Imatinib as a Paradigm of Targeted Therapies

An SH3-binding allosteric modulator stabilizes the global conformation of the AML-associated Src-family kinase, Hck

While ATP-site inhibitors for protein-tyrosine kinases are often effective drugs, their clinical utility can be limited by off-target activity and acquired resistance mutations due to the conserved nature of the ATP-binding site. However, combining ATP-site and allosteric kinase inhibitors can overcome these shortcomings in a double-drugging framework. Here we explored the allosteric effects of two pyrimidine diamines, PDA1 and PDA2, on the conformational dynamics and activity of the Src-family tyrosine kinase Hck, a promising drug target for acute myeloid leukemia. Using 1H-15N HSQC NMR, we mapped the binding site for both analogs to the SH3 domain. Despite the shared binding site, PDA1 and PDA2 had opposing effects on near-full-length Hck dynamics by hydrogen-deuterium exchange mass spectrometry, with PDA1 stabilizing and PDA2 disrupting the overall kinase conformation. Kinase activity assays were consistent with these observations, with PDA2 enhancing kinase activity while PDA1 was without effect. Molecular dynamics simulations predicted selective bridging of the kinase domain N-lobe and SH3 domain by PDA1, a mechanism of allosteric stabilization supported by site-directed mutagenesis of N-lobe contact sites. Cellular thermal shift assays confirmed SH3 domain-dependent interaction of PDA1 with WT Hck in myeloid leukemia cells and with a kinase domain gatekeeper mutant (T338M). These results identify PDA1 as a starting point for Src-family kinase allosteric inhibitor development that may work in concert with ATP-site inhibitors to suppress the evolution of resistance.

Gene Fusion Detection in Long-Read Transcriptome Datasets from Multiple Cancer Cell Lines

BACKGROUND

Fusion genes are important biomarkers in cancer research because their expression can produce abnormal proteins with oncogenic properties. Long-read RNA sequencing (long-read RNA-seq), which can sequence full-length mRNA transcripts, facilitates the detection of such fusion genes. Several tools have been proposed for detecting fusion genes in long-read RNA-seq datasets derived from cancer cells. However, the high sequencing error rate in long-read RNA-seq makes fusion gene detection challenging.

METHODS

To address this issue, additional steps were incorporated into the fusion detection tool to improve detection accuracy. These steps include anchoring breakpoints to exon boundaries, realigning unaligned regions, and clustering breakpoints. To evaluate the accuracy of our tool in detecting fusion genes, we compared its detection accuracy with two representative existing tools, JAFFAL and FusionSeeker.

RESULTS

Our tool outperformed the two existing tools in detecting fusion genes, as demonstrated in long-read RNA-seq datasets. We also identified potentially novel fusion genes consistently detected across multiple tools or datasets.

CONCLUSIONS

The application of our tool to the detection of fusion genes in long-read RNA-seq datasets from two different cancer cell lines demonstrated the detection effectiveness of this tool.

Unveiling the role of PIK3R1 in cancer: A comprehensive review of regulatory signaling and therapeutic implications

Phosphoinositide 3-kinase (PI3K) is responsible for phosphorylating phosphoinositides to generate secondary signaling molecules crucial for regulating various cellular processes, including cell growth, survival, and metabolism. The PI3K is a heterodimeric enzyme complex comprising of a catalytic subunit (p110α, p110β, or p110δ) and a regulatory subunit (p85). The binding of the regulatory subunit, p85, with the catalytic subunit, p110, forms an integral component of the PI3K enzyme. PIK3R1 (phosphoinositide-3-kinase regulatory subunit 1) belongs to class IA of the PI3K family. PIK3R1 exhibits structural complexity due to alternative splicing, giving rise to distinct isoforms, prominently p85α and p55α. While the primary p85α isoform comprises multiple domains, including Src homology 3 (SH3) domains, a Breakpoint Cluster Region Homology (BH) domain, and Src homology 2 (SH2) domains (iSH2 and nSH2), the shorter isoform, p55α, lacks certain domains present in p85α. In this review, we will highlight the intricate regulatory mechanisms governing PI3K signaling along with the impact of PIK3R1 alterations on cellular processes. We will further delve into the clinical significance of PIK3R1 mutations in various cancer types and their implications for prognosis and treatment outcomes. Additionally, we will discuss the evolving landscape of targeted therapies aimed at modulating PI3K-associated pathways. Overall, this review will provide insights into the dynamic interplay of PIK3R1 in cancer, fostering advancements in precision medicine and the development of targeted interventions.

Design, in silico Evaluation, and Determination of Antitumor Activity of Potential Inhibitors Against Protein Kinases: Application to BCR-ABL Tyrosine Kinase

Despite significant progress made over the past two decades in the treatment of chronic myeloid leukemia (CML), there is still an unmet need for effective and safe agents to treat patients with resistance and intolerance to the drugs used in clinic. In this work, we designed 2-arylaminopyrimidine amides of isoxazole-3-carboxylic acid, assessed in silico their inhibitory potential against Bcr-Abl tyrosine kinase, and determined their antitumor activity in K562 (CML), HL-60 (acute promyelocytic leukemia), and HeLa (cervical cancer) cells. Based on the analysis of computational and experimental data, three compounds with the antitumor activity against K562 and HL-60 cells were identified. The lead compound efficiently suppressed the growth of these cells, as evidenced by the low IC50 values of 2.8 ± 0.8 μM (K562) and 3.5 ± 0.2 μM (HL-60). The obtained compounds represent promising basic structures for the design of novel, effective, and safe anticancer drugs able to inhibit the catalytic activity of Bcr-Abl kinase by blocking the ATP-binding site of the enzyme.

Revolutionizing personalized cancer treatment: the synergy of next-generation sequencing and CRISPR/Cas9

In the context of cancer heterogeneity, the synergistic action of next-generation sequencing (NGS) and CRISPR/Cas9 plays a promising role in the personalized treatment of cancer. NGS enables high-throughput genomic profiling of tumors and pinpoints specific mutations that primarily lead to cancer. Oncologists use this information obtained from NGS in the form of DNA profiling or RNA analysis to tailor precision strategies based on an individual's unique molecular signature. Furthermore, the CRISPR technique enables precise editing of cancer-specific mutations, allowing targeted gene modifications. Harnessing the potential insights of NGS and CRISPR/Cas9 heralds a remarkable frontier in cancer therapeutics with unprecedented precision, effectiveness and minimal off-target effects.

Anchored-fusion enables targeted fusion search in bulk and single-cell RNA sequencing data

Here, we present Anchored-fusion, a highly sensitive fusion gene detection tool. It anchors a gene of interest, which often involves driver fusion events, and recovers non-unique matches of short-read sequences that are typically filtered out by conventional algorithms. In addition, Anchored-fusion contains a module based on a deep learning hierarchical structure that incorporates self-distillation learning (hierarchical view learning and distillation [HVLD]), which effectively filters out false positive chimeric fragments generated during sequencing while maintaining true fusion genes. Anchored-fusion enables highly sensitive detection of fusion genes, thus allowing for application in cases with low sequencing depths. We benchmark Anchored-fusion under various conditions and found it outperformed other tools in detecting fusion events in simulated data, bulk RNA sequencing (bRNA-seq) data, and single-cell RNA sequencing (scRNA-seq) data. Our results demonstrate that Anchored-fusion can be a useful tool for fusion detection tasks in clinically relevant RNA-seq data and can be applied to investigate intratumor heterogeneity in scRNA-seq data.

