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Anticancer therapies have been limited by the emergence of mutations and other adaptations. In bacteria, antibiotics activate the SOS response, which mobilizes error-prone factors that allow for continuous replication at the cost of mutagenesis. We investigated whether the treatment of lung cancer with EGFR inhibitors (EGFRi) similarly engages hypermutators. In cycling drug-tolerant persister (DTP) cells and in EGFRi-treated patients presenting residual disease, we observed upregulation of GAS6, whereas ablation of GAS6's receptor, AXL, eradicated resistance. Reciprocally, AXL overexpression enhanced DTP survival and accelerated the emergence of T790M, an EGFR mutation typical to resistant cells. Mechanistically, AXL induces low-fidelity DNA polymerases and activates their organizer, RAD18, by promoting neddylation. Metabolomics uncovered another hypermutator, AXL-driven activation of MYC, and increased purine synthesis that is unbalanced by pyrimidines. Aligning anti-AXL combination treatments with the transition from DTPs to resistant cells cured patient-derived xenografts. Hence, similar to bacteria, tumors tolerate therapy by engaging pharmacologically targetable endogenous mutators.Significance:EGFR-mutant lung cancers treated with kinase inhibitors often evolve resistance due to secondary mutations. We report that in similarity to the bacterial SOS response stimulated by antibiotics, endogenous mutators are activated in drug-treated cells, and this heralds tolerance. Blocking the process prevented resistance in xenograft models, which offers new treatment strategies.This article is highlighted in the In This Issue feature, p. 2483

Supplementary Figure from AXL and Error-Prone DNA Replication Confer Drug Resistance and Offer Strategies to Treat EGFR-Mutant Lung Cancer

Supplementary Data from AXL and Error-Prone DNA Replication Confer Drug Resistance and Offer Strategies to Treat EGFR-Mutant Lung Cancer

Lung cancer is the leading cause of cancer-related deaths worldwide. The paralogous transcriptional cofactors Yes-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ, also called WWTR1), the main downstream effectors of the Hippo signal transduction pathway, are emerging as pivotal determinants of malignancy in lung cancer. Traditionally, studies have tended to consider YAP and TAZ as functionally redundant transcriptional cofactors with similar biological impact. However, there is growing evidence that each of them also possesses distinct attributes. Here we sought to systematically characterize the division of labor between YAP and TAZ in non–small cell lung cancer (NSCLC), the most common histological subtype of lung cancer. Representative NSCLC cell lines as well as patient-derived data showed that the two paralogs orchestrated nonoverlapping transcriptional programs in this cancer type. YAP preferentially regulated gene sets associated with cell division and cell-cycle progression, whereas TAZ preferentially regulated genes associated with extracellular matrix organization. Depletion of YAP resulted in growth arrest, whereas its overexpression promoted cell proliferation. Likewise, depletion of TAZ compromised cell migration, whereas its overexpression enhanced migration. The differential effects of YAP and TAZ on key cellular processes were also associated with differential response to anticancer therapies. Uncovering the different activities and downstream effects of YAP and TAZ may thus facilitate better stratification of patients with lung cancer for anticancer therapies.Significance:Thease findings show that oncogenic paralogs YAP and TAZ have distinct roles in NSCLC and are associated with differential response to anticancer drugs, knowledge that may assist lung cancer therapy decisions.

List of 142 YAP-differential drugs and 38 TAZ-differential drugs in LUAD cells. Each row is a drug, and each column specifies additional information, including dose used in the screen, drug targets, indication, clinical phase and the p-value of the comparison.

Sequences of siRNAs and primers used in this study.

Gene Ontology results of either the YAP-correlated or TAZ-correlated genes in LUAD TCGA, determined by Metascape.

Supplementary Figures

Gene ontology results of either YAP-regulated or TAZ-regulated genes from H1299 RNA-seq analysis, determined by Metascape.

