TP53 germline pathogenic variants in modern humans were likely originated during recent human history

Pathogenic variants in human DNA damage repair genes mostly arose after the latest human out-of-Africa migration

Introduction

The DNA damage repair (DDR) system in human genome is pivotal in maintaining genomic integrity. Pathogenic variation (PV) in DDR genes impairs their function, leading to genome instability and increased susceptibility to diseases, especially cancer. Understanding the evolution origin and arising time of DDR PV is crucial for comprehending disease susceptibility in modern humans.

Methods

We used big data approach to identify the PVs in DDR genes in modern humans. We mined multiple genomic databases derived from 251,214 modern humans of African and non-Africans. We compared the DDR PVs between African and non-African. We also mined the DDR PVs in the genomic data derived from 5,031 ancient humans. We used the DDR PVs from ancient humans as the intermediate to further the DDR PVs between African and non-African.

Results and discussion

We identified 1,060 single-base DDR PVs across 77 DDR genes in modern humans of African and non-African. Direct comparison of the DDR PVs between African and non-African showed that 82.1% of the non-African PVs were not present in African. We further identified 397 single-base DDR PVs in 56 DDR genes in the 5,031 ancient humans dated between 45,045 and 100 years before present (BP) lived in Eurasian continent therefore the descendants of the latest out-of-Africa human migrants occurred 50,000-60,000 years ago. By referring to the ancient DDR PVs, we observed that 276 of the 397 (70.3%) ancient DDR PVs were exclusive in non-African, 106 (26.7%) were shared between non-African and African, and only 15 (3.8%) were exclusive in African. We further validated the distribution pattern by testing the PVs in BRCA and TP53, two of the important genes in genome stability maintenance, in African, non-African, and Ancient humans. Our study revealed that DDR PVs in modern humans mostly emerged after the latest out-of-Africa migration. The data provides a foundation to understand the evolutionary basis of disease susceptibility, in particular cancer, in modern humans.

Using Portuguese BRCA pathogenic variation as a model to study the impact of human admixture on human health

BACKGROUND

Admixture occurs between different ethnic human populations. The global colonization in recent centuries by Europeans led to the most significant admixture in human history. While admixture may enhance genetic diversity for better fitness, it may also impact on human health by transmitting genetic variants for disease susceptibility in the admixture population. The admixture by Portuguese global exploration initiated in the 15th century has reached over 20 million of Portuguese-heritage population worldwide. It provides a valuable model to study the impact of admixture on human health. BRCA1 and BRCA2 (BRCA) are two of the important tumor suppressor genes. The pathogenic variation (PV) in BRCA is well determined to cause high risk of hereditary breast and ovarian cancer. Tracing the distribution of Portuguese BRCA PV in Portuguese-heritage population will help to understand the impact of admixture on cancer susceptibility in modern humans. In this study, we analyzed the distribution of the Portuguese-originated BRCA variation in Brazilian population, which has high degree Portuguese-heritage.

METHODS

By comprehensive data mining, standardization and annotation, we generated a Portuguese-derived BRCA variation dataset and a Brazilian-derived BRCA variation dataset. We compared the two BRCA variation datasets to identify the BRCA variants shared between the two populations.

RESULTS

The Portuguese-derived BRCA variation dataset consists of 220 BRCA variants including 78 PVs from 11,482 Portuguese cancer patients, 93 (42.2%) in BRCA1 and 127 (57.7%) in BRCA2. Of the 556 Portuguese BRCA PV carriers carrying the 78 PVs, 331 (59.5%) carried the three Portuguese-BRCA founder PVs of BRCA1 c.2037delinsCC, BRCA1 c.3331_3334del and BRCA2 c.156_157insAlu. The Brazilian-derived BRCA variation dataset consists of 255 BRCA PVs from 7,711 cancer patients, 136 (53.3%) in BRCA1 and 119 (46.6%) in BRCA2. We developed an open database named dbBRCA-Portuguese ( https://genemutation.fhs.um.edu.mo/dbbrca-portuguese/ ) and an open database named dbBRCA-Brazilian ( https://genemutation.fhs.um.edu.mo/dbbrca-brazilian ) to host the BRCA variation data from Portuguese and Brazilian populations. We compared the BRCA PV datasets between Portuguese and Brazilian populations, and identified 29 Portuguese-specific BRCA PVs shared between Portuguese and Brazilian populations, 14 in BRCA1 including the Portuguese founder BRCA1 c.3331_3334del and BRCA1 c.2037delinsCC, and 15 in BRCA2 including the Portuguese founder BRCA2 c.156_157insAlu. Searching the 78 Portuguese BRCA PVs in over 5,000 ancient human genomes identified evolution origin for only 8 PVs in Europeans dated between 37,470 and 3,818 years before present, confirming the Portuguese-specificity of Portuguese BRCA PVs; comparing the 78 Portuguese BRCA PVs Portuguese, 255 Brazilian BRCA PVs, and 134 African BRCA PVs showed little overlapping, ruling out the possibility that the BRCA PVs shared between Portuguese and Brazilian may also be contributed by African.