Structure-Activity Relationship Study and Design Strategies of Hydantoin, Thiazolidinedione, and Rhodanine-Based Kinase Inhibitors: A Two-Decade Review

Cancer is one of the most prominent causes of the rapidly growing mortality numbers worldwide. Cancer originates from normal cells that have acquired the capability to alter their molecular, biochemical, and cellular traits. The alteration of cell signaling enzymes, such as kinases, can initiate and amplify cancer progression. As a curative method, the targeted therapy utilized small molecules' capability to inhibit kinase's cellular function. This review provides a brief history (1999-2023) of Small Molecule Kinase Inhibitors (SMKIs) discovery with their molecular perspective. Furthermore, this current review also addresses the application and the development of hydantoin, thiazolidinedione, and rhodanine-based derivatives as kinase inhibitors toward several subclasses (EGFR, PI3K, VEGFR, Pim, c-Met, CDK, IGFR, and ERK) accompanied by their structure-activity relationship study and their molecular interactions. The present work summarizes and compiles all the important structural information essential for developing hydantoin, thiazolidinedione, and rhodanine-based kinase inhibitors to improve their potency in the future.

Tag and Snag: A New Platform for Bioactive Natural Product Screening from Mixtures

Natural products provide an unparalleled diversity of small molecules to fuel drug screening efforts, but deconvoluting the pharmacological activity of natural product mixtures to identify key bioactive compounds remains a vexing and labor-intensive process. Therefore, we have developed a new platform to probe the non-specific pharmacological potential of compounds present in common dietary supplements via shotgun derivatization with isotopically labeled propanoic acid, a live cell affinity assay, which was used to selectively recognize the population of compounds which bind tightly to HeLa cells in culture, and a computational LC-MS data analysis of isotopically labeled compounds from cell lysate. The data analysis showed that hundreds of compounds were successfully derivatized in each extract, and dozens of those compounds showed high affinity for HeLa cells. In total, over a thousand isotopically labeled compounds were screened for cell affinity across three separate experiments, resulting in the identification of several known bioactive compounds with specific protein targets and six previously unreported structures. The new natural products include three tulsinol compounds which were isolated from Ocimum tenuiflorum and three valeraninium alkaloids from Valeriana officinalis. The valeraninium alkaloids constitute a distinct new family of alkaloids from valerian, which may have previously undescribed bioactivity. These results collectively demonstrate the tag and snag workflow's viability as a drug discovery method.

DrugRep: an automatic virtual screening server for drug repurposing

Computationally identifying new targets for existing drugs has drawn much attention in drug repurposing due to its advantages over de novo drugs, including low risk, low costs, and rapid pace. To facilitate the drug repurposing computation, we constructed an automated and parameter-free virtual screening server, namely DrugRep, which performed molecular 3D structure construction, binding pocket prediction, docking, similarity comparison and binding affinity screening in a fully automatic manner. DrugRep repurposed drugs not only by receptor-based screening but also by ligand-based screening. The former automatically detected possible binding pockets of the receptor with our cavity detection approach, and then performed batch docking over drugs with a widespread docking program, AutoDock Vina. The latter explored drugs using seven well-established similarity measuring tools, including our recently developed ligand-similarity-based methods LigMate and FitDock. DrugRep utilized easy-to-use graphic interfaces for the user operation, and offered interactive predictions with state-of-the-art accuracy. We expect that this freely available online drug repurposing tool could be beneficial to the drug discovery community. The web site is http://cao.labshare.cn/drugrep/.

Neoadjuvant immunotherapy and chemoimmunotherapy for stage II-III muscle invasive bladder cancer

Objective

Considering the striking evidence revealed by immunotherapy in advanced or metastatic bladder cancer, investigators have explored neoadjuvant immunotherapy and chemoimmunotherapy in muscle-invasive bladder cancer (MIBC). Currently, there have been a large number of studies reporting varied efficacy and safety of these approaches. Herein, we pooled the available evidence in terms of oncological outcomes (pathological complete response [pCR] and pathological partial response [pPR]) and safety outcomes (immune-related adverse events [irAEs], treatment-related adverse events [TRAEs]), through a systematic review and meta-analysis.

Method

We searched PubMed, Embase, Cochrane Library, and American Society of Clinical Oncology meeting abstracts to identify relevant studies up to June 2022. Studies were included if they evaluated the neoadjuvant immunotherapy or chemoimmunotherapy in MIBC and reported at least the pCR.

Results

A total of 22 records involving 843 patients were included. For pCR of immunotherapy, the pooled rate of immune checkpoint inhibitor (ICI) monotherapy and dual-ICIs therapy was 24% (95% confidence interval [CI]: 15.3% - 32.8%) and 32.1% (95%CI: 20.6% - 43.7%), respectively. For pCR of chemoimmunotherapy, the overall pooled rate was 42.6% (95% CI: 34.9% - 50.2%). Subgroup of gemcitabine/cisplatin (GC) plus ICI had a pCR rate of 41.7% (95%CI: 35.8% - 47.5%). In terms of safety, the pooled rate of Grade≥3 irAEs was 11.7% (95% CI: 6.5%-16.9%). In subgroup analysis, the Grade≥3 irAEs rate of ICI monotherapy, dual-ICIs therapy, and GC plus ICI therapy was 7.4% (95% CI: 4.3%-10.5%), 30.3% (95% CI: 15.3%-45.3%), and 14.5% (95% CI: 3.5% - 25.4%), respectively. Besides, the pooled Grade≥3 TRAEs rate for chemoimmunotherapy was 32.4% (95% CI: 13.1% - 51.6%).

Conclusion

Neoadjuvant immunotherapy and chemoimmunotherapy were effective and safe in the treatment of MIBC. Compared to ICI monotherapy, dual-ICIs therapy or chemoimmunotherapy can improve the response rate, while increasing the morbidity of Grade≥ 3 irAEs or Grade≥ 3 TRAEs.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/, identifier CRD4202233771.

