Background: Heart failure with preserved ejection fraction (HFpEF) constitutes half of all HF yet lacks effective therapy. Understanding its myocardial biology remains limited due to a paucity of heart tissue molecular analysis. Methods: We performed RNA sequencing on right ventricular septal endomyocardial biopsies prospectively obtained from patients with consensus criteria for HFpEF (n=41) and contrasted to RV-septal tissue from HF with reduced EF (HFrEF, n=30) and donor controls (CON, n=24). Principal component analysis (PCA) and hierarchical clustering tested for transcriptomic distinctiveness between groups and impact of co-morbidities, and differential gene expression with pathway enrichment contrasted HF groups to CON. Within HFpEF, non-negative matrix factorization (NMF) and weighted gene co-expression analysis (WGCNA) identified molecular subgroups and the resulting clusters were correlated with hemodynamic and clinical data. Results: HFpEF patients were more often women (59%), African American (68%), obese (median BMI 41), and hypertensive (98%), with clinical HF characterized by 65% NYHA III-IV, nearly all on a loop diuretic, and 70% with a HF hospitalization in the prior year. PCA separated HFpEF from HFrEF and CON with minimal overlap and this persisted after adjusting for primary co-morbidities: BMI, sex, age, diabetes, and renal function. Hierarchical clustering confirmed group separation. Nearly half the significantly altered genes in HFpEF versus CON (1882 up, 2593 down) changed in the same direction in HFrEF; however, 5745 genes were uniquely altered between HF groups. Compared to CON, uniquely upregulated genes in HFpEF were enriched in mitochondrial ATP synthesis/electron transport, pathways downregulated in HFrEF. HFpEF-specific down-regulated genes engaged endoplasmic reticulum stress, autophagy, and angiogenesis. BMI differences largely accounted for HFpEF upregulated genes whereas neither this nor broader co-morbidity adjustment altered pathways enriched in downregulated genes. NMF identified three HFpEF transcriptomic subgroups with distinctive pathways and clinical correlates, including a group closest to HFrEF with higher mortality, and a mostly female group with smaller hearts and pro-inflammatory signaling. These groupings remained after sex adjustment. WGCNA analysis yielded analogous gene-clusters and clinical groupings. Conclusions: HFpEF exhibits distinctive broad transcriptomic signatures and molecular subgroupings with particular clinical features and outcomes. The data reveal new signaling targets to consider for precision therapeutics.

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The characterization of cancer genomes has provided insight into somatically altered genes across tumors, transformed our understanding of cancer biology, and enabled tailoring of therapeutic strategies. However, the function of most cancer alleles remains mysterious, and many cancer features transcend their genomes. Consequently, tumor genomic characterization does not influence therapy for most patients. Approaches to understand the function and circuitry of cancer genes provide complementary approaches to elucidate both oncogene and non-oncogene dependencies. Emerging work indicates that the diversity of therapeutic targets engendered by non-oncogene dependencies is much larger than the list of recurrently mutated genes. Here we describe a framework for this expanded list of cancer targets, providing novel opportunities for clinical translation.

Natural killer (NK) cells have potent antitumor and antimetastatic activity. It is incompletely understood how cancer cells escape NK cell surveillance. Using ex vivo and in vivo models of metastasis, we establish that keratin-14+ breast cancer cells are vulnerable to NK cells. We then discovered that exposure to cancer cells causes NK cells to lose their cytotoxic ability and promote metastatic outgrowth. Gene expression comparisons revealed that healthy NK cells have an active NK cell molecular phenotype, whereas tumor-exposed (teNK) cells resemble resting NK cells. Receptor–ligand analysis between teNK cells and tumor cells revealed multiple potential targets. We next showed that treatment with antibodies targeting TIGIT, antibodies targeting KLRG1, or small-molecule inhibitors of DNA methyltransferases (DMNT) each reduced colony formation. Combinations of DNMT inhibitors with anti-TIGIT or anti-KLRG1 antibodies further reduced metastatic potential. We propose that NK-directed therapies targeting these pathways would be effective in the adjuvant setting to prevent metastatic recurrence.

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