ALDH1A1 and HLTF modulate the activity of lysosomal autophagy inhibitors in cancer cells

<p>Lysosomal autophagy inhibitors (LAI) such as hydroxychloroquine (HCQ) have significant activity in a subset of cancer cell lines. LAIs are being evaluated in cancer clinical trials, but genetic determinants of sensitivity to LAIs are unknown, making it difficult to predict which tumors would be most susceptible. Here we characterize differentially expressed genes in HCQ-sensitive (-S) and -resistant (-R) cancer cells. Notably, expression of canonical macroautophagy/autophagy genes was not associated with sensitivity to HCQ. Expression patterns of ALDH1A1 (aldehyde dehydrogenase 1 family member A1) and HLTF (helicase like transcription factor) identified HCQ-S (ALDH1A1_high HLTF_low; ALDH1A1_low HLTF_low) and HCQ-R (ALDH1A1_low HLTF_high) cells. ALDH1A1 overexpression was found to enhance LAI cell entry and cytotoxicity without directly affecting lysosome function or autophagic flux. Expression of HLTF allows repair of DNA damage caused by LAI-induced reactive oxygen species, leading to HCQ resistance. Sensitivity to HCQ is increased in cells where <i>HLTF</i> is silenced by promoter methylation. HLTF overexpression blunted the antitumor efficacy of chloroquine derivatives in vitro and in vivo. Analysis of tumor RNA sequencing data from >700 patients in the Cancer Genome Atlas identified cancers including colon cancer, renal cell carcinoma, and gastric cancers, that were enriched for the HCQ-S or HCQ-R signature. These results provide mechanistic insights into LAI efficacy, and guidance for LAI clinical development.</p

Genetic characteristics.

<p>Genetic characteristics.</p

A Modified Integrated Genetic Model for Risk Prediction in Younger Patients with Acute Myeloid Leukemia

<div><p>Background</p><p>Although cytogenetics-based prognostication systems are well described in acute myeloid leukemia (AML), overall survival (OS) remains highly variable within risk groups. An integrated genetic prognostic (IGP) model using cytogenetics plus mutations in nine genes was recently proposed for patients ≤60 years to improve classification. This model has not been validated in clinical practice.</p><p>Methods and Findings</p><p>We retrospectively studied 197 patients with newly diagnosed de novo AML. We compared OS curves among the mutational profiles defined by the IGP model. The IGP model assigned patients with intermediate cytogenetics as having favorable, intermediate or unfavorable mutational profiles. The IGP model reassigned 50 of 137 patients with intermediate cytogenetics to favorable or unfavorable mutational profiles. Median OS was 2.8 years among 14 patients with intermediate cytogenetics and favorable mutational profiles (mutant <i>NPM1</i> and mutant <i>IDH1</i> or <i>IDH2</i>) and 1.3 years among patients with intermediate mutational profiles. Among patients with intermediate cytogenetics labeled as having unfavorable mutational profiles, median OS was 0.8 years among 24 patients with <i>FLT3</i>-ITD positive AML and high-risk genetic changes (trisomy 8, <i>TET2</i> and/or <i>DNMT3A</i>) and 1.7 years among 12 patients with <i>FLT3</i>-ITD negative AML and high-risk mutations (<i>TET2</i>, <i>ASXL1</i> and/or <i>PHF6</i>). OS for patients with intermediate cytogenetics and favorable mutational profiles was similar to OS for patients with favorable cytogenetics (p = 0.697) and different from patients with intermediate cytogenetics and intermediate mutational profiles (p = 0.028). OS among patients with <i>FLT3</i>-ITD positive AML and high-risk genetic changes was similar to patients with unfavorable cytogenetics (p = 0.793) and different from patients with intermediate IGP profile (p = 0.022). Patients with <i>FLT3</i>-ITD negative AML and high-risk mutations, defined as ‘unfavorable’ in the IGP model, had OS similar to patients with intermediate IGP profile (p = 0.919).</p><p>Conclusions</p><p>The IGP model was not completely validated in our cohort. However, mutations in six out of the nine genes can be used to characterize survival (<i>NPMI</i>, <i>IDH1</i>, <i>IDH2</i>, <i>FLT3-</i>ITD, <i>TET2</i>, <i>DNMT3A</i>) and allow for more robust prognostication in the patients who are re-categorized by the IGP model. These mutations should be incorporated into clinical testing for younger patients outside of clinical trials, in order to guide therapy.</p></div

Overall survival in IGP model subgroups.

<p>A. Overall survival by cytogenetics and mutational profiles. Among patients with intermediate cytogenetics, three-year overall survival was 59% for those with favorable mutational profiles (A), 33% for those with intermediate mutational profiles (B), 51% for those who were <i>FLT3-</i>ITD negative with high-risk mutations (C) and 11% for those who were <i>FLT3-</i>ITD positive with high-risk mutations (D). Three-year overall survival was 77% among patients with favorable cytogenetics (favorable) and 21% among patients with unfavorable cytogenetics (unfavorable). B. Overall survival among patients with favorable mutational profiles. The overall survival curve for patients with intermediate cytogenetics and mutant <i>NPM1</i> plus mutant <i>IDH1</i> or <i>IDH2</i> was similar to the survival curve for patients with favorable cytogenetics (adjusted p = 0.697) and different from the survival curve for patients in the intermediate IGP risk group (adjusted p = 0.028). C. Overall survival among patients with <i>FLT3-</i>ITD negative AML and high-risk mutations. The overall survival curve for patients with <i>FLT3</i>-ITD negative (<i>FLT3-</i>ITD-) AML and co-occurring high-risk mutations (<i>TET2</i>, <i>ASXL1</i> and/or <i>PHF6</i>) was not significantly different from the survival curves for patients with unfavorable cytogenetics or patients with intermediate IGP risk (adjusted p = 0.111 and p = 0.919, respectively). D. Overall survival among patients with <i>FLT3</i>-ITD positive AML and high-risk mutations. The overall survival curve for patients with <i>FLT3</i>-ITD positive (<i>FLT3</i>-ITD+) AML and co-occurring high-risk mutations (trisomy 8, <i>TET2</i> and/or <i>DNMT3A</i>) was similar to the survival curve for patients with unfavorable cytogenetics (adjusted p = 0.793) and different from the survival curve for patients in the intermediate IGP risk group (adjusted p = 0.022).</p

Overall survival by integrated genetic prognostic (IGP) profile (n = 197).

<p>The overall survival curve for patients with favorable IGP risk was significantly different from the curve for patients with unfavorable IGP risk (adjusted p<0.001). There was no significant difference in survival curves between patients with favorable IGP risk and patients with intermediate IGP risk (adjusted p = 0.055), or between patients with unfavorable IGP risk and patients with intermediate IGP risk (adjusted p = 0.596).</p

Clinical characteristics.

<p>Clinical characteristics.</p

Schematic representation of integrated genetic prognostic (IGP) model and modified IGP model.

<p>Schematic representation of integrated genetic prognostic (IGP) model and modified IGP model.</p

Univariate and multivariate Cox models for overall survival (n = 197).

<p>Univariate and multivariate Cox models for overall survival (n = 197).</p

Overall survival by modified IGP profile (n = 197).

<p>The overall survival curve for patients with favorable M-IGP risk was significantly different from the survival curve for patients with unfavorable IGP risk (adjusted p<0.001). There was no significant difference in survival curves between patients with favorable M-IGP profiles and patients with intermediate M-IGP profiles (adjusted p = 0.178), or between patients with unfavorable M-IGP profiles and patients with intermediate M-IGP profiles (adjusted p = 0.100).</p