Screening chronic myeloid leukemia neutrophils using a novel 3-Dimensional Spectral Gradient Mapping algorithm on hyperspectral images

Background and objective Early diagnosis of chronic myeloid leukemia (CML) is important for effective treatment. The high spectral and spatial resolution of hyperspectral cellular or tissue images coupled with image analysis algorithms may provide avenues to detect and diagnose diseases early. Many algorithms have been used to analyze medical hyperspectral image data, each having their own strengths and short-comings. We present a novel 3-Dimensional Spectral Gradient Mapping (3-D SGM) method to analyze hyperspectral image cubes of CML versus healthy blood smears. Methods In the present study, we analyzed 13 hyperspectral image cubes of CML and healthy neutrophils. The 3-D SGM algorithm was compared to the conventional Windowed Spectral Angle Mapping (Windowed SAM) method. The 3-D SGM exploited the spectral information of the image cube together with the inter-band and inter-pixel data by extracting the 3-D gradient vector from each pixel. The Windowed SAM determined the similarity between the averaged window of a 2×2 training pixel group and the test pixel, in the multidimensional spectral angle. Results The specificity measure of 3-D SGM (97.7%) was superior to Windowed SAM (72.7%) at ruling out the presence of the disease, making it potentially ideal for screening patients. The positive likelihood ratio value of 3-D SGM (16.70) was superior in diagnosing the presence of the disease (i.e., positive test for CML) versus Windowed SAM (2.26). An accuracy value of 84.2% was achieved with 3-D SGM versus only 70.2% for Windowed SAM. Conclusion The new method is efficient and robust for analyzing hyperspectral images of CML versus healthy neutrophils. It has the potential to be developed into an inexpensive, minimally invasive method for screening CML, and could directly facilitate early diagnosis and treatment of the disease.

Oncology Drug Repurposing for Sepsis Treatment

Sepsis involves life-threatening organ dysfunction caused by a dysregulated host response to infection. Despite three decades of efforts and multiple clinical trials, no treatment, except antibiotics and supportive care, has been approved for this devastating syndrome. Simultaneously, numerous preclinical studies have shown the effectiveness of oncology-indicated drugs in ameliorating sepsis. Here we focus on cataloging these efforts with both oncology-approved and under-development drugs that have been repositioned to treat bacterial-induced sepsis models. In this context, we also envision the exciting prospect for further standard and oncology drug combination testing that could ultimately improve clinical outcomes in sepsis.

Identifying the oncogenic potential of gene fusions exploiting miRNAs

It is estimated that oncogenic gene fusions cause about 20% of human cancer morbidity. Identifying potentially oncogenic gene fusions may improve affected patients' diagnosis and treatment. Previous approaches to this issue included exploiting specific gene-related information, such as gene function and regulation. Here we propose a model that profits from the previous findings and includes the microRNAs in the oncogenic assessment. We present ChimerDriver, a tool to classify gene fusions as oncogenic or not oncogenic. ChimerDriver is based on a specifically designed neural network and trained on genetic and post-transcriptional information to obtain a reliable classification. The designed neural network integrates information related to transcription factors, gene ontologies, microRNAs and other detailed information related to the functions of the genes involved in the fusion and the gene fusion structure. As a result, the performances on the test set reached 0.83 f1-score and 96% recall. The comparison with state-of-the-art tools returned comparable or higher results. Moreover, ChimerDriver performed well in a real-world case where 21 out of 24 validated gene fusion samples were detected by the gene fusion detection tool Starfusion. ChimerDriver integrates transcriptional and post-transcriptional information in an ad-hoc designed neural network to effectively discriminate oncogenic gene fusions from passenger ones. ChimerDriver source code is freely available at https://github.com/martalovino/ChimerDriver.

Options to Improve the Action of PROTACs in Cancer: Development of Controlled Delivery Nanoparticles

Classical targeting in cancer focuses on the development of chemical structures able to bind to protein pockets with enzymatic activity. Some of these molecules are designed to bind the ATP side of the kinase domain avoiding protein activation and the subsequent oncogenic activity. A further improvement of these agents relies on the generation of non-allosteric inhibitors that once bound are able to limit the kinase function by producing a conformational change at the protein and, therefore, augmenting the antitumoural potency. Unfortunately, not all oncogenic proteins have enzymatic activity and cannot be chemically targeted with these types of molecular entities. Very recently, exploiting the protein degradation pathway through the ubiquitination and subsequent proteasomal degradation of key target proteins has gained momentum. With this approach, non-enzymatic proteins such as Transcription Factors can be degraded. In this regard, we provide an overview of current applications of the PROteolysis TArgeting Chimeras (PROTACs) compounds for the treatment of solid tumours and ways to overcome their limitations for clinical development. Among the different constraints for their development, improvements in bioavailability and safety, due to an optimized delivery, seem to be relevant. In this context, it is anticipated that those targeting pan-essential genes will have a narrow therapeutic index. In this article, we review the advantages and disadvantages of the potential use of drug delivery systems to improve the activity and safety of PROTACs.

System and network biology-based computational approaches for drug repositioning

Recent advances in computational biology have not only fastened the drug discovery process but have also proven to be a powerful tool for the search of existing molecules of therapeutic value for drug repurposing. The system biology-based drug repurposing approaches shorten the time and reduced the cost of the whole process when compared to de novo drug discovery. In the present pandemic situation, these computational approaches have emerged as a boon to tackle the COVID-19 associated morbidities and mortalities. In this chapter, we present the overview of system biology-based network system approaches which can be exploited for the drug repurposing of disease. Besides, we have included information on relevant repurposed drugs which are currently used for the treatment of COVID-19.

Weak-evidence Fusion Candidates Detected by a FusionPlex Assay Using the Ion Torrent System

BACKGROUND/AIM

The Archer FusionPlex platform is widely used for comprehensive fusion-gene detection in cancer tissues. This platform separately displays results for strong-evidence and weak-evidence fusion candidates (WEFCs). Distinctive fusion patterns are frequently found in the weak-evidence category and information about the patterns is clinically essential.

PATIENTS AND METHODS

We describe the type and frequency of WEFCs observed using the FusionPlex Sarcoma Panel (S Panel) and the FusionPlex ALK, RET, and ROS1 ver2 Panel (ARR Panel).

RESULTS

A total of 97 specimens were examined and 620 candidates were detected and categorized as WEFCs. A median of five WEFCs were detected per sample. In the S Panel group, there were 13 WEFCs with a frequency of more than 1%. In the ARR Panel group, a total of 16 WEFCs were detected with a frequency of more than 1%.

CONCLUSION

Specific WEFCs were detected according to the panel selected.

Diagnostic Validation of a Clinical Laboratory-Oriented Targeted RNA Sequencing System for Detecting Gene Fusions in Hematologic Malignancies

Targeted RNA sequencing (RNA-seq) is a highly accurate method for sequencing transcripts of interest with a high resolution and throughput. However, RNA-seq has not been widely performed in clinical molecular laboratories because of the complexity of data processing and interpretation. We developed and validated a customized RNA-seq panel and data processing protocol for fusion detection using 4 analytical validation samples and 51 clinical samples, covering seven types of hematologic malignancies. Analytical validation showed that the results for target gene coverage and between- and within-run precision and linearity tests were reliable. Using clinical samples, RNA-seq based on filtering and prioritization strategies detected all 25 known fusions previously found by multiplex reverse transcriptase-PCR and fluorescence in situ hybridization. It also detected nine novel fusions. Known fusions detected by RNA-seq included two IGH rearrangements supported by expression analysis. Novel fusions included six that targeted just one partner gene. In addition, 18 disease- and drug resistance-associated transcript variants in ABL1, GATA2, IKZF1, JAK2, RUNX1, and WT1 were designated simultaneously. Expression analysis showed distinct clustering according to subtype and lineage. In conclusion, this study showed that our customized RNA-seq system had a reliable and stable performance for fusion detection, with enhanced diagnostic yield for hematologic malignancies in a clinical diagnostic setting.

