New strategies for targeting drug combinations to overcome mutation-driven drug resistance

Investigation of the synergistic effect mechanism underlying sequential use of palbociclib and cisplatin through integral proteomic and glycoproteomic analysis

Chemoresistance largely hampers the clinical use of chemodrugs for cancer patients, combination or sequential drug treatment regimens have been designed to minimize chemotoxicity and resensitize chemoresistance. In this work, the cytotoxic effect of cisplatin was found to be enhanced by palbociclib pretreatment in HeLa cells. With the integration of liquid chromatography-mass spectrometry-based proteomic and N-glycoproteomic workflow, we found that palbociclib alone mainly enhanced the N-glycosylation alterations in HeLa cells, while cisplatin majorly increased the different expression proteins related to apoptosis pathways. As a result, the sequential use of two drugs induced a higher expression level of apoptosis proteins BAX and BAK. Those altered N-glycoproteins induced by palbociclib were implicated in pathways that were closely associated with cell membrane modification and drug sensitivity. Specifically, the top four frequently glycosylated proteins FOLR1, L1CAM, CD63, and LAMP1 were all associated with drug resistance or drug sensitivity. It is suspected that palbociclib-induced N-glycosylation on the membrane protein allowed the HeLa cell to become more vulnerable to cisplatin treatment. Our study provides new insights into the mechanisms underlying the sequential use of target drugs and chemotherapy drugs, meanwhile suggesting a high-efficiency approach that involves proteomic and N-glycoproteomic to facilitate drug discovery.

Use of Drug Sensitisers to Improve Therapeutic Index in Cancer

The clinical management of malignant tumours is challenging, often leading to severe adverse effects and death. Drug resistance (DR) antagonises the effectiveness of treatments, and increasing drug dosage can worsen the therapeutic index (TI). Current efforts to overcome DR predominantly involve the use of drug combinations, including applying multiple anti-cancerous drugs, employing drug sensitisers, which are chemical agents that enhance pharmacokinetics (PK), including the targeting of cellular pathways and regulating pertinent membrane transporters. While combining multiple compounds may lead to drug-drug interactions (DDI) or polypharmacy effect, the use of drug sensitisers permits rapid attainment of effective treatment dosages at the disease site to prevent early DR and minimise side effects and will reduce the chance of DDI as lower drug doses are required. This review highlights the essential use of TI in evaluating drug dosage for cancer treatment and discusses the lack of a unified standard for TI within the field. Commonly used benefit-risk assessment criteria are summarised, and the critical exploration of the current use of TI in the pharmaceutical industrial sector is included. Specifically, this review leads to the discussion of drug sensitisers to facilitate improved ratios of effective dose to toxic dose directly in humans. The combination of drug and sensitiser molecules might see additional benefits to rekindle those drugs that failed late-stage clinical trials by the removal of detrimental off-target activities through the use of lower drug doses. Drug combinations and employing drug sensitisers are potential means to combat DR. The evolution of drug combinations and polypharmacy on TI are reviewed. Notably, the novel binary weapon approach is introduced as a new opportunity to improve TI. This review emphasises the urgent need for a criterion to systematically evaluate drug safety and efficiency for practical implementation in the field.

Dual Starvations Induce Pyroptosis for Orthotopic Pancreatic Cancer Therapy through Simultaneous Deprivation of Glucose and Glutamine

Pancreatic cancer is a highly fatal disease, and existing treatment methods are ineffective, so it is urgent to develop new effective treatment strategies. The high dependence of pancreatic cancer cells on glucose and glutamine suggests that disrupting this dependency could serve as an alternative strategy for pancreatic cancer therapy. We identified the vital genes glucose transporter 1 (GLUT1) and alanine-serine-cysteine transporter 2 (ASCT2) through bioinformatics analysis, which regulate glucose and glutamine metabolism in pancreatic cancer, respectively. Human serum albumin nanoparticles (HSA NPs) for delivery of GLUT1 and ASCT2 inhibitors, BAY-876/V-9302@HSA NPs, were prepared by a self-assembly process. This nanodrug inhibits glucose and glutamine uptake of pancreatic cancer cells through the released BAY-876 and V-9302, leading to nutrition deprivation and oxidative stress. The inhibition of glutamine leads to the inhibition of the synthesis of the glutathione, which further aggravates oxidative stress. Both of them lead to a significant increase in reactive oxygen species, activating caspase 1 and GSDMD and finally inducing pyroptosis. This study provides a new effective strategy for orthotopic pancreatic cancer treatment by dual starvation-induced pyroptosis. The study for screening metabolic targets using bioinformatics analysis followed by constructing nanodrugs loaded with inhibitors will inspire future targeted metabolic therapy for pancreatic cancer.

