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T-cell receptors (TCR) can recognize the intracellular targets whereas antibodies only recognize the 25% of potential extracellular targets
survivin is expressed in multiple cancers and correlates with poor survival and prognosis
CD3 bispecific TCR to survivn (Ab to CD3 on T- cells and TCR to survivin on cancer cells presented in MHC Class A3)
ABBV184 effective in vivo in lung cancer models as single agent;
in humanized mouse tumor models CD3/survivin bispecific can recruit T cells into solid tumors; multiple immune cells CD4 and CD8 positive T cells were found to infiltrate into tumor
therapeutic window as measured by cytokine release assays in tumor vs. normal cells very wide (>25 fold)
ABBV184 does not bind platelets and has good in vivo safety profile
First- in human dose determination trial: used in vitro cancer cell assays to determine 1st human dose
looking at AML and lung cancer indications
phase 1 trial is underway for safety and efficacy and determine phase 2 dose
survivin has very few mutations so they are not worried about a changing epitope of their target TCR peptide of choice
The discovery of TNO155: A first in class SHP2 inhibitor
SHP2 is an intracellular phosphatase that is upstream of MEK ERK pathway; has an SH2 domain and PTP domain
knockdown of SHP2 inhibits tumor growth and colony formation in soft agar
55 TKIs there are very little phosphatase inhibitors; difficult to target the active catalytic site; inhibitors can be oxidized at the active site; so they tried to target the two domains and developed an allosteric inhibitor at binding site where three domains come together and stabilize it
they produced a number of chemical scaffolds that would bind and stabilize this allosteric site
block the redox reaction by blocking the cysteine in the binding site
lead compound had phototoxicity; used SAR analysis to improve affinity and reduce phototox effects
was very difficult to balance efficacy, binding properties, and tox by adjusting stuctures
TNO155 is their lead into trials
SHP2 expressed in T cells and they find good combo with I/O with uptick of CD8 cells
TNO155 is very selective no SHP1 inhibition; SHP2 can autoinhibit itself when three domains come together and stabilize; no cross reactivity with other phosphatases
they screened 1.5 million compounds and got low hit rate so that is why they needed to chemically engineer and improve on the classes they found as near hits
at the NCI they are pivoting some of their clinical trials to address COVID related issues like trials on tocilizumab and producing longitudinal cohorts of cancer patients and COVID for further analysis and studies
vaccine and antibody efforts at NCI and they are asking all their cancer centers (Cancer COVID Consortium) collecting data
Moonshot is collecting metadata but now COVID data from cellular therapy patients
they are about to publish new grants related to COVID and adding option to investigators to use current funds to do COVID related options
she says if at home take the time to think, write manuscripts, analyze data BE A REVIEWER FOR JOURNALS,
SSMMART project from Moonshot is still active
so far NCI and NIH grant process is ongoing although the peer review process is slower
they have extended deadlines with NO justification required (extend 90 days)
also allowing flexibility on use of grant money and allowing more early investigator rules and lax on those rules
non competitive renewals (type 5) will allow restructuring of project; contact program administrator
she and NCI heard rumors of institutions shutting down cancer research she is stressing to them not to do that
non refundable travel costs may be charged to the grant
NCI contemplating on extending the early investigator time
for more information go to NIH and NCI COVID-19 pages which have more guidances updated regularly
Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Evaluating Cancer Genomics from Normal Tissues Through Metastatic Disease 3:50 PM
Presenter/Authors
Kelly L. Bolton, Ryan N. Ptashkin, Teng Gao, Lior Braunstein, Sean M. Devlin, Minal Patel, Antonin Berthon, Aijazuddin Syed, Mariko Yabe, Catherine Coombs, Nicole M. Caltabellotta, Mike Walsh, Ken Offit, Zsofia Stadler, Choonsik Lee, Paul Pharoah, Konrad H. Stopsack, Barbara Spitzer, Simon Mantha, James Fagin, Laura Boucai, Christopher J. Gibson, Benjamin Ebert, Andrew L. Young, Todd Druley, Koichi Takahashi, Nancy Gillis, Markus Ball, Eric Padron, David Hyman, Jose Baselga, Larry Norton, Stuart Gardos, Virginia Klimek, Howard Scher, Dean Bajorin, Eder Paraiso, Ryma Benayed, Maria Arcilla, Marc Ladanyi, David Solit, Michael Berger, Martin Tallman, Montserrat Garcia-Closas, Nilanjan Chatterjee, Luis Diaz, Ross Levine, Lindsay Morton, Ahmet Zehir, Elli Papaemmanuil. Memorial Sloan Kettering Cancer Center, New York, NY, University of North Carolina at Chapel Hill, Chapel Hill, NC, University of Cambridge, Cambridge, United Kingdom, Dana-Farber Cancer Institute, Boston, MA, Washington University, St Louis, MO, The University of Texas MD Anderson Cancer Center, Houston, TX, Moffitt Cancer Center, Tampa, FL, National Cancer Institute, Bethesda, MD
Abstract
Recent studies among healthy individuals show evidence of somatic mutations in leukemia-associated genes, referred to as clonal hematopoiesis (CH). To determine the relationship between CH and oncologic therapy we collected sequential blood samples from 525 cancer patients (median sampling interval time = 23 months, range: 6-53 months) of whom 61% received cytotoxic therapy or external beam radiation therapy and 39% received either targeted/immunotherapy or were untreated. Samples were sequenced using deep targeted capture-based platforms. To determine whether CH mutational features were associated with tMN risk, we performed Cox proportional hazards regression on 9,549 cancer patients exposed to oncologic therapy of whom 75 cases developed tMN (median time to transformation=26 months). To further compare the genetic and clonal relationships between tMN and the proceeding CH, we analyzed 35 cases for which paired samples were available. We compared the growth rate of the variant allele fraction (VAF) of CH clones across treatment modalities and in untreated patients. A significant increase in the growth rate of CH mutations was seen in DDR genes among those receiving cytotoxic (p=0.03) or radiation therapy (p=0.02) during the follow-up period compared to patients who did not receive therapy. Similar growth rates among treated and untreated patients were seen for non-DDR CH genes such as DNMT3A. Increasing cumulative exposure to cytotoxic therapy (p=0.01) and external beam radiation therapy (2×10-8) resulted in higher growth rates for DDR CH mutations. Among 34 subjects with at least two CH mutations in which one mutation was in a DDR gene and one in a non-DDR gene, we studied competing clonal dynamics for multiple gene mutations within the same patient. The risk of tMN was positively associated with CH in a known myeloid neoplasm driver mutation (HR=6.9, p<10-6), and increased with the total number of mutations and clone size. The strongest associations were observed for mutations in TP53 and for CH with mutations in spliceosome genes (SRSF2, U2AF1 and SF3B1). Lower hemoglobin, lower platelet counts, lower neutrophil counts, higher red cell distribution width and higher mean corpuscular volume were all positively associated with increased tMN risk. Among 35 cases for which paired samples were available, in 19 patients (59%), we found evidence of at least one of these mutations at the time of pre-tMN sequencing and in 13 (41%), we identified two or more in the pre-tMN sample. In all cases the dominant clone at tMN transformation was defined by a mutation seen at CH Our serial sampling data provide clear evidence that oncologic therapy strongly selects for clones with mutations in the DDR genes and that these clones have limited competitive fitness, in the absence of cytotoxic or radiation therapy. We further validate the relevance of CH as a predictor and precursor of tMN in cancer patients. We show that CH mutations detected prior to tMN diagnosis were consistently part of the dominant clone at tMN diagnosis and demonstrate that oncologic therapy directly promotes clones with mutations in genes associated with chemo-resistant disease such as TP53.
therapy resulted also in clonal evolution and saw changes in splice variants and spliceosome
therapy promotes current DDR mutations
clonal hematopoeisis due to selective pressures
mutations, variants number all predictive of myeloid disease
deferring adjuvant therapy for breast cancer patients with patients in highest MDS risk group based on biomarkers, greatly reduced their risk for MDS
Presenter/AuthorsOlivia W. Lee, Akash Mitra, Won-Chul Lee, Kazutaka Fukumura, Hannah Beird, Miles Andrews, Grant Fischer, John N. Weinstein, Michael A. Davies, Jason Huse, P. Andrew Futreal. The University of Texas MD Anderson Cancer Center, TX, The University of Texas MD Anderson Cancer Center, TX, Olivia Newton-John Cancer Research Institute and School of Cancer Medicine, La Trobe University, AustraliaDisclosures O.W. Lee: None. A. Mitra: None. W. Lee: None. K. Fukumura: None. H. Beird: None. M. Andrews: ; Merck Sharp and Dohme. G. Fischer: None. J.N. Weinstein: None. M.A. Davies: ; Bristol-Myers Squibb. ; Novartis. ; Array BioPharma. ; Roche and Genentech. ; GlaxoSmithKline. ; Sanofi-Aventis. ; AstraZeneca. ; Myriad Genetics. ; Oncothyreon. J. Huse: None. P. Futreal: None.
Abstract: Brain metastases (BM) occur in 10-30% of patients with cancer. Approximately 200,000 new cases of brain metastases are diagnosed in the United States annually, with median survival after diagnosis ranging from 3 to 27 months. Recently, studies have identified significant genetic differences between BM and their corresponding primary tumors. It has been shown that BM harbor clinically actionable mutations that are distinct from those in the primary tumor samples. Additional genomic profiling of BM will provide deeper understanding of the pathogenesis of BM and suggest new therapeutic approaches.
We performed whole-exome sequencing of BM and matched tumors from 41 patients collected from renal cell carcinoma (RCC), breast cancer, lung cancer, and melanoma, which are known to be more likely to develop BM. We profiled total 126 fresh-frozen tumor samples and performed subsequent analyses of BM in comparison to paired primary tumor and extracranial metastases (ECM). We found that lung cancer shared the largest number of mutations between BM and matched tumors (83%), followed by melanoma (74%), RCC (51%), and Breast (26%), indicating that cancer type with high tumor mutational burden share more mutations with BM. Mutational signatures displayed limited differences, suggesting a lack of mutagenic processes specific to BM. However, point-mutation heterogeneity revealed that BM evolve separately into different subclones from their paired tumors regardless of cancer type, and some cancer driver genes were found in BM-specific subclones. These models and findings suggest that these driver genes may drive prometastatic subclones that lead to BM. 32 curated cancer gene mutations were detected and 71% of them were shared between BM and primary tumors or ECM. 29% of mutations were specific to BM, implying that BM often accumulate additional cancer gene mutations that are not present in primary tumors or ECM. Co-mutation analysis revealed a high frequency of TP53 nonsense mutation in BM, mostly in the DNA binding domain, suggesting TP53 nonsense mutation as a possible prerequisite for the development of BM. Copy number alteration analysis showed statistically significant differences between BM and their paired tumor samples in each cancer type (Wilcoxon test, p < 0.0385 for all). Both copy number gains and losses were consistently higher in BM for breast cancer (Wilcoxon test, p =1.307e-5) and lung cancer (Wilcoxon test, p =1.942e-5), implying greater genomic instability during the evolution of BM.
Our findings highlight that there are more unique mutations in BM, with significantly higher copy number alterations and tumor mutational burden. These genomic analyses could provide an opportunity for more reliable diagnostic decision-making, and these findings will be further tested with additional transcriptomic and epigenetic profiling for better characterization of BM-specific tumor microenvironments.
are there genomic signatures different in brain mets versus non metastatic or normal?
32 genes from curated databases were different between brain mets and primary tumor
frequent nonsense mutations in TP53
divergent clonal evolution of drivers in BMets from primary
they were able to match BM with other mutational signatures like smokers and lung cancer signatures
Presenter/AuthorsPeter Horak, Malachi Griffith, Arpad Danos, Beth A. Pitel, Subha Madhavan, Xuelu Liu, Jennifer Lee, Gordana Raca, Shirley Li, Alex H. Wagner, Shashikant Kulkarni, Obi L. Griffith, Debyani Chakravarty, Dmitriy Sonkin. National Center for Tumor Diseases, Heidelberg, Germany, Washington University School of Medicine, St. Louis, MO, Mayo Clinic, Rochester, MN, Georgetown University Medical Center, Washington, DC, Dana-Farber Cancer Institute, Boston, MA, Frederick National Laboratory for Cancer Research, Rockville, MD, University of Southern California, Los Angeles, CA, Sunquest, Boston, MA, Baylor College of Medicine, Houston, TX, Memorial Sloan Kettering Cancer Center, New York, NY, National Cancer Institute, Rockville, MDDisclosures P. Horak: None. M. Griffith: None. A. Danos: None. B.A. Pitel: None. S. Madhavan: ; Perthera Inc. X. Liu: None. J. Lee: None. G. Raca: None. S. Li: ; Sunquest Information Systems, Inc. A.H. Wagner: None. S. Kulkarni: ; Baylor Genetics. O.L. Griffith: None. D. Chakravarty: None. D. Sonkin: None.AbstractSomatic variants in cancer-relevant genes are interpreted from multiple partially overlapping perspectives. When considered in discovery and translational research endeavors, it is important to determine if a particular variant observed in a gene of interest is oncogenic/pathogenic or not, as such knowledge provides the foundation on which targeted cancer treatment research is based. In contrast, clinical applications are dominated by diagnostic, prognostic, or therapeutic interpretations which in part also depends on underlying variant oncogenicity/pathogenicity. The Association for Molecular Pathology, the American Society of Clinical Oncology, and the College of American Pathologists (AMP/ASCO/CAP) have published structured somatic variant clinical interpretation guidelines which specifically address diagnostic, prognostic, and therapeutic implications. These guidelines have been well-received by the oncology community. Many variant knowledgebases, clinical laboratories/centers have adopted or are in the process of adopting these guidelines. The AMP/ASCO/CAP guidelines also describe different data types which are used to determine oncogenicity/pathogenicity of a variant, such as: population frequency, functional data, computational predictions, segregation, and somatic frequency. A second collaborative effort created the European Society for Medical Oncology (ESMO) Scale for Clinical Actionability of molecular Targets to provide a harmonized vocabulary that provides an evidence-based ranking system of molecular targets that supports their value as clinical targets. However, neither of these clinical guideline systems provide systematic and comprehensive procedures for aggregating population frequency, functional data, computational predictions, segregation, and somatic frequency to consistently interpret variant oncogenicity/pathogenicity, as has been published in the ACMG/AMP guidelines for interpretation of pathogenicity of germline variants. In order to address this unmet need for somatic variant oncogenicity/pathogenicity interpretation procedures, the Variant Interpretation for Cancer Consortium (VICC, a GA4GH driver project) Knowledge Curation and Interpretation Standards (KCIS) working group (WG) has developed a Standard Operating Procedure (SOP) with contributions from members of ClinGen Somatic Clinical Domain WG, and ClinGen Somatic/Germline variant curation WG using an approach similar to the ACMG/AMP germline pathogenicity guidelines to categorize evidence of oncogenicity/pathogenicity as very strong, strong, moderate or supporting. This SOP enables consistent and comprehensive assessment of oncogenicity/pathogenicity of somatic variants and latest version of an SOP can be found at https://cancervariants.org/wg/kcis/.
best to use this SOP for somatic mutations and not rearangements
variants based on oncogenicity as strong to weak
useful variant knowledge on pathogenicity curated from known databases
the recommendations would provide some guideline on curating unknown somatic variants versus known variants of hereditary diseases
they have not curated RB1 mutations or variants (or for other RBs like RB2? p130?)
test has a specificity over 90% and intended to used along with guideline
The Circulating Cell-free Genome Atlas Study (clinical trial NCT02889978) (CCGA) study divided into three substudies: highest performing assay, refining assay, validation of assays
methylation based assays worked better than sequencing (bisulfite sequencing)
used a machine learning algorithm to help refine assay
prediction was >90%; subgroup for high clinical suspicion of cancer
HCS sensitivity was 100% and specificity very high; but sensitivity on training set was 40% and results may have been confounded by including kidney cancer
TOO tissue of origin was predicted in greater than 99% in both training and validation sets
A first-of-its-kind prospective study of a multi-cancer blood test to screen and manage 10,000 women with no history of cancer
DETECT-A study: prospective interventional study; can multi blood test be used prospectively and can lead to a personalized care; can the screen be used to complement current therapy?
10,000 women aged 65-75; these women could not have previous cancer and conducted through Geisinger Health Network; multi test detects DNA and protein and standard of care screening
the study focused on safety so a committee was consulted on each case, and used a diagnostic PET-CT
blood test alone not good but combined with protein and CT scans much higher (5 fold increase) detection for breast cancer
there are mutiple opportunities yet at same time there are still challenges to utilize these cell free tests in therapeutic monitoring, diagnostic, and screening however sensitivities for some cancers are still too low to use in large scale screening however can supplement current screening guidelines
we have to ask about false positive rate and need to concentrate on prospective studies
we must consider how tests will be used, population health studies will need to show improved survival
Phylogenetic tracking and minimal residual disease detection using ctDNA in early-stage NSCLC: A lung TRACERx study Chris Abbosh@ucl
TRACERx study in collaboration with Charles Swanton.
multiplex PCR to track 200 SNVs: correlate tumor tissue biopsy with ctDNA
spike in assay shows very good sensitivity and specificity for SNVs variants tracked, did over 400 TRACERx libraries
sensitivity increases when tracking more variants but specificity does go down a bit
tracking variants can show evidence of subclonal dynamics and evolution and copy number deletion events; they also show neoantigen editing or changing of their neoantigens
this assay can detect low variants in a reproducible manner
The TRACERx (TRAcking Cancer Evolution through therapy (Rx)) lung study is a multi-million pound research project taking place over nine years, which will transform our understanding of non-small cell lung cancer (NSCLC) and take a practical step towards an era of precision medicine. The study will uncover mechanisms of cancer evolution by analysing the intratumour heterogeneity in lung tumours from approximately 850 patients and tracking its evolutionary trajectory from diagnosis through to relapse. At £14 million, it’s the biggest single investment in lung cancer research by Cancer Research UK, and the start of a strategic UK-wide focus on the disease, aimed at making real progress for patients.