The Molecular Analysis for Therapy Choice (NCI-MATCH) Trial: Lessons for Genomic Trial Design

Background

The proportion of tumors of various histologies that may respond to drugs targeted to molecular alterations is unknown. NCI-MATCH, a collaboration between ECOG-ACRIN Cancer Research Group and the National Cancer Institute, was initiated to find efficacy signals by matching patients with refractory malignancies to treatment targeted to potential tumor molecular drivers regardless of cancer histology.

Methods

Trial development required assumptions about molecular target prevalence, accrual rates, treatment eligibility, and enrollment rates as well as consideration of logistical requirements. Central tumor profiling was performed with an investigational next-generation DNA–targeted sequencing assay of alterations in 143 genes, and protein expression of protein expression of phosphatase and tensin homolog, mutL homolog 1, mutS homolog 2, and RB transcriptional corepressor 1. Treatments were allocated with a validated computational platform (MATCHBOX). A preplanned interim analysis evaluated assumptions and feasibility in this novel trial.

Results

At interim analysis, accrual was robust, tumor biopsies were safe (<1% severe events), and profiling success was 87.3%. Actionable molecular alteration frequency met expectations, but assignment and enrollment lagged due to histology exclusions and mismatch of resources to demand. To address this lag, we revised estimates of mutation frequencies, increased screening sample size, added treatments, and improved assay throughput and efficiency (93.9% completion and 14-day turnaround).

Conclusions

The experiences in the design and implementation of the NCI-MATCH trial suggest that profiling from fresh tumor biopsies and assigning treatment can be performed efficiently in a large national network trial. The success of such trials necessitates a broad screening approach and many treatment options easily accessible to patients.

Tyrosine kinase inhibitors protect the salivary gland from radiation damage by increasing DNA double-strand break repair

We have previously shown that the tyrosine kinase inhibitors (TKIs) dasatinib and imatinib can protect salivary glands from irradiation (IR) damage without impacting tumor therapy. However, how they induce this protection is unknown. Here we show that TKIs mediate radioprotection by increasing the repair of DNA double-stranded breaks. DNA repair in IR-treated parotid cells, but not oral cancer cells, occurs more rapidly following pretreatment with imatinib or dasatinib and is accompanied by faster formation of DNA damage-induced foci. Similar results were observed in the parotid glands of mice pretreated with imatinib prior to IR, suggesting that TKIs "prime" cells for DNA repair. Mechanistically, we observed that TKIs increased IR-induced activation of DNA-PK, but not ATM. Pretreatment of parotid cells with the DNA-PK inhibitor NU7441 reversed the increase in DNA repair induced by TKIs. Reporter assays specific for homologous recombination (HR) or nonhomologous end joining (NHEJ) verified regulatation of both DNA repair pathways by imatinib. Moreover, TKIs also increased basal and IR-induced expression of genes associated with NHEJ (DNA ligase 4, Artemis, XLF) and HR (Rad50, Rad51 and BRCA1); depletion of DNA ligase 4 or BRCA1 reversed the increase in DNA repair mediated by TKIs. In addition, TKIs increased activation of the ERK survival pathway in parotid cells, and ERK was required for the increased survival of TKI-treated cells. Our studies demonstrate a dual mechanism by which TKIs provide radioprotection of the salivary gland tissues and support exploration of TKIs clinically in head and neck cancer patients undergoing IR therapy.

Recent Advances in Multi-target Drugs Targeting Protein Kinases and Histone Deacetylases in Cancer Therapy

Protein Kinase Inhibitors (PKIs) and Histone Deacetylase Inhibitors (HDACIs) are two important classes of anticancer agents and have provided a variety of small molecule drugs for the treatment of various types of human cancers. However, malignant tumors are of a multifactorial nature that can hardly be "cured" by targeting a single target, and treatment of cancers hence requires modulation of multiple biological targets to restore the physiological balance and generate sufficient therapeutic efficacy. Multi-target drugs have attracted great interest because of their advantages in the treatment of complex cancers by simultaneously targeting multiple signaling pathways and possibly leading to synergistic effects. Synergistic effects have been observed in the combination of kinase inhibitors, such as imatinib, dasatinib, or sorafenib, with an array of HDACIs including vorinostat, romidepsin, or panobinostat. A considerable number of multi-target agents based on PKIs and HDACIs have been developed. In this review, we summarize the recent literature on the development of multi-target kinase-HDAC inhibitors and provide our view on the challenges and future directions on this topic.

Characterization of genomic alterations in Chinese colorectal cancer patients

OBJECTIVE

Colorectal cancer is one of the most prevalent types of cancer worldwide. Right-sided and left-sided colorectal cancer (RCC and LCC) patients respond differently to treatment. We aimed to identify the different mutational profile between RCC and LCC and provided evidence for future precision therapy.

METHODS

A total of 630 Chinese colorectal cancer patients, including 467 (74.1%) LCC and 163 (25.9%) RCC, were enrolled in this cohort. Both formalin-fixed paraffin-embedded tumor tissues and matching blood samples were collected and deep sequenced targeting 450 cancer genes for genomic alteration analysis. Tumor mutational burden was measured by an algorithm developed in-house. Correlation analysis was performed by Fisher's exact test.

RESULTS

The most common mutated genes were TP53 (77.0%), APC (71.7%), KRAS (50.0%), SMAD4 (19.8%), PIK3CA (18.3%), FBXW7 (17.5%), TCF7L2 (12.5%), SOX9 (11.3%), LRP1B (10.8%), ARID1A (10.3%) and FAT4 (10.3%). The mutation frequencies of TP53 and APC in LCC were significantly higher than that of RCC, while the mutation frequency of PIK3CA was lower than that of RCC. Six gene fusions were specifically detected in RCC patients. Colorectal cancer sites were associated with gender (P = 4.15 × 10-5) and tumor differentiation (P = 0.059). In LCC, the gender-associated genes were FAT4, EP300, FAT1, LRP1, ARID1B, AR, FYN and TAF1, while in RCC, they were ARID1A, SMARCA4, LRP1 and GRIN2A. The mutations of 18 genes were associated with tumor differentiation (8 for LCC and 10 for RCC). High tumor mutational burden was more common in RCC. Our results implied more potential targeted drug therapy opportunities for RCC.

CONCLUSION

We describe the different molecular characteristics of LCC and RCC. Our result supported a better prognosis of RCC than LCC in Chinese colorectal cancer patients.