A new integrated framework for the identification of potential virus-drug associations

Introduction

With the increasingly serious problem of antiviral drug resistance, drug repurposing offers a time-efficient and cost-effective way to find potential therapeutic agents for disease. Computational models have the ability to quickly predict potential reusable drug candidates to treat diseases.

Methods

In this study, two matrix decomposition-based methods, i.e., Matrix Decomposition with Heterogeneous Graph Inference (MDHGI) and Bounded Nuclear Norm Regularization (BNNR), were integrated to predict anti-viral drugs. Moreover, global leave-one-out cross-validation (LOOCV), local LOOCV, and 5-fold cross-validation were implemented to evaluate the performance of the proposed model based on datasets of DrugVirus that consist of 933 known associations between 175 drugs and 95 viruses.

Results

The results showed that the area under the receiver operating characteristics curve (AUC) of global LOOCV and local LOOCV are 0.9035 and 0.8786, respectively. The average AUC and the standard deviation of the 5-fold cross-validation for DrugVirus datasets are 0.8856 ± 0.0032. We further implemented cross-validation based on MDAD and aBiofilm, respectively, to evaluate the performance of the model. In particle, MDAD (aBiofilm) dataset contains 2,470 (2,884) known associations between 1,373 (1,470) drugs and 173 (140) microbes. In addition, two types of case studies were carried out further to verify the effectiveness of the model based on the DrugVirus and MDAD datasets. The results of the case studies supported the effectiveness of MHBVDA in identifying potential virus-drug associations as well as predicting potential drugs for new microbes.

Combination Chemotherapy of Multidrug-resistant Early-stage Colon Cancer: Determining Optimal Dose Schedules by High-performance Computer Simulation

The goal of this project was to utilize mechanistic simulation to demonstrate a methodology that could determine drug combination dose schedules and dose intensities that would be most effective in eliminating multidrug resistant cancer cells in early-stage colon cancer. An agent-based model of cell dynamics in human colon crypts was calibrated using measurements of human biopsy specimens. Mutant cancer cells were simulated as cells that were resistant to each of two drugs when the drugs were used separately. The drugs, 5-flurouracil and sulindac, have different mechanisms of action. An artificial neural network was used to generate nearly two hundred thousand two-drug dose schedules. A high-performance computer simulated each dose schedule as a in silico clinical trial and evaluated each dose schedule for its efficiency to cure (eliminate) multidrug resistant cancer cells and its toxicity to the host, as indicated by continued crypt function. Among the dose schedules that were generated, 2430 dose schedules were found to cure all multidrug resistant mutants in each of the 50 simulated trials and retained colon crypt function. One dose schedule was optimal; it eliminated multidrug resistant cancer cells with the minimum toxicity and had a time schedule that would be practical for implementation in the clinic. These results demonstrate a procedure to identify which combination drug dose schedules could be most effective in eliminating drug resistant cancer cells. This was accomplished using a calibrated agent-based model of a human tissue, and a high-performance computer simulation of clinical trials.

