Machine learning unveils an immune-related DNA methylation profile in germline DNA from breast cancer patients.

BACKGROUND: There is an unmet need for precise biomarkers for early non-invasive breast cancer detection. Here, we aimed to identify blood-based DNA methylation biomarkers that are associated with breast cancer. METHODS: DNA methylation profiling was performed for 524 Asian Chinese individuals, comprising 256 breast cancer patients and 268 age-matched healthy controls, using the Infinium MethylationEPIC array. Feature selection was applied to 649,688 CpG sites in the training set. Predictive models were built by training three machine learning models, with performance evaluated on an independent test set. Enrichment analysis to identify transcription factors binding to regions associated with the selected CpG sites and pathway analysis for genes located nearby were conducted. RESULTS: A methylation profile comprising 51 CpGs was identified that effectively distinguishes breast cancer patients from healthy controls achieving an AUC of 0.823 on an independent test set. Notably, it outperformed all four previously reported breast cancer-associated methylation profiles. Enrichment analysis revealed enrichment of genomic loci associated with the binding of immune modulating AP-1 transcription factors, while pathway analysis of nearby genes showed an overrepresentation of immune-related pathways. CONCLUSION: This study has identified a breast cancer-associated methylation profile that is immune-related to potential for early cancer detection.

Alleviating misclassified germline variants in underrepresented populations: A strategy using popmax.

PURPOSE: Germline variant interpretation often depends on population-matched control cohorts. This is not feasible for population groups that are underrepresented in current population reference databases. METHODS: We classify germline variants with population-matched controls for 2 ancestrally diverse cohorts of patients: 132 early-onset or familial colorectal carcinoma patients from Singapore and 100 early-onset colorectal carcinoma patients from the United States. The effects of using a population-mismatched control cohort are simulated by swapping the control cohorts used for each patient cohort, with or without the popmax computational strategy. RESULTS: Population-matched classifications revealed a combined 62 pathogenic or likely pathogenic (P/LP) variants in 34 genes across both cohorts. Using a population-mismatched control cohort resulted in misclassification of non-P/LP variants as P/LP, driven by the absence of ancestry-specific rare variants in the control cohort. Popmax was more effective in alleviating misclassifications for the Singapore cohort than the US cohort. CONCLUSION: Underrepresented population groups can suffer from higher rates of false-positive P/LP results. Popmax can partially alleviate these misclassifications, but its efficacy still depends on the degree with which the population groups are represented in the control cohort.

Degradation of methylation signals in cryopreserved DNA.

BACKGROUND: Blood-based DNA methylation has shown great promise as a biomarker in a wide variety of diseases. Studies of DNA methylation in blood often utilize samples which have been cryopreserved for years or even decades. Therefore, changes in DNA methylation associated with long-term cryopreservation can introduce biases or otherwise mislead methylation analyses of cryopreserved DNA. However, previous studies have presented conflicting results with studies reporting hypomethylation, no effect, or even hypermethylation of DNA following long-term cryopreservation. These studies may have been limited by insufficient sample sizes, or by their profiling of methylation only on an aggregate global scale, or profiling of only a few CpGs. RESULTS: We analyzed two large prospective cohorts: a discovery (n = 126) and a validation (n = 136) cohort, where DNA was cryopreserved for up to four years. In both cohorts there was no detectable change in mean global methylation across increasing storage durations as DNA. However, when analysis was performed on the level of individual CpG methylation both cohorts exhibited a greater number of hypomethylated than hypermethylated CpGs at q-value < 0.05 (4049 hypomethylated but only 50 hypermethylated CpGs in discovery, and 63 hypomethylated but only 6 hypermethylated CpGs in validation). The results were the same even after controlling for age, storage duration as buffy coat prior to DNA extraction, and estimated cell type composition. Furthermore, we find that in both cohorts, CpGs have a greater likelihood to be hypomethylated the closer they are to a CpG island; except for CpGs at the CpG islands themselves which are less likely to be hypomethylated. CONCLUSION: Cryopreservation of DNA after a few years results in a detectable bias toward hypomethylation at the level of individual CpG methylation, though when analyzed in aggregate there is no detectable change in mean global methylation. Studies profiling methylation in cryopreserved DNA should be mindful of this hypomethylation bias, and more attention should be directed at developing more stable methods of DNA cryopreservation for biomedical research or clinical use.

Landscape of germline pathogenic variants in patients with dual primary breast and lung cancer.

