Notch signaling pathway: a comprehensive prognostic and gene expression profile analysis in breast cancer

Yousefi, Hassan; Bahramy, Afshin; Zafari, Narges; Delavar, Mohsen Rostamian; Nguyen, Khoa; Haghi, Atousa; Kandelouei, Tahmineh; Vittori, Cecilia; Jazireian, Parham; Maleki, Sajad; Imani, Danyal; Moshksar, Amin; Bitaraf, Amirreza; Babashah, Sadegh

doi:10.1186/s12885-022-10383-z

Cited by 28 publications

(12 citation statements)

References 140 publications

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“…17). The prognostic and regualtory role of Notch signaling pathway in breast cancer has been recently addressed [You+22; Cra+22]. Notch1 signaling encompasses a wide range of functions in determining cell fate, cell proliferation, and apoptosis [Art88; LK06].…”

Section: Resultsmentioning

confidence: 99%

Weighted Centroid Trees: A general approach for summarizing phylogenies in tumor mutation tree inference

Vasei,

Foroughmand Araabi,

Daneshgar

2023

Preprint

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Tumor mutation trees are the primary tools to model the evolution of cancer. Not only some tumor phylogeny inference methods may produce a set of trees having potential and parallel evolutionary histories, but also mutation trees from different patients may also exhibit similar evolutionary processes. When a set of correlated mutation trees is available, compressing the data into a single best-fit tree, exhibiting the shared evolutionary processes, is definitely of great importance and can be beneficial in many applications. In this study, we present a general setup to study and analyse the problem of finding a best-fit (centroid) tree to a given set of trees and we use our general setup to analyse mutation trees as our main motivation. For this letε:Tn→ ℝn×nbe an embedding of labeled rooted trees into the space of real square matrices and also letLbe a norm on this space. We introduce thenearest mapped treeproblem as the problem of finding a closest tree to a given matrix A with respect toεandL, i.e., a treeT*(A) for whichL(ε(T*(A)) − A) is minimized. Within this setup, our potential candidates for the embedding areadjacency,ancestry, anddistancematrices of trees, where we consider the cases ofL1andL2norms in our analysis. We show that the function d(T1,T2) =L(ε(T1) −ε(T2)) defines a family of dissimilarity measures, covering previously studiedparent-childandancestor-descendentmetrics. Also, we show that the nearest mapped tree problem is polynomial-time solvable for the adjacency matrix embedding and is 𝒩𝒫-hard for the ancestry and the distance embeddings. Theweighted centroid tree problemfor a given set of trees of sizekis naturally defined as a nearest mapped tree solution to a weighted sum of the corresponding matrix set. In this article we consider uniform weighted-sums for which all weights are equal, where in particular, the (classical)centroid treeis defined to be a solution when all weights are chosen to be equal to 1/k(i.e., the mean case). Similarly, theω-weighted centroid tree is a solution when all weights are equal toω/k. To show the generality of our setup, we prove that the solution-set of the centroid tree problem for the adjacency and the ancestry matrices are identical to the solution-set of theconsensus tree problemfor parent-child and ancestor-descendent distances already handled by the algorithms GraPhyC(2018) and TuELiP(2023), respectively. Next, to tackle this problem for some new cases, we provide integer linear programs to handle the nearest mapped tree problem for the ancestry and the distance embeddings, giving rise to solutions of the weighted centroid tree problem in these cases. To show the effectiveness of this approach, we provide an algorithm, WAncstILP2, to solve the 2-weighted centroid tree problem for the case of the ancestry matrix and we justify the importance of the weighted setup by showing the pioneering performance of WAncstILP2both in a comprehensive simulation analysis as well as on a real breast cancer dataset, in which, by finding the centroids as representatives of data clusters, we provide supporting evidence for the fact that some common aspects of these centroids can be considered as suitable candidates for reliable evolutionary information in relation to the original data. metrics.

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Section: Resultsmentioning

confidence: 99%

Weighted Centroid Trees: A general approach for summarizing phylogenies in tumor mutation tree inference

Vasei,

Foroughmand Araabi,

Daneshgar

2023

Preprint

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“…In our data, the NOTCH pathway was less frequently and abnormally activated in the CUPAx group, which might be associated with the hidden breast lesions in CUPAx. The classical NOTCH pathway was activated during normal breast evolution and maintains mammary development (Yousefi et al 2022 ; Chen et al 2021 ). Abnormal activation or mutation of NOTCH genes could result in the occurrence, progression, metastasis, and treatment resistance of breast cancer (Katoh et al 2020 ; Wang et al 2015 ).…”

Section: Discussionmentioning

confidence: 99%

Clinicopathologic features and genomic profiling of female axillary lymph node metastases from adenocarcinoma or poorly differentiated carcinoma of unknown primary

