Similar Datasets
Project description:Identifying resistance mutations in a drug target provides crucial information. Lentiviral transduction creates multiple types of mutations due to the error-prone nature of the HIV-1 reverse transcriptase (RT) and we show this property can be leveraged to identify mutations that confer resistance to targeted anti-cancer drugs, a technique we term “LentiMutate”. First, we improved LentiMutate by making the lentiviral RT more error-prone. Next, we applied this technique to two anti-cancer drugs, imatinib and AMG 510. We find novel deletions in BCR-ABL that confer resistance to BCR-ABL inhibitors and point mutations in the AMG 510 binding pocket or oncogenic non-G12C mutations, in KRAS-G12C or wild-type KRAS, respectively, that confer resistance to AMG 510. LentiMutate may prove highly valuable to clinical and preclinical cancer drug development
2021-07-25 | GSE164663 | GEO
Project description:Identifying resistance mutations in a drug target provides crucial information. Lentiviral transduction creates multiple types of mutations due to the error-prone nature of the HIV-1 reverse transcriptase (RT) and we show this property can be leveraged to identify mutations that confer resistance to targeted anti-cancer drugs, a technique we term “LentiMutate”. First, we improved LentiMutate by making the lentiviral RT more error-prone. Next, we applied this technique to two anti-cancer drugs, imatinib and AMG 510. We find novel deletions in BCR-ABL that confer resistance to BCR-ABL inhibitors and point mutations in the AMG 510 binding pocket or oncogenic non-G12C mutations, in KRAS-G12C or wild-type KRAS, respectively, that confer resistance to AMG 510. LentiMutate may prove highly valuable to clinical and preclinical cancer drug development
2021-07-25 | GSE164661 | GEO
Project description:Lentiviral-based mutagenesis to identify mutations that confer resistance to anti-cancer drugs
| PRJNA691514 | ENA
Project description:Lentiviral-based mutagenesis to identify mutations that confer resistance to anti-cancer drugs [lenti]
| PRJNA691528 | ENA
Project description:Lentiviral-based mutagenesis to identify mutations that confer resistance to anti-cancer drugs [umi]
| PRJNA691523 | ENA
Project description:Replication-incompetent gammaretroviral (?RV) and lentiviral (LV) vectors have both been used in insertional mutagenesis screens to identify cancer drivers. In this approach the vectors stably integrate in the host cell genome and induce cancers by dysregulating nearby genes. The cells that contain a retroviral vector provirus in or near a proto-oncogene or tumor suppressor are preferentially enriched in a tumor. ?RV and LV vectors have different integration profiles and genotoxic potential, making them potentially complementary tools for insertional mutagenesis screens. We performed screens using both ?RV and LV vectors to identify driver genes that mediate progression of androgen-independent prostate cancer (AIPC) using a xenotransplant mouse model. Vector transduced LNCaP cells were injected orthotopically into the prostate gland of immunodeficient mice. Mice that developed tumors were castrated to create an androgen-deficient environment and metastatic tumors that developed were analyzed. A high-throughput modified genomic sequencing PCR (MGS-PCR) approach identified the positions of vector integrations in these metastatic tumors. OR2A14, FER1L6, TAOK3, MAN1A2, MBNL2, SERBP1, PLEKHA2, SPTAN1, ADAMTS1, SLC30A5, ABCC1, SLC7A1 and SLC25A24 were identified as candidate prostate cancer (PC) progression genes. TAOK3 and ABCC1 expression in PC patients predicted the risk of recurrence after androgen deprivation therapy. Our data shows that ?RV and LV vectors are complementary approaches to identify cancer driver genes which may be promising potential biomarkers and therapeutic targets.
| S-EPMC5884640 | biostudies-literature
Project description:Identifying resistance mutations in a drug target provides crucial information. Lentiviral transduction creates multiple types of mutations due to the error-prone nature of the HIV-1 reverse transcriptase (RT). Here we optimized and leveraged this property to identify drug resistance mutations, developing a technique we term LentiMutate. This technique was validated by identifying clinically relevant EGFR resistance mutations, then applied to two additional clinical anticancer drugs: imatinib, a BCR-ABL inhibitor, and AMG 510, a KRAS G12C inhibitor. Novel deletions in BCR-ABL1 conferred resistance to imatinib. In KRAS-G12C or wild-type KRAS, point mutations in the AMG 510 binding pocket or oncogenic non-G12C mutations conferred resistance to AMG 510. LentiMutate should prove highly valuable for clinical and preclinical cancer-drug development. SIGNIFICANCE: LentiMutate can evaluate a drug's on-target activity and can nominate resistance mutations before they occur in patients, which could accelerate and refine drug development to increase the survival of patients with cancer.
| S-EPMC8448967 | biostudies-literature
Project description:Identifying resistance mutations in a drug target provides crucial information. Lentiviral transduction creates multiple types of mutations due to the error-prone nature of the HIV-1 reverse transcriptase (RT). We optimized and leveraged this property to identify drug resistance mutations, a technique we term LentiMutate. After validating this technique by identifying clinically relevant EGFR resistance mutations, we applied this technique to two additional anti-cancer drugs, imatinib and AMG 510. We find novel deletions in BCR-ABL1 that confer resistance to BCR-ABL1 inhibitors and point mutations in the AMG 510 binding pocket or oncogenic non-G12C mutations, in KRAS-G12C or wild-type KRAS, respectively, that confer resistance to AMG 510. LentiMutate may prove highly valuable to clinical and preclinical cancer drug development.
2021-07-28 | GSE180965 | GEO
Project description:Transposons and ?-retroviruses have been efficiently used as insertional mutagens in different tissues to identify molecular culprits of cancer. However, these systems are characterized by recurring integrations that accumulate in tumor cells and that hamper the identification of early cancer-driving events among bystander and progression-related events. We developed an insertional mutagenesis platform based on lentiviral vectors (LVVs) by which we could efficiently induce hepatocellular carcinoma (HCC) in three different mouse models. By virtue of the LVV's replication-deficient nature and broad genome-wide integration pattern, LVV-based insertional mutagenesis allowed identification of four previously unknown liver cancer-associated genes from a limited number of integrations. We validated the oncogenic potential of all the identified genes in vivo, with different levels of penetrance. The newly identified genes are likely to play a role in human cancer because they are upregulated, amplified and/or deleted in human HCCs and can predict clinical outcomes of patients.
| S-EPMC3589714 | biostudies-literature
Project description:The high transduction efficiency of lentiviral vectors in a wide variety of cells makes them an ideal tool for forward genetics screenings addressing issues of cancer research. Although molecular targeted therapies have provided significant advances in tumor treatment, relapses often occur by the expansion of tumor cell clones carrying mutations that confer resistance. Identification of the culprits of anticancer drug resistance is fundamental for the achievement of long-term response. Here, we developed a new lentiviral vector-based insertional mutagenesis screening to identify genes that confer resistance to clinically relevant targeted anticancer therapies. By applying this genome-wide approach to cell lines representing two subtypes of HER2(+) breast cancer, we identified 62 candidate lapatinib resistance genes. We validated the top ranking genes, i.e., PIK3CA and PIK3CB, by showing that their forced expression confers resistance to lapatinib in vitro and found that their mutation/overexpression is associated to poor prognosis in human breast tumors. Then, we successfully applied this approach to the identification of erlotinib resistance genes in pancreatic cancer, thus showing the intrinsic versatility of the approach. The acquired knowledge can help identifying combinations of targeted drugs to overcome the occurrence of resistance, thus opening new horizons for more effective treatment of tumors.
| S-EPMC4429698 | biostudies-literature