Breast cancer heterogeneity and its implication in personalized precision therapy

Guo, Liantao; Kong, Deguang; Liu, Jianhua; Zhan, Ling; Luo, Lan; Zheng, Weijie; Zheng, Qingyuan; Chen, Chuang; Sun, Shengrong

doi:10.1186/s40164-022-00363-1

Cited by 94 publications

(54 citation statements)

References 307 publications

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“…These discrepancies may arise from differences in target species, experimental design, or methodologies. It is essential to consider that breast cancer is a heterogeneous disease with various subtypes and stages [ 59 , 60 ], and its interaction with the gut microbiota may vary depending on these factors. Reduced colonization resistance has been linked to a decrease in diversity of microbial species within the microbiota in other systems [ 61 , 62 ].…”

Section: Discussionmentioning

confidence: 99%

Exploring the impact of breast cancer on colonization resistance of mouse microbiota using network node manipulation

Wu-Chuang,

Mateos-Hernandez,

Abuin-Denis

et al. 2024

Heliyon

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Section: Discussionmentioning

confidence: 99%

Exploring the impact of breast cancer on colonization resistance of mouse microbiota using network node manipulation

Wu-Chuang,

Mateos-Hernandez,

Abuin-Denis

et al. 2024

Heliyon

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“…Clonal evolution of a dominant or resistant clone is a potential mechanism for malignant spread and treatment resistance. Besides intratumor heterogeneity, breast cancer also shows increased intertumor heterogeneity among tumor tissues of different patients or different metastases ( 76 ). Changes in the genome, epigenome, transcriptome, and proteome heterogeneity can be reflected in various aspects of BRCA development, resistance to therapy and metastasis, such as biomarkers, metabolism, cell cycle, tumor microenvironment (TME), epithelial–mesenchymal transition (EMT), circulating tumor cells (CTCs), and clinical pathology.…”

Section: Discussionmentioning

confidence: 99%

KDM7A-DT induces genotoxic stress, tumorigenesis, and progression of p53 missense mutation-associated invasive breast cancer

Giannakakis,

Tsifintaris,

Gouzouasis

et al. 2024

Front. Oncol.

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Stress-induced promoter-associated and antisense lncRNAs (si-paancRNAs) originate from a reservoir of oxidative stress (OS)-specific promoters via RNAPII pausing-mediated divergent antisense transcription. Several studies have shown that the KDM7A divergent transcript gene (KDM7A-DT), which encodes a si-paancRNA, is overexpressed in some cancer types. However, the mechanisms of this overexpression and its corresponding roles in oncogenesis and cancer progression are poorly understood. We found that KDM7A-DT expression is correlated with highly aggressive cancer types and specific inherently determined subtypes (such as ductal invasive breast carcinoma (BRCA) basal subtype). Its regulation is determined by missense TP53 mutations in a subtype-specific context. KDM7A-DT transcribes several intermediate-sized ncRNAs and a full-length transcript, exhibiting distinct expression and localization patterns. Overexpression of KDM7A-DT upregulates TP53 protein expression and H2AX phosphorylation in nonmalignant fibroblasts, while in semi-transformed fibroblasts, OS superinduces KDM7A-DT expression in a TP53-dependent manner. KDM7A-DT knockdown and gene expression profiling in TP53-missense mutated luminal A BRCA variant, where it is abundantly expressed, indicate its significant role in cancer pathways. Endogenous over-expression of KDM7A-DT inhibits DNA damage response/repair (DDR/R) via the TP53BP1-mediated pathway, reducing apoptosis and promoting G2/M checkpoint arrest. Higher KDM7A-DT expression in BRCA is associated with KDM7A-DT locus gain/amplification, higher histologic grade, aneuploidy, hypoxia, immune modulation scores, and activation of the c-myc pathway. Higher KDM7A-DT expression is associated with relatively poor survival outcomes in patients with luminal A or Basal subtypes. In contrast, it is associated with favorable outcomes in patients with HER2+ER- or luminal B subtypes. KDM7A-DT levels are coregulated with critical transcripts and proteins aberrantly expressed in BRCA, including those involved in DNA repair via non-homologous end joining and epithelial-to-mesenchymal transition pathway. In summary, KDM7A-DT and its si-lncRNA exhibit several intrinsic biological and clinical characteristics that suggest important roles in invasive BRCA and its subtypes. KDM7A-DT-defined mRNA and protein subnetworks offer resources for identifying clinically relevant RNA-based signatures and prospective targets for therapeutic intervention.

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“…We expect these approaches to be most impactful in mutationally heterogeneous cancers, such as breast cancer, where heterogeneity challenges early diagnosis, treatment selection and prognosis prediction (46). The ultimate goal of computational systems biology approaches such as the one presented here is to enable personalised medicine by using models to get the right drugs to the right patients.…”

Section: Discussionmentioning

confidence: 99%

Patient-specific computational models predict prognosis in B cell lymphoma by quantifying pro-proliferative and anti-apoptotic signatures from genetic sequencing data

Norris

Jones

Mancini

et al. 2023

Preprint

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Genetic heterogeneity and co-occurring driver mutations contribute to poor clinical outcomes in cancer. However, the impact of multiple mutations on complex signalling networks is not easily predicted. We found that, by placing mutations into their cellular context, multi-scale agent-based mathematical models could predict how genetic events combine in haematological malignancies. Simulations of lymphoma and myeloma predicted co-occurring mutations synergised to increase tumour cell expansion beyond what would be expected from the impact of the individual mutations alone. Mutational synergy between MYC and BCL2 was consistent with the more aggressive disease course of patients with double-hit lymphoma, and mutational synergy between MCL1 and CKS1B was predictive of outcome in patients with gain 1q multiple myeloma. Incorporating patient-specific mutational profiles into personalised models of lymphoma patients with the worst clinical outcomes revealed a correlation between simulated mutational synergy and overall survival, which outperformed widely used classifications of lymphoma informed by gene expression or mutational data alone. Our results demonstrated that mutational synergy scores enabled prediction of the impact of co-occurring mutations and may improve personalised prognostic predictions.

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Breast cancer heterogeneity and its implication in personalized precision therapy

Cited by 94 publications

References 307 publications

Exploring the impact of breast cancer on colonization resistance of mouse microbiota using network node manipulation

Exploring the impact of breast cancer on colonization resistance of mouse microbiota using network node manipulation

KDM7A-DT induces genotoxic stress, tumorigenesis, and progression of p53 missense mutation-associated invasive breast cancer

Patient-specific computational models predict prognosis in B cell lymphoma by quantifying pro-proliferative and anti-apoptotic signatures from genetic sequencing data

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