Anticancer therapies have been limited by the emergence of mutations and other adaptations. In bacteria, antibiotics activate the SOS response, which mobilizes error-prone factors that allow for continuous replication at the cost of mutagenesis. We investigated whether the treatment of lung cancer with EGFR inhibitors (EGFRi) similarly engages hypermutators. In cycling drug-tolerant persister (DTP) cells and in EGFRi-treated patients presenting residual disease, we observed upregulation of GAS6, whereas ablation of GAS6's receptor, AXL, eradicated resistance. Reciprocally, AXL overexpression enhanced DTP survival and accelerated the emergence of T790M, an EGFR mutation typical to resistant cells. Mechanistically, AXL induces low-fidelity DNA polymerases and activates their organizer, RAD18, by promoting neddylation. Metabolomics uncovered another hypermutator, AXL-driven activation of MYC, and increased purine synthesis that is unbalanced by pyrimidines. Aligning anti-AXL combination treatments with the transition from DTPs to resistant cells cured patient-derived xenografts. Hence, similar to bacteria, tumors tolerate therapy by engaging pharmacologically targetable endogenous mutators. Significance: EGFR-mutant lung cancers treated with kinase inhibitors often evolve resistance due to secondary mutations. We report that in similarity to the bacterial SOS response stimulated by antibiotics, endogenous mutators are activated in drug-treated cells, and this heralds tolerance. Blocking the process prevented resistance in xenograft models, which offers new treatment strategies. This article is highlighted in the In This Issue feature, p. 2483

Missense mutations in the p53 tumor suppressor abound in human cancer. Common (“hotspot”) mutations endow mutant p53 (mutp53) proteins with oncogenic gain of function (GOF), including enhanced cell migration and invasiveness, favoring cancer progression. GOF is usually attributed to transcriptional effects of mutp53. To elucidate transcription-independent effects of mutp53, we characterized the protein interactome of the p53R273H mutant in cells derived from pancreatic ductal adenocarcinoma (PDAC), where p53R273H is the most frequent p53 mutant. We now report that p53R273H, but not the p53R175H hotspot mutant, interacts with SQSTM1/p62 and promotes cancer cell migration and invasion in a p62-dependent manner. Mechanistically, the p53R273H-p62 axis drives the proteasomal degradation of several cell junction–associated proteins, including the gap junction protein Connexin 43, facilitating scattered cell migration. Concordantly, down-regulation of Connexin 43 augments PDAC cell migration, while its forced overexpression blunts the promigratory effect of the p53R273H-p62 axis. These findings define a mechanism of mutp53 GOF.

Tumour suppressor p53 (TP53) is the most frequently mutated gene in cancer. Several hotspot p53 mutants not only lose tumour suppressive capabilities, but also function in a dominant-negative manner, suppressing canonical wild-type p53 function. Furthermore, some hotspot p53 mutants promote oncogenesis by gain-of-function mechanisms. Levels of p53 are regulated predominantly through regulation of protein stability and while wild-type p53 is normally kept at very low levels at steady-state, p53 mutants are often stabilized in tumours, which may be vital for their oncogenic properties. Here, we systematically profiled the factors that regulate protein stability of wild-type and mutant p53 using marker-based genome-wide CRISPR screens. We found that most proteins that regulate wild-type p53 also regulate a subset of p53 mutants with the exception of p53 R337H regulators, which are largely private to this mutant. Mechanistically, we identified FBXO42 as a novel positive regulator of a subset of p53 mutants comprising R273H, R248Q and R248W. We show that FBXO42 acts together with CCDC6 to regulate USP28-mediated p53 stabilization. Our work also identifies C16orf72 as a negative regulator of the stability of wild-type p53 and of all p53 mutants tested. C16orf72 is amplified in breast cancer, and we show that C16orf72 regulates p53 levels in mammary epithelium of mice and its overexpression results in accelerated breast cancer with reduced p53 levels. Together, this work provides a network view of the processes that regulate p53 stability, which might provide clues for reinforcing wild-type p53 or targeting mutant p53 in cancer.