Led by Professor Charles Swanton at UCL, the study will bring together a network of experts from different disciplines to help integrate clinical and genomic data and identify patients who could benefit from trials of new, targeted treatments. In addition, it will use a whole suite of cutting edge analytical techniques on these patients’ tumour samples, giving unprecedented insight into the genomic landscape of primary and metastatic tumours and the impact of treatment upon this landscape.
In future, TRACERx will enable us to define how intratumour heterogeneity impacts upon cancer immunity throughout tumour evolution and therapy. Such studies will help define how the clinical evaluation of intratumour heterogeneity can inform patient stratification and the development of combinatorial therapies incorporating conventional, targeted and immune based therapeutics.
Intratumour heterogeneity is increasingly recognised as a major hurdle to achieve improvements in therapeutic outcome and biomarker validation. Intratumour genetic diversity provides a substrate for tumour adaptation and evolution. However, the evolutionary genomic landscape of non-small cell lung cancer (NSCLC) and how it changes through the disease course has not been studied in detail. TRACERx is a prospective observational study with the following objectives:
Primary Objectives
Define the relationship between intratumour heterogeneity and clinical outcome following surgery and adjuvant therapy (including relationships between intratumour heterogeneity and clinical disease stage and histological subtypes of NSCLC).
Establish the impact of adjuvant platinum-containing regimens upon intratumour heterogeneity in relapsed disease compared to primary resected tumour.
Key Secondary Objectives
Develop and validate an intratumour heterogeneity (ITH) ratio index as a prognostic and predictive biomarker in relation to disease-free survival and overall survival.
Infer a complete picture of NSCLC evolutionary dynamics – define drivers of genomic instability, metastatic progression and drug resistance by identifying and tracking the dynamics of somatic mutational heterogeneity, and chromosomal structural and numerical instability present in the primary tumour and at metastatic sites. Individual tumour phylogenetic tree analysis will:
Establish the order of somatic events in relation to genomic instability onset and metastatic progression
Decipher genetic “bottlenecking” events following metastasis and drug therapy
Establish dynamics of tumour evolution during the disease course from early to late stage NSCLC.
Initiate a longitudinal biobank of circulating tumour cells (CTCs) and circulating-free tumour DNA (cfDNA) to develop analytical methods for the early detection and monitoring of tumour evolution over time.
Develop a longitudinal tissue resource to serve as a platform to assess the relationship between genetic intratumour heterogeneity and the host immune response.
Define relationships between intratumour heterogeneity and targeted/cytotoxic therapeutic outcome.
Use a lung cancer specific gene panel in a certified Good Clinical Practice (GCP) laboratory environment to define clonally dominant disease drivers to address the role of clonal driver dominance in targeted therapeutic response and to guide stratification of lung cancer treatment and future clinical study inclusion (paired primary-metastatic site comparisons in at least 270 patients with relapsed disease).
Utility of longitudinal circulating tumor DNA (ctDNA) modeling to predict RECIST-defined progression in first-line patients with epidermal growth factor receptor mutation-positive (EGFRm) advanced non-small cell lung cancer (NSCLC)
Martin Johnson
Impact of the EML4-ALK fusion variant on the efficacy of lorlatinib in patients (pts) with ALK-positive advanced non-small cell lung cancer (NSCLC) Todd Bauer
Lorlatinib, a smallmolecule inhibitor of ALK and ROS1, was granted accelerated U.S. Food and Drug Administration approval in November 2018 for patients with ALK-positive metastatic NSCLC whose disease has progressed on crizotinib and at least one other ALK inhibitor or whose disease has progressed on alectinib or ceritinib as the first ALK inhibitor therapy for metastatic disease. Todd M. Bauer, MD, a medical oncologist and senior investigator at Sarah Cannon Research Institute/Tennessee Oncology, PLLC, in Nashville, has been very involved with the development of lorlatinib since the beginning. In the following interview, Dr. Bauer discusses some of lorlatinib’s unique toxicities, as well as his first-hand experiences with the drug.
BACKGROUND: Lorlatinib is a potent, brain-penetrant, third-generation inhibitor of ALK and ROS1 tyrosine kinases with broad coverage of ALK mutations. In a phase 1 study, activity was seen in patients with ALK-positive non-small-cell lung cancer, most of whom had CNS metastases and progression after ALK-directed therapy. We aimed to analyse the overall and intracranial antitumour activity of lorlatinib in patients with ALK-positive, advanced non-small-cell lung cancer.
METHODS: In this phase 2 study, patients with histologically or cytologically ALK-positive or ROS1-positive, advanced, non-small-cell lung cancer, with or without CNS metastases, with an Eastern Cooperative Oncology Group performance status of 0, 1, or 2, and adequate end-organ function were eligible. Patients were enrolled into six different expansion cohorts (EXP1-6) on the basis of ALK and ROS1 status and previous therapy, and were given lorlatinib 100 mg orally once daily continuously in 21-day cycles. The primary endpoint was overall and intracranial tumour response by independent central review, assessed in pooled subgroups of ALK-positive patients. Analyses of activity and safety were based on the safety analysis set (ie, all patients who received at least one dose of lorlatinib) as assessed by independent central review. Patients with measurable CNS metastases at baseline by independent central review were included in the intracranial activity analyses. In this report, we present lorlatinib activity data for the ALK-positive patients (EXP1-5 only), and safety data for all treated patients (EXP1-6). This study is ongoing and is registered with ClinicalTrials.gov, number NCT01970865.
FINDINGS: Between Sept 15, 2015, and Oct 3, 2016, 276 patients were enrolled: 30 who were ALK positive and treatment naive (EXP1); 59 who were ALK positive and received previous crizotinib without (n=27; EXP2) or with (n=32; EXP3A) previous chemotherapy; 28 who were ALK positive and received one previous non-crizotinib ALK tyrosine kinase inhibitor, with or without chemotherapy (EXP3B); 112 who were ALK positive with two (n=66; EXP4) or three (n=46; EXP5) previous ALK tyrosine kinase inhibitors with or without chemotherapy; and 47 who were ROS1 positive with any previous treatment (EXP6). One patient in EXP4 died before receiving lorlatinib and was excluded from the safety analysis set. In treatment-naive patients (EXP1), an objective response was achieved in 27 (90·0%; 95% CI 73·5-97·9) of 30 patients. Three patients in EXP1 had measurable baseline CNS lesions per independent central review, and objective intracranial responses were observed in two (66·7%; 95% CI 9·4-99·2). In ALK-positive patients with at least one previous ALK tyrosine kinase inhibitor (EXP2-5), objective responses were achieved in 93 (47·0%; 39·9-54·2) of 198 patients and objective intracranial response in those with measurable baseline CNS lesions in 51 (63·0%; 51·5-73·4) of 81 patients. Objective response was achieved in 41 (69·5%; 95% CI 56·1-80·8) of 59 patients who had only received previous crizotinib (EXP2-3A), nine (32·1%; 15·9-52·4) of 28 patients with one previous non-crizotinib ALK tyrosine kinase inhibitor (EXP3B), and 43 (38·7%; 29·6-48·5) of 111 patients with two or more previous ALK tyrosine kinase inhibitors (EXP4-5). Objective intracranial response was achieved in 20 (87·0%; 95% CI 66·4-97·2) of 23 patients with measurable baseline CNS lesions in EXP2-3A, five (55·6%; 21·2-86·3) of nine patients in EXP3B, and 26 (53·1%; 38·3-67·5) of 49 patients in EXP4-5. The most common treatment-related adverse events across all patients were hypercholesterolaemia (224 [81%] of 275 patients overall and 43 [16%] grade 3-4) and hypertriglyceridaemia (166 [60%] overall and 43 [16%] grade 3-4). Serious treatment-related adverse events occurred in 19 (7%) of 275 patients and seven patients (3%) permanently discontinued treatment because of treatment-related adverse events. No treatment-related deaths were reported.
INTERPRETATION: Consistent with its broad ALK mutational coverage and CNS penetration, lorlatinib showed substantial overall and intracranial activity both in treatment-naive patients with ALK-positive non-small-cell lung cancer, and in those who had progressed on crizotinib, second-generation ALK tyrosine kinase inhibitors, or after up to three previous ALK tyrosine kinase inhibitors. Thus, lorlatinib could represent an effective treatment option for patients with ALK-positive non-small-cell lung cancer in first-line or subsequent therapy.
loratinib could be used for crizotanib resistant tumors based on EML4-ALK variants present in ctDNA
The American Association for Cancer Research (AACR) will hold its Annual Meeting as a Virtual Online Format. Registration is free and open to all, including non members. Please go to
Presentation titles are available through the online meeting planner. The program also includes six virtual poster sessions consisting of brief slide videos. Poster sessions will not be presented live but will be available for viewing on demand. Poster session topics are as follows:
11:45 a.m.-1:30 p.m.
Minisymposium: Emerging Signaling Vulnerabilities in Cancer
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11:45 a.m.-1:15 p.m.
Minisymposium: Advances in Cancer Drug Design and Discovery
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2:00 p.m.-4:50 p.m.
Clinical Plenary: Lung Cancer Targeted Therapy
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1:55 p.m.-4:15 p.m.
Clinical Plenary: Breast Cancer Therapy
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1:30 p.m.-3:30 p.m.
Minisymposium: Drugging Undrugged Cancer Targets
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4:50 p.m.-6:05 p.m.
Symposium: New Drugs on the Horizon 1_______________________
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4:50 p.m.-5:50 p.m.
Minisymposium: Therapeutic Modification of the Tumor Microenvironment or Microbiome
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4:00 p.m.-6:00 p.m.
Minisymposium: Advancing Cancer Research Through An International Cancer Registry: AACR Project GENIE Use Cases__________________________
All session times are EDT.
TUESDAY, APRIL 28
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Channel 3
9:00 a.m.-101:00 a.m.
Clinical Plenary: COVID-19 and Cancer
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11:00 a.m.-1:35 p.m.
Clinical Plenary: Adoptive Cell Transfer Therapy__________________________
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10:45 a.m.-12:30 p.m.
Symposium: New Drugs on the Horizon 2_________________________
Personalized Medicine, Omics, and Health Disparities in Cancer: Can Personalized Medicine Help Reduce the Disparity Problem?
Curator: Stephen J. Williams, PhD
UPDATED: 5/24/2026
Europe’s Medicine Access Crisis: What the Latest Data Means for Lung Cancer
This week, EFPIA published its annual WAIT Report. It tracks how quickly medicines approved by the European Medicines Agency reach people across EU member states. The 2025 data, covering 168 medicines approved between 2021 and 2024, makes for difficult reading.
Nearly half of those medicines, 49%, are not available to people in Europe. That figure has risen from 46% in 2019. The share of medicines fully available on public reimbursement lists has fallen from 42% in 2019 to 28% in 2025. A further 17% are only available under restricted conditions, up from 6% six years ago.
The median time from European marketing authorisation to availability across the continent is 532 days. In Germany, the median wait is 56 days. In Romania, it is 1,201 days. That is a difference of more than three years, for the same medicines, approved by the same regulatory body, for people living on the same continent.
For oncology, the trend is moving in the wrong direction. The average time to availability for cancer medicines has increased year on year. EFPIA’s analysis also flags a declining trend in the number of FDA-approved medicines subsequently approved by the EMA, with a particularly steep drop since October 2025.
These are system-level statistics. But behind every number is a person whose treatment options are shaped not by what science has made possible, but by where in Europe they happen to live.
What this means for lung cancer
Lung cancer is the leading cause of cancer-related death in Europe. It is also one of the most rapidly evolving areas of oncology. New treatment options, particularly in molecularly defined subtypes, have transformed outcomes for some groups over the past decade. The pipeline continues to produce results that would have been unimaginable ten years ago.
Yet the treatments that reach people in countries with faster, better-resourced reimbursement systems are the same treatments that remain unavailable or restricted for years in others. EFPIA’s data shows that Germany had 156 of the 168 tracked medicines available. Malta had 22. The gap between the best and worst performing countries in terms of availability was 88%.
This is not a question of what medicine can offer. It is a question of whether health systems, reimbursement frameworks, and pricing negotiations are structured in a way that gets treatments to the people who need them. As Lung Cancer Europe President Debra Montague wrote in her 2025-2026 Annual Report, “it has become clearer that these advancements are not reaching everyone equally.”
What people impacted by lung cancer are telling us
Access to approved medicines is one dimension of a broader picture. Lung Cancer Europe’s own research, drawn from surveys of more than 2,000 people impacted by lung cancer across 34 European countries, consistently shows that the challenges people face extend well beyond whether a medicine has been reimbursed.
Our 9th Report, published in November 2024, found that 40% of respondents did not receive enough information about their diagnosis, treatment, and care. Half received no information about alternative treatment options at all. Nearly nine in ten sought information outside the healthcare system, and one in four either could not find what they needed or encountered information that was inaccurate or unproven. Complex information was identified as the single biggest barrier to meaningful participation in treatment decisions.
Our 11th Report, launched in March 2026, focused on mental health. An average of 89.3% of all respondents experienced significant emotional difficulties following diagnosis. 31% received no mental health support at any point during their care. The burden falls unevenly. People living with small cell lung cancer reported the highest levels of distress, with 66.2% reporting a negative impact on their mental health. 74.3% were never referred to a patient organisation by their healthcare provider. People who had not undergone biomarker testing reported the poorest mental health outcomes of any group surveyed.
There is also a clear geographic dimension to mental health outcomes, one that maps closely onto the geographic inequality in treatment access that the EFPIA data describes. Respondents in Italy, Switzerland, and Denmark reported higher mental health scores. Those in Slovenia, Ukraine, and Greece reported the greatest negative psychological impact.
The pattern is consistent. Where people live in Europe determines not only which medicines are available to them, but the quality of information they receive, the extent to which they are involved in decisions about their own care, and the likelihood that their psychological wellbeing will be supported throughout the course of their illness.
What needs to change
The EFPIA report identifies the causes of these delays as multifactorial: slow regulatory processes, misalignment on evidence requirements, insufficient budgets in member states, and commercial decisions about where and when to launch. There is no single lever to pull. But the trend lines are moving in a direction that demands urgent attention from policymakers, health systems, and all stakeholders with a role in how medicines reach people.
Lung Cancer Europe calls on policymakers and healthcare providers across Europe to treat equitable access to treatment as a priority, not an aspiration. This means faster and more consistent reimbursement processes across member states, a commitment to closing the information gap that leaves too many people without the knowledge to understand and advocate for their own care, and the integration of psychological support as a standard component of the lung cancer care pathway.
The pipeline itself is also under pressure. New data published alongside the WAIT report shows a declining trend in the number of medicines approved by the US Food and Drug Administration that subsequently receive approval from the European Medicines Agency, with a particularly steep drop recorded since October 2025. For people living with lung cancer, where so many treatment advances in molecularly defined subtypes have originated from the global pipeline, a narrowing of what reaches European regulators at all would compound the access inequalities this data already describes.
The medicines exist. The evidence base is growing. The responsibility now is to ensure that what is possible for some becomes available to all.
In a Science Perspectives article by Timothy Rebbeck, health disparities, specifically cancer disparities existing in the sub-Saharan African (SSA) nations, highlighting the cancer incidence disparities which exist compared with cancer incidence in high income areas of the world [1]. The sub-Saharan African nations display a much higher incidence of prostate, breast, and cervix cancer and these cancers are predicted to double within the next twenty years, according to IARC[2]. Most importantly,
the histopathologic and demographic features of these tumors differ from those in high-income countries
meaning that the differences seen in incidence may reflect a true health disparity as increases rates in these cancers are not seen in high income countries (HIC).
Most frequent male cancers in SSA include prostate, lung, liver, leukemia, non-Hodgkin’s lymphoma, and Kaposi’s sarcoma (a cancer frequently seen in HIV infected patients [3]). In SSA women, breast and cervical cancer are the most common and these display higher rates than seen in high income countries. In fact, liver cancer is seen in SSA females at twice the rate, and in SSA males almost three times the rate as in high income countries.
Reasons for cancer disparity in SSA
Patients with cancer are often diagnosed at a late stage in SSA countries. This contrasts with patients from high income countries, which have their cancers usually diagnosed at an earlier stage, and with many cancers, like breast[4], ovarian[5, 6], and colon, detecting the tumor in the early stages is critical for a favorable outcome and prognosis[7-10]. In addition, late diagnosis also limits many therapeutic options for the cancer patient and diseases at later stages are much harder to manage, especially with respect to unresponsiveness and/or resistance of many therapies. In addition, treatments have to be performed in low-resource settings in SSA, and availability of clinical lab work and imaging technologies may be limited.
Molecular differences in SSA versus HIC cancers which may account for disparities
Emerging evidence suggests that there are distinct molecular signatures with SSA tumors with respect to histotype and pathology. For example Dr. Rebbeck mentions that Nigerian breast cancers were defined by increased mutational signatures associated with deficiency of the homologous recombination DNA repair pathway, pervasive mutations in the tumor suppressor gene TP53, mutations in GATA binding protein 3 (GATA3), and greater mutational burden, compared with breast tumors from African Americans or Caucasians[11]. However more research will be required to understand the etiology and causal factors related to this molecular distinction in mutational spectra.
It is believed that there is a higher rate of hereditary cancers in SSA. And many SSA cancers exhibit the more aggressive phenotype than in other parts of the world. For example breast tumors in SSA black cases are twice as likely than SSA Caucasian cases to be of the triple negative phenotype, which is generally more aggressive and tougher to detect and treat, as triple negative cancers are HER2 negative and therefore are not a candidate for Herceptin. Also BRCA1/2 mutations are more frequent in black SSA cases than in Caucasian SSA cases [12, 13].
Initiatives to Combat Health Disparities in SSA
Multiple initiatives are being proposed or in action to bring personalized medicine to the sub-Saharan African nations. These include:
H3Africa empowers African researchers to be competitive in genomic sciences, establishes and nurtures effective collaborations among African researchers on the African continent, and generates unique data that could be used to improve both African and global health.
