Anti-Neurodegenerating Activity: Structure-Activity Relationship Analysis of Flavonoids

An anti-neurodegeneration activity study was carried out for 80 flavonoid compounds. The structure-activity analysis of the structures was carried out by performing three different anti-neurodegeneration screening tests, showing that in these structures, the presence of a hydroxy substituent group at position C3' as well as C5' of ring B and a methoxy substituent group at the C7 position of ring A play a vital role in neuroprotective and antioxidant as well as anti-inflammatory activity. Further, we found structure (5) was the top-performing active structure out of 80 structures. Subsequently, a molecular docking study was carried out for the 3 lead flavonoid compounds (4), (5), and (23) and 21 similar hypothetical proposed structures to estimate the binding strength between the tested compounds and proteins potentially involved in disease causation. Ligand-based pharmacophores were generated to guide future drug design studies.

Abstract A2-18: The challenges of using large-scale genomics data to identify novel drivers of lung cancer

Lung cancer is one of the major causes of cancer deaths worldwide and only 30% of patients survive the disease for at least one year after diagnosis. Patients are often too frail to receive systemic chemotherapy and there is an urgent need for less toxic, efficacious, targeted therapies. Despite recent efforts with large-scale genomics data we still lack knowledge about driver mutations for the majority of lung cancers.

Increasingly, cancer researchers are using online cancer genomic databases to identify novel targets to investigate. A comparison of two prominent databases from different institutes (CCLE and COSMIC) revealed marked discrepancies in the detection of missense mutations in identical cell lines (57.38% conformity). A major reason for this discrepancy is inadequate sequencing of GC-rich areas. This is a significant issue for lung cancer, with a mutation signature predominantly affecting guanine and cytosine nucleotides and therefore preferring GC-rich regions.

We have therefore focused on GC-rich regions that next-generation-sequencing struggle to cover and discovered over 400 of these regions (cold-spots) in Cancer Consensus and kinase genes alone. We demonstrate how a PAK4 mutation, found in a GC-rich cold-spot in a lung adenocarcinoma cell line, activates the pERK pathway. This suggests that specific targeting of GC-rich regions may be required to uncover further oncogenes and tumour suppressors in lung cancer.

The high mutational burden of lung cancer creates additional challenges in distinguishing driver mutations from a multitude of passenger mutations. One solution is to use siRNA knockdown screens on all genes that are mutated in a cell line and assess cell viability. However we demonstrate that inconsistencies in mutational profiling of cell lines and passaging effects have the potential to influence these types of studies. These limitations also offer new explanations for the discrepancies seen when comparing pharmacogenomics studies.

Citation Format: Andrew M. Hudson, Tim Yates, Chris Wirth, Yaoyong Li, Wendy Trotter, Shameem Fawdar, Crispin Miller, John Brognard. The challenges of using large-scale genomics data to identify novel drivers of lung cancer. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A2-18.

Using large-scale genomics data to identify driver mutations in lung cancer: methods and challenges

Lung cancer is the commonest cause of cancer death in the world and carries a poor prognosis for most patients. While precision targeting of mutated proteins has given some successes for never- and light-smoking patients, there are no proven targeted therapies for the majority of smokers with the disease. Despite sequencing hundreds of lung cancers, known driver mutations are lacking for a majority of tumors. Distinguishing driver mutations from inconsequential passenger mutations in a given lung tumor is extremely challenging due to the high mutational burden of smoking-related cancers. Here we discuss the methods employed to identify driver mutations from these large datasets. We examine different approaches based on bioinformatics, in silico structural modeling and biological dependency screens and discuss the limitations of these approaches.