Biological and pharmacological roles of m6A modifications in cancer drug resistance

Cancer drug resistance represents the main obstacle in cancer treatment. Drug-resistant cancers exhibit complex molecular mechanisms to hit back therapy under pharmacological pressure. As a reversible epigenetic modification, N⁶-methyladenosine (m⁶A) RNA modification was regarded to be the most common epigenetic RNA modification. RNA methyltransferases (writers), demethylases (erasers), and m⁶A-binding proteins (readers) are frequently disordered in several tumors, thus regulating the expression of oncoproteins, enhancing tumorigenesis, cancer proliferation, development, and metastasis. The review elucidated the underlying role of m⁶A in therapy resistance. Alteration of the m⁶A modification affected drug efficacy by restructuring multidrug efflux transporters, drug-metabolizing enzymes, and anticancer drug targets. Furthermore, the variation resulted in resistance by regulating DNA damage repair, downstream adaptive response (apoptosis, autophagy, and oncogenic bypass signaling), cell stemness, tumor immune microenvironment, and exosomal non-coding RNA. It is highlighted that several small molecules targeting m⁶A regulators have shown significant potential for overcoming drug resistance in different cancer categories. Further inhibitors and activators of RNA m⁶A-modified proteins are expected to provide novel anticancer drugs, delivering the therapeutic potential for addressing the challenge of resistance in clinical resistance.

Evolution of small cell lung cancer tumor mutation: from molecular mechanisms to novel viewpoints

Small cell lung cancer (SCLC) is a clinically common malignant tumor originating from the lung neuroendocrine stem cells, which has a poor prognosis and accounts for approximately 15% of all lung cancer cases. However, research on its treatment has been slow, and the 5-year survival rate of patients with SCLC has been < 5% for many years. In recent years, the development and popularization of gene sequencing technology have facilitated the understanding of the gene mutation landscape and tumor evolution of SCLC, thereby leading to a more accurate prediction of the prognosis of SCLC and the development of individualized treatment. In this review, we aimed to discuss the mutation evolution of SCLC from the perspective of a tumor evolution theory and described the sequence of mutation evolution in the occurrence and development of SCLC. In addition, we summarized the existing whole-exome sequencing (WES) data of SCLC cases at our center along with relevant publications on sequencing. Thereafter, we discuss the role of different mutated pathways in the occurrence of SCLC to predict its prognosis more accurately and summarized individualized treatment strategies.

The role of lncRNA just proximal to XIST (JPX) in human disease phenotypes and RNA methylation: The novel biomarker and therapeutic target potential

Increasing evidence suggests that long non-coding RNAs (lncRNAs) are closely related to the initialization and development of human diseases. lncRNA just proximal to XIST (JPX), as a newly identified lncRNA, has been reported to be aberrantly expressed and associated with pathophysiological traits in numerous diseases, particularly cancers. More importantly, JPX has been proven to play important roles in various biological functions, including cell proliferation, migration, invasion, apoptosis, chemoresistance, and differentiation. In addition, we discuss the diverse molecular mechanisms and correlation with RNA methylation of JPX in several cancers. In this Review, we summarize current studies on JPX's roles in diseases and its potential application as a biomarker for both diagnoses and prognoses and a therapeutic target in human diseases.

Next-Generation Personalized Medicine: Implementation of Variability Patterns for Overcoming Drug Resistance in Chronic Diseases

Chronic diseases are a significant healthcare problem. Partial or complete non-responsiveness to chronic therapies is a significant obstacle to maintaining the long-term effect of drugs in these patients. A high degree of intra- and inter-patient variability defines pharmacodynamics, drug metabolism, and medication response. This variability is associated with partial or complete loss of drug effectiveness. Regular drug dosing schedules do not comply with physiological variability and contribute to resistance to chronic therapies. In this review, we describe a three-phase platform for overcoming drug resistance: introducing irregularity for improving drug response; establishing a deep learning, closed-loop algorithm for generating a personalized pattern of irregularity for overcoming drug resistance; and upscaling the algorithm by implementing quantified personal variability patterns along with other individualized genetic and proteomic-based ways. The closed-loop, dynamic, subject-tailored variability-based machinery can improve the efficacy of existing therapies in patients with chronic diseases.