There is currently a global effort to apply genomic science and associated technologies to further the understanding of health and disease in diverse populations. These efforts work to identify individuals and populations who are at risk for developing specific diseases, and to better understand underlying genetic and environmental contributions to that risk. Given the large amount of genetic diversity on the African continent, there exists an enormous opportunity to utilize such approaches to benefit African populations and to inform global health.
The Human Heredity and Health in Africa (H3Africa) consortium facilitates fundamental research into diseases on the African continent while also developing infrastructure, resources, training, and ethical guidelines to support a sustainable African research enterprise – led by African scientists, for the African people. The initiative consists of 51 African projects that include population-based genomic studies of common, non-communicable disorders such as heart and renal disease, as well as communicable diseases such as tuberculosis. These studies are led by African scientists and use genetic, clinical, and epidemiologic methods to identify hereditary and environmental contributions to health and disease. To establish a foundation for African scientists to continue this essential work into the future work, the consortium also supports many crucial capacity building elements, such as: ethical, legal, and social implications research; training and capacity building for bioinformatics; capacity for biobanking; and coordination and networking.
Advancing precision medicine in a way that is equitable and beneficial to society means ensuring that healthcare systems can adopt the most scientifically and technologically appropriate approaches to a more targeted and personalized way of diagnosing and treating disease. In certain instances, countries or institutions may be able to bypass, or “leapfrog”, legacy systems or approaches that prevail in developed country contexts.
The World Economic Forum’s Leapfrogging with Precision Medicine project will develop a set of tools and case studies demonstrating how a precision medicine approach in countries with greenfield policy spaces can potentially transform their healthcare delivery and outcomes. Policies and governance mechanisms that enable leapfrogging will be iterated and scaled up to other projects.
Successes in personalized genomic research in SSA
As Dr. Rebbeck states:
Because of the underlying genetic and genomic relationships between Africans and members of the African diaspora (primarily in North America and Europe), knowledge gained from research in SSA can be used to address health disparities that are prevalent in members of the African diaspora.
For example members of the West African heritage and genomic ancestry has been reported to confer the highest genomic risk for prostate cancer in any worldwide population [14].
Science 03 Jan 2020:
Vol. 367, Issue 6473, pp. 27-28
DOI: 10.1126/science.aay474
Summary/Abstract
Cancer is an increasing global public health burden. This is especially the case in sub-Saharan Africa (SSA); high rates of cancer—particularly of the prostate, breast, and cervix—characterize cancer in most countries in SSA. The number of these cancers in SSA is predicted to more than double in the next 20 years (1). Both the explanations for these increasing rates and the solutions to address this cancer epidemic require SSA-specific data and approaches. The histopathologic and demographic features of these tumors differ from those in high-income countries (HICs). Basic knowledge of the epidemiology, clinical features, and molecular characteristics of cancers in SSA is needed to build prevention and treatment tools that will address the future cancer burden. The distinct distribution and determinants of cancer in SSA provide an opportunity to generate knowledge about cancer risk factors, genomics, and opportunities for prevention and treatment globally, not only in Africa.
Parkin DM, Ferlay J, Jemal A, Borok M, Manraj S, N’Da G, Ogunbiyi F, Liu B, Bray F: Cancer in Sub-Saharan Africa: International Agency for Research on Cancer; 2018.
Chinula L, Moses A, Gopal S: HIV-associated malignancies in sub-Saharan Africa: progress, challenges, and opportunities. Current opinion in HIV and AIDS 2017, 12(1):89-95.
Colditz GA: Epidemiology of breast cancer. Findings from the nurses’ health study. Cancer 1993, 71(4 Suppl):1480-1489.
Hamilton TC, Penault-Llorca F, Dauplat J: [Natural history of ovarian adenocarcinomas: from epidemiology to experimentation]. Contracept Fertil Sex 1998, 26(11):800-804.
Garner EI: Advances in the early detection of ovarian carcinoma. J Reprod Med 2005, 50(6):447-453.
Brockbank EC, Harry V, Kolomainen D, Mukhopadhyay D, Sohaib A, Bridges JE, Nobbenhuis MA, Shepherd JH, Ind TE, Barton DP: Laparoscopic staging for apparent early stage ovarian or fallopian tube cancer. First case series from a UK cancer centre and systematic literature review. European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology 2013, 39(8):912-917.
Kolligs FT: Diagnostics and Epidemiology of Colorectal Cancer. Visceral medicine 2016, 32(3):158-164.
Rocken C, Neumann U, Ebert MP: [New approaches to early detection, estimation of prognosis and therapy for malignant tumours of the gastrointestinal tract]. Zeitschrift fur Gastroenterologie 2008, 46(2):216-222.
Srivastava S, Verma M, Henson DE: Biomarkers for early detection of colon cancer. Clinical cancer research : an official journal of the American Association for Cancer Research 2001, 7(5):1118-1126.
Pitt JJ, Riester M, Zheng Y, Yoshimatsu TF, Sanni A, Oluwasola O, Veloso A, Labrot E, Wang S, Odetunde A et al: Characterization of Nigerian breast cancer reveals prevalent homologous recombination deficiency and aggressive molecular features. Nature communications 2018, 9(1):4181.
Zheng Y, Walsh T, Gulsuner S, Casadei S, Lee MK, Ogundiran TO, Ademola A, Falusi AG, Adebamowo CA, Oluwasola AO et al: Inherited Breast Cancer in Nigerian Women. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2018, 36(28):2820-2825.
Rebbeck TR, Friebel TM, Friedman E, Hamann U, Huo D, Kwong A, Olah E, Olopade OI, Solano AR, Teo SH et al: Mutational spectrum in a worldwide study of 29,700 families with BRCA1 or BRCA2 mutations. Human mutation 2018, 39(5):593-620.
Lachance J, Berens AJ, Hansen MEB, Teng AK, Tishkoff SA, Rebbeck TR: Genetic Hitchhiking and Population Bottlenecks Contribute to Prostate Cancer Disparities in Men of African Descent. Cancer research 2018, 78(9):2432-2443.
Other articles on Cancer Health Disparities and Genomics on this Online Open Access Journal Include:
Leaders in Pharmaceutical Business Intelligence (LPBI) Group, Newsletter #1 – February 2020
Welcome to the premier issue of LPBI Group News, where readers can find relevant news and updates about science, business and medical innovation. This newsletter is distributed as a service for our readers.
The Conference Forum Highlights Immuno-Oncology 360° in New York
The Conference Forum is hosting Immuno-Oncology 360°, which reports on current data and developments of immuno-oncology in the science and business communities. The summit takes place on February 26-28 at the Crowne Plaza Times Square in New York.
Please visit www.io360summit.com to register and use code LPBI20 for a 20% discount.
e-Proceedings of 15th Annual Personalized Medicine Conference at Harvard Medical School
The 15th Annual Personalized Medicine Conference at Harvard Medical School, Boston last year [November 13-14, 2019], entitled The Paradigm Evolves, explored the science, business and policy issues facing personalized medicine. In today’s world, scientists need to understand how molecular diagnostics augmented by artificial intelligence, data analytics and digital health empowers physicians and patients in their health care decisions.
Please visit for LPBI Group coverage of the meeting, including social media activities at the conference:
3D Medical BioPrinting Technology Featured in Podcast
LPBI Group leaders, Aviva Lev-Ari, Ph.D., R.N., Stephen Williams, Ph.D., and Irina Robu, Ph.D., spoke with Partners in Health and Biz, a half-hour audio podcast that reaches 40,000 listeners, about the topic of 3D Medical BioPrinting Technology: A Revolution in Medicine.
The 3D BioPrinting technology is being used to develop advanced medical practices that will help with previously difficult processes, such as delivering drugs via micro-robots, targeting specific cancer cells and even assisting in difficult eye operations.
The table of contents in this book includes: Chapter 1: 3D Bioprinting: Latest Innovations in a Forty year-old Technology. Chapter 2: LPBI Initiative on 3D BioPrinting, Chapter 3: Cardiovascular BioPrinting, Chapter 4: Medical and Surgical Repairs – Advances in R&D Research, Chapter 5: Organ on a Chip, Chapter 6: FDA Regulatory Technology Issues, Chapter 7: DNA Origami, Chapter 8: Aptamers and 3D Scaffold Binding, Chapter 9: Advances and Future Prospects, Chapter 10: BioInks and MEMS, Chapter 11: BioMedical MEMS, Chapter 12: 3D Solid Organ Printing and Chapter 13: Medical 3D Printing: Sources and Trade Groups – List of Secondary Material.
New e-Book: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS & BioInformatics, Simulations and the Genome Ontology
LPBI Group’s latest e-book entitled, Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS &BioInformatics, Simulations and the Genome Ontology, offers the reader content curation with embedded videos and audio podcasts, real-time conference e-Proceedings by LPBI’s scientists and professors and archived tweets of quotes from speakers at leading biotechnology conferences.
The book integrates in a single volume four distinct perspectives: basic science, technologies and methodologies, clinical aspects and business and legal aspects of genomics research. “The materials in this book represents the scientific frontier in Biological Sciences and Medicine related to the genomics aspects of disease onset,” said Aviva Lev-Ari, Ph.D., R.N., and founder of LPBI Group.
The book addresses:
aspects of life: the Cell, the Organ, the Human Body and Human Populations;
methodologies of genomic data analysis: Next Generation Sequencing, Gene Editing, AI, Single Cell Genomics, Evolution Biology Genomics, Simulation Modeling in Genomics, Genotypes and Phenotypes Modeling, measurement of Epigenomics effects on disease, and developments in Pharmaco-Genomics.
Additionally, artificial Intelligence in medicine is covered in Part 3 of the e-Book, which represents the frontier in this emerging field, with topics, such as the science, technologies and methodologies, clinical aspects, business and legal implications as well as the latest machine learning algorithms harnessed for medical diagnosis.
This e-book is significant because it:
contains 326 articles on topics, such as gene editing, bioinformatics and genome ontology;
incorporates 74e-Proceedings created in real time by the Book’s authors and editors
includes four collectionsof Tweets representing quotes from speakers at global leading conferences on Genomics
has 13 locationsof Videos and Audio Podcasts that serve to enrich the e-Reader’s experience.
Science 07 Jun 2019:
Vol. 364, Issue 6444, pp. 941-942
DOI: 10.1126/science.aaw8299
Precision medicine is at a crossroads. Progress toward its central goal, to address persistent health inequities, will depend on enrolling populations in research that have been historically underrepresented, thus eliminating longstanding exclusions from such research (1). Yet the history of ethical violations related to protocols for inclusion in biomedical research, as well as the continued misuse of research results (such as white nationalists looking to genetic ancestry to support claims of racial superiority), continue to engender mistrust among these populations (2). For precision medicine research (PMR) to achieve its goal, all people must believe that there is value in providing information about themselves and their families, and that their participation will translate into equitable distribution of benefits. This requires an ethics of inclusion that considers what constitutes inclusive practices in PMR, what goals and values are being furthered through efforts to enhance diversity, and who participates in adjudicating these questions. The early stages of PMR offer a critical window in which to intervene before research practices and their consequences become locked in (3).
Initiatives such as the All of Us program have set out to collect and analyze health information and biological samples from millions of people (1). At the same time, questions of trust in biomedical research persist. For example, although the recent assertions of white nationalists were eventually denounced by the American Society of Human Genetics (4), the misuse of ancestry testing may have already undermined public trust in genetic research.
There are also infamous failures in research that included historically underrepresented groups, including practices of deceit, as in the Tuskegee Syphilis Study, or the misuse of samples, as with the Havasupai tribe (5). Many people who are being asked to give their data and samples for PMR must not only reconcile such past research abuses, but also weigh future risks of potential misuse of their data.
To help assuage these concerns, ongoing PMR studies should open themselves up to research, conducted by social scientists and ethicists, that examines how their approaches enhance diversity and inclusion. Empirical studies are needed to account for how diversity is conceptualized and how goals of inclusion are operationalized throughout the life course of PMR studies. This is not limited to selection and recruitment of populations but extends to efforts to engage participants and communities, through data collection and measurement, and interpretations and applications of study findings. A commitment to transparency is an important step toward cultivating public trust in PMR’s mission and practices.
From Inclusion to Inclusive
The lack of diverse representation in precision medicine and other biomedical research is a well-known problem. For example, rare genetic variants may be overlooked—or their association with common, complex diseases can be misinterpreted—as a result of sampling bias in genetics research (6). Concentrating research efforts on samples with largely European ancestry has limited the ability of scientists to make generalizable inferences about the relationships among genes, lifestyle, environmental exposures, and disease risks, and thereby threatens the equitable translation of PMR for broad public health benefit (7).
However, recruiting for diverse research participation alone is not enough. As with any push for “diversity,” related questions arise about how to describe, define, measure, compare, and explain inferred similarities and differences among individuals and groups (8). In the face of ambivalence about how to represent population variation, there is ample evidence that researchers resort to using definitions of diversity that are heterogeneous, inconsistent, and sometimes competing (9). Varying approaches are not inherently problematic; depending on the scientific question, some measures may be more theoretically justified than others and, in many cases, a combination of measures can be leveraged to offer greater insight (10). For example, studies have shown that American adults who do not self-identify as white report better mental and physical health if they think others perceive them as white (11, 12).
The benefit of using multiple measures of race and ancestry also extends to genetic studies. In a study of hypertension in Puerto Rico, not only did classifications based on skin color and socioeconomic status better predict blood pressure than genetic ancestry, the inclusion of these sociocultural measures also revealed an association between a genetic polymorphism and hypertension that was otherwise hidden (13). Thus, practices that allow for a diversity of measurement approaches, when accompanied by a commitment to transparency about the rationales for chosen approaches, are likely to benefit PMR research more than striving for a single gold standard that would apply across all studies. These definitional and measurement issues are not merely semantic. They also are socially consequential to broader perceptions of PMR research and the potential to achieve its goals of inclusion.
Study Practices, Improve Outcomes
Given the uncertainty and complexities of the current, early phase of PMR, the time is ripe for empirical studies that enable assessment and modulation of research practices and scientific priorities in light of their social and ethical implications. Studying ongoing scientific practices in real time can help to anticipate unintended consequences that would limit researchers’ ability to meet diversity recruitment goals, address both social and biological causes of health disparities, and distribute the benefits of PMR equitably. We suggest at least two areas for empirical attention and potential intervention.
First, we need to understand how “upstream” decisions about how to characterize study populations and exposures influence “downstream” research findings of what are deemed causal factors. For example, when precision medicine researchers rely on self-identification with U.S. Census categories to characterize race and ethnicity, this tends to circumscribe their investigation of potential gene-environment interactions that may affect health. The convenience and routine nature of Census categories seemed to lead scientists to infer that the reasons for differences among groups were self-evident and required no additional exploration (9). The ripple effects of initial study design decisions go beyond issues of recruitment to shape other facets of research across the life course of a project, from community engagement and the return of results to the interpretation of study findings for human health.
Second, PMR studies are situated within an ecosystem of funding agencies, regulatory bodies, disciplines, and other scholars. This partly explains the use of varied terminology, different conceptual understandings and interpretations of research questions, and heterogeneous goals for inclusion. It also makes it important to explore how expectations related to funding and regulation influence research definitions of diversity and benchmarks for inclusion.
For example, who defines a diverse study population, and how might those definitions vary across different institutional actors? Who determines the metrics that constitute successful inclusion, and why? Within a research consortium, how are expectations for data sharing and harmonization reconciled with individual studies’ goals for recruitment and analysis? In complex research fields that include multiple investigators, organizations, and agendas, how are heterogeneous, perhaps even competing, priorities negotiated? To date, no studies have addressed these questions or investigated how decisions facilitate, or compromise, goals of diversity and inclusion.
The life course of individual studies and the ecosystems in which they reside cannot be easily separated and therefore must be studied in parallel to understand how meanings of diversity are shaped and how goals of inclusion are pursued. Empirically “studying the studies” will also be instrumental in creating mechanisms for transparency about how PMR is conducted and how trade-offs among competing goals are resolved. Establishing open lines of inquiry that study upstream practices may allow researchers to anticipate and address downstream decisions about how results can be interpreted and should be communicated, with a particular eye toward the consequences for communities recruited to augment diversity. Understanding how scientists negotiate the challenges and barriers to achieving diversity that go beyond fulfilling recruitment numbers is a critical step toward promoting meaningful inclusion in PMR.
Transparent Reflection, Cultivation of Trust
Emerging research on public perceptions of PMR suggests that although there is general support, questions of trust loom large. What we learn from studies that examine on-the-ground approaches aimed at enhancing diversity and inclusion, and how the research community reflects and responds with improvements in practices as needed, will play a key role in building a culture of openness that is critical for cultivating public trust.
Cultivating long-term, trusting relationships with participants underrepresented in biomedical research has been linked to a broad range of research practices. Some of these include the willingness of researchers to (i) address the effect of history and experience on marginalized groups’ trust in researchers and clinicians; (ii) engage concerns about potential group harms and risks of stigmatization and discrimination; (iii) develop relationships with participants and communities that are characterized by transparency, clear communication, and mutual commitment; and (iv) integrate participants’ values and expectations of responsible oversight beyond initial informed consent (14). These findings underscore the importance of multidisciplinary teams that include social scientists, ethicists, and policy-makers, who can identify and help to implement practices that respect the histories and concerns of diverse publics.
A commitment to an ethics of inclusion begins with a recognition that risks from the misuse of genetic and biomedical research are unevenly distributed. History makes plain that a multitude of research practices ranging from unnecessarily limited study populations and taken-for-granted data collection procedures to analytic and interpretive missteps can unintentionally bolster claims of racial superiority or inferiority and provoke group harm (15). Sustained commitment to transparency about the goals, limits, and potential uses of research is key to further cultivating trust and building long-term research relationships with populations underrepresented in biomedical studies.
As calls for increasing diversity and inclusion in PMR grow, funding and organizational pathways must be developed that integrate empirical studies of scientific practices and their rationales to determine how goals of inclusion and equity are being addressed and to identify where reform is required. In-depth, multidisciplinary empirical investigations of how diversity is defined, operationalized, and implemented can provide important insights and lessons learned for guiding emerging science, and in so doing, meet our ethical obligations to ensure transparency and meaningful inclusion.