BACKGROUND: Cancer predisposition is most often studied in the context of single cancers. However, inherited cancer predispositions can also give rise to multiple primary cancers. Yet, there is a paucity of studies on genetic predisposition in multiple primary cancers, especially those outside of well-defined cancer predisposition syndromes. This study aimed to identify germline variants associated with dual primary cancers of the breast and lung. METHODS: Exome sequencing was performed on germline DNA from 55 Singapore patients (52 [95%] never-smokers) with dual primaries in the breast and lung, confirmed by histopathology. Using two large control cohorts: the local SG10K_Health (n = 9770) and gnomAD non-cancer East Asians (n = 9626); and two additional local case cohorts of early-onset or familial breast cancer (n = 290), and lung cancer (n = 209), variants were assessed for pathogenicity in accordance with ACMG/AMP guidelines. In particular, comparisons were made with known pathogenic or likely pathogenic variants in the ClinVar database, pathogenicity predictions were obtained from in silico prediction software, and case-control association analyses were performed. RESULTS: Altogether, we identified 19 pathogenic or likely pathogenic variants from 16 genes, detected in 17 of 55 (31%) patients. Six of the 19 variants were identified using ClinVar, while 13 variants were classified pathogenic or likely pathogenic using ACMG/AMP guidelines. The 16 genes include well-known cancer predisposition genes such as BRCA2, TP53, and RAD51D; but also lesser known cancer genes EXT2, WWOX, GATA2, and GPC3. Most of these genes are involved in DNA damage repair, reaffirming the role of impaired DNA repair mechanisms in the development of multiple malignancies. These variants warrant further investigations in additional populations. CONCLUSIONS: We have identified both known and novel variants significantly enriched in patients with primary breast and lung malignancies, expanding the body of known cancer predisposition variants for both breast and lung cancer. These variants are mostly from genes involved in DNA repair, affirming the role of impaired DNA repair in the predisposition and development of multiple cancers.

Whole-exome sequencing of BRCA-negative breast cancer patients and case-control analyses identify variants associated with breast cancer susceptibility.

BACKGROUND: For the majority of individuals with early-onset or familial breast cancer referred for genetic testing, the genetic basis of their familial breast cancer remains unexplained. To identify novel germline variants associated with breast cancer predisposition, whole-exome sequencing (WES) was performed. METHODS: WES on 290 BRCA1/BRCA2-negative Singaporeans with early-onset breast cancer and/or a family history of breast cancer was done. Case-control analysis against the East-Asian subpopulation (EAS) from the Genome Aggregation Database (gnomAD) identified variants enriched in cases, which were further selected by occurrence in cancer gene databases. Variants were further evaluated in repeated case-control analyses using a second case cohort from the database of Genotypes and Phenotypes (dbGaP) comprising 466 early-onset breast cancer patients from the United States, and a Singapore SG10K_Health control cohort. RESULTS: Forty-nine breast cancer-associated germline pathogenic variants in 37 genes were identified in Singapore cases versus gnomAD (EAS). Compared against SG10K_Health controls, 13 of 49 variants remain significantly enriched (False Discovery Rate (FDR)-adjusted p < 0.05). Comparing these 49 variants in dbGaP cases against gnomAD (EAS) and SG10K_Health controls revealed 23 concordant variants that were significantly enriched (FDR-adjusted p < 0.05). Fourteen variants were consistently enriched in breast cancer cases across all comparisons (FDR-adjusted p < 0.05). Seven variants in GPRIN2, NRG1, MYO5A, CLIP1, CUX1, GNAS and MGA were confirmed by Sanger sequencing. CONCLUSIONS: In conclusion, we have identified pathogenic variants in genes associated with breast cancer predisposition. Importantly, many of these variants were significant in a second case cohort from dbGaP, suggesting that the strategy of using case-control analysis to select variants could potentially be utilized for identifying variants associated with cancer susceptibility.

Germline Variants Associated with Nasopharyngeal Carcinoma Predisposition Identified through Whole-Exome Sequencing.

The current understanding of genetic susceptibility factors for nasopharyngeal carcinoma (NPC) is still incomplete. To identify novel germline variants associated with NPC predisposition, we analysed whole-exome sequencing data from 119 NPC patients from Singapore with a family history of NPC and/or with early-onset NPC, together with 1337 Singaporean participants without NPC. Variants were prioritised and filtered by selecting variants with minor allele frequencies of <1% in both local control (n = 1337) and gnomAD non-cancer (EAS) (n = 9626) cohorts and a high pathogenicity prediction (CADD score > 20). Using single-variant testing, we identified 17 rare pathogenic variants in 17 genes that were associated with NPC. Consistent evidence of enrichment in NPC patients was observed for five of these variants (in JAK2, PRDM16, LRP1B, NIN, and NKX2-1) from an independent case-control comparison of 156 NPC patients and 9770 unaffected individuals. In a family with five siblings, a FANCE variant (p. P445S) was detected in two affected members, but not in three unaffected members. Gene-based burden testing recapitulated variants in NKX2-1 and FANCE as being associated with NPC risk. Using pathway analysis, endocytosis and immune-modulating pathways were found to be enriched for mutation burden. This study has identified NPC-predisposing variants and genes which could shed new insights into the genetic predisposition of NPC.

An accessible, open-source mobile application for macromolecular visualization using augmented reality.

Understanding macromolecular structures is essential for biology education. Augmented reality (AR) applications have shown promise in science, technology, engineering, and mathematics (STEM) education, but are not widely used for protein visualization. While there are some tools for AR protein visualization, none of them are accessible to the layperson who possesses neither specialized AR hardware nor the technical skill to comfortably navigate three-dimensional (3D) rendering and file conversions. Here, we describe Palantir, an open source mobile Android application easily installable on compatible devices from the Google Play Store. Palantir does not require specialized hardware, printed image, manual 3D rendering, or file format conversion. Palantir makes AR macromolecular visualization accessible to anyone with a compatible mobile device, and we hope it finds widespread application in STEM education.