Combinatorial Therapy of Cancer: Possible Advantages of Involving Modulators of Ionic Mechanisms

Cancer is a global health problem that 1 in 2-3 people can expect to experience during their lifetime. Several different modalities exist for cancer management, but all of these suffer from significant shortcomings in both diagnosis and therapy. Apart from developing completely new therapies, a viable way forward is to improve the efficacy of the existing modalities. One way is to combine these with each other or with other complementary approaches. An emerging latter approach is derived from ionic mechanisms, mainly ion channels and exchangers. We evaluate the evidence for this systematically for the main treatment methods: surgery, chemotherapy, radiotherapy and targeted therapies (including monoclonal antibodies, steroid hormones, tyrosine kinase inhibitors and immunotherapy). In surgery, the possible systemic use of local anesthetics to suppress subsequent relapse is still being discussed. For all the other methods, there is significant positive evidence for several cancers and a range of modulators of ionic mechanisms. This applies also to some of the undesirable side effects of the treatments. In chemotherapy, for example, there is evidence for co-treatment with modulators of the potassium channel (Kv11.1), pH regulation (sodium-hydrogen exchanger) and Na+-K+-ATPase (digoxin). Voltage-gated sodium channels, shown previously to promote metastasis, appear to be particularly useful for co-targeting with inhibitors of tyrosine kinases, especially epidermal growth factor. It is concluded that combining current orthodox treatment modalities with modulators of ionic mechanisms can produce beneficial effects including (i) making the treatment more effective, e.g., by lowering doses; (ii) avoiding the onset of resistance to therapy; (iii) reducing undesirable side effects. However, in many cases, prospective clinical trials are needed to put the findings firmly into clinical context.

Chronotherapy of Early Colon Cancer: Advantage of Morning Dose Schedules

Colon adenomas with proliferating mutant cells may progress to invasive carcinomas. Proliferation of cells in human colorectal tissue is circadian, greater in the interval 4 to 12 hours after midnight than 16 to 24 hours after midnight. We have tested the hypothesis that chemotherapy administered during the time of greater cell proliferation will be more effective than chemotherapy administered during the time of lesser proliferation. An agent-based computer model of cell proliferation in colon crypts was calibrated with measurements of cell numbers in human biopsy specimens. It was used to simulate cytotoxic chemotherapy of an early stage of colon cancer, adenomas with about 20% of mutant cells. Chemotherapy doses were scheduled at different 4-hour intervals during the 24-hour day, and repeated at weekly intervals. Chemotherapy administered at 4 to 8 hours after midnight cured mutant cells in 100% of 50 trials with an average time to cure of 7.82 days (s.e.m. = 0.99). In contrast, chemotherapy administered at 20 to 24 hours after midnight cured only 18% of 50 trials, with the average time to cure of 23.51 days (s.e.m. = 2.42). These simulation results suggest that clinical chemotherapy of early colon cancer may be more effective when given in the morning than later in the day.

Drug Repurposing for Cancer Therapy in the Era of Precision Medicine

Drug repurposing refers to the identification of clinically approved drugs with the known safety profiles and defined pharmacokinetic properties for new indications. Despite the advances in oncology research, cancers are still associated with the most unmet medical needs. Drug repurposing has emerged as a useful approach for the search for effective and durable cancer treatment. It may also represent a promising strategy to facilitate precision cancer treatment and overcome drug resistance. The repurposing of non-cancer drugs for precision oncology effectively extends the inventory of actionable molecular targets and thus increases the number of patients who may benefit from precision cancer treatment. In cancer types where genetic heterogeneity is so high that it is not feasible to identify strong repurposed drug candidates for standard treatment, the precision oncology approach offers individual patients access to novel treatment options. For repurposed candidates with low potency, a combination of multiple repurposed drugs may produce a synergistic therapeutic effect. Precautions should be taken when combining repurposed drugs with anticancer agents to avoid detrimental drug-drug interactions and unwanted side effects. New multifactorial data analysis and artificial intelligence methods are needed to untangle the complex association of molecular signatures influencing specific cancer subtypes to facilitate drug repurposing in precision oncology.

Metformin sensitises hepatocarcinoma cells to methotrexate by targeting dihydrofolate reductase

Metformin, the first-line drug for type II diabetes, has recently been considered an anticancer agent. However, the molecular target and underlying mechanism of metformin's anti-cancer effects remain largely unclear. Herein, we report that metformin treatment increases the sensitivity of hepatocarcinoma cells to methotrexate (MTX) by suppressing the expression of the one-carbon metabolism enzyme DHFR. We show that the combination of metformin and MTX blocks nucleotide metabolism and thus effectively inhibits cell cycle progression and tumorigenesis. Mechanistically, metformin not only transcriptionally represses DHFR via E2F4 but also promotes lysosomal degradation of the DHFR protein. Notably, metformin dramatically increases the response of patient-derived hepatocarcinoma organoids to MTX without obvious toxicity to organoids derived from normal liver tissue. Taken together, our findings identify an important role for DHFR in the suppressive effects of metformin on therapeutic resistance, thus revealing a therapeutically targetable potential vulnerability in hepatocarcinoma.