New Mutant KRAS Inhibitors Are Showing Promise in Cancer Clinical Trials: Hope For the Once ‘Undruggable’ Target, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)
New Mutant KRAS Inhibitors Are Showing Promise in Cancer Clinical Trials: Hope For the Once ‘Undruggable’ Target
Curator: Stephen J. Williams, Ph.D.
UPDATED 10/2/2021
A Newly Identified Mutant RAS G12C GTPase Activating Protein (GAP) may lead to discovery of new class of RAS inhibitors
From the journal Science in Filling in the GAPs in understanding RAS: A newly identified regulator increases the efficacy of a new class of targeted anti-RAS drugs.
According to canonical thinking, mutationally activated RAS (constitutive activation) is insensitive to GTPase-activating proteins (GAPs). GAPs accelerated the conversion of GTP bound to RAS to GDP, a critical step in the inactivation of RAS signaling cycle. However a small molecule has just been FDA approved, sotorasib, in cancer cells by binding only the GDP bound KRAS G12C mutant. A few non small cell lung cancers (NSCLC) are resistant to another such inhibitor, adagrasib. In the same Science issue, another paper by Li et. al. explains the potential that a GAP, RGS3, may play in this conundrum and demonstrates that certain other inhibitors of the RAS cycle, mainly the GEF (guanine exchange factor) SOS1, in combination with MEK inhibitors may circumvent this resistance.
Inhibitors of mutant KRAS
The KRASG12C (Gly12→Cys) mutant is refractory to canonical GAPs, p120 RASGAP and neurofibromin, but not RGS3, which promotes GTP hydrolysis. The resulting GDP-bound KRASG12C is an anticancer drug target. Combination with inhibitors of SOS1 or with inhibitors of downstream signaling may further improve efficacy.
There is now considerable and increasing evidence for a causal role of aberrant activity of the Ras superfamily of small GTPases in human cancers. These GTPases act as GDP-GTP-regulated binary switches that control many fundamental cellular processes. A common mechanism of GTPase deregulation in cancer is the deregulated expression and/or activity of their regulatory proteins, guanine nucleotide exchange factors (GEFs) that promote formation of the active GTP-bound state and GTPase activating proteins (GAPs) that return the GTPase to its GDP-bound inactive state. We assess the association of GEFs and GAPs with cancer and their druggability for cancer therapeutics.
Box 1
Ras superfamily of small GTPases
The human Ras superfamily comprised of over 150 members which is divided into five major branches on the basis of sequence and functional similarities1, 2. In addition to the three Ras isoforms, other members of the Ras family with important roles in cancer include Rheb and Ral proteins. The ~20 kDa core G domain (corresponding to Ras residues 4–166) is conserved among all Ras superfamily proteins and is involved in GTP binding and hydrolysis148. This domain is comprised of five conserved guanine nucleotide consensus sequence elements (Ras residue numbering) involved in binding phosphate/Mg2+ (PM) or the guanine base (G). The switch I (Ras residues 30–38) and II (59–76) regions change in conformation during GDP-GTP cycling and contribute to preferential effector binding to the GTP-bound state and the core effector domain (E; Ras residues 32–40). Ras and Rho family proteins have additional C-terminal hypervariable (HV) sequences that commonly terminate with a CAAX motif that signals for farnesyl or geranylgeranyl isoprenoid addition to the cysteine residue, proteolytic removal of the AAX residues and carboxylmethylation of the prenylated cysteine. Some are modified additionally by a palmitate fatty acid to cysteine residues in the HV sequence that contributes to membrane association. Rab proteins also contain a C-terminal HV region that terminates with cysteine-containing motifs that are modified by addition of geranylgeranyl lipids, with some undergoing carboxylmethylation. Arf family proteins are characterized by an N-terminal extension involved in membrane interaction, with some cotranslationally modified by addition of a myristate fatty acid. Ran is not lipid modified but contains a C-terminal extension that is essential for function. Rho proteins are characterized by an up to 13 amino acid “Rho insert” sequence positioned between Ras residues 122 and 123 involved in effector regulation.
The GDP-GTP cycle
Ras superfamily proteins possess intrinsic guanine nucleotide exchange and GTP hydrolysis activities. However, these activities are too low to allow efficient and rapid cycling between their active GTP-bound and inactive GDP-bound states. GEFs and GAPs accelerate and regulate these intrinsic activities. Members of the different branches of the superfamily are regulated by GEFs and GAPs with structurally distinct catalytic domains3, 4, 149–152. Here we have utilized the Rho family as an example to illustrate the complexity of this process, where multiple GEFs and GAPs may regulate one specific GTPase. For the 20 human Rho GTPases there are 83 GEFs and 67 GAPs and a subset of Rho GTPases are not likely regulated by GEFs and GAPs (e.g., Rnd3/RhoE). Rho GTPases are activated by distinct RhoGEF families. Dbl family RhoGEFs (68) possesses a tandem Dbl homology (DH) catalytic and pleckstrin homology (PH) regulatory domain topology. DOCK family RhoGEFs (11) are characterized by two regions of high sequence conservation that are designated Dock-homology region regulatory DHR-1 and catalytic DHR-2 domains. Two other RhoGEFs have been described (SWAP70 and SLAT) contain a PH but no DH domain (2) and smgGDS (1) is an unusual GEF in that it functions as a GEF for some Rho as well as non-Rho family GTPases. At least 24 Dbl RhoGEFs have been reported to activate RhoA151. Rho (and Rab) GTPases are also controlled by a third class of regulatory proteins, Rho dissociation inhibitors (RhoGDI) (of which there are 3) whose main function involves regulation of Rho GTPase membrane association by masking the isoprenoid group.
So GEFs like SOS 1,2,3 are responsible for activation of the G Protien RAS upon Receptor Tyrosine Kinase (RTK) activation by a multitude of growth factors. The GAPs are responsible for termination of the activated RAS cycle and now RAS, in its normal unmuted version, can now be activated again. The G12C mutant keeps RAS in its activated state as GAPs cannot fascilitate the hydroylsis of GTP.
Li et al. (in this issue) theorized that there must be cellular factors that stimulate formation of GDP-bound KRAS G12C, enabling its vulnerability to KRAS G12C inhibitors, and discovered a regulator of G protein signaling 3 (RGS3), which had GAP activity previously for heterotrimeric G proteins GαI and Gαq with unexpected GAP activity for the KRAS G12C mutant. They also found the fully activated GTP bound KRAS G12C is dependent on RTK-mediated activation of SOS1. This suggested that SOS1 inhibitors with MEK inhibitors could be effective against mutant KRAS.
The paper by Li is summarized below:
The G protein signaling regulator RGS3 enhances the GTPase activity of KRAS
Recently reported to be effective in patients with lung cancer, KRASG12C inhibitors bind to the inactive, or guanosine diphosphate (GDP)–bound, state of the oncoprotein and require guanosine triphosphate (GTP) hydrolysis for inhibition. However, KRAS mutations prevent the catalytic arginine of GTPase-activating proteins (GAPs) from enhancing an otherwise slow hydrolysis rate. If KRAS mutants are indeed insensitive to GAPs, it is unclear how KRASG12C hydrolyzes sufficient GTP to allow inactive state–selective inhibition. Here, we show that RGS3, a GAP previously known for regulating G protein–coupled receptors, can also enhance the GTPase activity of mutant and wild-type KRAS proteins. Our study reveals an unexpected mechanism that inactivates KRAS and explains the vulnerability to emerging clinically effective therapeutics.
UPDATED 09/26/2021
The KRAS G12C Inhibitor MRTX849 Provides Insight toward Therapeutic Susceptibility of KRAS-Mutant Cancers in Mouse Models and Patients
Source: Hallin J, Engstrom LD, Hargis L, Calinisan A, Aranda R, Briere DM, Sudhakar N, Bowcut V, Baer BR, Ballard JA, Burkard MR, Fell JB, Fischer JP, Vigers GP, Xue Y, Gatto S, Fernandez-Banet J, Pavlicek A, Velastagui K, Chao RC, Barton J, Pierobon M, Baldelli E, Patricoin EF 3rd, Cassidy DP, Marx MA, Rybkin II, Johnson ML, Ou SI, Lito P, Papadopoulos KP, Jänne PA, Olson P, Christensen JG. The KRASG12C Inhibitor MRTX849 Provides Insight toward Therapeutic Susceptibility of KRAS-Mutant Cancers in Mouse Models and Patients. Cancer Discov. 2020 Jan;10(1):54-71. doi: 10.1158/2159-8290.CD-19-1167. Epub 2019 Oct 28. PMID: 31658955; PMCID: PMC6954325.
Abstract
Despite decades of research, efforts to directly target KRAS have been challenging. MRTX849 was identified as a potent, selective, and covalent KRASG12C inhibitor that exhibits favorable drug-like properties, selectively modifies mutant cysteine 12 in GDP-bound KRASG12C, and inhibits KRAS-dependent signaling. MRTX849 demonstrated pronounced tumor regression in 17 of 26 (65%) KRASG12C-positive cell line- and patient-derived xenograft models from multiple tumor types, and objective responses have been observed in patients with KRASG12C-positive lung and colon adenocarcinomas. Comprehensive pharmacodynamic and pharmacogenomic profiling in sensitive and partially resistant nonclinical models identified mechanisms implicated in limiting antitumor activity including KRAS nucleotide cycling and pathways that induce feedback reactivation and/or bypass KRAS dependence. These factors included activation of receptor tyrosine kinases (RTK), bypass of KRAS dependence, and genetic dysregulation of cell cycle. Combinations of MRTX849 with agents that target RTKs, mTOR, or cell cycle demonstrated enhanced response and marked tumor regression in several tumor models, including MRTX849-refractory models. SIGNIFICANCE: The discovery of MRTX849 provides a long-awaited opportunity to selectively target KRASG12C in patients. The in-depth characterization of MRTX849 activity, elucidation of response and resistance mechanisms, and identification of effective combinations provide new insight toward KRAS dependence and the rational development of this class of agents.
Introduction
KRAS is one of the most frequently mutated oncogenes in cancer; however, efforts to directly target KRAS have been largely unsuccessful due to its high affinity for GTP/GDP and the lack of a clear binding pocket (1–4). More recently, compounds were identified that covalently bind to KRASG12C at the cysteine 12 residue, lock the protein in its inactive GDP-bound conformation, inhibit KRAS-dependent signaling, and elicit antitumor responses in tumor models (5–7). Advances on early findings demonstrated that the binding pocket under the switch II region was exploitable for drug discovery, culminating in the identification of more potent KRASG12C inhibitors with improved physiochemical properties that are now entering clinical trials. The identification of KRASG12C inhibitors provides a renewed opportunity to develop a more comprehensive understanding of the role of KRAS as a driver oncogene and to explore the clinical utility of direct KRAS inhibition.
KRASG12C mutations are present in lung and colon adenocarcinomas as well as smaller fractions of other cancers. The genetic context of KRASG12C alteration can vary significantly among tumors and is predicted to affect response to KRAS inhibition. KRAS mutations are often enriched in tumors due to amplification of mutant or loss of wild-type allele (8, 9). In addition, KRAS mutations often co-occur with other key genetic alterations including TP53 and CDKN2A in multiple cancers, KEAP1 and/or STK11 in lung adenocarcinoma, or APC and PIK3CA in colon cancer (3, 8–12). Whether differences in KRAS-mutant allele fraction or co-occurrence with other mutations influence response to KRAS blockade is not yet well understood. In addition, due to the critical importance of the RAS pathway in normal cellular function, there is extensive pathway isoform redundancy and a comprehensive regulatory network in normal cells to ensure tight control of temporal pathway signaling. RAS pathway negative feedback signaling is mediated by ERK1/2 and receptor tyrosine kinases (RTK) as well as by ERK pathway target genes including dual-specificity phosphatases (DUSP) and Sprouty (SPRY) proteins (13–17). One important clinically relevant example is provided by the reactivation of ERK signaling observed following treatment of BRAFV600E-mutant cancers with selective BRAF inhibitors (18–20). The observed intertumoral heterogeneity and extensive feedback signaling network in KRAS-mutant cancers may necessitate strategies to more comprehensively block oncogenic signal transduction and deepen the antitumor response in concert with KRAS blockade (15, 21, 22).
Potential strategies to augment the response to KRASG12C inhibitor treatment are evident at multiple nodes of the signaling pathway regulatory machinery. RAS proteins are small GTPases that normally cycle between an active, GTP-bound state and an inactive, GDP-bound state. RAS proteins are loaded with GTP through guanine nucleotide exchange factors (e.g., SOS1) which are activated by upstream RTKs, triggering subsequent interaction with effector proteins that activate RAS-dependent signaling. RAS proteins hydrolyze GTP to GDP through their intrinsic GTPase activity, which is dramatically enhanced by GTPase-activating proteins (GAP). Mutations at codons 12 and 13 in RAS proteins impair GAP-stimulated GTP hydrolysis, leaving RAS predominantly in the GTP-bound, active state.
Potent covalent KRASG12C inhibitors described to date bind only GDP-bound KRAS (5–7). Although codon 12 and 13 mutations decrease the fraction of GDP-bound KRAS, recent biochemical analyses revealed that KRASG12C exhibits the highest intrinsic GTP hydrolysis rate and highest nucleotide exchange rate among KRAS mutants (23). Furthermore, the nucleotide-bound state of KRASG12C can be shifted toward the GDP-bound state by pharmacologically modulating upstream signaling with RTK inhibitors that increase the activity of KRASG12C inhibitors (7, 22, 24). Likewise, SHP2 is a phosphatase that positively transduces RTK signaling to KRAS. Accordingly, SHP2 inhibitors are active in cancers driven by KRAS mutations that are dependent on nucleotide cycling, including KRASG12C (25–27).
MRTX849 is among the first KRASG12C inhibitors to advance to clinical trials. The comprehensive and durable inhibition of KRASG12C by MRTX849 provides a unique opportunity to understand the extent to which KRAS functions as an oncogenic driver. In addition, the observation that the response to blockade of KRAS is markedly different in vitro and in vivo indicates that evaluation of the consequences of KRAS blockade in in vivo model systems is critical to understand the role of KRAS-driven tumor progression. The demonstration of partial responses in patients with lung and colon adenocarcinomas treated with MRTX849 in clinical trials indicates that results observed in tumor models extend to KRASG12C-positive human cancers. Our comprehensive molecular characterization of multiple tumor models at baseline and during response to KRAS inhibition has provided further insight toward the contextual role of KRAS mutation in the setting of genetic and tumoral heterogeneity. Finally, further interrogation of these genetic alterations and signaling pathways utilizing functional genomics strategies including CRISPR and combination approaches uncovered regulatory nodes that sensitize tumors to KRAS inhibition when cotargeted.
Introduction
KRAS is one of the most frequently mutated oncogenes in cancer; however, efforts to directly target KRAS have been largely unsuccessful due to its high affinity for GTP/GDP and the lack of a clear binding pocket (1–4). More recently, compounds were identified that covalently bind to KRASG12C at the cysteine 12 residue, lock the protein in its inactive GDP-bound conformation, inhibit KRAS-dependent signaling, and elicit antitumor responses in tumor models (5–7). Advances on early findings demonstrated that the binding pocket under the switch II region was exploitable for drug discovery, culminating in the identification of more potent KRASG12C inhibitors with improved physiochemical properties that are now entering clinical trials. The identification of KRASG12C inhibitors provides a renewed opportunity to develop a more comprehensive understanding of the role of KRAS as a driver oncogene and to explore the clinical utility of direct KRAS inhibition.
KRASG12C mutations are present in lung and colon adenocarcinomas as well as smaller fractions of other cancers. The genetic context of KRASG12C alteration can vary significantly among tumors and is predicted to affect response to KRAS inhibition. KRAS mutations are often enriched in tumors due to amplification of mutant or loss of wild-type allele (8, 9). In addition, KRAS mutations often co-occur with other key genetic alterations including TP53 and CDKN2A in multiple cancers, KEAP1 and/or STK11 in lung adenocarcinoma, or APC and PIK3CA in colon cancer (3, 8–12). Whether differences in KRAS-mutant allele fraction or co-occurrence with other mutations influence response to KRAS blockade is not yet well understood. In addition, due to the critical importance of the RAS pathway in normal cellular function, there is extensive pathway isoform redundancy and a comprehensive regulatory network in normal cells to ensure tight control of temporal pathway signaling. RAS pathway negative feedback signaling is mediated by ERK1/2 and receptor tyrosine kinases (RTK) as well as by ERK pathway target genes including dual-specificity phosphatases (DUSP) and Sprouty (SPRY) proteins (13–17). One important clinically relevant example is provided by the reactivation of ERK signaling observed following treatment of BRAFV600E-mutant cancers with selective BRAF inhibitors (18–20). The observed intertumoral heterogeneity and extensive feedback signaling network in KRAS-mutant cancers may necessitate strategies to more comprehensively block oncogenic signal transduction and deepen the antitumor response in concert with KRAS blockade (15, 21, 22).
Potential strategies to augment the response to KRASG12C inhibitor treatment are evident at multiple nodes of the signaling pathway regulatory machinery. RAS proteins are small GTPases that normally cycle between an active, GTP-bound state and an inactive, GDP-bound state. RAS proteins are loaded with GTP through guanine nucleotide exchange factors (e.g., SOS1) which are activated by upstream RTKs, triggering subsequent interaction with effector proteins that activate RAS-dependent signaling. RAS proteins hydrolyze GTP to GDP through their intrinsic GTPase activity, which is dramatically enhanced by GTPase-activating proteins (GAP). Mutations at codons 12 and 13 in RAS proteins impair GAP-stimulated GTP hydrolysis, leaving RAS predominantly in the GTP-bound, active state.
