Identification of Intrinsic Drug Resistance and Its Biomarkers in High-Throughput Pharmacogenomic and CRISPR Screens

Siglec-7 glyco-immune binding mAbs or NK cell engager biologics induce potent antitumor immunity against ovarian cancers

Ovarian cancer (OC) is a lethal gynecologic malignancy, with modest responses to CPI. Engagement of additional immune arms, such as NK cells, may be of value. We focused on Siglec-7 as a surface antigen for engaging this population. Human antibodies against Siglec-7 were developed and characterized. Coculture of OC cells with PBMCs/NKs and Siglec-7 binding antibodies showed NK-mediated killing of OC lines. Anti-Siglec-7 mAb (DB7.2) enhanced survival in OC-challenged mice. In addition, the combination of DB7.2 and anti-PD-1 demonstrated further improved OC killing in vitro. To use Siglec-7 engagement as an OC-specific strategy, we engineered an NK cell engager (NKCE) to simultaneously engage NK cells through Siglec-7, and OC targets through FSHR. The NKCE demonstrated robust in vitro killing of FSHR+ OC, controlled tumors, and improved survival in OC-challenged mice. These studies support additional investigation of the Siglec-7 targeting approaches as important tools for OC and other recalcitrant cancers.

Recent Advances and Therapeutic Strategies Using CRISPR Genome Editing Technique for the Treatment of Cancer

CRISPR genome editing technique has the potential to target cancer cells in a precise manner. The latest advancements have helped to address one of the prominent concerns about this strategy which is the off-target integrations observed with dsDNA and have resulted in more studies being carried out for potentially safer and more targeted gene therapy, so as to make it available for the clinical trials in order to effectively treat cancer. CRISPR screens offer great potential for the high throughput investigation of the gene functionality in various tumors. It extends its capability to identify the tumor growth essential genes, therapeutic resistant genes, and immunotherapeutic responses. CRISPR screens are mostly performed in in vitro models, but latest advancements focus on developing in vivo models to view cancer progression in animal models. It also allows the detection of factors responsible for tumorigenesis. In CRISPR screens key parameters are optimized in order to meet proficient gene targeting efficiencies. It also detects various molecular effectors required for gene regulation in different cancers, essential pathways which modulate cytotoxicity to immunotherapy in cancer cells, important genes which contribute to cancer cell survival in hypoxic states and modulate cancer long non-coding RNAs. The current review focuses on the recent developments in the therapeutic application of CRISPR technology for cancer therapy. Furthermore, the associated challenges and safety concerns along with the various strategies that can be implemented to overcome these drawbacks has been discussed.

Comparative kinase and cancer cell panel profiling of kinase inhibitors approved for clinical use from 2018 to 2020

During the last two decades, kinase inhibitors have become the major drug class for targeted cancer therapy. Although the number of approved kinase inhibitors increases rapidly, comprehensive in vitro profiling and comparison of inhibitor activities is often lacking in the public domain. Here we report the extensive profiling and comparison of 21 kinase inhibitors approved by the FDA for oncology indications since June 2018 and 13 previously approved comparators on panels of 255 biochemical kinase assays and 134 cancer cell line viability assays. Comparison of the cellular inhibition profiles of the EGFR inhibitors gefitinib, dacomitinib, and osimertinib identified the uncommon EGFR p.G719S mutation as a common response marker for EGFR inhibitors. Additionally, the FGFR inhibitors erdafitinib, infigratinib, and pemigatinib potently inhibited the viability of cell lines which harbored oncogenic alterations in FGFR1-3, irrespective of the specific clinical indications of the FGFR inhibitors. These results underscore the utility of in vitro kinase inhibitor profiling in cells for identifying new potential stratification markers for patient selection. Furthermore, comparison of the in vitro inhibition profiles of the RET inhibitors pralsetinib and selpercatinib revealed they had very similar biochemical and cellular selectivity. As an exception, an NTRK3 fusion-positive cell line was potently inhibited by pralsetinib but not by selpercatinib, which could be explained by the targeting of TRK kinases in biochemical assays by pralsetinib but not selpercatinib. This illustrates that unexpected differences in cellular activities between inhibitors that act through the same primary target can be explained by subtle differences in biochemical targeting. Lastly, FLT3-mutant cell lines were responsive to both FLT3 inhibitors gilteritinib and midostaurin, and the PI3K inhibitor duvelisib. Biochemical profiling revealed that the FLT3 and PI3K inhibitors targeted distinct kinases, indicating that unique dependencies can be identified by combined biochemical and cellular profiling of kinase inhibitors. This study provides the first large scale kinase assay or cell panel profiling study for newly approved kinase inhibitors, and shows that comprehensive in vitro profiling of kinase inhibitors can provide rationales for therapy selection and indication expansion of approved kinase inhibitors.