Effective early diagnosis for NSCLC: an algorithm

INTRODUCTION

Lung cancer still remains undiagnosed for most patients until the disease is inoperable.

AREAS COVERED

We performed search on PubMed with the keywords: EBUS, radial-EBUS, bronchoscopy, lung cancer, electromagnetic navigation, ct-biopsy, transthoracic biopsy. We present diagnostic equipment and imaging techniques such as positron emission tomography, endoscopical navigation systems, endobronchial ultrasound, radial-endobronchial ultrasound, transthoracic ultrasound biopsy, and computed tomography guided biopsies.

EXPERT OPINION

However, lack of early disease symptoms remains the most important issue and therefore we should direct our efforts to screening and early disease diagnosis. An algorithm is proposed for biopsy upon initial disease diagnosis.

Orthogonal targeting of osteoclasts and myeloma cells for radionuclide stimulated dynamic therapy induces multidimensional cell death pathways

Rationale: Multiple myeloma (MM) is a multifocal malignancy of bone marrow plasma cells, characterized by vicious cycles of remission and relapse that eventually culminate in death. The disease remains mostly incurable largely due to the complex interactions between the bone microenvironment (BME) and MM cells (MMC). In the “vicious cycle” of bone disease, abnormal activation of osteoclasts (OCs) by MMC causes severe osteolysis, promotes immune evasion, and stimulates the growth of MMC. Disrupting these cancer-stroma interactions would enhance treatment response.

Methods: To disrupt this cycle, we orthogonally targeted nanomicelles (NM) loaded with non-therapeutic doses of a photosensitizer, titanocene (TC), to VLA-4 (α4ß1, CD49d/CD29) expressing MMC (MM1.S) and αvß3 (CD51/CD61) expressing OC. Concurrently, a non-lethal dose of a radiopharmaceutical, ¹⁸F-fluorodeoxyglucose ([¹⁸F]FDG) administered systemically interacted with TC (radionuclide stimulated therapy, RaST) to generate cytotoxic reactive oxygen species (ROS). The in vitro and in vivo effects of RaST were characterized in MM1.S cell line, as well as in xenograft and isograft MM animal models.

Results: Our data revealed that RaST induced non-enzymatic hydroperoxidation of cellular lipids culminating in mitochondrial dysfunction, DNA fragmentation, and caspase-dependent apoptosis of MMC using VLA-4 avid TC-NMs. RaST upregulated the expression of BAX, Bcl-2, and p53, highlighting the induction of apoptosis via the BAK-independent pathway. The enhancement of multicopper oxidase enzyme F5 expression, which inhibits lipid hydroperoxidation and Fenton reaction, was not sufficient to overcome RaST-induced increase in the accumulation of irreversible function-perturbing α,ß-aldehydes that exerted significant and long-lasting damage to both DNA and proteins. In vivo, either VLA-4-TC-NM or αvß3-TC-NMs RaST induced a significant therapeutic effect on immunocompromised but not immunocompetent MM-bearing mouse models. Combined treatment with both VLA-4-TC-NM and αvß3-TC-NMs synergistically inhibited osteolysis, reduced tumor burden, and prevented rapid relapse in both in vivo models of MM.

Conclusions: By targeting MM and bone cells simultaneously, combination RaST suppressed MM disease progression through a multi-prong action on the vicious cycle of bone cancer. Instead of using the standard multidrug approach, our work reveals a unique photophysical treatment paradigm that uses nontoxic doses of a single light-sensitive drug directed orthogonally to cancer and bone cells, followed by radionuclide-stimulated generation of ROS to inhibit tumor progression and minimize osteolysis in both immunocompetent murine and immunocompromised human MM models.