Potent covalent KRASG12C inhibitors described to date bind only GDP-bound KRAS (5–7). Although codon 12 and 13 mutations decrease the fraction of GDP-bound KRAS, recent biochemical analyses revealed that KRASG12C exhibits the highest intrinsic GTP hydrolysis rate and highest nucleotide exchange rate among KRAS mutants (23). Furthermore, the nucleotide-bound state of KRASG12C can be shifted toward the GDP-bound state by pharmacologically modulating upstream signaling with RTK inhibitors that increase the activity of KRASG12C inhibitors (7, 22, 24). Likewise, SHP2 is a phosphatase that positively transduces RTK signaling to KRAS. Accordingly, SHP2 inhibitors are active in cancers driven by KRAS mutations that are dependent on nucleotide cycling, including KRASG12C (25–27).
MRTX849 is among the first KRASG12C inhibitors to advance to clinical trials. The comprehensive and durable inhibition of KRASG12C by MRTX849 provides a unique opportunity to understand the extent to which KRAS functions as an oncogenic driver. In addition, the observation that the response to blockade of KRAS is markedly different in vitro and in vivo indicates that evaluation of the consequences of KRAS blockade in in vivo model systems is critical to understand the role of KRAS-driven tumor progression. The demonstration of partial responses in patients with lung and colon adenocarcinomas treated with MRTX849 in clinical trials indicates that results observed in tumor models extend to KRASG12C-positive human cancers. Our comprehensive molecular characterization of multiple tumor models at baseline and during response to KRAS inhibition has provided further insight toward the contextual role of KRAS mutation in the setting of genetic and tumoral heterogeneity. Finally, further interrogation of these genetic alterations and signaling pathways utilizing functional genomics strategies including CRISPR and combination approaches uncovered regulatory nodes that sensitize tumors to KRAS inhibition when cotargeted.
Results
MRTX849 Is a Potent and Selective Inhibitor of KRASG12C, KRAS-Dependent Signal Transduction, and Cell Viability In Vitro
A structure-based drug design approach, including optimization for favorable drug-like properties, led to the discovery of MRTX849 as a potent, covalent KRASG12C inhibitor (Fig. 1A; Supplementary Table S1). An LC/MS-based KRASG12C protein modification assay revealed that MRTX849 demonstrated much greater modification of KRASG12C when preloaded with GDP compared with GTP (Supplementary Table S2), supporting that MRTX849 binds to and stabilizes the inactive GDP-bound form of KRASG12C. Indeed, introducing a comutation that impairs the GTPase activity of KRASG12C (24) attenuated the inhibitory activity of MRTX1257, a close analogue of MRTX849 (Supplementary Fig. S1A). Secondary mutations that modulate the nucleotide exchange function of KRASG12C also affected inhibition by MRTX1257, supporting that the MRTX compound series is dependent on KRASG12C nucleotide cycling.
MRTX849 is a potent, covalent KRASG12C inhibitor in vitro. A, Structure of MRTX849. B, Immunoblot protein Western blot analyses of KRAS pathway targets in MIA PaCa-2 cells treated from 1 hours to 72 hours with MRTX849 at 100 nmol/L. C, Immunoblot protein Western blot analyses of KRAS pathway targets in MIA PaCa-2 cells treated for 24 hours with MRTX849 over a 13-point dose response. D, Left y-axis shows active RAS ELISA assay to determine the reduction in RAS-GTP abundance following MRTX849 treatment in MIA PaCa-2 cells for 24 hours. The vehicle value was normalized to 1 by dividing all average values by the vehicle value. Right y-axis shows quantitation of KRAS band shift by MRTX849 treatment in MIA PaCa-2 cells for 24 hours as assessed by Western blot and densitometry. E, In-cell Western blot assay to evaluate modulation of pERK in MIA PaCa-2 cells grown in standard tissue-culture conditions treated with MRTX849 over a time course. F, CellTiter-Glo assay to evaluate cell viability performed on seven KRASG12C-mutant cell lines and three non–KRASG12C-mutant cell lines grown in 2-D tissue-culture conditions in a 3-day assay (left plot) or 3-D conditions using 96-well, ULA plates in a 12-day assay (right plot).
We next determined the cellular activity of MRTX849 utilizing the KRASG12C-mutant H358 lung and MIA PaCa-2 pancreatic cancer cell lines. In both models, MRTX849 demonstrated an upward electrophoretic mobility shift of KRASG12C protein band migration by immunoblot, indicative of covalent modification of KRASG12C. A maximal mobility shift was observed by 1 hour, was maintained through 72 hours (Fig 1B; Supplementary Fig. S1B), and was evident at concentrations as low as 2 nmol/L with near-maximal modification observed at 15.6 nmol/L (Fig. 1C; Supplementary Fig. S1C). Comparable inhibition of active RAS was observed as determined by a RAF RAS-binding domain capture ELISA assay (Fig. 1D; 1D). MRTX849 also inhibited KRAS-dependent signaling targets including ERK1/2 phosphorylation (pERK; Thr202/Tyr204 ERK1), S6 phosphorylation (pS6; RSK-dependent Ser235/236), and expression of the ERK-regulated DUSP6, each with IC50 values in the single-digit nanomolar range in both cell lines (Fig. 1B and C; Supplementary Fig. S1B and S1C). The evaluation of pERK over a time course of 48 hours indicated maximal inhibition was observed at 24 hours (Fig. 1E; Supplementary Fig. S1E). Treatment with the des-acrylamide version of MRTX849, which is unable to covalently bind to KRASG12C, did not demonstrate significant inhibition of ERK phosphorylation (Supplementary Fig. S1F). The H358 cell line was selected for determination of MRTX849 cysteine selectivity utilizing an LC/MS-based proteomics approach able to detect approximately 6,000 cysteine-containing peptides. After treatment for 3 hours, decreased KRASG12C Cys12-free peptide was detected with treated-to-control ratios of 0.029 and 0.008 determined at 1 and 10 μmol/L, respectively, indicating near-complete engagement of the intended target (Supplementary Table S3). In contrast, the only other peptides identified were from lysine-tRNA ligase (KARS) at Cys209 near the detection limit, indicating a high degree of selectivity toward KRASCYS12.
To evaluate the breadth of MRTX849 activity, its effect on cell viability was determined across a panel of 17 KRASG12C-mutant and 3 non–KRASG12C-mutant cancer cell lines using 2-D (3-day, adherent cells) and 3-D (12-day, spheroids) cell-growth conditions. MRTX849 potently inhibited cell growth in the vast majority of KRASG12C-mutant cell lines with IC50 values ranging between 10 and 973 nmol/L in the 2-D format and between 0.2 and 1,042 nmol/L in the 3-D format (Supplementary Table S4; Fig. 1F). In agreement with prior KRASG12C inhibitor studies (5), MRTX849 demonstrated improved potency in the 3-D assay format, as all but one KRASG12C-mutant cell line exhibited an IC50 value below 100 nmol/L. Although MRTX849 was broadly effective in inhibiting viability of KRASG12C-mutant cell lines, IC50 values varied across the cell panel by 100-fold, suggesting a differential degree of sensitivity to treatment. All three non–KRASG12C-mutant cell lines tested demonstrated IC50 values greater than 1 μmol/L in 2-D conditions and greater than 3 μmol/L in 3-D conditions, suggesting the effect of MRTX849 on cell viability was dependent on the presence of KRASG12C.
To determine whether the difference in sensitivity across the cell panel correlated with the ability of MRTX849 to bind to KRAS or inhibit KRAS-dependent signal transduction, seven KRASG12C-mutant cancer cell lines were selected from the panel for further evaluation. In each cell line, MRTX849 demonstrated a very similar concentration-dependent electrophoretic mobility shift (IC50) for KRASG12C protein migration, suggesting that the ability to bind to and modify KRASG12C does not readily account for differences in response in viability studies (Fig. 1B and C; Supplementary Figs. S1B and S1C and S2A and S2B). The effect of MRTX849 on selected phosphoproteins implicated in mediating KRAS-dependent signaling was also evaluated across the cell panel by immunoblot and/or reverse-phase protein array (RPPA) following treatment for 6 or 24 hours. Notably, the concentration–response relationship and maximal effect of MRTX849 on inhibition of ERK and S6S235/236 phosphorylation varied across the cell panel (Supplementary Fig. S2A and S2C; Supplementary Table S7). MRTX849 demonstrated only partial inhibition of pERK in KYSE-410 and SW1573 cells and a minimal effect on pS6S235/236 in SW1573, H2030, and KYSE-410 cells (Supplementary Fig. S2A and S2C). Each of these cell lines were among those that exhibited a submaximal response to MRTX849 in both 2-D and 3-D viability assays (Fig. 1F). Although KRAS is implicated in mediating signal transduction through the PI3K and mTOR pathways, there was minimal evidence of a significant and/or durable effect of MRTX849 on AKT (S473, T308) or 4E-BP1 (T37/T46, S65, T70) phosphorylation at any time point in any cell lines evaluated (Supplementary Fig. S2D). However, MRTX849 demonstrated concentration-dependent partial inhibition of the mTOR-dependent signaling targets p70 S6 kinase (T412) and/or pS6 (S240/44) in the H358, MIA PaCa-2,H2122, and H1373 cell lines, each of which exhibited a maximal response to treatment. Together, these data suggest that maximizing inhibition of KRAS-dependent ERK and S6 signaling may be required to elicit a robust response in tumor-cell viability assays.
MRTX849 Treatment In Vivo Leads to Dose-Dependent KRASG12C Modification, KRAS Pathway Inhibition, and Antitumor Efficacy
Studies were conducted to evaluate MRTX849 antitumor activity along with its pharmacokinetic and pharmacodynamic properties in vivo, both to understand the clinical utility of this agent and to provide insight toward response to treatment. MRTX849 demonstrated moderate plasma clearance and prolonged half-life following oral administration (Supplementary Table S1; Supplementary Fig. S3). To evaluate the pharmacodynamic response to MRTX849 and to correlate drug exposure with target inhibition, MRTX849 was administered via oral gavage over a range of dose levels to H358 xenograft–bearing mice, and plasma and tumors were collected at defined time points. The fraction of covalently modified KRASG12C protein was proportional to the plasma concentration of MRTX849 (Fig. 2A). When evaluated over time after a single oral dose at 30 mg/kg, the modified fraction of KRASG12C was 74% at 6 hours after dose and gradually decreased to 47% by 72 hours (Fig. 2B). This extended pharmacodynamic effect, despite declining levels of MRTX849 in plasma, was consistent with the irreversible inhibition of KRASG12C by MRTX849 and the relatively long half-life for the KRASG12C protein (∼24–48 hours; Supplementary Table S5). The modification of KRASG12C was maximized after repeated daily dosing for 3 days at 30 mg/kg (Fig. 2B), and higher dose levels did not demonstrate additional KRASG12C modification in multiple tumor models (data not shown). The maximum level of modification of approximately 80%, despite increasing dose and plasma levels of MRTX849, suggests that accurate measurement of complete inhibition of KRASG12C utilizing LC/MS may not be attainable, potentially due to a pool of active, noncycling, or unfolded KRASG12C protein in tumors. Together, these studies demonstrated a dose-dependent increase in covalent modification of KRASG12C by MRTX849 and that the majority of targetable KRAS was covalently modified by MRTX849 over a repeated administration schedule at dose levels at or exceeding 30 mg/kg.
MRTX849 modifies KRASG12C and inhibits KRAS signaling and tumor growth in vivo. A, MRTX849 was administered orally as a single dose to mice bearing established H358 xenografts (average tumor volume ∼350 mm3) at 10, 30, and 100 mg/kg. KRAS modification and MRTX849 plasma concentration data from n = 3 mice are shown as mean ± SD. KRASG12C modification was statistically significant versus vehicle control using the two-tailed Student t test. **, P < 0.01. B, MRTX849 was administered orally as a single dose or daily (QD) for 3 days to mice bearing established H358 xenografts (average tumor volume ∼350 mm3) at 30 mg/kg. Plasma was collected at 0.5, 2, 6, 24, 48, and 72 hours after administration of the last dose, and tumors were collected at 6, 24, 48, and 72 hours after dose. KRASG12C modification and MRTX849 plasma concentration data are shown from n = 3 mice as mean ± SD. Induction of modified KRASG12C protein at all time points was determined to be statistically significant versus vehicle control using two-way ANOVA. In addition, induction of modified KRASG12C protein at 72 hours in day 1 samples and 48 and 72 hours in day 3 samples was statistically significant versus the 6-hour time point. Brackets indicate P < 0.05 as compared with left-most sample. C, MRTX849 was administered as in A. Tumors were collected 6 hours after dose, and total and phosphorylated ERK1/2 and total and phosphorylated S6 were analyzed by immunoblot and quantified by densitometric analysis. Relative fluorescence intensity of pERK1/2 and pS6 was normalized by dividing pERK1/2 and pS6 by total ERK1/2 and total S6, respectively. Vehicle-treated tumors were normalized to 1 by dividing all average values by the vehicle value. Average pERK1/2 and pS6 values were divided by the average value in vehicle-treated tumors. Data shown represent the average of 2 to 3 tumors per treatment group plus SD. Reduction of pS6 relative fluorescence intensity was determined to be statistically significant versus vehicle control using the two-tailed Student t test. Brackets indicate P < 0.05 compared with left-most sample. D, MRTX849 was administered as in B. Tumors were collected at 6, 24, 48, or 72 hours after administration of the last dose, and total and phosphorylated ERK1/2 and total and phosphorylated S6 were analyzed as in C. Data shown represent the average of 3 to 4 tumors per treatment group plus SD. Reduction of pS6 relative fluorescence intensity on day 3 was determined to be statistically significant versus vehicle control using two-way ANOVA. Brackets indicate P < 0.05 compared with left-most sample. E, MRTX849 was administered via daily oral gavage at the doses indicated to mice bearing established MIA PaCa-2 xenografts. Dosing was initiated when tumors were approximately 350 to 400 mm3.MRTX849 was administered to mice daily until day 16. Data are shown as mean tumor volume ± SEM. Tumor volumes at day 16 were determined to be statistically significant versus vehicle control via two-tailed Student t test. **, P < 0.01; *, P < 0.05.
To evaluate the effect of MRTX849 on KRAS-dependent signal transduction in vivo, a single dose of MRTX849 at 10, 30, or 100 mg/kg was administered to H358 tumor–bearing mice. Dose-dependent inhibition of ERK1/2 and pS6S235/36 phosphorylation was observed at 6 hours after dose based on immunoblot and densitometric analysis (Fig. 2C). MRTX849 also demonstrated marked inhibition of ERK1/2 and S6S235/36 phosphorylation after one or three daily doses at 6 or 24 hours, and levels gradually recovered by 72 hours after the final dose (Fig. 2D). pERK1/2 and pS6S235/36 were further evaluated in formalin-fixed, paraffin-embedded sections from vehicle-treated and MRTX849-treated xenografts in four tumor models utilizing IHC methods coupled with image analysis algorithms. These studies demonstrated increased pERK1/2 and pS6 in nontumor/stromal cells following MRTX849 administration, indicating that immunoblotting studies with bulk tumor lysate likely underrepresent the degree of pathway inhibition in tumor cells, whereas IHC-based evaluation may more accurately reflect both the degree and spatial impact of pathway inhibition. Maximal inhibition was observed for both ERK and S6S235/36 phosphorylation after a single dose at the 6-hour time point, with a rebound in signaling evident 24 hours after single dose in each model (Supplementary Fig. S4). Marked inhibition of ERK phosphorylation was observed at 6 hours after administration, with 89%, 94%, and 94% inhibition observed compared with vehicle controls in MIA PaCa-2, H1373, and H2122 tumors, respectively (H358 pERK not quantifiable). This indicates that dose levels at or exceeding 30 mg/kg dose maximized inhibition of ERK phosphorylation in multiple models (Supplementary Fig. S4A and S4B). Inhibition of S6 phosphorylation at 6 hours was more variable, with percent inhibition values of 76%, 50%, 86%, and 56% observed in MIA PaCa-2, H1373, H358, and H2122 tumors, respectively (Supplementary Fig. S4B). Together, these data indicate that consistent acute (6 hours) inhibition of KRAS-dependent ERK phosphorylation was maximized in all evaluated models, whereas inhibition of S6S235/36 was more variable, presumably due to varying degrees of KRAS-independent activation of this pathway in different tumor models.
MIA PaCa-2 and H358 were selected as MRTX849-responsive tumor models, thereby enabling a high-resolution understanding of dose–response relationships. Significant, dose-dependent, antitumor activity was observed at the 3, 10, 30, and 100 mg/kg dose levels in the MIA PaCa-2 model (Fig. 2E). Evidence of rapid tumor regression was observed at the earliest post-treatment tumor measurement, and animals in the 30 and 100 mg/kg cohorts exhibited evidence of a complete response at study day 15. Dosing was stopped at study day 16, and all 4 mice in the 100 mg/kg cohort and 2 of 7 mice in the 30 mg/kg cohort remained tumor-free through study day 70 (Supplementary Fig. S5A). In a second MIA PaCa-2 study, dose-dependent antitumor efficacy was observed at the 5, 10, and 20 mg/kg dose levels, and 2 of 5 mice at the 20 mg/kg dose level exhibited complete tumor regression (Supplementary Fig. S5B). Significant dose-dependent antitumor efficacy was also observed in the H358 model, including 61% and 79% tumor regression at the 30 and 100 mg/kg dose levels, respectively, at day 22 (Supplementary Fig. S5C). MRTX849 was well tolerated, and no effect on body weight was observed at all dose levels evaluated (Supplementary Fig. S5D). These studies indicated that MRTX849 demonstrated dose-dependent antitumor efficacy over a well-tolerated dose range and that the maximally efficacious dose of MRTX849 is between 30 and 100 mg/kg/day.