Discrepancies in cancer genomic sequencing highlight opportunities for driver mutation discovery

Cancer genome sequencing is being used at an increasing rate to identify actionable driver mutations that can inform therapeutic intervention strategies. A comparison of two of the most prominent cancer genome sequencing databases from different institutes (Cancer Cell Line Encyclopedia and Catalogue of Somatic Mutations in Cancer) revealed marked discrepancies in the detection of missense mutations in identical cell lines (57.38% conformity). The main reason for this discrepancy is inadequate sequencing of GC-rich areas of the exome. We have therefore mapped over 400 regions of consistent inadequate sequencing (cold-spots) in known cancer-causing genes and kinases, in 368 of which neither institute finds mutations. We demonstrate, using a newly identified PAK4 mutation as proof of principle, that specific targeting and sequencing of these GC-rich cold-spot regions can lead to the identification of novel driver mutations in known tumor suppressors and oncogenes. We highlight that cross-referencing between genomic databases is required to comprehensively assess genomic alterations in commonly used cell lines and that there are still significant opportunities to identify novel drivers of tumorigenesis in poorly sequenced areas of the exome. Finally, we assess other reasons for the observed discrepancy, such as variations in dbSNP filtering and the acquisition/loss of mutations, to give explanations as to why there is a discrepancy in pharmacogenomic studies, given recent concerns with poor reproducibility of data.

Mixed lineage kinases activate MEK independently of RAF to mediate resistance to RAF inhibitors

RAF inhibitor therapy yields significant reductions in tumour burden in the majority of V600E-positive melanoma patients; however, resistance occurs within 2-18 months. Here we demonstrate that the mixed lineage kinases (MLK1-4) are MEK kinases that reactivate the MEK/ERK pathway in the presence of RAF inhibitors. Expression of MLK1-4 mediates resistance to RAF inhibitors and promotes survival in V600E-positive melanoma cell lines. Furthermore, we observe upregulation of the MLKs in 9 of 21 melanoma patients with acquired drug resistance. Consistent with this observation, MLKs promote resistance to RAF inhibitors in mouse models and contribute to acquired resistance in a cell line model. Lastly, we observe that a majority of MLK1 mutations identified in patients are gain-of-function mutations. In summary, our data demonstrate a role for MLKs as direct activators of the MEK/ERK pathway with implications for melanomagenesis and resistance to RAF inhibitors.

Abstract A10: Targeted genetic dependency screen facilitates identification of actionable mutations in FGFR4, MAP3K9, and PAK5 in lung cancer

Approximately 70% of patients with non-small-cell lung cancer present with late-stage disease and have limited treatment options, so there is a pressing need to develop efficacious targeted therapies for these patients. This remains a major challenge as the underlying genetic causes of ~50% of non-small-cell lung cancers remain unknown. We have recently demonstrated that a targeted genetic dependency screen is an efficient approach to identify somatic cancer alterations that are functionally important. By using this approach, we have identified three kinases with gain-of-function mutations in lung cancer, namely FGFR4, MAP3K9, and PAK5 (1). Mutations in these kinases are activating toward the ERK pathway, and targeted depletion of the mutated kinases inhibits proliferation, suppresses constitutive activation of downstream signaling pathways, and results in specific killing of the lung cancer cells. Genomic profiling of patients with lung cancer is ushering in an era of personalized medicine; however, lack of actionable mutations presents a significant hurdle. Our study indicates that targeted genetic dependency screens will be an effective strategy to elucidate somatic variants that are essential for lung cancer cell viability.

Citation Format: Shameem Fawdar, Eleanor W. Trotter, Yaoyong Li, Crispin Miller, John Brognard. Targeted genetic dependency screen facilitates identification of actionable mutations in FGFR4, MAP3K9, and PAK5 in lung cancer. [abstract]. In: Proceedings of the AACR-IASLC Joint Conference on Molecular Origins of Lung Cancer; 2014 Jan 6-9; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2014;20(2Suppl):Abstract nr A10.

Protein kinase cδ deficiency causes mendelian systemic lupus erythematosus with B cell-defective apoptosis and hyperproliferation

OBJECTIVE

Systemic lupus erythematosus (SLE) is a prototype autoimmune disease that is assumed to occur via a complex interplay of environmental and genetic factors. Rare causes of monogenic SLE have been described, providing unique insights into fundamental mechanisms of immune tolerance. The aim of this study was to identify the cause of an autosomal-recessive form of SLE.

