Integrating a Polygenic Risk Score into a clinical setting would impact risk predictions in familial breast cancer

Clinical genome sequencing in patients with hereditary breast and ovarian cancer: Concept, implementation and benefits

Hereditary breast and ovarian cancer (HBOC) is one of the most frequent genetic cancer predisposition syndromes. Individuals at risk are identified mainly by family history and histopathological criteria. The current standard genetic testing is exome or panel sequencing. However, many high-risk families remain genetically unexplained. Genome sequencing has the potential to increase the diagnostic yield. This single-center real-world study aims to evaluate advantages of short-read genome sequencing (GS) in HBOC families. We report genome sequencing results of 818 index patients, who fulfilled clinical criteria for genetic testing. Data analysis showed less sequencing gaps and a more uniform coverage compared to a large cohort of in-house exomes. Samples were sequenced at an average depth of 41.2x for the HBOC core genes. Pathogenic variants were found in 9 of 13 core genes in 12.2 % of the patients. GS allowed the classification of a BRCA1 duplication and detected a whole-exon inversion in BARD1, as well as a deep intronic CHEK2 variant. Furthermore, we successfully used the BRIDGES-PRS in our HBOC cohort and found a significant effect size compared to the control cohort (p = 4.804-14, Cohen's-D: 0.476), proving the transferability to a German cohort. GS offers a wealth of information, including the improved detection of structural variants, copy number variants, and parallel detection of complex genetic markers. This has the potential for future analyses, including intronic and intergenic regions. Finally, it also allows for a more streamlined process by converging several tests into one. The approach presented will give guidance for the implementation of GS in HBOC diagnostics.

Efficient blockLASSO for polygenic scores with applications to all of us and UK Biobank

We develop a "block" LASSO (blockLASSO) approach for training polygenic scores (PGS) and demonstrate its use in All of Us (AoU) and the UK Biobank (UKB). blockLASSO utilizes the approximate block diagonal structure (due to chromosomal partition of the genome) of linkage disequilibrium (LD). The new implementation can be used for exploratory and methods research where repeated PGS training is necessary and expensive. For 11 different phenotypes, in two different biobanks, and across 5 different ancestry groups (African, American, East Asian, European, and South Asian) - we demonstrate that blockLASSO is generally as effective for training PGS as a (global) LASSO. Previous work has shown penalized regression methods produce competitive PGS to alternative approaches. It has been shown that some phenotypes are more/less polygenic than others. Using sparse algorithms, an accurate PGS can be trained for type 1 diabetes (T1D) using ∼ 100 single nucleotide variants (SNVs), but a PGS for body mass index (BMI) would need more than 10k SNVs. blockLASSO produces similar PGS for phenotypes while training with just a fraction of the variants per block. Within AoU (using only genetic information) block PGS for T1D reaches an AUC of 0 . 63 ± 0.02 and for BMI a correlation of 0 . 21 ± 0.01 , whereas a global LASSO approach which finds for T1D an AUC 0 . 65 ± 0.03 and BMI a correlation 0 . 19 ± 0.03 . This new block approach is more computationally efficient and scalable than naive global machine learning approaches and makes it ideal for exploratory methods investigations based on penalized regression.

Gender-Specific Genetic Predisposition to Breast Cancer: BRCA Genes and Beyond

Among neoplastic diseases, breast cancer (BC) is one of the most influenced by gender. Despite common misconceptions associating BC as a women-only disease, BC can also occur in men. Additionally, transgender individuals may also experience BC. Genetic risk factors play a relevant role in BC predisposition, with important implications in precision prevention and treatment. The genetic architecture of BC susceptibility is similar in women and men, with high-, moderate-, and low-penetrance risk variants; however, some sex-specific features have emerged. Inherited high-penetrance pathogenic variants (PVs) in BRCA1 and BRCA2 genes are the strongest BC genetic risk factor. BRCA1 and BRCA2 PVs are more commonly associated with increased risk of female and male BC, respectively. Notably, BRCA-associated BCs are characterized by sex-specific pathologic features. Recently, next-generation sequencing technologies have helped to provide more insights on the role of moderate-penetrance BC risk variants, particularly in PALB2, CHEK2, and ATM genes, while international collaborative genome-wide association studies have contributed evidence on common low-penetrance BC risk variants, on their combined effect in polygenic models, and on their role as risk modulators in BRCA1/2 PV carriers. Overall, all these studies suggested that the genetic basis of male BC, although similar, may differ from female BC. Evaluating the genetic component of male BC as a distinct entity from female BC is the first step to improve both personalized risk assessment and therapeutic choices of patients of both sexes in order to reach gender equality in BC care. In this review, we summarize the latest research in the field of BC genetic predisposition with a particular focus on similarities and differences in male and female BC, and we also discuss the implications, challenges, and open issues that surround the establishment of a gender-oriented clinical management for BC.

Cuproptosis-related lncRNA SNHG16 as a biomarker for the diagnosis and prognosis of head and neck squamous cell carcinoma

Background

We aim to investigate the potential value of cuproptosis-related lncRNA signaling in predicting clinical prognosis and immunotherapy and its relationship with drug sensitivity in head and neck squamous cell carcinoma (HNSCC).

Methods

We first identified the lncRNAs associated with cuproptosis genes in HNSCC and then conducted a series of analytical studies to investigate the expression and prognostic significance of these lncRNAs. Finally, we used RT-qPCR to validate our findings in a laryngeal squamous cell carcinoma cell line and 12 pairs of laryngeal squamous cell carcinoma and adjacent normal tissues.

Results

We identified 11 differentially expressed lncRNAs that were associated with cuproptosis genes in HNSCC and also served as prognostic markers for this cancer. Enrichment analysis revealed that these lncRNAs were related to immune-related functions that were suppressed in patients with oncogene mutations in the high-risk group. The patients with a high tumor mutation burden exhibited poor overall survival (OS). We used the tumor immune dysfunction and exclusion model to show that the patients in the high-risk group had great potential for immune evasion and less effective immunotherapy. We also identified several drugs that could be effective in treating HNSCC. Experimental validation showed that AC090587.1 and AC012184.3 exhibited differential expression between the TU686 and HBE cell lines, and SNHG16 showed differential expression among the TU686, TU212, and control HBE cells. Among the 12 pairs of cancer and adjacent tissues collected in the clinic, only SNHG16 showed differential expression. Targeted therapy against SNHG16 holds promise as a prospective novel strategy for the clinical management of HNSCC.