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HER3 activation, through NRG1 ligand-dependent and independent heterodimerization with HER2 or EGFR, can drive tumor growth and survival via potent PI3K pathway signaling. HER3 activation has emerged as an important mechanism for both tumor progression and acquired resistance to standard of care therapies in multiple indications. With an effective biomarker strategy to select for patients with HER3 driven cancer, potent inhibition of HER3-driven heterodimerization has the potential to confer profound clinical impact. HER3 targeting approaches to date have not shown expected clinical efficacy. Suboptimal HER3 inhibition is one possible explanation; to prevent downstream PI3K signalling, it is critical to fully block both ligand-dependent and independent HER3 activation. Further, despite the clinical evaluation of several anti-HER3 antibodies, only limited progress has been made to establish predictive biomarkers of response to HER3 inhibition. The most thoroughly studied biomarkers predicting response have been increased expression and genomic rearrangements of the HER3 ligand, NRG1. For example, oncogenic NRG1-fusions have been identified as tumor drivers in up to 0.2% of all solid cancers. Few biomarkers predicting lack of response have been reported to date. HMBD-001, is an unique anti-HER3 antibody rationally developed to bind the dimerization interface of HER3 in order to block all HER3 heterodimerization. In contrast to other anti-HER3 antibodies that predominantly bind to the NRG1 binding domain, we observed potent and superior in vitro and in vivo tumor growth inhibition for HMBD-001 in multiple cancer models, including NRG1-fusion driven models. We show that HMBD-001 binds to HER3 with high affinity even in the presence of high concentrations of NRG1, in contrast to other antibodies in which NRG1 competes for the HER3 ligand binding site, thereby decreasing affinity and likely potency. Notably, HMBD-001 treatment of an NRG1-fusion ovarian PDX model showed superior tumor growth inhibition compared with anti-HER3 and anti-HER2/HER3 bispecific antibodies targeting the NRG1 binding domain of HER3. To develop a robust biomarker signature for patient selection beyond NRG1-fusions, we interrogated the genomic and transcriptomic data of all preclinical models for which HMBD-001 efficacy data was available, including in vitro and in vivo models representing multiple HER3 associated cancer sub-types. We identified a novel gene signature that was robustly predictive of HMBD-001 response across a wide range of cancers, including loss of function and gain of function mutations in specific downstream mediators of the MAPK and PI3K signaling pathways. In conclusion, the superior potency of HMBD-001 in preclinical models predicts more complete inhibition of HER3 and better responses in HER3 driven cancers that can be identified using a novel gene signature biomarker. Clinical trials of HMBD-001 in HER3 driven cancers, including those with NRG1-fusions, are expected to commence in 2021. Citation Format: Dipti Thakkar, Shalini Paliwal, Shreya Kar, Namita Gandhi, Konrad Paszkiewicz, Piers Ingram, Jerome Boyd-Kirkup. An anti-HER3 antibody, HMBD-001, that uniquely binds to and blocks the HER3 heterodimerization interface, shows superior tumor growth inhibition in biomarker-defined preclinical cancer models including NRG1-fusion driven cancers [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2021 Oct 7-10. Philadelphia (PA): AACR; Mol Cancer Ther 2021;20(12 Suppl):Abstract nr P197.

How individual genes are regulated from a mitochondrial polycistronic transcript to have variable expression remains an enigma. Here, through bisulfite sequencing and strand-specific mapping, we show mitochondrial genomes in humans and other animals are strongly biased to light (L)-strand non-CpG methylation with conserved peak loci preferentially located at gene–gene boundaries, which was also independently validated by MeDIP and FspEI digestion. Such mtDNA methylation patterns are conserved across different species and developmental stages but display dynamic local or global changes during development and aging. Knockout of DNMT3A alone perturbed mtDNA regional methylation patterns, but not global levels, and altered mitochondrial gene expression, copy number, and oxygen respiration. Overexpression of DNMT3A strongly increased mtDNA methylation and strand bias. Overall, methylation at gene bodies and boundaries was negatively associated with mitochondrial transcript abundance and also polycistronic transcript processing. Furthermore, HPLC-MS confirmed the methylation signals on mitochondria DNA. Together, these data provide high-resolution mtDNA methylation maps that revealed a strand-specific non-CpG methylation, its dynamic regulation, and its impact on the polycistronic mitochondrial transcript processing.