TP53 gene mutations are very common in human cancer. While such mutations abrogate the tumor suppressive activities of the wild‐type (wt) p53 protein, some of them also endow the mutant (mut) protein with oncogenic gain of function (GOF), facilitating cancer progression. Yet, p53 may acquire altered functionality even without being mutated; in particular, experiments with cultured cells revealed that wtp53 can be rewired to adopt mut‐like features in response to growth factors or cancer‐mimicking genetic manipulations. To assess whether such rewiring also occurs in human tumors, we interrogated gene expression profiles and pathway deregulation patterns in the METABRIC breast cancer (BC) dataset as a function of TP53 gene mutation status. Harnessing the power of machine learning, we optimized a gene expression classifier for ER+Her2‐ patients that distinguishes tumors carrying TP53 mutations from those retaining wt TP53. Interestingly, a small subset of wt TP53 tumors displayed gene expression and pathway deregulation patterns markedly similar to those of TP53‐mutated tumors. Moreover, similar to TP53‐mutated tumors, these ‘pseudomutant’ cases displayed a signature for enhanced proliferation and had worse prognosis than typical wtp53 tumors. Notably, these tumors revealed upregulation of genes which, in BC cell lines, were reported to be positively regulated by p53 GOF mutants. Thus, such tumors may benefit from mut p53‐associated activities without having to accrue TP53 mutations., In ER+Her2‐ breast cancer (BC), p53 tumor suppressor gene mutations are associated with bad prognosis, relative to tumors that retain wild‐type (wt) p53. Applying machine learning to a large BC dataset reveals a subset of ER+Her2‐ tumors (pseudomutant p53 tumors) which, despite retaining wt p53, display gene expression and pathway deregulation profiles typical of p53‐mutated tumors, correlating with bad prognosis.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer, which is refractory to all currently available treatments and bears dismal prognosis. About 70% of all PDAC cases harbor mutations in the TP53 tumor suppressor gene. Many of those are missense mutations, resulting in abundant production of mutant p53 (mutp53) protein in the cancer cells. Analysis of human PDAC patient data from The Cancer Genome Atlas (TCGA) revealed a negative association between the presence of missense mutp53 and infiltration of CD8(+) T cells into the tumor. Moreover, CD8(+) T cell infiltration was negatively correlated with the expression of fibrosis-associated genes. Importantly, silencing of endogenous mutp53 in KPC cells, derived from mouse PDAC tumors driven by mutant Kras and mutp53, down-regulated fibrosis and elevated CD8(+) T cell infiltration in the tumors arising upon orthotopic injection of these cells into the pancreas of syngeneic mice. Moreover, the tumors generated by mutp53-silenced KPC cells were markedly smaller than those elicited by mutp53-proficient control KPC cells. Altogether, our findings suggest that missense p53 mutations may contribute to worse PDAC prognosis by promoting a more vigorous fibrotic tumor microenvironment and impeding the ability of the immune system to eliminate the cancer cells.

Colorectal cancer (CRC) is the third most common cancer worldwide. The TP53 gene is mutated in approximately 60% of all CRC cases. Sporadic CRC is characterized by high prevalence of TP53 hotspot missense mutations. In particular, over 20 percent of all TP53-mutated CRC tumors carry either the p53R175H structural mutant or the p53R273H DNA contact mutant. Importantly, clinical data analysis suggests that CRC tumors harboring p53 R273 mutations are more prone to progress to metastatic disease than those with R175 mutations, in association with decreased survival. By combining in vitro CRC cell line models and human CRC data mining, we identified a unique transcriptional signature orchestrated by p53R273H, implicating activation of oncogenic signaling pathways and predicting worse patient outcome. Concordantly, p53R273H selectively promotes rapid CRC cell spreading, migration and invasion in vitro and metastasis in vivo. Mechanistically, the transcriptional output of p53R273H is associated with, and presumably driven by, its preferential binding to regulatory elements of R273 signature genes. Together, this demonstrates that different TP53 missense mutations contribute differently to cancer progression, and that p53R273H possesses distinct gain-of-function activities in CRC that bear on disease course and possibly on patient management strategy. Given that practically all current analytical cancer gene panels include TP53, elucidation of the differential impact of distinct TP53 mutations on disease features is expected to make information on TP53 mutations more actionable and holds potential for better precision-based medicine.

