High-throughput sequencing and rare genetic diseases

A systematic review of computational approaches to understand cancer biology for informed drug repurposing

Cancer is the second leading cause of death globally, trailing only heart disease. In the United States alone, 1.9 million new cancer cases and 609,360 deaths were recorded for 2022. Unfortunately, the success rate for new cancer drug development remains less than 10%, making the disease particularly challenging. This low success rate is largely attributed to the complex and poorly understood nature of cancer etiology. Therefore, it is critical to find alternative approaches to understanding cancer biology and developing effective treatments. One such approach is drug repurposing, which offers a shorter drug development timeline and lower costs while increasing the likelihood of success. In this review, we provide a comprehensive analysis of computational approaches for understanding cancer biology, including systems biology, multi-omics, and pathway analysis. Additionally, we examine the use of these methods for drug repurposing in cancer, including the databases and tools that are used for cancer research. Finally, we present case studies of drug repurposing, discussing their limitations and offering recommendations for future research in this area.

Experience of a multidisciplinary task force with exome sequencing for Mendelian disorders

BACKGROUND

In order to optimally integrate the use of high-throughput sequencing (HTS) as a tool in clinical diagnostics of likely monogenic disorders, we have created a multidisciplinary "Genome Clinic Task Force" at the University Hospitals of Geneva, which is composed of clinical and molecular geneticists, bioinformaticians, technicians, bioethicists, and a coordinator.

METHODS AND RESULTS

We have implemented whole exome sequencing (WES) with subsequent targeted bioinformatics analysis of gene lists for specific disorders. Clinical cases of heterogeneous Mendelian disorders that could potentially benefit from HTS are presented and discussed during the sessions of the task force. Debate concerning the interpretation of identified variants and the content of the final report constitutes a major part of the task force's work. Furthermore, issues related to bioethics, genetic counseling, quality control, and reimbursement are also addressed.

CONCLUSIONS

This multidisciplinary task force has enabled us to create a platform for regular exchanges between all involved experts in order to deal with the multiple complex issues related to HTS in clinical practice and to continuously improve the diagnostic use of HTS. In addition, this task force was instrumental to formally approve the reimbursement of HTS for molecular diagnosis of Mendelian disorders in Switzerland.

Diagnostic exome sequencing to elucidate the genetic basis of likely recessive disorders in consanguineous families

Rare, atypical, and undiagnosed autosomal-recessive disorders frequently occur in the offspring of consanguineous couples. Current routine diagnostic genetic tests fail to establish a diagnosis in many cases. We employed exome sequencing to identify the underlying molecular defects in patients with unresolved but putatively autosomal-recessive disorders in consanguineous families and postulated that the pathogenic variants would reside within homozygous regions. Fifty consanguineous families participated in the study, with a wide spectrum of clinical phenotypes suggestive of autosomal-recessive inheritance, but with no definitive molecular diagnosis. DNA samples from the patient(s), unaffected sibling(s), and the parents were genotyped with a 720K SNP array. Exome sequencing and array CGH (comparative genomic hybridization) were then performed on one affected individual per family. High-confidence pathogenic variants were found in homozygosity in known disease-causing genes in 18 families (36%) (one by array CGH and 17 by exome sequencing), accounting for the clinical phenotype in whole or in part. In the remainder of the families, no causative variant in a known pathogenic gene was identified. Our study shows that exome sequencing, in addition to being a powerful diagnostic tool, promises to rapidly expand our knowledge of rare genetic Mendelian disorders and can be used to establish more detailed causative links between mutant genotypes and clinical phenotypes.

Simultaneous identification and prioritization of variants in familial, de novo, and somatic genetic disorders with VariantMaster

There is increasing interest in clinical genetics pertaining to the utilization of high-throughput sequencing data for accurate diagnoses of monogenic diseases. Moreover, massive whole-exome sequencing of tumors has provided significant advances in the understanding of cancer development through the recognition of somatic driver variants. To improve the identification of the variants from HTS, we developed VariantMaster, an original program that accurately and efficiently extracts causative variants in familial and sporadic genetic diseases. The algorithm takes into account predicted variants (SNPs and indels) in affected individuals or tumor samples and utilizes the row (BAM) data to robustly estimate the conditional probability of segregation in a family, as well as the probability of it being de novo or somatic. In familial cases, various modes of inheritance are considered: X-linked, autosomal dominant, and recessive (homozygosity or compound heterozygosity). Moreover, VariantMaster integrates phenotypes and genotypes, and employs Annovar to produce additional information such as allelic frequencies in the general population and damaging scores to further reduce the number of putative variants. As a proof of concept, we successfully applied VariantMaster to identify (1) de novo mutations in a previously described data set, (2) causative variants in a rare Mendelian genetic disease, and (3) known and new “driver” mutations in previously reported cancer data sets. Our results demonstrate that VariantMaster is considerably more accurate in terms of precision and sensitivity compared with previously published algorithms.

Opportunity for selection in human health

Natural selection defined by differential survival and reproduction of individuals in populations is influenced by genetic, developmental, and environmental factors operating at every age and stage in human life history: generation of gametes, conception, birth, maturation, reproduction, senescence, and death. Biological systems are built upon a hierarchical organization nesting subcellular organelles, cells, tissues, and organs within individuals, individuals within families, and families within populations, and the latter among other populations. Natural selection often acts simultaneously at more than one level of biological organization and on specific traits, which we define as multilevel selection. Under this model, the individual is a fundamental unit of biological organization and also of selection, imbedded in a larger evolutionary context, just as it is a unit of medical intervention imbedded in larger biological, cultural, and environmental contexts. Here, we view human health and life span as necessary consequences of natural selection, operating at all levels and phases of biological hierarchy in human life history as well as in sociological and environmental milieu. An understanding of the spectrum of opportunities for natural selection will help us develop novel approaches to improving healthy life span through specific and global interventions that simultaneously focus on multiple levels of biological organization. Indeed, many opportunities exist to apply multilevel selection models employed in evolutionary biology and biodemography to improving human health at all hierarchical levels. Multilevel selection perspective provides a rational theoretical foundation for a synthesis of medicine and evolution that could lead to discovering effective predictive, preventive, palliative, potentially curative, and individualized approaches in medicine and in global health programs.