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Abstract DNA damage resistance is a major barrier to effective DNA-damaging therapy in multiple myeloma (MM). To discover mechanisms through which MM cells overcome DNA damage, we investigate how MM cells become resistant to antisense oligonucleotide (ASO) therapy targeting Interleukin enhancer binding factor 2 (ILF2), a DNA damage regulator that is overexpressed in 70% of MM patients whose disease has progressed after standard therapies have failed. Here, we show that MM cells undergo adaptive metabolic rewiring to restore energy balance and promote survival in response to DNA damage activation. Using a CRISPR/Cas9 screening strategy, we identify the mitochondrial DNA repair protein DNA2, whose loss of function suppresses MM cells’ ability to overcome ILF2 ASO−induced DNA damage, as being essential to counteracting oxidative DNA damage. Our study reveals a mechanism of vulnerability of MM cells that have an increased demand for mitochondrial metabolism upon DNA damage activation.

Notch1 is frequently activated promoting T-cell acute lymphoblastic leukaemia (T-ALL). Here, the authors show that Notch1 induces oxidative phosphorylation dependency in T-ALL and synergism when inhibiting both mitochondrial complex I and glutaminolysis in preclinical murine and human xenograft models.

Abstract Purpose This study aimed to evaluate the utility of inflammation-based prognostic scores (IBPS) and systemic immune-inflammation index (SII) in the treatment of oral cancer patients. Methods For the 183 patients enrolled in this study, IBPS and SII were calculated from peripheral blood samples obtained before and after treatment and at the time of relapse. We examined overall survival (OS) and disease-free survival (DFS) using previously reported cut-off values for IBPS. Cut-off values of neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), and prognostic nutritional index (PNI) were analyzed as NLR 1.79, PLR 114.97, LMR 5, and PNI 52.44. The cut-off value for SII was set at 569. OS and DFS were analyzed by Kaplan–Meier methods using the cutoff of each IBPS and SII. Univariate analysis and multivariate analysis using Cox proportional hazards were performed for OS and DFS. Results Kaplan–Meier methods showed the high-PNI group showed good prognosis including OS and DFS, while the high-SII group displayed poor DFS. Univariate analysis showed that pre-treatment high PNI and low SII were significantly associated with better prognosis. Multivariate analysis identified pre-treatment PNI as independently associated with OS. For DFS, univariate analysis using Cox proportional hazards modeling showed that pre-treatment high NLR and high SII were significantly associated with worse prognosis, while high PNI was significantly associated with better prognosis. Multivariate analysis identified pre-treatment PNI and SII as independently associated with DFS. Parameters of PNI and SII components were compared between pre-treatment, post-treatment and at relapse in the high- and low-PNI groups. PNI was predominantly decreased in both high- and low-PNI groups at post-treatment and at relapse compared to pre-treatment. This trend was also observed for albumin. Conclusions Higher pre-treatment PNI was associated with better OS, while lower pre-treatment PNI and higher treatment SII were associated with poorer DFS in oral cancer patients. Our data indicated that PNI and SII might offer useful biomarkers for gauging prognosis and the efficacy of conventional therapies.

The regulation of resistance to IDH inhibitors in acute myeloid leukaemia is not completely understood. Here the authors reveal with integrative multi-omics analyses that stemness features are major drivers of primary resistance, while high-risk mutations drive acquired resistance.

Understanding the evolutionary trajectory of cancer samples may enable understanding resistance to treatment. Here, the authors used single cell sequencing of a cohort of acute myeloid leukemia tumours and identify features of linear and branching evolution in tumours.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-19902-7