LKB1 acts as a critical brake for the glucagon‐mediated fasting response

Abstract As important as the fasting response is for survival, an inability to shut it down once nutrients become available can lead to exacerbated disease and severe wasting. The liver is central to transitions between feeding and fasting states, with glucagon being a key initiator of the hepatic fasting response. However, the precise mechanisms controlling fasting are not well defined. One potential mediator of these transitions is liver kinase B1 (LKB1), given its role in nutrient sensing. Here, we show LKB1 knockout mice have a severe wasting and prolonged fasting phenotype despite increased food intake. By applying RNA sequencing and intravital microscopy, we show that loss of LKB1 leads to a dramatic reprogramming of the hepatic lobule through robust up‐regulation of periportal genes and functions. This is likely mediated through the opposing effect that LKB1 has on glucagon pathways and gene expression. Conclusion: Our findings show that LKB1 acts as a brake to the glucagon‐mediated fasting response, resulting in “periportalization” of the hepatic lobule and whole‐body metabolic inefficiency. These findings reveal a mechanism by which hepatic metabolic compartmentalization is regulated by nutrient‐sensing

Novel CDK12/13 Inhibitors AU-15506 and AU-16770 Are Potent Anti-Cancer Agents in EGFR Mutant Lung Adenocarcinoma with and without Osimertinib Resistance

Osimertinib is a third-generation epidermal growth factor receptor and tyrosine kinase inhibitor (EGFR-TKI) approved for the treatment of lung adenocarcinoma patients harboring EGFR mutations. However, acquired resistance to this targeted therapy is inevitable, leading to disease relapse within a few years. Therefore, understanding the molecular mechanisms of osimertinib resistance and identifying novel targets to overcome such resistance are unmet needs of cancer patients. Here, we investigated the efficacy of two novel CDK12/13 inhibitors, AU-15506 and AU-16770, in osimertinib-resistant EGFR mutant lung adenocarcinoma cells in culture and xenograft models in vivo. We demonstrate that these drugs, either alone or in combination with osimertinib, are potent inhibitors of osimertinib-resistant as well as -sensitive lung adenocarcinoma cells in culture. Interestingly, only the CDK12/13 inhibitor in combination with osimertinib, although not as monotherapy, suppresses the growth of resistant tumors in xenograft models in vivo. Taken together, the results of this study suggest that inhibition of CDK12/13 in combination with osimertinib has the potential to overcome osimertinib resistance in EGFR mutant lung adenocarcinoma patients

FIGURE 1 from Functional Heterogeneity in MET Pathway Activation in PDX Models of Osimertinib-resistant EGFR-driven Lung Cancer

Generation of spatial and temporally heterogenous osimertinib-resistant EGFR-mutant NSCLC PDX models and treatment study design. A, Schematic diagram of the prospective clinical trial of LAT for osimertinib-treated EGFR-mutant lung cancer (RT: radiotherapy). PDXs were generated from osimertinib-resistant tumor tissue either at first or second progression on osimertinib or after standard of care (S.O.C) therapy. B, Multi-region and temporal tumor samples from surgical resections or biopsies used for PDX generation are shown for each individual patient. Putative mechanism of resistance to osimertinib as evidenced by exome and or transcriptome sequencing (Roper et al., Cell Reports Medicine 2020) is shown below each set of PDXs. Color denotes timing of sample acquisition. Red: first progression on osimertinib; Green: second progression on osimertinib; Blue: progression on S.O.C treatment. C, Illustrations of PDX generation from 3 patients with EGFR-mutant lung cancer with MET polysomy by FISH (MET ≥ 4.0 and MET/CEP7 ratio is MET amplification by FISH (MET/CEP7 ratio ≥2.0 or ≥6 MET copies per cell) as a mechanism of resistance to osimertinib. D, Study design for treatment with MET inhibitor (savolitinib) with a third-generation EGFR TKI (osimertinib). PDXs with spatial heterogeneity in MET pathway activation (LAT001_6B and LAT001_9B), PDXs with temporal heterogeneity in MET pathway activation (LAT006_2B and LAT006_0118) and an additional validation PDX (LAT015_6B) were treated with vehicle, osimertinib, savolitinib, and osimertinib plus savolitinib combination followed by assessment of efficacy and identification of predictive markers.</p