MRTX849 Demonstrates Broad-Spectrum Tumor Regression in KRASG12C Cell Line and Patient-Derived Xenograft Models
To evaluate the breadth of antitumor activity across genetically and histologically heterogeneous KRASG12C-mutant cancer models, MRTX849 was evaluated at a fixed dose of 100 mg/kg/day (a dose projected to demonstrate near-maximal target inhibition in most models) in a panel of human KRASG12C-mutant cell line–derived xenograft (CDX) and patient-derived xenograft (PDX) models. MRTX849 demonstrated tumor regression exceeding 30% volume reduction from baseline in 17 of 26 models (65%) at approximately 3 weeks of treatment (Fig. 3A; Supplementary Table S6). By comparison, MRTX849 did not exhibit significant antitumor activity at 100 mg/kg in three non–KRASG12C-mutant models (Fig. 3A; Supplementary Table S6). Together, these results indicate that KRASG12C-mutant tumors are broadly dependent upon mutant KRAS for tumor-cell growth and survival and that MRTX849 elicits antitumor activity through a KRASG12C-dependent mechanism.
Antitumor activity of MRTX849 in KRASG12C-mutant and non–KRASG12C-mutant human tumor xenograft models. A, MRTX849 was administered via oral gavage at 100 mg/kg every day to mice bearing the CDX or PDX model indicated. Dosing was initiated when tumors were, on average, approximately 250 to 400 mm3. MRTX849 was formulated as a free base and resuspended as a solution in 10% Captisol and 50 mmol/L citrate buffer, pH 5.0. The percent change from baseline control was calculated at days 19 to 22 for most models. Statistical significance was determined for each model and is shown in Supplementary Table S6. Status of mutations and alterations in key genes is shown below each model. MAF (%), percent KRASG12C-mutant allele fraction by RNA-seq; CNV, copy-number variation; * denotes very high CDK4 expression by RNA-seq and possible amplification. HER family status was determined by averaging EGFR, ERBB2, and ERBB3 RNA-seq expression for CDX (CCLE) or PDX (Crown huBase) models. Positive HER family calls denote greater than the median expression of the models tested. CDX and PDX model HER family calls were determined independently. B, Tumor-growth inhibition plots from representative xenograft models that were categorized as sensitive, partially sensitive, or treatment refractory.
Although MRTX849 exhibited marked antitumor responses in the majority of models tested, a response pattern ranging from delayed tumor growth to complete regression was observed across the xenograft panel. The response to treatment was categorized as sensitive, partially sensitive, or treatment refractory (Fig. 3B). Rank order and Pearson statistical analyses were performed to evaluate the correlation between in vitro potency (IC50 in 2-D or 3-D viability assays) and antitumor response in vivo (% regression or progression on day 22), and a significant correlation between response in cell lines compared with tumor models was not observed (Supplementary Fig. S6A and S6B). Thus, we focused on a comprehensive analysis of correlates with MRTX849 tumor response in vivo, including tumor histology, co-occurring genetic alterations, as well as baseline or drug-induced changes in expression of KRAS-related genes [RNA sequencing (RNA-seq)] and/or protein signaling networks (RPPA in 18 models, ref. 28; Supplementary Fig. S7). No individual genetic alteration, including but not limited to KRAS-mutant allele frequency, TP53, STK11, or CDKN2A, predicted the antitumor activity of MRTX849. Interestingly, baseline gene and/or protein expression of selected members of the HER family of RTKs and of regulators of early cell-cycle transition did exhibit a trend with the degree of antitumor response, suggesting these pathways may influence the response to KRAS inhibitors (Supplementary Fig. S7A). Together, these data indicate that there are no individual binary biomarkers that clearly predict therapeutic response and that the molecular complexity and heterogeneity present in distinct KRAS-mutated tumors may contribute to the response to target blockade.
MRTX849 Antitumor Activity Translates to RECIST Responses in Patients with Cancer
A 45-year-old female former smoker diagnosed with stage IV lung adenocarcinoma and refractory to multiple lines of therapy including carboplatin/pemetrexed/pembrolizumab, docetaxel, and investigational treatment with binimetinib and palbociclib was enrolled onto the MRTX849-001 phase Ib clinical trial with two bilateral lung lesions and mediastinal lymph node as target lesions. Targeted next-generation sequencing (NGS) demonstrated a KRASG12C mutation (c.34G>T). In addition, loss-of-function KEAP1 (K97M) and STK11 (E223*) mutations were detected and are predicted to be deleterious to their respective proteins. The patient was administered MRTX849 (600 mg twice a day) and had marked clinical improvement within 2 weeks, including complete resolution of baseline cough and oxygen dependency. A RECIST-defined partial response of 33% reduction of target lesions was observed at cycle 3 day 1 (45 days), and the patient continues on study (Fig. 4A).
Activity of MRTX849 in patients with lung and colon cancers. A, Pretreatment and 6-week scans of a heavily pretreated patient with a KRASG12C mutation–positive lung adenocarcinoma indicating 33% reduction of target lesions. Patient continues on study. The top plots show a coronal view, and bottom plots an axial view of CT chest images prior to MRTX849 treatment (left) and after two cycles of MRTX849 treatment (right). B, Baseline, 6-week (Cycle 2), and 12-week (Cycle 4) scans of a patient with a KRASG12C mutation–positive colon adenocarcinoma. Partial response (PR) was confirmed at Cycle 4, and patient continues on study. Four lesions (TL1–4) are shown with axial views of CT images prior to MRTX849 treatment (top), after two cycles of MRTX849 treatment (center), and after four cycles of MRTX849 treatment (bottom).
A 47-year-old female never-smoker with metastatic adenocarcinoma of the left colon who exhibited progressive disease after receiving multiple lines of systemic therapy, including FOLFOX plus bevacizumab, single-agent capecitabine, FOLFIRI plus bevacizumab, and an investigational antibody–drug conjugate, was enrolled into the MRTX849-001 phase Ib clinical trial. This patient had extensive metastases involving the liver, peritoneum, ovaries, and lymph nodes. Targeted NGS identified a KRASG12C mutation. The patient was administered MRTX849 (600 mg twice a day) and demonstrated marked clinical improvement within 3 weeks and a visible decrease in size of her umbilical Sister Mary Joseph nodule. Her carcinoembryonic antigen levels decreased from 77 ng/mLat baseline to 11 ng/mL at cycle 2 day 1 and 3 ng/mL by cycle 3 day 1 (normal range, 0–5 ng/mL). A RECIST-defined partial response with a 37% reduction of target lesions and complete response of a nontarget lesion was observed at cycle 3 day 1(day 42). Confirmatory CT scans were conducted at cycle 5, day 1 (day 84) and indicated a confirmed RECIST partial response with further reduction of target lesions at −47% from baseline (Fig. 4B). The patient remains on treatment through Cycle 6.
Temporal Effects of MRTX849 on KRAS-Dependent Signaling and Feedback Pathways and Relationship to Antitumor Activity Following Repeat Dosing in Xenograft Models
A comprehensive analysis was conducted to evaluate MRTX849-induced temporal molecular changes to further interrogate mechanisms of drug response across sensitive and partially sensitive models. To evaluate temporal changes in global gene expression, xenograft-bearing mice were administered vehicle or 100 mg/kg MRTX849, and RNA-seq was performed on tumors at 6 and 24 hours after treatment. Gene expression was evaluated at day 1 and day 5 for the sensitive models MIA PaCa-2 and H1373 to ensure sufficient tissue availability from regressing tumors, or at day 7 in the partially sensitive models H358, H2122, and H2030 to coordinate with tumor stasis plateau. The top differentially expressed gene set enrichment analysis (GSEA) hallmark gene sets, regardless of tumor response, in all five models were several KRAS-annotated gene sets confirming MRTX849 selectively inhibits multiple genes directly related to KRAS signaling. MYC, mTOR, cell cycle, and apoptosis/BCL2 pathway gene sets were also strongly differentially expressed, confirming MRTX849 broadly affected multiple well-established, KRAS-regulated pathways, several of which have proved difficult to directly inhibit with previous targeted therapies (Fig. 5A and B; Supplementary Fig. S8A—S8D). The marked impact of MRTX849 on a large number of genes that regulate cell cycle and apoptosis provides further insight into molecular mechanisms which mediate its antitumor activity.
MRTX849 treatment in vivo regulates KRAS-dependent oncogenic signaling and feedback-inhibitory pathways. A, Volcano plots displaying differentially expressed genes in xenograft tumors 24 hours after oral administration of vehicle or 100 mg/kg MRTX849 in a representative MRTX849-sensitive (H1373) and MRTX849-partially sensitive (H358) model. Significance denoted in the legend (Padj < 0.01). B, GSEA heat maps depicting hallmark signature pathways differentially regulated in at least one model 24 hours following oral administration of a single 100 mg/kg MRTX849 dose compared with vehicle. Normalized enrichment score shown in all models 6 or 24 hours after a single dose (QD × 1) or 5 (QD × 5) or 7 (QD × 7) days dosing. C, Genes that feedback-inhibit MAP kinase signaling are downregulated following MRTX849 treatment in all five cell line xenografts assessed by RNA-seq. TPM, Transcripts Per Kilobase Million.
Targeted RNA-seq analysis was performed on genes implicated in the temporal regulation of external signaling inputs and feedback pathways which collectively temper signaling flux through the RAS–RAF–MEK–ERK MAP kinase (MAPK) pathway including DUSP, SPRY, and PHLDA family genes (13, 18). These MAPK pathway–negative regulators were each ranked among the most strongly decreased genes following MRTX849 treatment, providing evidence that ERK-dependent transcriptional output is blocked and that pathways involved in reactivation of RTK- and ERK-dependent signaling were activated (Fig. 5C; Supplementary Fig. S4A).
On the basis of the observation of dynamic changes in transcriptional programs linked to KRAS pathway reactivation, IHC plus quantitative imaging of tumor cell–specific pERK and pS6 was evaluated over a range of time points. In the sensitive MIA PaCa-2 and H1373 tumor models, treatment with MRTX849 (100 mg/kg) demonstrated ≥90% inhibition of ERK phosphorylation at 6 and 24 hours on both days 1 and 5 (Supplementary Fig. S4). In contrast, in the partially sensitive H358 and H2122 models, robust inhibition of ERK phosphorylation was observed at 6 hours after a single dose; however, marked recovery of ERK phosphorylation was observed at 24 hours after single dose and at both 6 and 24 hours following 7 days of repeat-dose administration. Because DUSP, SPRY, and ETV family transcripts remain downregulated through 5 to 7 days in all models, it is evident that other independent factors contribute to temporal reactivation of ERK (Fig. 5C). Similar to what was observed with single-dose administration, the effect of MRTX849 on pS6 was variable over time and did not track with the antitumor activity of MRTX849. Together, these results suggest that the extent and duration of inhibition of pERK may track with the magnitude of antitumor efficacy of KRASG12C inhibitors and that further evaluation of the role of S6 is required to understand if it plays a role in drug sensitivity.
The effect of MRTX849 on cell proliferation and apoptosis was characterized by IHC analysis of Ki-67 or cleaved caspase-3 after a single dose or repeat administration. The fraction of Ki-67–positive cells was significantly reduced in tumors after repeat administration in all four models tested, further supporting a broadly operative antiproliferative mechanism, independent of the magnitude of MRTX849 antitumor response (Supplementary Fig. S4). Induction of apoptosis as determined by cleaved caspase-3 immunostaining was also evident on day 1 of treatment (6 and/or 24 hours after treatment) in the sensitive H358, MIA PaCa-2, and H1373 models (79%–100% maximal regression) but not in the partially sensitive H2122 model (Supplementary Fig. S4). An expanded RPPA-based pathway analysis of several models also indicated a correlation between antitumor activity of MRTX849 and decreased survivin (statistically significant at days 5/7 in 7 models evaluated; Supplementary Fig. S7B) and a trend toward increased cleaved caspase-3 induction (day 1, P = 0.08, 16 models), supporting the induction of apoptosis as a key mediator of a cytoreductive antitumor response (Supplementary Fig. S7C). Interestingly, the magnitude of reduction of MYC and cyclin B1 protein levels at days 5/7 also closely correlated with MRTX849 antitumor activity, consistent with their roles as critical regulators of KRAS-mediated cell growth and survival pathways (Supplementary Fig. S7B). Collectively, these data support that durable inhibition of ERK activity and maximal inhibition of ERK-regulated outputs including MYC and E2F-mediated transcription are associated with induction of apoptosis and maximal response to MRTX849 treatment.
CRISPR/Cas9 Screen Identifies Vulnerabilities and Modifiers of Response to MRTX849 in KRASG12C-Mutant Cancer Cell Lines In Vitro and In Vivo
The correlative analysis of genomic or proteomic markers with response to MRTX849 in the defined panel of models provided only limited insight toward mechanism of therapeutic response or resistance. Therefore, we directly interrogated the role of selected genes in mediating therapeutic response utilizing a focused CRISPR/Cas9 knockout screen targeting approximately 400 genes including many genes involved in KRAS signaling. This was conducted in H358 and H2122 cells in vitro and in H2122 xenografts in vivo in the presence and absence of MRTX849 treatment (Supplementary Fig. S9A–S9F). In MRTX849-anchored screens in vitro, single guide RNAs (sgRNA) that target RAS signaling pathway genes including MYC, SHP2 (H2122), mTOR pathway (MTOR and RPS6), and cell-cycle genes (CDK1, CDK2, CDK4/6, and RB1) were identified to affect cell fitness. sgRNAs that target KEAP1 and CBL were enriched in the H2122 model, demonstrating cell-specific genetic routes toward improved fitness through loss of classic tumor-suppressor genes, including in the context of MRTX849 treatment. KRAS sgRNA dropout was less pronounced in the MRTX849-treated cells compared with DMSO control–treated cells, as would be expected with redundant depletion of the drug target (Supplementary Fig. S9C and S9D). To evaluate whether a distinct KRAS dependence or modulation of MRTX849 therapeutic response was observed in vitro versus in vivo, xenograft-bearing mice bearing H2122 cells (∼250 mm3) transduced with the sgRNA library were orally administered vehicle or MRTX849 for 2 weeks (Supplementary Fig. S9A, S9E, and S9F). In MRTX849-treated xenografts, sgRNAs targeting cell cycle, SHP2, MYC, and mTOR pathway genes remained among the top depleted sgRNAs, demonstrating that inhibition of these targets in vivo, in the context of KRAS inhibition, leads to further tumor-growth inhibition over and above the effects of KRAS inhibition alone (Supplementary Fig. S9E and S9F). sgRNAs targeting the tumor suppressor KEAP1 were enriched in MRTX849-treated xenografts, suggesting loss of KEAP1 may represent a mechanism of intrinsic or acquired resistance. Interestingly, NRAS was one of the top enriched genes in the vehicle-treated xenografts, suggesting NRAS functions as a tumor suppressor in this context; however, enrichment was not as pronounced in the MRTX849-treated xenografts, suggesting NRAS may compensate for KRAS in the context of KRAS inhibition (Supplementary Fig. S9F). Collectively, these data demonstrate the importance of selected proteins that regulate RTK- and RAS-dependent signaling and cell-cycle transition in mediating the oncogenic effects of mutant KRAS, and also provide a catalog of potentially druggable vulnerabilities that complement KRAS blockade.
Cancer Therapeutic Combination Screen to Identify Rational and Clinically Tractable Strategies to Address Feedback and Resistance Pathways
To further interrogate pathways that mediate the antitumor response to MRTX849 and to identify combinations capable of enhancing response to MRTX849, a combination screen was conducted in vitro using a focused library of small-molecule inhibitors across a panel of cell lines (Supplementary Fig. S10A and S10B; Supplementary Table S8). Approximately 70 compounds targeting relevant pathways (RTKs, MAPK/ERK, PI3K, mTOR, cell cycle) were tested in a 3- or 7-day viability assay, and synergistic combinations were identified and ranked. Multiple hits from this screen were then identified for additional evaluation in combination studies with MRTX849, including the HER family inhibitor afatinib, the CDK4/6 inhibitor palbociclib, the SHP2 inhibitor RMC-4550, and mTOR pathway inhibitors.
Combination Strategies That Target Upstream Signaling Pathways Implicated in Extrinsic Regulation of KRAS Nucleotide Cycling and Feedback/Bypass Pathways
MRTX849 in combination with HER family inhibitors synergistically inhibited tumor-cell viability in the majority of cell lines evaluated and were the top hit in the combination screen in vitro (Supplementary Fig. S10). Cell lines with the highest (top 50th percentile) average composite baseline RNA expression values of selected HER family members exhibited the highest synergy scores to these combinations (Supplementary Fig. S11A). Afatinib was selected as a prototype HER family inhibitor based on its broad in vitro combination activity. Combination studies were conducted with MRTX849 and afatinib in five tumor models that were partially sensitive or treatment refractory to single-agent MRTX849. The MRTX849 and afatinib combination demonstrated significantly greater antitumor efficacy compared with either single agent in all five models evaluated, including multiple models exhibiting complete or near-complete responses to the combination (Fig. 6A; Supplementary Fig. S11B).
HER family and SHP2 inhibitor combinations further inhibit KRAS signaling and exhibit increased antitumor responses. A, MRTX849 at 100 mg/kg, afatinib at 12.5 mg/kg, or the combination was administered daily via oral gavage to mice bearing the H2122 or KYSE-410 cell line xenografts (n = 5). Combination treatment led to a statistically significant decrease in tumor growth compared with either single-agent treatment. *, Padj < 0.01. B, Quantification of KRAS mobility shift and pERK in H2122 cells treated for 24 hours with MRTX849 (0.1–73 nmol/L), afatinib (200 nmol/L), or the combination assessed by Western blot densitometry. C, MRTX849 at 100 mg/kg, afatinib at 12.5 mg/kg, or the combination was administered once or daily for 7 days via oral gavage to mice bearing H2122 cell line xenografts (n = 3/group). Tumors were harvested at 6 and 24 hours following the final dose. Tumor sections were stained for pERK and pS6 via IHC methods. Quantitation of images shown by H-score in tumor tissue. Reduction of pERK or pS6 staining intensity was determined to be statistically significant relative to vehicle or either single agent using one-way ANOVA. Brackets indicate P < 0.05 compared with left-most sample. D, Quantitation of KRAS band shift and pERK after 24-hour treatment with MRTX849 (0.1–73 nmol/L), RMC-4550 (1 μmol/L), or the combination in H358 cells assessed by Western blot densitometry. E, MRTX849 at 100 mg/kg, RMC-4550 at 30 mg/kg, or the combination was administered daily via oral gavage to mice bearing the KYSE-410 or H358 cell line xenografts (n = 5/group). Combination treatment led to a statistically significant reduction in tumor growth compared with either single agent on the last day of dosing. *, Padj < 0.05. F, MRTX849 at 100 mg/kg, RMC-4550 at 30 mg/kg, or the combination was administered via oral gavage to mice bearing KYSE-410 cell line xenografts (n = 3/group), and tumors were harvested at 6 and 24 hours post-dose. Tumor sections were stained with pERK or pS6 via IHC methods. Quantitation of images shown by H-score in tumor tissue. Reduction of pERK staining intensity was determined to be statistically significant relative to RMC-4550 alone using one-way ANOVA. Brackets indicate P < 0.05 compared with left-most sample.