Tang,

Zhu,

et al. 2024

J Cancer Res Clin Oncol

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Purpose Axillary lymph node metastases from adenocarcinoma or poorly differentiated carcinoma of unknown primary (CUPAx) is a rare disease in women. This retrospective study intended to examine the clinicopathological features of CUPAx and compared CUPAx genetically with axillary lymph node metastases from breast cancer (BCAx), investigating differences in their biological behavior. Methods We conducted the clinical and prognostic analysis of 58 CUPAx patients in West China Hospital spanning from 2009 to 2021. Gemonic profiling of 12 CUPAx patients and 16 BCAx patients was conducted by the FoundationOne CDx (F1CDx) platform. Moreover, we also compared the gene mutation spectrum and relevant pathways between the two groups and both TCGA and COSMIC databases. Results The majority of the 58 CUPAx patients were HR-/HER2- subtype. Most patients received mastectomy combined radiotherapy (50 Gy/25f). CUPAx patients who received mastectomy instead of breast-conserving surgery had a more favorable overall prognosis. Radiotherapy in chest wall/breast and supraclavicular/infraclavicular fossa was the independent prognostic factor (HR = 0.05, 95%CI = 0.00–0.93, P = 0.04). In 28 sequencing samples (CUPAx, n = 12, BCAx, n = 16) and 401 TCGA-BRCA patients, IRS2 only mutated in CUPAx (33.33%) but amplified in BCAx (11.11%) and TCGA-BRCA (1.5%). Pathway analysis revealed that BCAx had more NOTCH pathway mutations than CUPAx. Enrichment analysis showed that CUPAx enriched more in mammary development and PML bodies than BCAx, but less in the positive regulation of kinase activity. Conclusions More active treatment methods, like chemotherapy, mastectomy and postoperative radiotherapy, could improve the prognosis of CUPAx. The differential mutation genes of CUPAx and BCAx might be associated with their respective biological behaviors like invasiveness and prognosis.

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“…Mammography has a variable rate of false positives ranging from 12% to 65%, which is responsible for the over-diagnosis of 31% of all breast cancer cases ( Nassar et al, 2017 ). Other imaging techniques such as MRI, ultrasound, CT, and PET are also accompanied by some limitations such as low sensitivity and specificity and being expensive ( Alyami, 2021 ; Su et al, 2021 ; Jin et al, 2021 ; Darbeheshti et al, 2022 ; Yousefi et al, 2022 ). As a result, it is deemed necessary to introduce new biomarkers that can overcome these limitations.…”

Section: Discussionmentioning

confidence: 99%

Prognostic and diagnostic values of non-coding RNAs as biomarkers for breast cancer: An umbrella review and pan-cancer analysis

Bahramy

Zafari

Rajabi

et al. 2023

Front. Mol. Biosci.

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Background: Breast cancer (BC) is the most common cancer in women. The incidence and morbidity of BC are expected to rise rapidly. The stage at which BC is diagnosed has a significant impact on clinical outcomes. When detected early, an overall 5-year survival rate of up to 90% is possible. Although numerous studies have been conducted to assess the prognostic and diagnostic values of non-coding RNAs (ncRNAs) in breast cancer, their overall potential remains unclear. In this field of study, there are various systematic reviews and meta-analysis studies that report volumes of data. In this study, we tried to collect all these systematic reviews and meta-analysis studies in order to re-analyze their data without any restriction to breast cancer or non-coding RNA type, to make it as comprehensive as possible.Methods: Three databases, namely, PubMed, Scopus, and Web of Science (WoS), were searched to find any relevant meta-analysis studies. After thoroughly searching, the screening of titles, abstracts, and full-text and the quality of all included studies were assessed using the AMSTAR tool. All the required data including hazard ratios (HRs), sensitivity (SENS), and specificity (SPEC) were extracted for further analysis, and all analyses were carried out using Stata.Results: In the prognostic part, our initial search of three databases produced 10,548 articles, of which 58 studies were included in the current study. We assessed the correlation of non-coding RNA (ncRNA) expression with different survival outcomes in breast cancer patients: overall survival (OS) (HR = 1.521), disease-free survival (DFS) (HR = 1.33), recurrence-free survival (RFS) (HR = 1.66), progression-free survival (PFS) (HR = 1.71), metastasis-free survival (MFS) (HR = 0.90), and disease-specific survival (DSS) (HR = 0.37). After eliminating low-quality studies, the results did not change significantly. In the diagnostic part, 22 articles and 30 datasets were retrieved from 8,453 articles. The quality of all studies was determined. The bivariate and random-effects models were used to assess the diagnostic value of ncRNAs. The overall area under the curve (AUC) of ncRNAs in differentiated patients is 0.88 (SENS: 80% and SPEC: 82%). There was no difference in the potential of single and combined ncRNAs in differentiated BC patients. However, the overall potential of microRNAs (miRNAs) is higher than that of long non-coding RNAs (lncRNAs). No evidence of publication bias was found in the current study. Nine miRNAs, four lncRNAs, and five gene targets showed significant OS and RFS between normal and cancer patients based on pan-cancer data analysis, demonstrating their potential prognostic value.Conclusion: The present umbrella review showed that ncRNAs, including lncRNAs and miRNAs, can be used as prognostic and diagnostic biomarkers for breast cancer patients, regardless of the sample sources, ethnicity of patients, and subtype of breast cancer.

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Notch signaling pathway: a comprehensive prognostic and gene expression profile analysis in breast cancer

Cited by 28 publications

References 140 publications

Weighted Centroid Trees: A general approach for summarizing phylogenies in tumor mutation tree inference

Weighted Centroid Trees: A general approach for summarizing phylogenies in tumor mutation tree inference

Clinicopathologic features and genomic profiling of female axillary lymph node metastases from adenocarcinoma or poorly differentiated carcinoma of unknown primary

Prognostic and diagnostic values of non-coding RNAs as biomarkers for breast cancer: An umbrella review and pan-cancer analysis

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