0.014). The rate of CLDN4-positive tumors was significantly increased in tumors of a higher grade (P?=?0.003). Importantly, negative CLDN1 expression was associated with worse relapse-free survival (RFS) in both lymph node positive (LN+) and negative (LN-) cases (both P<0.001). Similarly it was also associated with shorter overall survival (OS)(P?=?0.003 in LN+ cases; P?=?0.018 in LN- cases). In the LN+ subgroup, CLDN2-negative cases had a significantly higher risk of recurrence (P?=?0.008). Multivariate analysis revealed that negative CLDN1 expression was an independent prognostic factor for high risk of both recurrence and death (HR 5.529, 95% CI 2.664-11.475, P<0.001; HR 3.459, 95% CI 1.555-7.696, P?=?0.002). However, neither CLDN4 nor CLDN7 expression was associated with survival.ConclusionIn TNBC, the CLDN1-negative phenotype predicts a high risk of recurrence and death. The absence of CLDN1 expression is strongly suggested to be an independent adverse prognostic factor in this heterogeneous subtype of breast cancer.

Project description:Microglandular adenosis (MGA) is a rare proliferative lesion of the breast composed of small glands lacking myoepithelial cells and lined by S100-positive, oestrogen receptor (ER)-negative, progesterone receptor (PR)-negative, and HER2-negative epithelial cells. There is evidence to suggest that MGA may constitute a non-obligate precursor of triple-negative breast cancer (TNBC). We sought to define the genomic landscape of pure MGA and of MGA, atypical MGA (AMGA) and associated TNBCs, and to determine whether synchronous MGA, AMGA, and TNBCs would be clonally related. Two pure MGAs and eight cases of MGA and/or AMGA associated with in situ or invasive TNBC were collected, microdissected, and subjected to massively parallel sequencing targeting all coding regions of 236 genes recurrently mutated in breast cancer or related to DNA repair. Pure MGAs lacked clonal non-synonymous somatic mutations and displayed limited copy number alterations (CNAs); conversely, all MGAs (n = 7) and AMGAs (n = 3) associated with TNBC harboured at least one somatic non-synonymous mutation (range 3-14 and 1-10, respectively). In all cases where TNBCs were analyzed, identical TP53 mutations and similar patterns of gene CNAs were found in the MGA and/or AMGA and in the associated TNBC. In the MGA/AMGA associated with TNBC lacking TP53 mutations, somatic mutations affecting PI3K pathway-related genes (eg PTEN, PIK3CA, and INPP4B) and tyrosine kinase receptor signalling-related genes (eg ERBB3 and FGFR2) were identified. At diagnosis, MGAs associated with TNBC were found to display subclonal populations, and clonal shifts in the progression from MGA to AMGA and/or to TNBC were observed. Our results demonstrate the heterogeneity of MGAs, and that MGAs associated with TNBC, but not necessarily pure MGAs, are genetically advanced, clonal, and neoplastic lesions harbouring recurrent mutations in TP53 and/or other cancer genes, supporting the notion that a subset of MGAs and AMGAs may constitute non-obligate precursors of TNBCs.

Dataset Information

Robust pathway sampling in phenotype prediction. Application to triple negative breast cancer.

Publications

Robust pathway sampling in phenotype prediction. Application to triple negative breast cancer.

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