Inhibition of the FACT Complex Targets Aberrant Hedgehog Signaling and Overcomes Resistance to Smoothened Antagonists

Hedgehog signaling is aberrantly activated in hematologic malignancies and solid tumors, and targeting it is a promising therapeutic strategy against these cancers. Resistance to clinically available hedgehog-targeted Smoothened inhibitor (SMOi) drugs has become a critical issue in hedgehog-driven cancer treatment. Our previous studies identified inhibition of BET and CDK7 as two epigenetic/transcriptional-targeted therapeutic strategies for overcoming SMOi resistance, providing a promising direction for anti-hedgehog drug development. To uncover additional strategies for inhibiting aberrant hedgehog activity, here we performed CRISPR-Cas9 screening with an single-guide RNA library targeting epigenetic and transcriptional modulators in hedgehog-driven medulloblastoma cells, combined with tumor dataset analyses. Structure specific recognition protein 1 (SSRP1), a subunit of facilitates chromatin transcription (FACT) complex, was identified as a hedgehog-induced essential oncogene and therapeutic target in hedgehog-driven cancer. The FACT inhibitor CBL0137, which has entered clinical trials for cancer, effectively suppressed in vitro and in vivo growth of multiple SMOi-responsive and SMOi-resistant hedgehog-driven cancer models. Mechanistically, CBL0137 exerted anti-hedgehog activity by targeting transcription of GLI1 and GLI2, which are core transcription factors of the hedgehog pathway. SSRP1 bound the promoter regions of GLI1 and GLI2, while CBL0137 treatment substantially disrupted these interactions. Moreover, CBL0137 synergized with BET or CDK7 inhibitors to antagonize aberrant hedgehog pathway and growth of hedgehog-driven cancer models. Taken together, these results identify FACT inhibition as a promising epigenetic/transcriptional-targeted therapeutic strategy for treating hedgehog-driven cancers and overcoming SMOi resistance. SIGNIFICANCE: This study identifies FACT inhibition as an anti-hedgehog therapeutic strategy for overcoming resistance to Smoothened inhibitors and provides preclinical support for initiating clinical trials of FACT-targeted drug CBL0137 against hedgehog-driven cancers.

Circular RNAs in the tumour microenvironment

BACKGROUND

Circular RNAs (circRNAs) are a new class of endogenous non-coding RNAs (ncRNAs) widely expressed in eukaryotic cells. Mounting evidence has highlighted circRNAs as critical regulators of various tumours. More importantly, circRNAs have been revealed to recruit and reprogram key components involved in the tumour microenvironment (TME), and mediate various signaling pathways, thus affecting tumourigenesis, angiogenesis, immune response, and metastatic progression. In this review, we briefly introduce the biogenesis, characteristics and classification of circRNAs, and describe various mechanistic models of circRNAs. Further, we provide the first systematic overview of the interplay between circRNAs and cellular/non-cellular counterparts of the TME and highlight the potential of circRNAs as prospective biomarkers or targets in cancer clinics. Finally, we discuss the biological mechanisms through which the circRNAs drive development of resistance, revealing the mystery of circRNAs in drug resistance of tumours.

SHORT CONCLUSION

Deep understanding the emerging role of circRNAs and their involvements in the TME may provide potential biomarkers and therapeutic targets for cancer patients. The combined targeting of circRNAs and co-activated components in the TME may achieve higher therapeutic efficiency and become a new mode of tumour therapy in the future.

The essential oil composition of selected Hemerocallis cultivars and their biological activity

The horticultural cultivars of Hemerocallis (daylily) have been used to treat diseases such as insomnia, inflammation and depression, and also as a vegetable in eastern Asia. Taking into consideration the fact, that the volatile compounds in Hemerocallis cultivars have not been investigated to date, we decided to study the composition of the essential oils (EOs) from the aerial parts of ten varieties collecting in Poland. EOs, obtained by hydrodistillation, were analyzed by GC/MS method that resulted in identification of 23-36 volatile compounds comprising 89.5%–96.3% of the total amount. The essential oils differed in their composition and they can be classified into three groups. The antibacterial and antioxidant activities of EOs were also evaluated. Gram-negative strains were most strongly inhibited by all tested oils. Two model systems have been used for the antioxidant efficacy, 2,2-diphenyl-1-picryl-hydrazyl (DPPH•) andβ-carotene bleaching assays. The essential oils with the high presence of oxygenated monoterpenes and monoterpene hydrocarbons showed higher antioxidant activity. The chemical composition of EOs of Hemerocallis cultivars and their biological activity is reported for the first time. Thus, the findings presented here suggest that the aerial parts of Hemerocallis cultivars may be candidates for the development of new phytomedicine.