Dual Kinase Targeting in Leukemia

Pharmacological cancer therapy is often based on the concurrent inhibition of different survival pathways to improve treatment outcomes and to reduce the risk of relapses. While this strategy is traditionally pursued only through the co-administration of several drugs, the recent development of multi-targeting drugs (i.e., compounds intrinsically able to simultaneously target several macromolecules involved in cancer onset) has had a dramatic impact on cancer treatment. This review focuses on the most recent developments in dual-kinase inhibitors used in acute myeloid leukemia (AML), chronic myelogenous leukemia (CML), and lymphoid tumors, giving details on preclinical studies as well as ongoing clinical trials. A brief overview of dual-targeting inhibitors (kinase/histone deacetylase (HDAC) and kinase/tubulin polymerization inhibitors) applied to leukemia is also given. Finally, the very recently developed Proteolysis Targeting Chimeras (PROTAC)-based kinase inhibitors are presented.

Cytogenetic and molecular genetic methods for chromosomal translocations detection with reference to the KMT2A/MLL gene

Acute leukemias (ALs) are often associated with chromosomal translocations, in particular, KMT2A/MLL gene rearrangements. Identification or confirmation of these translocations is carried out by a number of genetic and molecular methods, some of which are routinely used in clinical practice, while others are primarily used for research purposes. In the clinic, these methods serve to clarify diagnoses and monitor the course of disease and therapy. On the other hand, the identification of new translocations and the confirmation of known translocations are of key importance in the study of disease mechanisms and further molecular classification. There are multiple methods for the detection of rearrangements that differ in their principle of operation, the type of problem being solved, and the cost-result ratio. This review is intended to help researchers and clinicians studying AL and related chromosomal translocations to navigate this variety of methods. All methods considered in the review are grouped by their principle of action and include karyotyping, fluorescence in situ hybridization (FISH) with probes for whole chromosomes or individual loci, PCR and reverse transcription-based methods, and high-throughput sequencing. Another characteristic of the described methods is the type of problem being solved. This can be the discovery of new rearrangements, the determination of unknown partner genes participating in the rearrangement, or the confirmation of the proposed rearrangement between the two genes. We consider the specifics of the application, the basic principle of each method, and its pros and cons. To illustrate the application, examples of studying the rearrangements of the KMT2A/MLL gene, one of the genes that are often rearranged in AL, are mentioned.

Cancer Epigenomics and Beyond: Advancing the Precision Oncology Paradigm

How cancers are characterized and treated has evolved over the past few decades. Major advances in genomics tools and techniques have revealed interlinked regulatory pathways of cancers with unprecedented detail. Early discoveries led to success with rationally targeted small molecules and more recently with immunomodulatory agents, setting the stage for precision oncology. However, drug resistance to every agent has thus far proven intractable, sending us back to fill the gaps in our rudimentary knowledge of tumor biology. Epigenetics is emerging as a fundamental process in every hallmark of cancer. Large-scale interrogation of the cancer epigenome continues to reveal new mechanisms of astounding complexity. In this review, I present selected experimental and clinical examples that have shaped our understanding of cancer at the molecular level. Translation of our collective erudition into revolutionary diagnostic and treatment strategies will advance the precision oncology paradigm.

In Vitro Evolution Reveals a Single Mutation as Sole Source of Src-Family Kinase C-Helix-out Inhibitor Resistance

Understanding cancer cell drug resistance to protein-tyrosine kinase inhibitors, which often arises from acquired mutations in the target kinase, is central to the development of more durable therapies. Experimental systems that reveal potential paths to resistance for a given inhibitor and kinase target have an important role in preclinical development of kinase inhibitor drugs. Here, we employed a codon mutagenesis strategy to define the mutational landscape of acquired resistance in HCK, a member of the SRC tyrosine kinase family and therapeutic target in acute myeloid leukemia (AML). Using PCR-based saturation mutagenesis, we created a cDNA library designed to replace each codon in the HCK open reading frame with all possible codons. This HCK mutant library was used to transform Rat-2 fibroblasts, followed by selection for resistant colonies with A-419259, a pyrrolopyrimidine HCK inhibitor and drug lead for AML. X-ray crystallography has shown that A-419259 binding induces outward rotation of the kinase domain αC-helix, a conformation incompatible with phosphotransfer. Remarkably, only a single resistance mutation evolved during A-419259 selection: histidine substitution for threonine at the gatekeeper position in the kinase domain. Deep sequencing confirmed representation of nearly all other missense mutations across the entire HCK open reading frame. This observation suggests that A-419259 and other C-helix-out Src-family kinase inhibitors may have a narrow path to acquired resistance in the context of AML cases where Hck is an oncogenic driver.

Glioblastomas harboring gene fusions detected by next-generation sequencing

Oncogenic gene fusions have been reported in diffuse gliomas and may serve as potential therapeutic targets. Here, using next-generation sequencing analysis (Illumina TruSight Tumor 170 panel), we analyzed a total of 356 diffuse gliomas collected from 2017 to 2019 to evaluate clinical, pathological, and genetic features of gene fusion. We found 53 cases of glioblastomas harboring the following oncogenic gene fusions: MET (n = 18), EGFR (n = 14), FGFR (n = 12), NTRK (n = 5), RET (n = 2), AKT3 (n = 1), and PDGFRA fusions (n = 1). Gene fusions were consistently observed in both IDH-wildtype and IDH-mutant glioblastomas (8.8% and 9.4%, p = 1.000). PTPRZ1-MET fusion was the only fusion that genetically resembled secondary glioblastomas (i.e., high frequency of IDH mutation, ATRX loss, TP53 mutation, and absence of EGFR amplification), whereas other gene fusion types were similar to primary glioblastomas (i.e., high frequency of IDH-wildtype, TERT mutation, EGFR amplification, and PTEN mutation). In IDH-wildtype glioblastoma patients, multivariable analysis revealed that the PTPRZ1-MET fusion was associated with poor progression-free survival (HR [95% CI]: 5.42 (1.72-17.05), p = 0.004). Additionally, we described two novel cases of CCDC6-RET fusion in glioma. Collectively, our findings indicate that targetable gene fusions are associated with aggressive biological behavior and can aid the clinical treatment strategy for glioma patients.

Open-source chemogenomic data-driven algorithms for predicting drug-target interactions

While novel technologies such as high-throughput screening have advanced together with significant investment by pharmaceutical companies during the past decades, the success rate for drug development has not yet been improved prompting researchers looking for new strategies of drug discovery. Drug repositioning is a potential approach to solve this dilemma. However, experimental identification and validation of potential drug targets encoded by the human genome is both costly and time-consuming. Therefore, effective computational approaches have been proposed to facilitate drug repositioning, which have proved to be successful in drug discovery. Doubtlessly, the availability of open-accessible data from basic chemical biology research and the success of human genome sequencing are crucial to develop effective in silico drug repositioning methods allowing the identification of potential targets for existing drugs. In this work, we review several chemogenomic data-driven computational algorithms with source codes publicly accessible for predicting drug-target interactions (DTIs). We organize these algorithms by model properties and model evolutionary relationships. We re-implemented five representative algorithms in R programming language, and compared these algorithms by means of mean percentile ranking, a new recall-based evaluation metric in the DTI prediction research field. We anticipate that this review will be objective and helpful to researchers who would like to further improve existing algorithms or need to choose appropriate algorithms to infer potential DTIs in the projects. The source codes for DTI predictions are available at: https://github.com/minghao2016/chemogenomicAlg4DTIpred.

