Evaluation of cfDNA as an early detection assay for dense tissue breast cancer

Bibliometric analysis of phosphoglycerate kinase 1 expression in breast cancer and its distinct upregulation in triple-negative breast cancer

BACKGROUND

Phosphoglycerate kinase 1 (PGK1) has been identified as a possible biomarker for breast cancer (BC) and may play a role in the development and advancement of triple-negative BC (TNBC).

AIM

To explore the PGK1 and BC research status and PGK1 expression and mechanism differences among TNBC, non-TNBC, and normal breast tissue.

METHODS

PGK1 and BC related literature was downloaded from Web of Science Core Collection Core Collection. Publication counts, key-word frequency, cooperation networks, and theme trends were analyzed. Normal breast, TNBC, and non-TNBC mRNA data were gathered, and differentially expressed genes obtained. Area under the summary receiver operating characteristic curves, sensitivity and specificity of PGK1 expression were determined. Kaplan Meier revealed PGK1's prognostic implication. PGK1 co-expressed genes were explored, and Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Disease Ontology applied. Protein-protein interaction networks were constructed. Hub genes identified.

RESULTS

PGK1 and BC related publications have surged since 2020, with China leading the way. The most frequent keyword was "Expression". Collaborative networks were found among co-citations, countries, institutions, and authors. PGK1 expression and BC progression were research hotspots, and PGK1 expression and BC survival were research frontiers. In 16 TNBC vs non-cancerous breast and 15 TNBC vs non-TNBC datasets, PGK1 mRNA levels were higher in 1159 TNBC than 1205 non-cancerous breast cases [standardized mean differences (SMD): 0.85, 95% confidence interval (95%CI): 0.54-1.16, I² = 86%, P < 0.001]. PGK1 expression was higher in 1520 TNBC than 7072 non-TNBC cases (SMD: 0.25, 95%CI: 0.03-0.47, I² = 91%, P = 0.02). Recurrence free survival was lower in PGK1-high-expression than PGK1-low-expression group (hazard ratio: 1.282, P = 0.023). PGK1 co-expressed genes were concentrated in ATP metabolic process, HIF-1 signaling, and glycolysis/gluconeogenesis pathways.

CONCLUSION

PGK1 expression is a research hotspot and frontier direction in the BC field. PGK1 may play a strong role in promoting cancer in TNBC by mediating metabolism and HIF-1 signaling pathways.

Use of ctDNA in early breast cancer: analytical validity and clinical potential

Circulating free tumor DNA (ctDNA) analysis is gaining popularity in precision oncology, particularly in metastatic breast cancer, as it provides non-invasive, real-time tumor information to complement tissue biopsies, allowing for tailored treatment strategies and improved patient selection in clinical trials. Its use in early breast cancer has been limited so far, due to the relatively low sensitivity of available techniques in a setting characterized by lower levels of ctDNA shedding. However, advances in sequencing and bioinformatics, as well as the use of methylome profiles, have led to an increasing interest in the application of ctDNA analysis in early breast cancer, from screening to curative treatment evaluation and minimal residual disease (MRD) detection. With multiple prospective clinical trials in this setting, ctDNA evaluation may become useful in clinical practice. This article reviews the data regarding the analytical validity of the currently available tests for ctDNA detection and the clinical potential of ctDNA analysis in early breast cancer.

Enhancer regulatory networks globally connect non-coding breast cancer loci to cancer genes

Genetic studies have associated thousands of enhancers with breast cancer. However, the vast majority have not been functionally characterized. Thus, it remains unclear how variant-associated enhancers contribute to cancer. Here, we perform single-cell CRISPRi screens of 3,512 regulatory elements associated with breast cancer to measure the impact of these regions on transcriptional phenotypes. Analysis of >500,000 single-cell transcriptomes in two breast cancer cell lines shows that perturbation of variant-associated enhancers disrupts breast cancer gene programs. We observe variant-associated enhancers that directly or indirectly regulate the expression of cancer genes. We also find one-to-multiple and multiple-to-one network motifs where enhancers indirectly regulate cancer genes. Notably, multiple variant-associated enhancers indirectly regulate TP53. Comparative studies illustrate sub-type specific functions between enhancers in ER+ and ER- cells. Finally, we developed the pySpade package to facilitate analysis of single-cell enhancer screens. Overall, we demonstrate that enhancers form regulatory networks that link cancer genes in the genome, providing a more comprehensive understanding of the contribution of enhancers to breast cancer development.

Variant Characterization of a Representative Large Pedigree Suggests "Variant Risk Clusters" Convey Varying Predisposition of Risk to Lynch Syndrome

Recently, worldwide incidences of young adult aggressive colorectal cancer (CRC) have rapidly increased. Of these incidences diagnosed as familial Lynch syndrome (LS) CRC, outcomes are extremely poor. In this study, we seek novel familial germline variants from a large pedigree Tunisian family with 12 LS-affected individuals to identify putative germline variants associated with varying risk of LS. Whole-genome sequencing analysis was performed to identify known and novel germline variants shared between affected and non-affected pedigree members. SNPs, indels, and structural variants (SVs) were computationally identified, and their oncological influence was predicted using the Genetic Association of Complex Diseases and Disorders, OncoKB, and My Cancer Genome databases. Of 94 germline familial variants identified with predicted functional impact, 37 SNPs/indels were detected in 28 genes, 2 of which (MLH1 and PRH1-TAS2R14) have known association with CRC and 4 others (PPP1R13B, LAMA5, FTO, and NLRP14) have known association with non-CRC cancers. In addition, 48 of 57 identified SVs overlap with 43 genes. Three of these genes (RELN, IRS2, and FOXP1) have a known association with non-CRC digestive cancers and one (RRAS2) has a known association with non-CRC cancer. Our study identified 83 novel, predicted functionally impactful germline variants grouped in three "variant risk clusters" shared in three familiarly associated LS groups (high, intermediate and low risk). This variant characterization study demonstrates that large pedigree investigations provide important evidence supporting the hypothesis that different "variant risk clusters" can convey different mechanisms of risk and oncogenesis of LS-CRC even within the same pedigree.