Identification of Genetic Mutations in Cancer: Challenge and Opportunity in the New Era of Targeted Therapy

The introduction of targeted therapy is the biggest success in the treatment of cancer in the past few decades. However, heterogeneous cancer is characterized by diverse molecular alterations as well as multiple clinical profiles. Specific genetic mutations in cancer therapy targets may increase drug sensitivity, or more frequently result in therapeutic resistance. In the past 3 years, several novel targeted therapies have been approved for cancer treatment, including drugs with new targets (i.e., anti-PD1/PDL1 therapies and CDK4/6 inhibitors), mutation targeting drugs (i.e., the EGFR T790M targeting osimertinib), drugs with multiple targets (i.e., the EGFR/HER2 dual inhibitor neratinib) and drug combinations (i.e., encorafenib/binimetinib and dabrafenib/trametinib). In this perspective, we focus on the most up-to-date knowledge of targeted therapy and describe how genetic mutations influence the sensitivity of targeted therapy, highlighting the challenges faced within this era of precision medicine. Moreover, the strategies that deal with mutation-driven resistance are further discussed. Advances in these areas would allow for more targeted and effective therapeutic options for cancer patients.

Identification of pyrrolopyrimidine derivative PP-13 as a novel microtubule-destabilizing agent with promising anticancer properties

Despite the emergence of targeted therapies and immunotherapy, chemotherapy remains the gold-standard for the treatment of most patients with solid malignancies. Spindle poisons that interfere with microtubule dynamics are commonly used in chemotherapy drug combinations. However, their troublesome side effects and the emergence of chemoresistance highlight the need for identifying alternative agents. We performed a high throughput cell-based screening and selected a pyrrolopyrimidine molecule (named PP-13). In the present study, we evaluated its anticancer properties in vitro and in vivo. We showed that PP-13 exerted cytotoxic effects on various cancer cells, including those resistant to current targeted therapies and chemotherapies. PP-13 induced a transient mitotic blockade by interfering with both mitotic spindle organization and microtubule dynamics and finally led to mitotic slippage, aneuploidy and direct apoptotic death. PP-13 was identified as a microtubule-targeting agent that binds directly to the colchicine site in β-tubulin. Interestingly, PP-13 overcame the multidrug-resistant cancer cell phenotype and significantly reduced tumour growth and metastatic invasiveness without any noticeable toxicity for the chicken embryo in vivo. Overall, PP-13 appears to be a novel synthetic microtubule inhibitor with interesting anticancer properties and could be further investigated as a potent alternative for the management of malignancies including chemoresistant ones.

Tomorrow's genome medicine in lung cancer

Tomorrow's genome medicine in lung cancer should focus more on the homogeneity and heterogeneity of lung cancer which play an important role in the development of drug resistance, genetic complexity, as well as confusion and difficulty of early diagnosis and therapy. Chromosome positioning and repositioning may contribute to the sensitivity of lung cancer cells to therapy, the heterogeneity associated with drug resistance, and the mechanism of lung carcinogenesis. The CCCTC-binding factor plays critical roles in genome topology and function, increased risk of carcinogenicity, and potential of lung cancer-specific mediations. Chromosome reposition in lung cancer can be regulated by CCCTC binding factor. Single-cell gene sequencing, as part of genome medicine, was paid special attention in lung cancer to understand mechanical phenotypes, single-cell biology, heterogeneity, and chromosome positioning and function of single lung cancer cells. We at first propose to develop an intelligent single-cell robot of human cells to integrate together systems information of molecules, genes, proteins, organelles, membranes, architectures, signals, and functions. It can be a powerful automatic system to assist clinicians in the decision-making, molecular understanding, risk analyzing, and prognosis predicting.