Summary Cancer immunotherapy focuses on inhibitors of checkpoint proteins, such as programmed death ligand 1 (PD-L1). Unlike RAS-mutated lung cancers, EGFR mutant tumors have a generally low response to immunotherapy. Because treatment outcomes vary by EGFR allele, intrinsic and microenvironmental factors may be involved. Among all non-immunological signaling pathways surveyed in patients’ datasets, EGFR signaling is best associated with high PD-L1. Correspondingly, active EGFRs stabilize PD-L1 transcripts and depletion of PD-L1 severely inhibits EGFR-driven tumorigenicity and metastasis in mice. The underlying mechanisms involve the recruitment of phospholipase C-γ1 (PLC-γ1) to a cytoplasmic motif of PD-L1, which enhances PLC-γ1 activation by EGFR. Once stimulated, PLC-γ1 activates calcium flux, Rho GTPases, and protein kinase C, collectively promoting an aggressive phenotype. Anti-PD-L1 antibodies can inhibit these intrinsic functions of PD-L1. Our results portray PD-L1 as a molecular amplifier of EGFR signaling and improve the understanding of the resistance of EGFR+ tumors to immunotherapy., Graphical abstract, Highlights • Unlike promoter-mediated PD-L1 induction by IFN-γ, EGFR rapidly stabilizes PD-L1 mRNA • Once induced, PD-L1 enhances metastasis in vivo and chemotaxis toward EGF • PD-L1 physically binds with and enhances activation of phospholipase C-γ1 by EGFR • PLC-γ1 binds a PD-L1’s cytoplasmic segment implicated in protection from cytotoxicity, Unlike patients expressing mutant KRAS, patients with lung cancer harboring EGFR mutations are relatively resistant to immunotherapy. Because responses differ by EGFR allele, Ghosh et al. investigate the EGFR-to-PD-L1 axis. They report a three-way collaboration among EGFR, PD-L1, and phospholipase C-γ1. Targeting this triad may enhance responses to immunotherapy.

Cancer immunotherapy has focused on inhibitors of checkpoint proteins, such as Programmed Death Ligand 1 (PD-L1). Unlike RAS-mutated lung cancers, EGFR mutant tumors have generally low response to immunotherapy. Because treatment outcomes vary by EGFR allele, we assumed that intrinsic and microenvironmental factors are involved. Among all non-immunological signaling pathways we surveyed in patients’ datasets, EGFR signaling best associated with high PD-L1. Correspondingly, active EGFRs stabilized PD-L1’s transcripts and depleting PD-L1 severely inhibited EGFR-driven tumorigenicity and metastasis in mice. The underlying mechanisms involve physical recruitment of an auto-inhibited phospholipase C-g1 (PLC-g1) to PD-L1, which enhances trans-phosphorylation by EGFR. Once activated, pPLC-g1 stimulates calcium flux, RHO GTPases and protein kinase C, thereby establishing an aggressive mesenchymal phenotype. We show that approved anti-PD-L1 antibodies can inhibit these intrinsic functions of PD-L1. Our results portray PD-L1 as a molecular amplifier of EGFR signaling and lay the foundation for understanding resistance of EGFR mutant tumors to immunotherapy.

This chapter provides an overview of discrete manufacturing and industries that fall under it. It also explains how MII fulfills the need of such industries. It explains how the SAP MII and its related modules can be used to fill the gap of information flow between management and production.

This chapter explains the manufacturing industry. It also discusses SAP MII and how it fills the gap of information flow between management and production. Along with that, it explains the history and features of SAP MII introduced in the manufacturing sector and how to work with it.

With the advancement in the technology, SAP MII has evolved with new patches and upgraded versions. It started with SAP MII version 11.5 and the latest version is 15.1.

This chapter provides an overview of process manufacturing and the industries that fall under this kind of manufacturing. It also explains how SAP MII and its related modules can be used to provide solutions to those industries.

Before diving deep into the SAP MII technically and correlating it with the functional requirements, the basic conceptual integral configurations and intelligent development IDE and its functions should be clear to the professionals. This chapter explains the basics of SAP MII, the steps related to its various configurations, and its development components and other basic features.

In every programming and technical platform, there is a recommended approach by the product owner. Similarly with SAP MII, there are dos and don’ts that need to be followed. SAP MII is a platform, so there are few recommendations from SAP. The best practices explained here should be followed for best performance and effectiveness of the solution.

This chapter explains why you should use SAP MII in the manufacturing industry. It explains the challenges that are being faced in manufacturing and the role SAP MII plays in overcoming these challenges.