To evaluate whether afatinib affected covalent modification of KRASG12C by MRTX849, partially sensitive H2122 cells were treated with increasing concentrations of MRTX849 alone or in the presence of afatinib (200 nmol/L, IC90), and the mobility shift in KRAS protein was densitometrically determined from immunoblots. A clear shift in the concentration response to MRTX849 was apparent in the presence of afatinib, indicating that the combination increased the fraction of modified KRASG12C consistent with the putative role of HER family receptors in extrinsic regulation of KRASG12C GTP loading (Fig. 6B). The concentration–response relationship for inhibition of ERK phosphorylation was also clearly shifted in the presence of afatinib. To further evaluate the effect of the combination on KRAS-dependent signaling, four cell lines (H2030, H2122, H358, and KYSE-410) were treated with a range of MRTX849 concentrations in the presence or absence of afatinib for 6 or 24 hours, and key signaling molecules were evaluated by RPPA. Afatinib demonstrated clear inhibition of EGFR (pY1068) and HER2 (pY1248) activity and partial inhibition of ERK, AKT (S473), and p70S6K phosphorylation at both time points (Supplementary Fig. S11C). The effect of afatinib on S6 (S235/236, S240/244) and p90 RSK (S380) phosphorylation was variable and exhibited only minimal inhibition in most of the cell lines evaluated. The combination of afatinib and MRTX849 demonstrated markedly enhanced concentration-dependent inhibition and/or a greater magnitude of effect on ERK, RSK, p70 S6K, and S6 (S235/236) phosphorylation compared with MRTX849 alone at both 6 and 24 hours. Of note, neither afatinib nor MRTX849 alone inhibited S6 phosphorylation at the S240/244 site regulated by mTOR/S6K, whereas the combination demonstrated marked inhibition at 24 hours.
In vivo, the combination also exhibited a trend toward increased pERK and pS6 (S235/236) inhibition in the partially sensitive H2122 model in combination groups as determined by quantitation of immunostaining after 1- or 7-day administration (Fig. 6C). Similar results were observed in the MRTX849-refractory KYSE-410 model, and the combination also increased the number of apoptotic cells in this model (Supplementary Fig. S12A–S12C). Collectively, these data indicate that upstream baseline HER family activation may limit the ability of MRTX849 to achieve robust inhibition of the ERK and mTOR–S6 signaling pathways. Accordingly, the combination of afatinib and MRTX849 can limit feedback reactivation of ERK and demonstrate complementary inhibition of AKT–mTOR–S6 signaling, resulting in significantly improved antitumor activity.
SHP2 inhibition has been shown to inhibit the growth of cells that harbor KRASG12C mutations, and this effect is likely mediated, in part, by decreasing KRAS GTP loading (25–27). To evaluate whether SHP2 inhibition enhanced covalent modification of KRASG12C by MRTX849, H358 and H2122 cells were incubated with increasing MRTX849 concentrations with or without the SHP2 inhibitor RMC-4550. In both cell lines, cotreatment with RMC-4550 (1 μmol/L, IC90) demonstrated a MRTX849 concentration-dependent increase in KRASG12C protein modification and a concomitant decrease in ERK phosphorylation compared with MRTX849 alone (Fig. 6D; Supplementary Fig. S13A). RPPA analysis of KRAS-dependent signaling was conducted at 6 or 24 hours after treatment in three cell lines (H358, H2030, H2122) over a range of MRTX849 concentrations in the presence or absence of RMC-4550. RMC-4550 demonstrated robust inhibition of ERK phosphorylation and partial inhibition of p90 RSK (S380) and p70 S6K (T412) at both time points (Supplementary Fig. S13B). The combination of RMC-4550 and MRTX849 demonstrated incrementally increased concentration-dependent inhibition of ERK and RSK phosphorylation in all cell lines at both 6 and 24 hours and markedly improved inhibition of S6 (S235/236) phosphorylation compared with MRTX849 alone in H2122 and H358 cells at 24 hours. In addition, the combination demonstrated near-complete inactivation of KRAS in MRTX849-refractory KYSE-410 xenografts as determined using an active RAS ELISA assay, and this was significant compared with single agents (Supplementary Fig. S13C). On the basis of these findings, combination studies were conducted with MRTX849 and RMC-4550 in six KRASG12C-mutated tumor models in vivo, and the combination demonstrated significantly greater antitumor efficacy compared with either single agent in 4 of 6 models evaluated (Fig. 6E; Supplementary Fig. S13D). Consistent with the in vitro data, the combination also demonstrated a significant decrease in ERK phosphorylation compared with either single agent in the KYSE-410 model as determined by quantitation of tumor-cell immunostaining on day 1 at 6 and 24 hours and day 7 at 6 hours after dose (Fig. 6F). Together, these data indicate that EGFR family and SHP2 blockade can augment the antitumor activity of KRASG12C inhibitors through enhancing covalent target modification and establishing a more comprehensive blockade of KRAS-dependent signaling.
Combinations That Inhibit Bypass Pathways Downstream of KRAS and Exhibit Increased Antitumor Activity in Xenograft Models
KRAS is implicated in regulation of the oncogenic S6 protein translation pathway through both ERK-dependent activation of RSK, which phosphorylates S6 at Ser235/236, and cross-talk with the PI3K and mTOR pathway that additionally phosphorylates S6 at Ser240/244 (29). However, the S6 pathway can also be activated independently of mutated KRAS in tumor cells through hyperactivated RTK signaling, PI3K activation, or STK11 mutations, each of which converge on mTOR-mediated activation of S6. In the in vitro combination screen, mTOR inhibitors demonstrated synergy in a subset of evaluated cell lines (Supplementary Fig. S14A). To further evaluate the effect of the combination on KRAS and mTOR pathway–dependent signaling, four cell lines were treated with MRTX849 in the presence or absence of the selective ATP-competitive mTOR inhibitor vistusertib (1 μmol/L), for 6 or 24 hours, and several signaling molecules were evaluated by RPPA. Vistusertib demonstrated clear and robust inhibition of several components of the PI3K–mTOR signaling pathway including AKT (S473), p70 S6K (T412), S6 (pS235/236, S240/244), and 4E-BP1 (S65, T70) phosphorylation in each cell line at both time points consistent with its mechanism of action (Supplementary Fig. S14B). MRTX849 alone did not affect 4E-BP1 or S6 (S240/244) activity, and it exhibited a variable and cell line–dependent effect on p70 S6K and S6 (pS235/236) phosphorylation in these cell lines. Vistusertib also demonstrated marked induction of ERK phosphorylation, often several-fold over vehicle control, at both time points in all four cell lines, consistent with prior reports (30). The combination of vistusertib and MRTX849 demonstrated a comparable level of inhibition of ERK phosphorylation compared with single-agent MRTX849, indicating that the activation of ERK signaling by vistusertib was impeded by the combination of the two agents. In addition, MRTX849 combined with vistusertib further inhibited p70 S6K and AKT S473 phosphorylation compared with either single agent. Near-complete inhibition of S6 (S235/236, S240/244) phosphorylation at limit of detection was observed for the combination in each cell line at evaluated time points.
Consequently, a cohort of tumor models was identified, and the combination of MRTX849 with the selective mTOR inhibitor vistusertib demonstrated marked tumor regression and significantly improved antitumor activity compared with either single agent in all six models evaluated (Fig. 7A; Supplementary Fig. S14C). MRTX849 in combination with a second, differentiated mTOR inhibitor, everolimus, which inhibits TORC1 but not TORC2, in the H2030 xenograft model also demonstrated a striking combination effect (Supplementary Fig. S14D). In the KRASG12C, STK11-mutant H2030 model, MRTX849 demonstrated marked inhibition of ERK phosphorylation through 24 hours, but exhibited only partial inhibition of pS6235/36 at 6 hours after dose, on days 1 and 7 (Fig. 7B and C). Vistusertib demonstrated marked inhibition of pS6235/36 at 6 hours after treatment with evidence of recovery by 24 hours. The combination of vistusertib and MRTX849 did not have a further effect on ERK phosphorylation but demonstrated a significant reduction in pS6235/36 on day 1 at 24 hours compared with vistusertib alone and a trend toward reduced pS6235/36 on both day 1 and day 7 at 6 hours compared with either single agent (Fig. 7B; Supplementary Fig. S14E). Together, these data indicate that MRTX849 and mTOR inhibitor combination demonstrates complementary inhibition of the ERK and mTOR–S6 signaling pathways, resulting in broad antitumor activity in KRASG12C-mutant tumor models.
CDK4/6 and mTOR combinations suppress independently hyperactivated downstream pathways and exhibit increased antitumor responses. A, MRTX849 at 100 mg/kg, vistusertib at 15 mg/kg, or the combination was administered daily via oral gavage to mice bearing the H2122 or H2030 cell line xenografts (n = 5/group). Combination treatment led to a statistically significant decrease in tumor growth compared with either single-agent treatment. *, Padj < 0.05. B, MRTX849 at 100 mg/kg, vistusertib at 15 mg/kg, or the combination was administered once or daily for 7 days via oral gavage to mice bearing H2030 cell line xenografts (n = 3/group). Tumors were harvested at 6 and 24 hours following the final dose. Tumor sections were stained with pERK and pS6 via IHC methods. Quantitation of images shown by H-score in tumor tissue. Reduction of pERK or pS6 staining intensity was determined to be statistically significant relative to vehicle or either single agent using one-way ANOVA. Brackets indicate P < 0.05 compared with left-most sample. C, Protein Western blot analysis of KRAS pathway targets in H2030 xenografts treated with MRTX849 (100 mg/kg), vistusertib (15 mg/kg), or the combination, 6 or 24 hours after a single dose. D, Protein Western blot analysis of KRAS pathway and cell-cycle targets in H2122 cells treated for 24 hours with MRTX849, palbociclib, or the combination. E, Normalized RNA-seq gene-expression data on E2F targets in H2122 xenografts treated with MRTX849, palbociclib, or the combination, 6 and 24 hours after a single daily dose or seven daily doses. F, MRTX849 at 100 mg/kg, palbociclib at 130 mg/kg, or the combination was administered daily via oral gavage to mice bearing the H2122 or SW1573 cell line xenografts (n = 5). Combination treatment led to a statistically significant decrease in tumor growth compared with either single-agent treatment. *, Padj < 0.05.
Signaling through KRAS is known to mediate cell proliferation, at least in part, through the regulation of the cyclin D family and triggering RB/E2F-dependent entry of cells into cell cycle. Loss-of-function mutations and homozygous deletions in the cell-cycle tumor suppressor CDKN2A (p16) are coincident in a subset of KRAS-mutant non–small cell lung cancer (NSCLC) and hyperactivate CDK4/6-dependent RB phosphorylation and cell-cycle transition. In the CDKN2A-null H2122 and SW1573 cell lines in vitro, MRTX849 demonstrated concentration-dependent partial inhibition of RB phosphorylation (pRB pS807/811) and concurrent increase in p27 in H2122 cells, but not SW1573 cells, at 24 hours (Fig. 7D; Supplementary Fig. S15A). MRTX849 in combination with the CDK4/6 inhibitor palbociclib (1 μmol/L) demonstrated near-complete inhibition of pRB in both H2122 and SW1573 cells and further induced p27 in H2122 cells. Interestingly, pS6 (S235/236) was also much more effectively suppressed by the combination in both H2122 and SW1573 cells, which is consistent with a recent report (31). RNA expression of target genes and RPPA analysis of target protein signaling events were also used as a readout of cell-cycle inhibition in the H2122 tumor model in vivo, and the combination of MRTX849 and palbociclib significantly inhibited E2F1 and selected E2F family target genes, induced p27 protein expression to a greater degree compared with either single agent, and further reduced the number of Ki-67–positive cells after 7 days of administration (Fig. 7E; Supplementary Fig. S15B and S15C). In addition, the combination demonstrated a significant decrease in pRB (S780) compared with either single agent after 7 days of administration in SW1573 tumors in vivo (Supplementary Fig. S15D). This combination also induced tumor regression in five tumor xenograft models that was significant compared with either single-agent control (Fig. 7F; Supplementary Fig. S15E). Although not significant, a trend was noted in which models with CDKN2A homozygous deletion exhibited an increased antitumor response to the combination of MRTX849 and CDK4/6 inhibition compared with models lacking evidence of genetic dysregulation of key cell-cycle genes (Supplementary Fig. S15F and S15G).
Discussion
The identification of MRTX849 as a highly selective KRASG12C inhibitor capable of near-complete inhibition of KRAS in vivo provides a renewed opportunity to better understand the role of this mutation as an oncogenic driver in various cancers and to guide rational clinical trial design. The lack of a significant correlation between sensitivity to MRTX849 antitumor activity in in vitro versus in vivo model systems made it necessary to further study KRAS oncogene dependence in tumor models in vivo, a more clinically relevant setting. The demonstration that MRTX849 exhibited significant antitumor efficacy in all evaluated KRASG12C-mutated cancer models and demonstrated marked regression in the majority (65%) confirms that this mutation is a broadly operative oncogenic driver and that MRTX849 represents a compelling therapeutic opportunity. This evidence of activity extended to patients, as demonstrated by RECIST partial responses in 2 patients enrolled in a phase I clinical trial of MRTX849. Collectively however, these data also illustrate that the degree of dependence of cancer cells on the presence of a KRASG12C mutation for growth and survival can vary across tumors and that co-occurring genetic alterations observed in KRAS-mutated cancers may influence response to direct targeted therapy. The further observation that KRAS mutations occur across different cancers and that no single co-occurring genetic alteration predicted response to treatment illustrates the genetic heterogeneity of KRAS-driven cancers. Findings in the present studies are consistent with other functional genomics or therapeutic strategies to block KRAS function across panels of cell lines or models which demonstrated a highly significant response of KRAS-mutant cells to target knockdown, a heterogeneous magnitude of response, and no clear co-occurring aberrations that predict resistance to target blockade (5, 32, 33). Interestingly, despite the implication that certain mutations that co-occur with KRAS including TP53, STK11, and KEAP1 may limit therapeutic response in KRASG12C-positive lung cancers, none of these mutations correlated with response or resistance in the cell-line panel. In addition, the partial response we reported in the patient with lung adenocarcinoma was observed in a patient harboring deleterious comutations in both STK11 and KEAP1. Together, these data further illustrate the heterogeneity and complexity of KRAS-mutated cancers and suggest that no binary co-occurring genetic event may be predictive of therapeutic response.
Temporal and dose–response analysis indicated maximal modification of KRASG12C and durable inhibition of KRAS-dependent signaling was important in maximizing therapeutic response. The recovery of ERK signaling and the inability to inhibit mTOR–S6 signaling despite continued treatment were each associated with transient or submaximal response to MRTX849. ERK1/2 is implicated in direct phosphorylation and negative feedback regulation of EGFR (T669), FGFR1 (S777), and SOS1, and each of these targets may facilitate KRASG12C-independent resetting of ERK signaling flux (34–36). The rapid and remarkable suppression of ERK pathway–regulated transcripts such as DUSP and SPRY/SPRED family members by MRTX849 in all models evaluated is consistent with that observed for RAF inhibitors and is implicated in reactivation of ERK and RTK signaling (18, 19). The dual-specificity phosphatases DUSP4 and 6 were strongly suppressed by MRTX849 and are implicated in dephosphorylating and inactivating ERK1/2 (14, 18, 37), whereas SPRY family members are implicated in the negative regulation of RTKs and adaptor proteins (e.g., GRB2), and may participate in modifying RAS family nucleotide exchange and effector binding (e.g., RAF1; ref. 38). Although suppression of DUSP and SPRY/SPRED was broadly observed in all models, the magnitude of signaling reactivation and response to MRTX849 varied across models. This suggests some tumor models harbor additional factors that bypass KRAS dependence or affect RAS pathway signaling flux, such as expression or activation of selected RTKs (e.g., ERBB2 amplification in the KYSE-410 model) or STK11 loss-of-function mutations, and may be primed for feedback reactivation of RAS-dependent signaling and/or limit the degree of signaling inhibition by MRTX849. This phenomenon was observed for BRAFV600E-mutant colon cancer (but not melanoma) which exhibits high baseline EGFR expression, is primed for rapid feedback activation of this RTK, and is resistant to single-agent inhibition but highly responsive to cotargeting BRAF (and/or MEK) and EGFR (20). In addition, blockade of BRAF or MEK1/2 resulted in feedback-mediated activation of the PI3K–mTOR signaling pathway in concert with the coactivation of upstream RTKs (e.g., EGFR), resulting in bypass of ERK pathway dependence and therapeutic resistance (17, 20, 39). The observations that baseline expression of HER family RTKs trended with MRTX849 antitumor activity and that CRISPR-based drug-anchored screens implicated EGFR, SHP2, and mTOR–S6 pathways as cotargetable vulnerabilities both support the hypothesis that these targets act as conditional response modifiers.