A spatial map of hepatic mitochondria uncovers functional heterogeneity shaped by nutrient-sensing signaling

Abstract In the liver, mitochondria are exposed to different concentrations of nutrients due to their spatial positioning across the periportal and pericentral axis. How the mitochondria sense and integrate these signals to respond and maintain homeostasis is not known. Here, we combine intravital microscopy, spatial proteomics, and functional assessment to investigate mitochondrial heterogeneity in the context of liver zonation. We find that periportal and pericentral mitochondria are morphologically and functionally distinct; beta-oxidation is elevated in periportal regions, while lipid synthesis is predominant in the pericentral mitochondria. In addition, comparative phosphoproteomics reveals spatially distinct patterns of mitochondrial composition and potential regulation via phosphorylation. Acute pharmacological modulation of nutrient sensing through AMPK and mTOR shifts mitochondrial phenotypes in the periportal and pericentral regions, linking nutrient gradients across the lobule and mitochondrial heterogeneity. This study highlights the role of protein phosphorylation in mitochondrial structure, function, and overall homeostasis in hepatic metabolic zonation. These findings have important implications for liver physiology and disease

FIGURE 4 from Functional Heterogeneity in MET Pathway Activation in PDX Models of Osimertinib-resistant EGFR-driven Lung Cancer

Heterogeneity in MET polysomy and MET amplification in osimertinib-resistant EGFR-mutant NSCLC. A, Representative phospho-MET IHC (several are reused from Fig. 2D), MET FISH images and MET FISH scoring from PDXs with MET polysomy. B, Representative phospho-MET IHC, MET FISH images and MET FISH scoring from longitudinally collected tumor samples from patient LAT006 at first progression on osimertinib, second progression after osimertinib rechallenge, and upon further progression on chemoimmunotherapy. Scale bars, 50 µm.</p

FIGURE 5 from Functional Heterogeneity in MET Pathway Activation in PDX Models of Osimertinib-resistant EGFR-driven Lung Cancer

Phospho-MET expression is an indicator of MET activity post-osimertinib treatment; and proposed clinical flow diagram for treating EGFR-mutant NSCLC with evidence of MET pathway activation after osimertinib resistance. Representative phospho-MET IHC, MET FISH images and MET FISH scoring from pre- and post-osimertinib resistant tumors from patient LAT028 (multiple spatially heterogenous post-osimertinib resistant tumors shown; A) and from patient LAT021 (B). Scale bars, 50 µm. C, Clinical flow diagram for osimertinib-resistant EGFR-mutant NSCLC with evidence of MET pathway activation.</p

FIGURE 2 from Functional Heterogeneity in MET Pathway Activation in PDX Models of Osimertinib-resistant EGFR-driven Lung Cancer

Efficacy and determinants of response to osimertinib and savolitinib combination among osimertinib-resistant EGFR-mutant NSCLC PDX models with spatially and temporally heterogenous MET pathway activation. Tumor growth inhibition studies in MET polysomy (A) and MET amplified (B) PDXs. Dashed vertical lines delineate when treatment was stopped. Asterisks signify statistical significance between osimertinib and savolitinib combination and osimertinib alone treatment arms. P values were calculated by t test. P values C, Association between response to osimertinib and savolitinib combination and IHC features (phospho-MET, c-MET), copy number and FISH parameters (number of MET copies and MET/CEP7 ratio). Response is defined as >25 days until reaching tumor size endpoint in osimertinib and savolitinib combination compared with osimertinib treatment alone. Individual circles represent a unique tumor for each represented PDX model. D, Representative c-MET and phospho-MET IHC images of PDX tumors with and without response to osimertinib and savolitinib combination. Scale bars, 50 µm.</p