Challenges and future of precision tumor treatment.
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Challenges and future of precision tumor treatment.
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Challenges and future of precision tumor treatment.
Technological breakthroughs in genomics and proteomics continue to drive tumor biology forward.
The forward-looking molecular characteristics of cancer enable doctors to determine the genomic changes of each patient’s tumor in real time, and to choose personalized treatment plans based on these detailed data.
Although only a few patients currently benefit from precision targeted therapy, this group will continue to grow as the field progresses.
The scope of precision oncology is rapidly expanding to address previously insurmountable targets and rare genomic drivers.
At the same time, previously unrecognized biological and therapeutic complexities are emerging.
How to further expand the benefits of genome-driven oncology, including proposing strategies for improving drug design, more detailed patient selection, and designing next-generation genome-driven clinical trials, will help accelerate our understanding of tumor biology and continue to improve The patient’s prognosis.
Current status of targeted therapy
Some people think that the first targeted therapy can be traced back to the 131I treatment of thyroid cancer in the 1940s. Now representative ones include Tamoxifen, a selective estrogen receptor ( ER ) modulator, used to prevent the recurrence of ER-positive breast cancer ( approved by the FDA in 1977 ); Gleevec, a type used to treat chronic granuloma ABL kinase inhibitors for cell leukemia ( approved by the FDA in 2001 ); and monoclonal antibodies, such as rituximab and trastuzumab, were approved for lymphoma ( 1997 ) and breast cancer ( 1998 ), respectively. Because antibodies usually cannot penetrate cell membranes and Intracellular target binding, so it is used to target the extracellular receptors of cancer cells.
As shown in the table above, cancer drugs have successfully developed several types of targets. In general, in drug development, G protein-coupled receptors are the most commonly used targets, followed by kinases; however, for cancer, protein kinases are by far the most productive target in small molecule drug development. The human genome encodes approximately 500 protein kinases, including two major families of tyrosine and serine/threonine kinases.
As of mid-2019, the FDA has approved 48 protein kinase inhibitors for clinical use, most of which target receptor tyrosine kinases; 43 have been approved for cancer treatment, and many more are in preclinical and clinical applications test. A key point of the development of kinase inhibitors in the future is to further explore potential targets and continue to develop inhibitors against multiple targets, that is, a single inhibitor can target a preferred set of kinases.
Current status of immunotherapy
The development of personalized medicine is accompanied by the development of tumor immunotherapy. The innovation of genomics has promoted the discovery of new immune targets and promoted reasonable methods for the design of immunotherapy clinical trials. Since the anti-CTLA-4 antibody ( ipilimumab ) was approved for the treatment of advanced melanoma in 2011, personalized treatment for immune checkpoints has promoted the transformation of many cancer treatment models. Anti-PD-1 antibody alone won 9 FDA in 2018 New approval.
Sequencing cancer genomes is a powerful tool in precision medicine. The use of multi-platform technology can identify more potential targets, thereby increasing the probability of matching effective drugs. For example, Pembrolizumab ( anti-PD-1 ) is approved for cancers with high microsatellite instability and mismatch repair defects, making it the first drug to treat solid tumors based on biomarker predictions, regardless of tumor type .
Chimeric antigen receptor ( CAR ) engineered T cells is another important breakthrough in personalized medicine. Clinical trials using CAR-T cells have produced a high response rate in leukemia and lymphoma. The FDA approved CAR-T cells for the treatment of relapsed/refractory acute lymphoblastic leukemia and diffuse large B-cell lymphoma in children and young adults. tumor. As more and more solid tumor clinical trials are underway, interest in the application of CAR-T cell therapy in solid tumors is also increasing.