Activation of RTK signaling in the context of KRASG12C-mutant cancer was predicted to limit MRTX849 therapeutic response both by enhancing extrinsic regulation of GTPase activity and initiating KRAS-independent ERK and mTOR–S6 pathway activation. Therefore, HER family and SHP2 inhibition were employed as strategies to either block the critical RTK family in KRAS-mutant cells or block collective RTK signaling downstream, respectively. As MRTX849 binds only GDP-KRASG12C, both HER family and SHP2 inhibition each enhanced KRASG12C modification by MRTX849 and significantly improved antitumor activity. This observation is consistent with the putative role of activated RTKs in the engagement of SHP2 to mediate SOS1-dependent RAS GTP loading and to diminish RAS GAP activity, each of which converge on enhanced RAS activation state (40). The afatinib combination demonstrated a clear and marked inhibition of both the ERK–RSK and AKT–mTOR–S6 signaling pathways, whereas the SHP2 inhibitor combination demonstrated a clear impact on ERK–RSK signaling and a relatively less prominent impact on mTOR–S6 signaling. Although afatinib may more effectively address mTOR–S6 bypass signaling, SHP2 inhibition should be an effective combinatorial strategy to combat other RTKs outside of the HER family, such as FGFRs or MET, that could affect KRAS dependence. To further address bypass signaling mediated by RTK activation or STK11 mutations, each of which activate the mTOR–S6 signaling pathway independently of KRAS, mTOR inhibition in combination with MRTX849 was also evaluated. MRTX849 in combination with vistusertib, in fact, demonstrated significantly improved antitumor activity in vivo compared with either single agent in all six tumor models evaluated, regardless of STK11 mutational status. Consistent with the mechanism of action of vistusertib, comprehensive inhibition of AKT–mTOR–S6 signaling was observed for vistusertib alone and near-complete inhibition of pS6S235–36 and pS6240–44 was observed in combination. In addition, the marked feedback reactivation of ERK by vistusertib was relieved by the combination. The induction of ERK activity has been observed in tumor cells following mTORC1 inhibition by rapalogs or ATP-competitive inhibitors and has been implicated in limiting antitumor activity of this class of agents (30, 41, 42), supporting the suppression of ERK signaling by MRTX849 as a key mechanism of response to the combination. Notably, all three combination strategies converge on more comprehensive inhibition of KRAS-dependent signaling, converging on ERK and S6 activity. In addition, although the inhibition of the AKT–mTOR–S6 pathway did not correlate with model response to MRTX849 (potentially due to tumor heterogeneity), the observations that both MTOR and RPS6 drop out in drug-anchored CRISPR screens and that effective combination strategies more comprehensively block this pathway illustrate its likely importance in maximizing therapeutic response in KRAS-mutated cancers.
Cell-cycle dysregulation due to genetic alterations in cell-cycle regulators identified additional factors that could modify the therapeutic response to MRTX849. In addition, CDKN2A, RB1, CDK4, and CDK6 were all identified as gene targets that affected cell fitness in CRISPR screens. Genetic alterations including homozygous deletion of CDKN2A or amplification of CDK4 or CCND1 comprise up to 20% of KRAS-mutated NSCLC (43). Combination studies with MRTX849 and palbociclib in vivo demonstrated more comprehensive inhibition of RB and E2F family target genes and increased antitumor activity compared with either single agent in NSCLC models. In addition, these studies indicated that the combination resulted in more effective inhibition of S6 (S235/236) phosphorylation, establishing a previously unappreciated connection between cell-cycle blockade and protein translation pathways. Notably, this combination was especially effective in CDKN2A-deleted models, suggesting that this combination strategy may be primarily beneficial in a molecularly defined subset of patients characterized by decoupling of cell-cycle regulation from KRAS.
Collectively, models exhibiting a cytoreductive response to single-agent MRTX849 demonstrated a more comprehensive and durable inhibition of KRAS-dependent signaling and induction of an apoptotic response. These data suggest that maintaining durable inhibition of KRAS-dependent signaling below a defined threshold is required to elicit tumor regression. The elucidation of mechanisms that limit the therapeutic response to single-agent KRAS inhibition has provided insight toward strategies to enhance therapeutic activity in KRAS-mutant tumors. Of the 35% of models (9/26) that did not exhibit durable regression with single-agent MRTX849 treatment, five models (KYSE410, SW1573, H2122, H2030, and LU6405) were selected for rational combination studies, and at least one combination demonstrated significant improvement in antitumor efficacy and elicited a >50% tumor regression in all five models evaluated. These results suggest that essentially all KRASG12C-mutated cancers can derive clinical benefit from direct KRAS inhibitor–directed therapy either alone or in combination. Furthermore, rational pathway-centric combination regimens directed at hallmark signaling nodes may be directed to genetically defined patient subsets. For example, KRAS-mutated NSCLC exhibits mutually exclusive, co-occurring genetic alterations in STK11 and CDKN2A (43). The present data suggest that KRASG12C/STK11-mutated NSCLC could be readily addressed by combining a KRASG12C inhibitor with an RTK or mTOR inhibitor, whereas KRASG12C/CDKN2A-mutated NSCLC could be more effectively addressed by combination with a CDK4/6 inhibitor. Collectively, the present studies support the broad utility of covalent KRASG12C inhibitors in treating KRASG12C-mutated cancers and provide defining strategies to identify patients likely to benefit from single-agent therapy or rationally directed combinations.
UPDATED 02/07/2021
The November 1st issue of Science highlights a series of findings which give cancer researchers some hope in finally winning a thirty year war with the discovery of drugs that target KRAS, one of the most commonly mutated oncogenes (25% of cancers), and thought to be a major driver of tumorigenesis. Once considered an undruggable target, mainly because of the smooth surface with no obvious pockets to fit a drug in, as well as the plethora of failed attempts to develop such an inhibitor, new findings with recently developed candidates, highlighted in this article and other curated within, are finally giving hope to researchers and oncologists who have been hoping for a clinically successful inhibitor of this once considered elusive target.
Figure 1Mechanism of Action of ARS853 showing that the inhibitors may not need bind to the active conformation of KRAS for efficacy
Abstract: Two recent studies evaluated a small molecule that specifically binds to and inactivates the KRAS G12C mutant. The new findings argue that the perception that mutant KRAS is persistently frozen in its active GTP-bound form may not be accurate.
Although the development of the KRASG12C-specific inhibitor, compound 12 (Ostrem et al., 2013), was groundbreaking, subsequent studies found that the potency of compound 12 in cellular assays was limited (Lito et al., 2016, Patricelli et al., 2016). A search for more-effective analogs led to the development of ARS853 (Patricelli et al., 2016), which exhibited a 600-fold increase of its reaction rate in vitro over compound 12 and cellular activities in the low micromolar range.
A Summary and more in-depth curation of the Science article is given below:
Cancer researchers are making progress toward a goal that has eluded them for more than 30 years: shrinking tumors by shutting off a protein called KRAS that drives growth in many cancer types. A new type of drug aimed at KRAS made tumors disappear in mice and shrank tumors in lung cancer patients, two companies report in papers published this week. It’s not yet clear whether the drugs will extend patients’ lives, but the results are generating a wave of excitement. And one company, Amgen, reports an unexpected bonus: Its drug also appears to stimulate the immune system to attack tumors, suggesting it could be even more powerful if paired with widely available immunotherapy treatments.
In 2013, Dr. Kevan Shokat’s lab at UCSF discovered a small molecule that could fit in the groove of the KRAS mutant G12C. The G12C as well as the G12D is a common mutation found in KRAS in cancers. KRAS p.G12C mutations predominate in NSCLC comprising 11%–16% of lung adenocarcinomas (45%–50% of mutant KRAS is p.G12C) (Campbell et al., 2016; Jordan et al., 2017), as well as 1%–4% of pancreatic and colorectal adenocarcinomas, respectively (Bailey et al., 2016; Giannakis et al., 2016). This inhibitor was effective in shrinking, in mouse studies conducted by Wellspring Biosciences, implanted tumors containing this mutant KRAS.
Amgen press release on AMG510 Clinical Trial at ASCO 2019
THOUSAND OAKS, Calif., June 3, 2019 /PRNewswire/ — Amgen (NASDAQ: AMGN) today announced the first clinical results from a Phase 1 study evaluating investigational AMG 510, the first KRASG12C inhibitor to reach the clinical stage. In the trial, there were no dose-limiting toxicities at tested dose levels. AMG 510 showed anti-tumor activity when administered as a monotherapy in patients with locally-advanced or metastatic KRASG12C mutant solid tumors. These data are being presented during an oral session at the 55th Annual Meeting of the American Society of Clinical Oncology (ASCO) in Chicago.
“KRAS has been a target of active exploration in cancer research since it was identified as one of the first oncogenes more than 30 years ago, but it remained undruggable due to a lack of traditional small molecule binding pockets on the protein. AMG 510 seeks to crack the KRAS code by exploiting a previously hidden groove on the protein surface,” said David M. Reese, M.D., executive vice president of Research and Development at Amgen. “By irreversibly binding to cysteine 12 on the mutated KRAS protein, AMG 510 is designed to lock it into an inactive state. With high selectivity for KRASG12C, we believe investigational AMG 510 has high potential as both a monotherapy and in combination with other targeted and immune therapies.”
The Phase 1, first-in-human, open-label multicenter study enrolled 35 patients with various tumor types (14 non-small cell lung cancer [NSCLC], 19 colorectal cancer [CRC] and two other). Eligible patients were heavily pretreated with at least two or more prior lines of treatment, consistent with their tumor type and stage of disease.
Canon, J., Rex, K., Saiki, A.Y. et al. The clinical KRAS(G12C) inhibitor AMG 510 drives anti-tumour immunity. Nature 575, 217–223 (2019) doi:10.1038/s41586-019-1694-1
Besides blocking tumor growth, AMG510 appears to stimulate T cells to attack the tumor, thus potentially supplying a two pronged attack to the tumor, inhibiting oncogenic RAS and stimulating anti-tumor immunity.
Nearly four decades have passed since researchers first identified the RAS gene family, which includes HRAS, NRAS and KRAS. RAS is the most frequently mutated family of oncogenes – or potentially cancerous genes – in human cancers.1,2 While research efforts have been able to identify and develop treatments for other driver gene mutations that contribute to cancer growth, success with treating KRAS, the most frequently mutated variant of the RAS family, has remained elusive.2 But now there is hope.
Amgen, a leading biotechnology company, has taken on one of the toughest challenges of the last 40 years in cancer research.3 Chemical biologist Kevan Shokat’s lab at the University of California, San Francisco, identified a small molecule that could slip into a groove on a KRAS mutation called G12C in 2013.4 Building on their own research strategies and this new insight, scientists at Amgen used structural biology and medicinal chemistry to identify an adjacent groove, and by November 2017, made the initial decision to advance the molecule that would become investigational sotorasib.5
KRAS G12C is the most common KRAS mutation in NSCLC.6,7 In the U.S., about 13% of patients with NSCLC harbor the KRAS G12C mutation.8 There is a high unmet need and poor outcomes in the second-line treatment of KRAS G12C-driven non-small cell lung cancer (NSCLC) and, currently, there are no KRASG12C targeted therapies approved.2
According to Amgen’s head of research and development David Reese, “the company’s scientists had an idea some time ago that the future of oncology would be led by the marriage of immuno-oncology and precision therapy. We wanted to go after high value targets, and RAS proteins are one of them.”
At the same time that scientists discovered investigational sotorasib, the team was undertaking a project to map out every step it takes to progress a potential new treatment from an idea in a lab to being made available for patients. The goal was to shrink timelines and eliminate gaps to develop drugs more rapidly in order to reach patients with serious illnesses like NSCLC as quickly as possible.
Because of this effort to rapidly accelerate the speed of innovation, sotorasib entered clinical trials in humans less than 12 months.5 Sotorasib was the first investigational KRASG12C inhibitor to enter the clinic, and is now being studied in the broadest clinical program exploring 10 combinations with global investigational sites spanning five continents.9 In a little more than two years, the sotorasib clinical program has established a clinical data set of more than 700 patients studied across 13 tumor types.9
The investigational treatment was recently submitted to the FDA for review and was granted Breakthrough Therapy designation, a distinction designed to expedite the development and review of drugs.5 It was also accepted into the FDA’s Real-Time Oncology Review pilot program, which aims to explore a more efficient review process.5
To learn more about Amgen and how the speed of innovation is bringing new oncology treatments to patients with high unmet needs, visit Amgen.com/KnowKRAS.
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1 Ryan MB, et al. Nat Rev Clin Oncol. 2018;15:709-720.
2 Cox AD, et al. Nat Rev Drug Discov. 2014;13:828-851.
3 Kim D, et al. Cell. 2020. doi:10.1016/j.cell.2020.09.044.
Campbell, J.D., Alexandrov, A., Kim, J., Wala, J., Berger, A.H., Pedamallu, C.S., Shukla, S.A., Guo, G., Brooks, A.N., Murray, B.A., et al.; Cancer Genome Atlas Research Network (2016). Distinct patterns of somatic genome alterations in lung adenocarcinomas and squamous cell carcinomas. Nat. Genet.48, 607–616
Jordan, E.J., Kim, H.R., Arcila, M.E., Barron, D., Chakravarty, D., Gao, J., Chang, M.T., Ni, A., Kundra, R., Jonsson, P., et al. (2017). Prospective comprehensive molecular characterization of lung adenocarcinomas for efficient patient matching to approved and emerging therapies. Cancer Discov. 7, 596–609.
Bailey, P., Chang, D.K., Nones, K., Johns, A.L., Patch, A.M., Gingras, M.C., Miller, D.K., Christ, A.N., Bruxner, T.J., Quinn, M.C., et al.; Australian Pancreatic Cancer Genome Initiative (2016). Genomic analyses identify molecular subtypes of pancreatic cancer. Nature 531, 47–52.
Giannakis, M., Mu, X.J., Shukla, S.A., Qian, Z.R., Cohen, O., Nishihara, R., Bahl, S., Cao, Y., Amin-Mansour, A., Yamauchi, M., et al. (2016). Genomic correlates of immune-cell infiltrates in colorectal carcinoma. Cell Rep. 15, 857–865.
Complex rearrangements and oncogene amplification revealed by long-read DNA and RNA sequencing of a breast cancer cell line, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)
Complex rearrangements and oncogene amplification revealed by long-read DNA and RNA sequencing of a breast cancer cell line
Reporter: Stephen J. Williams, PhD
In a Genome Research report by Marie Nattestad et al. [1], the SK-BR-3 breast cancer cell line was sequenced using a long read single molecule sequencing protocol in order to develop one of the most detailed maps of structural variations in a cancer genome to date. The authors detected over 20,000 variants with this new sequencing modality, whereas most of these variants would have been missed by short read sequencing. In addition, a complex sequence of nested duplications and translocations occurred surrounding the ERBB2 (HER2) while full-length transcriptomic analysis revealed novel gene fusions within the nested genomic variants. The authors suggest that combining this long-read genome and transcriptome sequencing results in a more comprehensive coverage of tumor gene variants and “sheds new light on the complex mechanisms involved in cancer genome evolution.”
Genomic instability is a hallmark of cancer [2], which lead to numerous genetic variations such as:
Copy number variations
Chromosomal alterations
Gene fusions
Deletions
Gene duplications
Insertions
Translocations
Efforts such as the Cancer Genome Atlas [3], and the International Genome Consortium (2010) use short-read sequencing technology to detect and analyze thousands of commonly occurring mutations however short-read technology has a high false positive and negative rate for detecting less common genetic structural variations {as high as 50% [4]}. In addition, short reads cannot detect variations in close proximity to each other or on the same molecule, therefore underestimating the variation number.
Methods: The authors used a long-read sequencing technology from Pacific Biosciences (SMRT) to analyze the mutational and structural variation in the SK-BR-3 breast cancer cell line. A split read and within-read mapping approach was used to detect variants of different types and sizes. In general, long-reads have better alignment qualities than short reads, resulting in higher quality mapping. Transcriptomic analysis was performed using Iso-Seq.
Results: Using the SMRT long-read sequencing technology from Pacific Biosciences, the authors were able to obtain 71.9% sequencing coverage with average read length of 9.8 kb for the SK-BR-3 genome.
A few notes:
Most amplified regions (33.6 copies) around the locus spanning the ERBB2 oncogene and around MYC locus (38 copies), EGFR locus (7 copies) and BCAS1 (16.8 copies)
The locus 8q24.12 had the most amplifications (this locus contains the SNTB1 gene) at 69.2 copies
Long-read sequencing showed more insertions than deletions and suggests an underestimate of the lengths of low complexity regions in the human reference genome
Found 1,493 long read variants, 603 of which were between different chromosomes
Using Iso-Seq in conjunction with the long-read platform, they detected 1,692,379 isoforms (93%) mapping to the reference genome and 53 putative gene fusions (39 of which they found genomic evidence)
A table modified from the paper on the gene fusions is given below:
Table 1. Gene fusions with RNA evidence from Iso-Seq and DNA evidence from SMRT DNA sequencing where the genomic path is found using SplitThreader from Sniffles variant calls. Note link in table is GeneCard for each gene.
SplitThreader found two different paths for the RAD51B-SEMA6D gene fusion and for the LINC00536-PVT1 gene fusion. Number of Iso-Seq reads refers to full-length HQ-filtered reads. Alignments of SMRT DNA sequence reads supporting each of these gene fusions are shown in Supplemental Note S2.
References
Nattestad M, Goodwin S, Ng K, Baslan T, Sedlazeck FJ, Rescheneder P, Garvin T, Fang H, Gurtowski J, Hutton E et al: Complex rearrangements and oncogene amplifications revealed by long-read DNA and RNA sequencing of a breast cancer cell line.Genome research 2018, 28(8):1126-1135.
Kandoth C, McLellan MD, Vandin F, Ye K, Niu B, Lu C, Xie M, Zhang Q, McMichael JF, Wyczalkowski MA et al: Mutational landscape and significance across 12 major cancer types. Nature 2013, 502(7471):333-339.
Sudmant PH, Rausch T, Gardner EJ, Handsaker RE, Abyzov A, Huddleston J, Zhang Y, Ye K, Jun G, Fritz MH et al: An integrated map of structural variation in 2,504 human genomes. Nature 2015, 526(7571):75-81.
Other articles on Cancer Genome Sequencing in this Open Access Journal Include:
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