Genomics-Guided Immunotherapy for Precision Medicine in Cancer

Next-generation sequencing (NGS) data have been central to the development of targeted therapy and immunotherapy for precision oncology. In targeted therapy, drugs directly attack cancer, by altering the expression of critical cancer genes identified with cancer genome profiling. Immunotherapy drugs indirectly attack cancer, by inducing the immune system to attack and treat cancer. Harnessing genomic data for deployment and development of immunotherapy comprises the field of immunogenomics. The discovery of a link between cancer cells escaping immune destruction and cancer progression, led to extensive research into this mechanism and drug development. In the past few years, FDA has granted accelerated approval to several immunotherapy cancer treatment drugs, pembrolizumab, nivolumab, and atezolizumab, belonging to the class of checkpoint inhibitors. Utilization of pretreatment genomic cancer screening to identify patients most likely to respond to immunotherapy and to customize immunotherapy for a given patient, promises to improve cancer treatment outcomes. Recent advances in molecular profiling, high-throughput sequencing, and computational efficiency has made immunogenomics the major tenet of precision medicine in cancer treatment. This review provides a brief overview on the state of art of immunogenomics in precision cancer medicine.

IGF2/IGF1R Signaling as a Therapeutic Target in MYB-Positive Adenoid Cystic Carcinomas and Other Fusion Gene-Driven Tumors

Chromosome rearrangements resulting in pathogenetically important gene fusions are a common feature of many cancers. They are often potent oncogenic drivers and have key functions in central cellular processes and pathways and encode transcription factors, transcriptional co-regulators, growth factor receptors, tyrosine kinases, and chromatin modifiers. In addition to being useful diagnostic biomarkers, they are also targets for development of new molecularly targeted therapies. Studies in recent decades have shown that several oncogenic gene fusions interact with the insulin-like growth factor (IGF) signaling pathway. For example, the MYB-NFIB fusion in adenoid cystic carcinoma is regulated by IGF1R through an autocrine loop, and IGF1R is a downstream target of the EWSR1-WT1 and PAX3-FKHR fusions in desmoplastic small round cell tumors and alveolar rhabdomyosarcoma, respectively. Here, we will discuss the mechanisms behind the interactions between oncogenic gene fusions and the IGF signaling pathway. We will also discuss the role of therapeutic inhibition of IGF1R in fusion gene driven malignancies.

Diagnosis of fusion genes using targeted RNA sequencing

Fusion genes are a major cause of cancer. Their rapid and accurate diagnosis can inform clinical action, but current molecular diagnostic assays are restricted in resolution and throughput. Here, we show that targeted RNA sequencing (RNAseq) can overcome these limitations. First, we establish that fusion gene detection with targeted RNAseq is both sensitive and quantitative by optimising laboratory and bioinformatic variables using spike-in standards and cell lines. Next, we analyse a clinical patient cohort and improve the overall fusion gene diagnostic rate from 63% with conventional approaches to 76% with targeted RNAseq while demonstrating high concordance for patient samples with previous diagnoses. Finally, we show that targeted RNAseq offers additional advantages by simultaneously measuring gene expression levels and profiling the immune-receptor repertoire. We anticipate that targeted RNAseq will improve clinical fusion gene detection, and its increasing use will provide a deeper understanding of fusion gene biology.

Rapid and accurate detection of fusion genes is important in cancer diagnostics. Here, the authors demonstrate that targeted RNA sequencing provides fast, sensitive and quantitative gene fusion detection and overcomes the limitations of approaches currently in clinical use.

New rapid method to detect BCR-ABL fusion genes with multiplex RT-qPCR in one-tube at a time

Fast identification of BCR-ABL fusion genes is critical for precise diagnosis, risk stratification and therapy scheme selection in leukemia. More convenient methods are needed for quickly detection of the BCR-ABL fusion genes. Multiplex fluorescent reverse transcription quantitative real-time PCR (Multiplex RT-qPCR) methods are developed for detection of the at least 14 subtypes of BCR-ABL fusion genes in one tube at a time by using patients' bone marrow samples. The new Multiplex RT-qPCR method could quickly detect BCR-ABL fusion genes with sensitivity up to 10-10⁶ copies. It can detect the fusion genes in patients' bone marrow samples containing any subtypes of the major bcr (M-bcr) e13a2, e14a2, e13a3 and e14a3, the minor bcr (m-bcr) e1a2 and e1a3, the micro bcr (μ-bcr) e19a2 and e19a3, and the nano bcr (n-bcr) e6a2 and e6a3. The specificity is comparable to the FISH methods. The cutoff for clinical diagnosis of BCR-ABL(+) is also determined by testing in clinical chronic myeloid leukemia samples. This is a new fast method with high sensitivity and specificity for clinical detection of BCR-ABL fusion genes. It will benefit the precise diagnosis, targeted therapy and minimal residual disease (MRD) monitoring in leukemia.

Dual FLT3/TOPK inhibitor with activity against FLT3-ITD secondary mutations potently inhibits acute myeloid leukemia cell lines

Aim:

Approximately 30% of acute myeloid leukemia (AML) patients carry FLT3 tyrosine kinase domain (TKD) mutations or internal tandem duplication (FLT3-ITD). Currently there is a paucity of compounds that are active against drug-resistant FLT3-ITD, which contains secondary mutations in the TKD, mainly at residues D835/F691.

Results:

HSD1169, a novel compound, is active against FLT3-ITD (D835 or F691). HSD1169 is also active against T-LAK cell-originated protein kinase (TOPK), a collaborating kinase that is highly expressed in AML cell lines. HSD1169 was active against MV4–11 and Molm-14 (FLT3-ITD cell lines) but not NOMO-1 or HL60 (FLT3-WT cell lines). HSD1169 was also active against sorafenib-resistant Molm13-res cell line (containing FLT3-ITD/D835Y).

Conclusion:

HSD1169 or an analog could become a therapeutic agent for AML containing drug-resistant FLT3-ITD.

Proteomics and Mass Spectrometry for Cancer Biomarker Discovery

Proteomics is a rapidly advancing field not only in the field of biology but also in translational cancer research. In recent years, mass spectrometry and associated technologies have been explored to identify proteins or a set of proteins specific to a given disease, for the purpose of disease detection and diagnosis. Such biomarkers are being investigated in samples including cells, tissues, serum/plasma, and other types of body fluids. When sufficiently refined, proteomic technologies may pave the way for early detection of cancer or individualized therapy for cancer. Mass spectrometry approaches coupled with bioinformatic tools are being developed for biomarker discovery and validation. Understanding basic concepts and application of such technology by investigators in the field may accelerate the clinical application of protein biomarkers in disease management.