A novel Bayesian network inference algorithm for integrative analysis of heterogeneous deep sequencing data

Summary Epigenetic modifications are critical determinants of cellular and developmental states. Epigenetic changes, such as decreased H3K27me3 histone methylation on insulin/IGF1 genes, have been previously shown to modulate lifespan through gene expression regulation. However, global epigenetic changes during aging and their biological functions, if any, remain elusive. Here, we examined the histone modification H3K4 dimethylation (H3K4me2) in the prefrontal cortex of individual rhesus macaques at different ages by chromatin immunoprecipitation, followed by deep sequencing (ChIP-seq) at the whole genome level. Through integrative analysis of the ChIP-seq profiles with gene expression data, we found that H3K4me2 increased at promoters and enhancers globally during postnatal development and aging, and those that correspond to gene expression changes in cis are enriched for stress responses, such as the DNA damage response. This suggests that metabolic and environmental stresses experienced by an organism are associated with the progressive opening of chromatin. In support of this, we also observed increased expression of two H3K4 methyltransferases, SETD7 and DPY30, in aged macaque brain.

Aging can be defined as a process of progressive decline in the physiological capacity of an organism, manifested by accumulated alteration and destabilization at the whole system level. Systems biology approaches offer a promising new perspective to examine the old problem of aging. We begin this review by introducing the concepts of systems biology, and then illustrate the application of systems biology approaches to aging research, from gene expression profiling to network analysis. We then introduce the network that can be constructed using known lifespan and aging regulators, and conclude with a look forward to the future of systems biology in aging research. In summary, systems biology is not only a young field that may help us understand aging at a higher level, but also an important platform that can link different levels of knowledge on aging, moving us closer to a more comprehensive control of systematic decline during aging.

With the rapidly increasing availability of high-throughput in situ hybridization images, how to effectively analyze these images at high resolution for global patterns and testable hypotheses has become an urgent challenge. Here we developed a semi-automated image analysis pipeline to analyze in situ hybridization images of E14.5 mouse embryos at single-cell resolution for more than 1600 telencephalon-expressed genes from the Eurexpress database. Using this pipeline, we derived the spatial gene expression profiles at single-cell resolution across the cortical layers to gain insight into the key processes occurring during cerebral cortex development. These profiles displayed high spatial modularity in gene expression, precisely recapitulated known differentiation zones, and uncovered additional unknown transition zones or cellular states. In particular, they revealed a distinctive spatial transition phase dedicated to chromatin remodeling events during neural differentiation, which can be validated by genomic clustering patterns, epigenetic modifications switches, and network modules. Our analysis further revealed a role of mitotic checkpoints during spatial gene expression state transition. As a novel approach to analyzing at the single-cell level the spatial modularity, dynamic trajectory, and transient states of gene expression during embryonic neural differentiation and to inferring regulatory events, our approach will be useful and applicable in many different systems for understanding the dynamic differentiation processes in vivo and at high resolution.

It is tempting to assume that a gradual accumulation of damage ‘causes’ an organism to age, but other biological processes present during the lifespan, whether ‘programmed’ or ‘hijacked’, could control the type and speed of aging. Theories of aging have classically focused on changes at the genomic level; however, individuals with similar genetic backgrounds can age very differently. Epigenetic modifications include DNA methylation, histone modifications and ncRNA. Environmental cues may be ‘remembered’ during lifespan through changes to the epigenome that affect the rate of aging. Changes to the epigenomic landscape are now known to associate with aging, but so far causal links to longevity are only beginning to be revealed. Nevertheless, it is becoming apparent that there is significant reciprocal regulation occurring between the epigenomic levels. Future work utilizing new technologies and techniques should build a clearer picture of the link between epigenomic changes and aging.

Summary Human female life expectancy is higher than that of males. Intriguingly, it has been reported that women display faster rates of age-related cognitive decline and a higher prevalence of Alzheimer’s disease (AD). To assess the molecular bases of these contradictory trends, we analyzed differences in expression changes with age between adult males and females, in four brain regions. In the superior frontal gyrus (SFG), a part of the prefrontal cortex, we observed manifest differences between the two sexes in the timing of age-related changes, that is, sexual heterochrony. Intriguingly, age-related expression changes predominantly occurred earlier, or at a faster pace, in females compared to men. These changes included decreased energy production and neural function and up-regulation of the immune response, all major features of brain aging. Furthermore, we found that accelerated expression changes in the female SFG correlated with expression changes observed in AD, as well as stress effects in the frontal cortex. Accelerated aging-related changes in the female SFG transcriptome may provide a link between a higher stress exposure or sensitivity in women and the higher prevalence of AD.