CONCLUSION

Our study provides evidence that the admixture in recent human history contributed to cancer susceptibility in modern humans.

Onco-Breastomics: An Eco-Evo-Devo Holistic Approach

Known as a diverse collection of neoplastic diseases, breast cancer (BC) can be hyperbolically characterized as a dynamic pseudo-organ, a living organism able to build a complex, open, hierarchically organized, self-sustainable, and self-renewable tumor system, a population, a species, a local community, a biocenosis, or an evolving dynamical ecosystem (i.e., immune or metabolic ecosystem) that emphasizes both developmental continuity and spatio-temporal change. Moreover, a cancer cell community, also known as an oncobiota, has been described as non-sexually reproducing species, as well as a migratory or invasive species that expresses intelligent behavior, or an endangered or parasite species that fights to survive, to optimize its features inside the host's ecosystem, or that is able to exploit or to disrupt its host circadian cycle for improving the own proliferation and spreading. BC tumorigenesis has also been compared with the early embryo and placenta development that may suggest new strategies for research and therapy. Furthermore, BC has also been characterized as an environmental disease or as an ecological disorder. Many mechanisms of cancer progression have been explained by principles of ecology, developmental biology, and evolutionary paradigms. Many authors have discussed ecological, developmental, and evolutionary strategies for more successful anti-cancer therapies, or for understanding the ecological, developmental, and evolutionary bases of BC exploitable vulnerabilities. Herein, we used the integrated framework of three well known ecological theories: the Bronfenbrenner's theory of human development, the Vannote's River Continuum Concept (RCC), and the Ecological Evolutionary Developmental Biology (Eco-Evo-Devo) theory, to explain and understand several eco-evo-devo-based principles that govern BC progression. Multi-omics fields, taken together as onco-breastomics, offer better opportunities to integrate, analyze, and interpret large amounts of complex heterogeneous data, such as various and big-omics data obtained by multiple investigative modalities, for understanding the eco-evo-devo-based principles that drive BC progression and treatment. These integrative eco-evo-devo theories can help clinicians better diagnose and treat BC, for example, by using non-invasive biomarkers in liquid-biopsies that have emerged from integrated omics-based data that accurately reflect the biomolecular landscape of the primary tumor in order to avoid mutilating preventive surgery, like bilateral mastectomy. From the perspective of preventive, personalized, and participatory medicine, these hypotheses may help patients to think about this disease as a process governed by natural rules, to understand the possible causes of the disease, and to gain control on their own health.

Multiple TP53 p.R337H haplotypes and implications for tumor susceptibility

The germline TP53 p.R337H mutation is reported as the most common germline TP53 variant. It exists at a remarkably high frequency in the population of southeast Brazil as founder mutation in two distinct haplotypes with the most frequent co-segregating with the p.E134∗ variant of the XAF1 tumor suppressor and an increased cancer risk. Founder mutations demonstrate linkage disequilibrium with neighboring genetic polymorphic markers that can be used to identify the founder variant in different geographic regions and diverse populations. We report here a shared haplotype among Brazilian, Portuguese, and Spanish families and the existence of three additional distinct TP53 p.R337H alleles. Mitochondrial DNA sequencing and Y-STR profiling of Brazilian carriers of the founder TP53 p.R337H allele reveal an excess of Native American haplogroups in maternal lineages and exclusively European haplogroups in paternal lineages, consistent with communities established through male European settlers with extensive intermarriage with Indigenous women. The identification of founder and independent TP53 p.R337H alleles underlines the importance for considering the haplotype as a functional unit and the additive effects of constitutive polymorphisms and associated variants in modifier genes that can influence the cancer phenotype.

Classification of MLH1 Missense VUS Using Protein Structure-Based Deep Learning-Ramachandran Plot-Molecular Dynamics Simulations Method

Pathogenic variation in DNA mismatch repair (MMR) gene MLH1 is associated with Lynch syndrome (LS), an autosomal dominant hereditary cancer. Of the 3798 MLH1 germline variants collected in the ClinVar database, 38.7% (1469) were missense variants, of which 81.6% (1199) were classified as Variants of Uncertain Significance (VUS) due to the lack of functional evidence. Further determination of the impact of VUS on MLH1 function is important for the VUS carriers to take preventive action. We recently developed a protein structure-based method named "Deep Learning-Ramachandran Plot-Molecular Dynamics Simulation (DL-RP-MDS)" to evaluate the deleteriousness of MLH1 missense VUS. The method extracts protein structural information by using the Ramachandran plot-molecular dynamics simulation (RP-MDS) method, then combines the variation data with an unsupervised learning model composed of auto-encoder and neural network classifier to identify the variants causing significant change in protein structure. In this report, we applied the method to classify 447 MLH1 missense VUS. We predicted 126/447 (28.2%) MLH1 missense VUS were deleterious. Our study demonstrates that DL-RP-MDS is able to classify the missense VUS based solely on their impact on protein structure.