CK1α ablation in keratinocytes induces p53-dependent, sunburn-protective skin hyperpigmentation

Casein kinase 1α (CK1α), a component of the β-catenin destruction complex, is a critical regulator of Wnt signaling; its ablation induces both Wnt and p53 activation. To characterize the role of CK1α (encoded by Csnk1a1) in skin physiology, we crossed mice harboring floxed Csnk1a1 with mice expressing K14-Cre-ER^T2 to generate mice in which tamoxifen induces the deletion of Csnk1a1 exclusively in keratinocytes [single-knockout (SKO) mice]. As expected, CK1α loss was accompanied by β-catenin and p53 stabilization, with the preferential induction of p53 target genes, but phenotypically most striking was hyperpigmentation of the skin, importantly without tumorigenesis, for at least 9 mo after Csnk1a1 ablation. The number of epidermal melanocytes and eumelanin levels were dramatically increased in SKO mice. To clarify the putative role of p53 in epidermal hyperpigmentation, we established K14-Cre-ER^T2 CK1α/p53 double-knockout (DKO) mice and found that coablation failed to induce epidermal hyperpigmentation, demonstrating that it was p53-dependent. Transcriptome analysis of the epidermis revealed p53-dependent up-regulation of Kit ligand (KitL). SKO mice treated with ACK2 (a Kit-neutralizing antibody) or imatinib (a Kit inhibitor) abrogated the CK1α ablation-induced hyperpigmentation, demonstrating that it requires the KitL/Kit pathway. Pro-opiomelanocortin (POMC), a precursor of α-melanocyte-stimulating hormone (α-MSH), was not activated in the CK1α ablation-induced hyperpigmentation, which is in contrast to the mechanism of p53-dependent UV tanning. Nevertheless, acute sunburn effects were successfully prevented in the hyperpigmented skin of SKO mice. CK1α inhibition induces skin-protective eumelanin but no carcinogenic pheomelanin and may therefore constitute an effective strategy for safely increasing eumelanin via UV-independent pathways, protecting against acute sunburn.

Overcoming ABC transporter-mediated multidrug resistance: The dual role of tyrosine kinase inhibitors as multitargeting agents

Resistance to conventional and target specific antitumor drugs still remains one of the major cause of treatment failure and patience death. This condition often involves ATP-binding cassette (ABC) transporters that, by pumping the drugs outside from cancer cells, attenuate the potency of chemotherapeutics and negatively impact on the fate of anticancer therapy. In recent years, several tyrosine kinase inhibitors (TKIs) (e.g., imatinib, nilotinib, dasatinib, ponatinib, gefitinib, erlotinib, lapatinib, vandetanib, sunitinib, sorafenib) have been reported to interact with ABC transporters (e.g., ABCB1, ABCC1, ABCG2, ABCC10). This finding disclosed a very complex scenario in which TKIs may behave as substrates or inhibitors depending on the expression of specific pumps, drug concentration, affinity for transporters and types of co-administered agents. In this context, in-depth investigation on TKI chemosensitizing functions might provide a strong rationale for combining TKIs and conventional therapeutics in specific malignancies. The reposition of TKIs as antagonists of ABC transporters opens a new way towards anticancer therapy and clinical strategies aimed at counteracting drug resistance. This review will focus on some paradigmatic examples of the complex and not yet fully elucidated interaction between clinical available TKIs (e.g. BCR-ABL, EGFR, VEGFR inhibitors) with the main ABC transporters implicated in multidrug resistance.

BIRC6 mediates imatinib resistance independently of Mcl-1

Baculoviral IAP repeat containing 6 (BIRC6) is a member of the inhibitors of apoptosis proteins (IAPs), a family of functionally and structurally related proteins that inhibit apoptosis. BIRC6 has been implicated in drug resistance in several different human cancers, however mechanisms regulating BIRC6 have not been extensively explored. Our phosphoproteomic analysis of an imatinib-resistant chronic myelogenous leukemia (CML) cell line (MYL-R) identified increased amounts of a BIRC6 peptide phosphorylated at S480, S482, and S486 compared to imatinib-sensitive CML cells (MYL). Thus we investigated the role of BIRC6 in mediating imatinib resistance and compared it to the well-characterized anti-apoptotic protein, Mcl-1. Both BIRC6 and Mcl-1 were elevated in MYL-R compared to MYL cells. Lentiviral shRNA knockdown of BIRC6 in MYL-R cells increased imatinib-stimulated caspase activation and resulted in a ~20-25-fold increase in imatinib sensitivity, without affecting Mcl-1. Treating MYL-R cells with CDK9 inhibitors decreased BIRC6 mRNA, but not BIRC6 protein levels. By contrast, while CDK9 inhibitors reduced Mcl-1 mRNA and protein, they did not affect imatinib sensitivity. Since the Src family kinase Lyn is highly expressed and active in MYL-R cells, we tested the effects of Lyn inhibition on BIRC6 and Mcl-1. RNAi-mediated knockdown or inhibition of Lyn (dasatinib/ponatinib) reduced BIRC6 protein stability and increased caspase activation. Inhibition of Lyn also increased formation of an N-terminal BIRC6 fragment in parallel with reduced amount of the BIRC6 phosphopeptide, suggesting that Lyn may regulate BIRC6 phosphorylation and stability. In summary, our data show that BIRC6 stability is dependent on Lyn, and that BIRC6 mediates imatinib sensitivity independently of Mcl-1 or CDK9. Hence, BIRC6 may be a novel target for the treatment of drug-resistant CML where Mcl-1 or CDK9 inhibitors have failed.

Computational and mechanistic studies on the effect of galactoxyloglucan: Imatinib nanoconjugate in imatinib resistant K562 cells

Imatinib mesylate, a BCR/ABL fusion protein inhibitor, is the first-line treatment against chronic myelogenous leukemia. In spite of its advantageous viewpoints, imatinib still has genuine impediments like undesirable side effects and tumor resistance during chemotherapy. Nanoparticles with sustainable release profile will help in targeted delivery of anticancer drugs while minimizing deleterious side effects and drug resistance. The use of biopolymers like galactoxyloglucan (PST001) for the fabrication of imatinib mesylate nanoparticles could impart its use in overcoming multidrug resistance in chronic myelogenous leukemia patients with minimal side effects. This study involved in the synthesis of PST-Imatinib nanoconjugates with appreciable drug payload and excellent cytotoxicity against drug-resistant chronic myelogenous leukemia cell line (K562) in comparison with free drug. The use of bioinformatics tool revealed better binding affinity for the drug–polysaccharide complex than the drug alone with three proteins: 3QX3 (Topoisomerase), 1M17 (EGFR tyrosine kinase domain), and 3QRJ (ABL1 kinase domain). Assessment of the biochemical, hematological, and histopathological parameters in mice upheld the security and adequacy of the nanoconjugate compared to free drug. Although perspective investigations are warranted, in a condition like drug resistance in leukemia, this nanoconjugate would display a productive approach in cancer therapeutics.