METHODS

We studied 3 siblings with juvenile-onset SLE from 1 consanguineous kindred and used next-generation sequencing to identify mutations in the disease-associated gene. We performed extensive biochemical, immunologic, and functional assays to assess the impact of the identified mutations on B cell biology.

RESULTS

We identified a homozygous missense mutation in PRKCD, encoding protein kinase δ (PKCδ), in all 3 affected siblings. Mutation of PRKCD resulted in reduced expression and activity of the encoded protein PKCδ (involved in the deletion of autoreactive B cells), leading to resistance to B cell receptor- and calcium-dependent apoptosis and increased B cell proliferation. Thus, as for mice deficient in PKCδ, which exhibit an SLE phenotype and B cell expansion, we observed an increased number of immature B cells in the affected family members and a developmental shift toward naive B cells with an immature phenotype.

CONCLUSION

Our findings indicate that PKCδ is crucial in regulating B cell tolerance and preventing self-reactivity in humans, and that PKCδ deficiency represents a novel genetic defect of apoptosis leading to SLE.

Targeted genetic dependency screen facilitates identification of actionable mutations in FGFR4, MAP3K9, and PAK5 in lung cancer

Approximately 70% of patients with non-small-cell lung cancer present with late-stage disease and have limited treatment options, so there is a pressing need to develop efficacious targeted therapies for these patients. This remains a major challenge as the underlying genetic causes of ~50% of non-small-cell lung cancers remain unknown. Here we demonstrate that a targeted genetic dependency screen is an efficient approach to identify somatic cancer alterations that are functionally important. By using this approach, we have identified three kinases with gain-of-function mutations in lung cancer, namely FGFR4, MAP3K9, and PAK5. Mutations in these kinases are activating toward the ERK pathway, and targeted depletion of the mutated kinases inhibits proliferation, suppresses constitutive activation of downstream signaling pathways, and results in specific killing of the lung cancer cells. Genomic profiling of patients with lung cancer is ushering in an era of personalized medicine; however, lack of actionable mutations presents a significant hurdle. Our study indicates that targeted genetic dependency screens will be an effective strategy to elucidate somatic variants that are essential for lung cancer cell viability.

Abstract 2999: Targeted depletion of all somatically mutated genes in lung cancer cells facilitates identification of mutationally activated novel drivers of lung cancer

Approximately 70% of all NSCLC patients present with late stage disease (stage III-IV) and there is a pressing need to develop better therapies for these patients. This remains a major challenge as the underlying genetic causes of nearly half of all NSCLCs remain unknown. Recent success with therapies targeting mutationally activated EGFR and constitutively active EML4-ALK serve as proof of principle that drugs targeting genetically activated drivers of lung cancer result in better, more durable therapeutic responses in patients. In an effort to identify novel mutationally activated drivers of lung cancer, we performed a targeted siRNA screen to knockdown all somatically mutated genes in a panel of six NSCLC cell lines. Using this approach we have identified three mutationally activated drivers that include MLK1, PAK7 and FGFR4. We demonstrate that mutations in these genes are activating, that the cancer cells that harbour the genetically activated oncogenes rely on these drivers to maintain cell proliferation and survival and inhibition of these activated kinases results in specific killing of the lung cancer cells. As cancer genomic data accumulates at an unprecedented rate, approaches must be developed to filter through this data to identify druggable drivers that could lead to better therapeutic options for patients in the clinic. Our studies demonstrate that combining targeted siRNA screens with cancer genomics will be a successful approach to identify novel drivers of cancer.

Citation Format: Shameem Fawdar, Eleanor W. Trotter, Yaoyong Li, Sara Ientile, Crispin Miller, John Brognard. Targeted depletion of all somatically mutated genes in lung cancer cells facilitates identification of mutationally activated novel drivers of lung cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2999. doi:10.1158/1538-7445.AM2013-2999