Biomarker LEPRE1 induces pelitinib-specific drug responsiveness by regulating ABCG2 expression and tumor transition states in human leukemia and lung cancer

Biomarkers for treatment sensitivity or drug resistance used in precision medicine include prognostic and predictive molecules, critical factors in selecting appropriate treatment protocols and improving survival rates. However, identification of accurate biomarkers remain challenging due to the high risk of false-positive findings and lack of functional validation results for each biomarker. Here, we discovered a mechanical correlation between leucine proline-enriched proteoglycan 1 (LEPRE1) and pelitinib drug sensitivity using in silico statistical methods and confirmed the correlation in acute myeloid leukemia (AML) and A549 lung cancer cells. We determined that high LEPRE1 levels induce protein kinase B activation, overexpression of ATP-binding cassette superfamily G member 2 (ABCG2) and E-cadherin, and cell colonization, resulting in a cancer stem cell-like phenotype. Sensitivity to pelitinib increases in LEPRE1-overexpressing cells due to the reversing effect of ABCG2 upregulation. LEPRE1 silencing induces pelitinib resistance and promotes epithelial-to-mesenchymal transition through actin rearrangement via a series of Src/ERK/cofilin cascades. The in silico results identified a mechanistic relationship between LEPRE1 and pelitinib drug sensitivity, confirmed in two cancer types. This study demonstrates the potential of LEPRE1 as a biomarker in cancer through in-silico prediction and in vitro experiments supporting the clinical development of personalized medicine strategies based on bioinformatics findings.

Battling Chemoresistance in Cancer: Root Causes and Strategies to Uproot Them

With nearly 10 million deaths, cancer is the leading cause of mortality worldwide. Along with major key parameters that control cancer treatment management, such as diagnosis, resistance to the classical and new chemotherapeutic reagents continues to be a significant problem. Intrinsic or acquired chemoresistance leads to cancer recurrence in many cases that eventually causes failure in the successful treatment and death of cancer patients. Various determinants, including tumor heterogeneity and tumor microenvironment, could cause chemoresistance through a diverse range of mechanisms. In this review, we summarize the key determinants and the underlying mechanisms by which chemoresistance appears. We then describe which strategies have been implemented and studied to combat such a lethal phenomenon in the management of cancer treatment, with emphasis on the need to improve the early diagnosis of cancer complemented by combination therapy.

Artificial intelligence in early drug discovery enabling precision medicine

Introduction: Precision medicine is the concept of treating diseases based on environmental factors, lifestyles, and molecular profiles of patients. This approach has been found to increase success rates of clinical trials and accelerate drug approvals. However, current precision medicine applications in early drug discovery use only a handful of molecular biomarkers to make decisions, whilst clinics gear up to capture the full molecular landscape of patients in the near future. This deep multi-omics characterization demands new analysis strategies to identify appropriate treatment regimens, which we envision will be pioneered by artificial intelligence.Areas covered: In this review, the authors discuss the current state of drug discovery in precision medicine and present our vision of how artificial intelligence will impact biomarker discovery and drug design.Expert opinion: Precision medicine is expected to revolutionize modern medicine; however, its traditional form is focusing on a few biomarkers, thus not equipped to leverage the full power of molecular landscapes. For learning how the development of drugs can be tailored to the heterogeneity of patients across their molecular profiles, artificial intelligence algorithms are the next frontier in precision medicine and will enable a fully personalized approach in drug design, and thus ultimately impacting clinical practice.