Citations

Abstract Immune checkpoint blockade (ICB) has revolutionized cancer therapy. However, the response of patients to ICB is difficult to predict. Here, we examined 81 patients with lung cancer under ICB treatment and found that patients with MET amplification were resistant to ICB and had a poor progression-free survival. Tumors with MET amplifications had significantly decreased STING levels and antitumor T-cell infiltration. Furthermore, we performed deep single-cell RNA sequencing on more than 20,000 single immune cells and identified an immunosuppressive signature with increased subsets of XIST- and CD96-positive exhausted natural killer (NK) cells and decreased CD8+ T-cell and NK-cell populations in patients with MET amplification. Mechanistically, we found that oncogenic MET signaling induces phosphorylation of UPF1 and downregulates tumor cell STING expression via modulation of the 3′-UTR length of STING by UPF1. Decreased efficiency of ICB by MET amplification can be overcome by inhibiting MET. Significance: We suggest that the combination of MET inhibitor together with ICB will overcome ICB resistance induced by MET amplification. Our report reveals much-needed information that will benefit the treatment of patients with primary MET amplification or EGFR–tyrosine kinase inhibitor resistant-related MET amplification. This article is highlighted in the In This Issue feature, p. 2659

Abstract RPA is a critical factor for DNA replication and replication stress response. Surprisingly, we found that chromatin RPA stability is tightly regulated. We report that the GDP/GTP exchange factor DOCK7 acts as a critical replication stress regulator to promote RPA stability on chromatin. DOCK7 is phosphorylated by ATR and then recruited by MDC1 to the chromatin and replication fork during replication stress. DOCK7-mediated Rac1/Cdc42 activation leads to the activation of PAK1, which subsequently phosphorylates RPA1 at S135 and T180 to stabilize chromatin-loaded RPA1 and ensure proper replication stress response. Moreover, DOCK7 is overexpressed in ovarian cancer and depleting DOCK7 sensitizes cancer cells to camptothecin. Taken together, our results highlight a novel role for DOCK7 in regulation of the replication stress response and highlight potential therapeutic targets to overcome chemoresistance in cancer.

Abstract PARP inhibitors induce DNA lesions, the repair of which are highly dependent on homologous recombination (HR), and preferentially kill HR‐ deficient cancers. However, cancer cells have developed several mechanisms to transform HR and confer drug resistance to PARP inhibition. Therefore, there is a great clinical interest in exploring new therapies that induce HR deficiency (HRD), thereby sensitizing cancer cells to PARP inhibitors. Here, we found that GSK2578215A, a high‐selective and effective leucine‐rich repeat kinase 2 (LRRK2) inhibitor, or LRRK2 depletion suppresses HR preventing the recruitment of RAD51 to DNA damage sites through disruption of the interaction of RAD51 and BRCA2. Moreover, LRRK2 inhibition or depletion increases the susceptibility of ovarian cancer cells to Olaparib in vitro and in vivo. In clinical specimens, LRRK2 high expression is high related with advanced clinical characteristics and poor survival of ovarian cancer patients. All these findings indicate ovarian cancers expressing high levels of LRRK2 are more resistant to treatment potentially through promoting HR. Furthermore, combination treatment with an LRRK2 and PARP inhibitor may be a novel strategy to improve the effectiveness of LRRK2 expression ovarian cancers.

Abstract Proton Bragg peak irradiation has a higher ionizing density than conventional photon irradiation or the entrance of the proton beam profile. Whether targeting the DNA damage response (DDR) could enhance vulnerability to the distinct pattern of damage induced by proton Bragg peak irradiation is currently unknown. Here, we performed genetic or pharmacologic manipulation of key DDR elements and evaluated DNA damage signaling, DNA repair, and tumor control in cell lines and xenografts treated with the same physical dose across a radiotherapy linear energy transfer spectrum. Radiotherapy consisted of 6 MV photons and the entrance beam or Bragg peak of a 76.8 MeV spot scanning proton beam. More complex DNA double-strand breaks (DSB) induced by Bragg peak proton irradiation preferentially underwent resection and engaged homologous recombination (HR) machinery. Unexpectedly, the ataxia-telangiectasia mutated (ATM) inhibitor, AZD0156, but not an inhibitor of ATM and Rad3-related, rendered cells hypersensitive to more densely ionizing proton Bragg peak irradiation. ATM inhibition blocked resection and shunted more DSBs to processing by toxic ligation through nonhomologous end-joining, whereas loss of DNA ligation via XRCC4 or Lig4 knockdown rescued resection and abolished the enhanced Bragg peak cell killing. Proton Bragg peak monotherapy selectively sensitized cell lines and tumor xenografts with inherent HR defects, and the repair defect induced by ATM inhibitor coadministration showed enhanced efficacy in HR-proficient models. In summary, inherent defects in HR or administration of an ATM inhibitor in HR-proficient tumors selectively enhances the relative biological effectiveness of proton Bragg peak irradiation. Significance: Coadministration of an ATM inhibitor rewires DNA repair machinery to render cancer cells uniquely hypersensitive to DNA damage induced by the proton Bragg peak, which is characterized by higher density ionization. See related commentary by Nickoloff, p. 3156

Abstract Purpose: T-cell immunoglobulin and ITIM domain (TIGIT), a member of the immune checkpoint family, is important in normal T-cell biology. However, the phenotypical profile and clinical relevance of TIGIT in follicular lymphoma is largely unknown. Experimental Design: Biopsy specimens from a cohort of 82 patients with follicular lymphoma were analyzed using mass cytometry to explore the phenotype and biological and clinical significance of TIGIT+ T cells. Results: TIGIT is highly expressed on intratumoral T cells and its expression alters T-cell phenotype in follicular lymphoma. TIGIT is abundantly expressed on Treg cells, resulting in an enhanced suppressive property. TIGIT expression on non-Treg/TFH T cells defines a population that exhibits an exhausted phenotype. Clinically, increased numbers of TIGIT+ T cells are associated with inferior patient outcomes and poor survival. We observe that anti–PD-1 therapy with pembrolizumab alters the phenotype of TIGIT+ T subsets and identifies a role for CD28 expression on TIGIT+ T cells in treatment response. Conclusions: The current study provides a comprehensive analysis of the phenotypic profile of intratumoral TIGIT+ T subsets and their prognostic relevance in follicular lymphoma. Inhibition of TIGIT signaling may be an additional mechanism to prevent T-cell suppression and exhaustion in B-cell lymphoma.

We clarify that DNA damage triggers autophagy by CHK2-FOXK axis, and misregulation of this pathway leads to chemoresistance.

Abstract In clinical cancer treatment, genomic alterations would often affect the response of patients to anticancer drugs. Studies have shown that molecular features of tumors could be biomarkers predictive of sensitivity or resistance to anticancer agents, but the identification of actionable mutations are often constrained by the incomplete understanding of cancer genomes. Recent progresses of next-generation sequencing technology greatly facilitate the extensive molecular characterization of tumors and promote precision medicine in cancers. More and more clinical studies, cancer cell lines studies, CRISPR screening studies as well as patient-derived model studies were performed to identify potential actionable mutations predictive of drug response, which provide rich resources of molecularly and pharmacologically profiled cancer samples at different levels. Such abundance of data also enables the development of various computational models and algorithms to solve the problem of drug sensitivity prediction, biomarker identification and in silico drug prioritization by the integration of multiomics data. Here, we review the recent development of methods and resources that identifies mutation-dependent effects for cancer treatment in clinical studies, functional genomics studies and computational studies and discuss the remaining gaps and future directions in this area.