KRAS Testing: Optimizing Cancer Therapy.
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ABSTRACT:
SUBMITTER: Carlson B
PROVIDER: S-EPMC2816163 | biostudies-literature | 2009
REPOSITORIES: biostudies-literature
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Project description:BackgroundLung cancer patients with KRAS mutation(s) have a poor prognosis due in part to the development of resistance to currently available therapeutic interventions. Development of a new class of anticancer agents that directly targets KRAS may provide a more attractive option for the treatment of KRAS-mutant lung cancer.ResultsHere we identified a small molecule KRAS agonist, KRA-533, that binds the GTP/GDP-binding pocket of KRAS. In vitro GDP/GTP exchange assay reveals that KRA-533 activates KRAS by preventing the cleavage of GTP into GDP, leading to the accumulation of GTP-KRAS, an active form of KRAS. Treatment of human lung cancer cells with KRA-533 resulted in increased KRAS activity and suppression of cell growth. Lung cancer cell lines with KRAS mutation were relatively more sensitive to KRA-533 than cell lines without KRAS mutation. Mutating one of the hydrogen-bonds among the KRA-533 binding amino acids in KRAS (mutant K117A) resulted in failure of KRAS to bind KRA-533. KRA-533 had no effect on the activity of K117A mutant KRAS, suggesting that KRA-533 binding to K117 is required for KRA-533 to enhance KRAS activity. Intriguingly, KRA-533-mediated KRAS activation not only promoted apoptosis but also autophagic cell death. In mutant KRAS lung cancer xenografts and genetically engineered mutant KRAS-driven lung cancer models, KRA-533 suppressed malignant growth without significant toxicity to normal tissues.ConclusionsThe development of this KRAS agonist as a new class of anticancer drug offers a potentially effective strategy for the treatment of lung cancer with KRAS mutation and/or mutant KRAS-driven lung cancer.
| S-EPMC6456974 | biostudies-literature
Project description:KRAS mutations are the most frequent gain-of-function alterations in patients with lung adenocarcinoma (LADC) in the Western world. Although they have been identified decades ago, prior efforts to target KRAS signaling with single-agent therapeutic approaches such as farnesyl transferase inhibitors, prenylation inhibition, impairment of KRAS downstream signaling, and synthetic lethality screens have been unsuccessful. Moreover, the role of KRAS oncogene in LADC is still not fully understood, and its prognostic and predictive impact with regards to the standard of care therapy remains controversial. Of note, KRAS-related studies that included general non-small cell lung cancer (NSCLC) population instead of LADC patients should be very carefully evaluated. Recently, however, comprehensive genomic profiling and wide-spectrum analysis of other co-occurring genetic alterations have identified unique therapeutic vulnerabilities. Novel targeted agents such as the covalent KRAS G12C inhibitors or the recently proposed combinatory approaches are some examples which may allow a tailored treatment for LADC patients harboring KRAS mutations. This review summarizes the current knowledge about the therapeutic approaches of KRAS-mutated LADC and provides an update on the most recent advances in KRAS-targeted anti-cancer strategies, with a focus on potential clinical implications.
| S-EPMC7680319 | biostudies-literature
Project description: Not available
| S-EPMC7354316 | biostudies-literature
Project description:Gastroesophageal adenocarcinomas (GEAs) harbor recurrent amplification of KRAS, leading to marked overexpression of WT KRAS protein. We previously demonstrated that SHP2 phosphatase, which acts to promote KRAS and downstream MAPK pathway activation, is a target in these tumors when combined with MEK inhibition. We hypothesized that SHP2 inhibitors may serve as a foundation for developing novel combination inhibitor strategies for therapy of KRAS-amplified GEA, including with targets outside the MAPK pathway. Here, we explore potential targets to effectively augment the efficacy of SHP2 inhibition, starting with genome-wide CRISPR screens in KRAS-amplified GEA cell lines with and without SHP2 inhibition. We identify candidate targets within the MAPK pathway and among upstream RTKs that may enhance SHP2 efficacy in KRAS-amplified GEA. Additional in vitro and in vivo experiments demonstrated the potent cytotoxicity of pan-ERBB kinase inhibitions in vitro and in vivo. Furthermore, beyond targets within the MAPK pathway, we demonstrate that inhibition of CDK4/6 combines potently with SHP2 inhibition in KRAS-amplified GEA, with greater efficacy of this combination in KRAS-amplified, compared with KRAS-mutant, tumors. These results suggest therapeutic combinations for clinical study in KRAS-amplified GEAs.