Extracellular vesicle communication pathways as regulatory targets of oncogenic transformation

Pathogenesis of human cancers bridges intracellular oncogenic driver events and their impact on intercellular communication. Among multiple mediators of this 'pathological connectivity' the role of extracellular vesicles (EVs) and their subsets (exosomes, ectosomes, oncosomes) is of particular interest for several reasons. The release of EVs from cancer cells represents a unique mechanism of regulated expulsion of bioactive molecules, a process that also mediates cell-to-cell transfer of lipids, proteins, and nucleic acids. Biological effects of these processes have been implicated in several aspects of cancer-related pathology, including tumour growth, invasion, angiogenesis, metastasis, immunity and thrombosis. Notably, the emerging evidence suggests that oncogenic mutations may impact several aspects of EV-mediated cell-cell communication including: (i) EV release rate and protein content; (ii) molecular composition of cancer EVs; (iii) the inclusion of oncogenic and mutant macromolecules in the EV cargo; (iv) EV-mediated release of genomic DNA; (v) deregulation of mechanisms responsible for EV biogenesis (vesiculome) and (vi) mechanisms of EV uptake by cancer cells. Intriguingly, EV-mediated intercellular transfer of mutant and oncogenic molecules between subpopulations of cancer cells, their indolent counterparts and stroma may exert profound biological effects that often resemble (but are not tantamount to) oncogenic transformation, including changes in cell growth, clonogenicity and angiogenic phenotype, or cause cell stress and death. However, several biological barriers likely curtail a permanent horizontal transformation of normal cells through EV-mediated mechanisms. The ongoing analysis and targeting of EV-mediated intercellular communication pathways can be viewed as a new therapeutic paradigm in cancer, while the analysis of oncogenic cargo contained in EVs released from cancer cells into biofluids is being developed for clinical use as a biomarker and companion diagnostics. Indeed, studies are underway to further explore the multiple links between molecular causality in cancer and various aspects of cellular vesiculation.

Limited Impact of Imatinib in a Murine Model of Sclerodermatous Chronic Graft-versus-Host Disease

BACKGROUND

Sclerodermatous chronic Graft-versus-Host Disease (scl-cGVHD) is one of the most severe form of cGVHD. The Platelet-derived Grotwth Factor (PDGF) and the Transforming Growth Factor-β (TGF-β) play a significant role in the fibrosing process occurring in scl-cGVHD. This prompted us to assess the impact of the PDGF-r and c-Abl tyrosine kinase inhibitor imatinib on scl-cGVHD.

METHODS

To assess the impact of imatinib on T cell subset proliferation in vivo, Balb/cJ recipient mice were lethally (7 Gy) irradiated and then injected with 10x106 bone marrow cells from B10.D2 mice on day 0. Fourteen days later, 70x106 carboxyfluorescein succinimidyl ester (CFSE)-labeled splenocytes from B10.D2 mice were infused and imatinib or sterile water was administered for 5 days. To induce severe scl-cGVHD, Balb/cJ mice were injected i.v. with 10.106 bone marrow cells and 70.106 splenocytes from B10.D2 donor mice after 7 Gy irradiation. Mice were then given sterile water or imatinib from day +7 after transplantation to the end of the experiment (day +52).

RESULTS

Imatinib decreased the proliferation of total T cells (P = 0.02), CD8+ T cells (P = 0.01), and of regulatory T cells (Tregs) (P = 0.02) in the spleen. In the severe scl-cGVHD model, imatinib-treated mice had significantly lower levels of PDGF-r phosphorylation than control mice on day 29 after transplantation (P = 0.008). However, scl-cGVHD scores were similar between vehicle- and imatinib-treated mice during the whole experiment, while there was a suggestion for less weight loss in imatinib-treated mice that reached statistical significance at day +52 following transplantation (P = 0.02).

CONCLUSIONS

Imatinib had a limited impact in murine scl-cGVHD despite significant inhibition of PDGF-r.

Somatic Engineering of Oncogenic Chromosomal Rearrangements: A Perspective

The ability to engineer specific mutations in mice has proven essential to advancing our understanding of the molecular basis of cancer. Chromosomal rearrangements, a common and clinically relevant class of cancer-causing mutations, have however remained difficult to faithfully recapitulate in vivo The development of genetic tools for in vivo somatic genome editing has recently overcome this limitation and led to the generation of more sophisticated and accurate preclinical models of human cancers. Here, we review the potential applications of these new technologies to the study of tumor biology and discuss their advantages over more conventional strategies, their limitations, and the remaining challenges. Cancer Res; 76(17); 4918-23. ©2016 AACR.

c-Abl Tyrosine Kinase Adopts Multiple Active Conformational States in Solution

Protein tyrosine kinases of the Abl family have diverse roles in normal cellular regulation and drive several forms of leukemia as oncogenic fusion proteins. In the crystal structure of the inactive c-Abl kinase core, the SH2 and SH3 domains dock onto the back of the kinase domain, resulting in a compact, assembled state. This inactive conformation is stabilized by the interaction of the myristoylated N-cap with a pocket in the C-lobe of the kinase domain. Mutations that perturb these intramolecular interactions result in kinase activation. Here, we present X-ray scattering solution structures of multidomain c-Abl kinase core proteins modeling diverse active states. Surprisingly, the relative positions of the regulatory N-cap, SH3, and SH2 domains in an active myristic acid binding pocket mutant (A356N) were virtually identical to those of the assembled wild-type kinase core, indicating that Abl kinase activation does not require dramatic reorganization of the downregulated core structure. In contrast, the positions of the SH2 and SH3 domains in a clinically relevant imatinib-resistant gatekeeper mutant (T315I) appear to be reconfigured relative to their positions in the wild-type protein. Our results demonstrate that c-Abl kinase activation can occur either with (T315I) or without (A356N) global allosteric changes in the core, revealing the potential for previously unrecognized signaling diversity.

The landscape of gene fusions and somatic mutations in salivary gland neoplasms - Implications for diagnosis and therapy

Recent studies of the genomic landscape of salivary gland tumors have provided important insights into the molecular pathogenesis of these tumors. The most consistent alterations identified include a translocation-generated gene fusion network involving transcription factors, transcriptional coactivators, tyrosine kinase receptors, and other kinases. In addition, next-generation sequencing studies of a few subtypes of salivary neoplasms have revealed hotspot mutations in individual genes and mutations clustering to specific pathways frequently altered in cancer. Although limited, these studies have opened up new avenues for improved classification and targeted therapies of salivary gland cancers. In this review, we summarize the latest developments in this field, focusing on tumor types for which clinically important molecular data are available.

Targeting therapeutic liabilities engendered by PIK3R1 mutations for cancer treatment

The regulatory subunit of PI3K, p85α (encoded by PIK3R1), binds, stabilizes and inhibits the PI3K p110 catalytic subunit. Functional characterization of PIK3R1 mutations has identified not only hypomorphs with reduced inhibition of p110, but also hypomorphs and dominant negative mutants that disrupt a novel regulatory role of p85α on PTEN or neomorphs that activate unexpected signaling pathways. The diverse phenotypic spectrum of these PIK3R1 driver mutations underscores the need for different treatment strategies targeting tumors harboring these mutations. This article describes the functional consequences of the spectrum of PIK3R1 driver mutations and therapeutic liabilities they may engender.