| S-EPMC9977440 | biostudies-literature
Project description:We identified a polyclonal CD8+ T-cell response against mutant KRAS G12D in tumor-infiltrating lymphocytes obtained from a patient with metastatic colorectal cancer. We observed objective regression of all seven lung metastases after the infusion of approximately 1.11×1011 HLA-C*08:02-restricted tumor-infiltrating lymphocytes that were composed of four different T-cell clonotypes that specifically targeted KRAS G12D. However, one of these lesions had progressed on evaluation 9 months after therapy. The lesion was resected and found to have lost the chromosome 6 haplotype encoding the HLA-C*08:02 class I major histocompatibility complex (MHC) molecule. The loss of expression of this molecule provided a direct mechanism of tumor immune evasion. Thus, the infusion of CD8+ cells targeting mutant KRAS mediated effective antitumor immunotherapy against a cancer that expressed mutant KRAS G12D and HLA-C*08:02.
| S-EPMC5178827 | biostudies-literature
Project description:Recent clinical trials have shown that adaptive drug therapies can be more efficient than a standard cancer treatment based on a continuous use of maximum tolerated doses (MTD). The adaptive therapy paradigm is not based on a preset schedule; instead, the doses are administered based on the current state of tumour. But the adaptive treatment policies examined so far have been largely ad hoc. We propose a method for systematically optimizing adaptive policies based on an evolutionary game theory model of cancer dynamics. Given a set of treatment objectives, we use the framework of dynamic programming to find the optimal treatment strategies. In particular, we optimize the total drug usage and time to recovery by solving a Hamilton-Jacobi-Bellman equation. We compare MTD-based treatment strategy with optimal adaptive treatment policies and show that the latter can significantly decrease the total amount of drugs prescribed while also increasing the fraction of initial tumour states from which the recovery is possible. We conclude that the use of optimal control theory to improve adaptive policies is a promising concept in cancer treatment and should be integrated into clinical trial design.
| S-EPMC7211445 | biostudies-literature
Project description:COVID-19 testing across India uses a mix of two types of tests. Rapid Antigen Tests (RATs) are relatively inexpensive point-of-care lateral-flow-assay tests, but they are also less sensitive. The reverse-transcriptase polymerase-chain-reaction (RT-PCR) test has close to 100% sensitivity and specificity in a laboratory setting, but delays in returning results, as well as increased costs relative to RATs, may vitiate this advantage. India-wide, about 49% of COVID-19 tests are RATs, but some Indian states, including the large states of Uttar Pradesh (pop. 227.9 million) and Bihar (pop. 121.3 million) use a much higher proportion of such tests. Here we show, using simulations based on epidemiological network models, that the judicious use of RATs can yield epidemiological outcomes comparable to those obtained through RT-PCR-based testing and isolation of positives, provided a few conditions are met. These are (a) that RAT test sensitivity is not too low, (b) that a reasonably large fraction of the population, of order 0.5% per day, can be tested, (c) that those testing positive are isolated for a sufficient duration, and that (d) testing is accompanied by other non-pharmaceutical interventions for increased effectiveness. We assess optimal testing regimes, taking into account test sensitivity and specificity, background seroprevalence and current test pricing. We find, surprisingly, that even 100% RAT test regimes should be acceptable, from both an epidemiological as well as a economic standpoint, provided the conditions outlined above are met.
| S-EPMC8297905 | biostudies-literature
Project description:PURPOSE:An assay for the single-nucleotide polymorphism (SNP), rs61764370, has recently been commercially marketed as a clinical test to aid ovarian cancer risk evaluation in women with family histories of the disease. rs67164370 is in a 3'-UTR miRNA binding site of the KRAS oncogene and is a candidate for epithelial ovarian cancer (EOC) susceptibility. However, only one published article, analyzing fewer than 1,000 subjects in total, has examined this association. EXPERIMENTAL DESIGN:Risk association was evaluated in 8,669 cases of invasive EOC and 10,012 controls from 19 studies participating in the Ovarian Cancer Association Consortium, and in 683 cases and 2,044 controls carrying BRCA1 mutations from studies in the Consortium of Investigators of Modifiers of BRCA1/2. Prognosis association was also examined in a subset of five studies with progression-free survival (PFS) data and 18 studies with all-cause mortality data. RESULTS:No evidence of association was observed between genotype and risk of unselected EOC (OR = 1.02, 95% CI: 0.95-1.10), serous EOC (OR = 1.08, 95% CI: 0.98-1.18), familial EOC (OR = 1.09, 95% CI: 0.78-1.54), or among women carrying deleterious mutations in BRCA1 (OR = 1.09, 95% CI: 0.88-1.36). There was little evidence for association with survival time among unselected cases (HR = 1.10, 95% CI: 0.99-1.22), among serous cases (HR = 1.12, 95% CI = 0.99-1.28), or with PFS in 540 cases treated with carboplatin and paclitaxel (HR = 1.18, 95% CI: 0.93-1.52). CONCLUSIONS:These data exclude the possibility of an association between rs61764370 and a clinically significant risk of ovarian cancer or of familial ovarian cancer. Use of this SNP for ovarian cancer clinical risk prediction, therefore, seems unwarranted.
| S-EPMC3107901 | biostudies-literature
Project description:Human epidermal growth factor receptor 2 positive (HER2+) breast cancer is frequently treated with drugs that target the HER2 receptor, such as trastuzumab, in combination with chemotherapy, such as doxorubicin. However, an open problem in treatment design is to determine the therapeutic regimen that optimally combines these two treatments to yield optimal tumor control. Working with data quantifying temporal changes in tumor volume due to different trastuzumab and doxorubicin treatment protocols in a murine model of human HER2+ breast cancer, we propose a complete framework for model development, calibration, selection, and treatment optimization to find the optimal treatment protocol. Through different assumptions for the drug-tumor interactions, we propose ten different models to characterize the dynamic relationship between tumor volume and drug availability, as well as the drug-drug interaction. Using a Bayesian framework, each of these models are calibrated to the dataset and the model with the highest Bayesian information criterion weight is selected to represent the biological system. The selected model captures the inhibition of trastuzumab due to pre-treatment with doxorubicin, as well as the increase in doxorubicin efficacy due to pre-treatment with trastuzumab. We then apply optimal control theory (OCT) to this model to identify two optimal treatment protocols. In the first optimized protocol, we fix the maximum dosage for doxorubicin and trastuzumab to be the same as the maximum dose delivered experimentally, while trying to minimize tumor burden. Within this constraint, optimal control theory indicates the optimal regimen is to first deliver two doses of trastuzumab on days 35 and 36, followed by two doses of doxorubicin on days 37 and 38. This protocol predicts an additional 45% reduction in tumor burden compared to that achieved with the experimentally delivered regimen. In the second optimized protocol we fix the tumor control to be the same as that obtained experimentally, and attempt to reduce the doxorubicin dose. Within this constraint, the optimal regimen is the same as the first optimized protocol but uses only 43% of the doxorubicin dose used experimentally. This protocol predicts tumor control equivalent to that achieved experimentally. These results strongly suggest the utility of mathematical modeling and optimal control theory for identifying therapeutic regimens maximizing efficacy and minimizing toxicity.
| S-EPMC10552906 | biostudies-literature
Project description:The precise delivery of cytotoxic radiation to cancer cells through the combination of a specific targeting vector with a radionuclide for targeted radionuclide therapy (TRT) has proven valuable for cancer care. TRT is increasingly being considered a relevant treatment method in fighting micro-metastases in the case of relapsed and disseminated disease. While antibodies were the first vectors applied in TRT, increasing research data has cited antibody fragments and peptides with superior properties and thus a growing interest in application. As further studies are completed and the need for novel radiopharmaceuticals nurtures, rigorous considerations in the design, laboratory analysis, pre-clinical evaluation, and clinical translation must be considered to ensure improved safety and effectiveness. Here, we assess the status and recent development of biological-based radiopharmaceuticals, with a focus on peptides and antibody fragments. Challenges in radiopharmaceutical design range from target selection, vector design, choice of radionuclides and associated radiochemistry. Dosimetry estimation, and the assessment of mechanisms to increase tumor uptake while reducing off-target exposure are discussed.
| S-EPMC10221679 | biostudies-literature