CAR has also been applied to natural killer ( NK ) cells. CAR-NK cells show significant anti-tumor activity in the clinic, and may have higher safety than CAR-T cells. Since allogeneic CAR-NK cell infusion is well tolerated, CAR-NK cells can be used off-the-shelf. In addition, because circulating CAR-NK cells have a short lifespan and limited toxicity, they are unlikely to cause cytokine release syndrome. Since CAR-NK cells kill tumor cells through CAR-dependent and CAR-independent mechanisms, CAR-NK cells may also achieve greater success in eliminating heterogeneous tumors. The production of sufficient numbers of NK cells and the lack of effective gene transfer methods are still obstacles to NK cell immunotherapy.
Various omics techniques have also been used to discover tumor-associated antigens ( TAA ). There is evidence that immunotherapy for a special type of TAA called tumor neoantigen ( TNA ) will bring greater clinical effects. Unlike TAAs, TAAs can be expressed by some healthy tissues during development, while TNAs are the result of tumor-specific gene changes. Of course, the mutation load and the number of neoantigens vary between different cancers, with the highest frequency of somatic mutations found in skin cancer, lung cancer, and colon cancer.
Although there are no clear biomarkers to predict the patient’s response to immunotherapy, high tumor mutation burden, neoantigens, DNA damage repair and mutations in the mismatch repair pathway are all considered predictive biomarkers, because with As the number of somatic mutations increases, the number of potential biomarkers will increase in response. Heterogeneity within tumors and genetic variation of HLA genes are involved in the presentation of tumor neoantigens to T cells, and it has also been shown to affect the response of immunotherapy. Looking ahead, the use of specific biomarkers to combine certain variants of individualized peptide vaccines with immunostimulants ( including adjuvants, immune checkpoint inhibitors, and chemotherapy ) will be the use of personalized drugs to target anti-tumor immune responses Bring great hope.
Gaps and challenges
Although significant progress has been made in patient management, precision medicine still faces great challenges, as only a limited series of drugs are currently approved for the treatment of cancers associated with specific gene mutations. The clinical relevance of many mutations to a variety of cancers is unclear.
One of the most researched targets related to all cancers is the Ras oncoprotein. RAS activating mutations can be found in about one-third of cancers. Therefore, RAS inhibitors have a wide range of uses in many treatment options. Ras acts as a binary switch in the key signal transduction pathway, combining with GTP for enzymatic hydrolysis and signal transmission. However, because RAS is a featureless, nearly spherical structure without obvious binding sites, it is difficult to synthesize a compound that can target binding and inhibit its activity. Synonymous with “prepared medicine” target. However, the recent approval of sotorasib ( AMG 510 ) brings hope.
The second type of therapeutic target considered to be non-druggable is transcription factor, which may represent nearly 20% of the currently confirmed oncogene pool and is particularly important in childhood cancers. Due to the large interaction surface between protein and nucleic acid, it is difficult for transcription factors to be directly targeted by small molecules. Recently, methods of suppressing transcription factors through selective degradation or epigenetic down-regulation have brought us some exciting results.
The research challenges of personalized immunotherapy specifically include identifying strong tumor antigens and neoantigens, enhancing T cell infiltration in tumors, responding to changes in the expression of major histocompatibility, and counteracting T cell immunosuppression. Perhaps the most immediate challenge is to find more reliable clinical biomarkers to predict immunotherapy response and guide treatment decisions.
The cancer cells within the tumor are highly heterogeneous, which poses a challenge to achieve a durable response after cancer treatment. For immunotherapy, persistence and acquired drug resistance are still relatively unknown areas, and antigen presentation that reflects the overall mutation in the tumor is still elusive.
Understanding how to best combine targeted drugs with chemotherapy, radiotherapy, surgery, and immunotherapy is expected to help overcome the problem of resistance and produce a longer-lasting response. In order to fully verify the safety and effectiveness of the combination therapy, considerable clinical trials are required. Unfortunately, only less than 2% of adult cancer patients participate in active clinical trials. In addition, the analysis of drug clinical trials shows that the main reason for failure is usually the lack of sufficient efficacy for the intended target or target population. A recent analysis of Phase 3 clinical trials showed that 57% of failures were due to insufficient efficacy, while only 17% of failures were due to toxicity.
At present, artificial intelligence is changing the rules of the game. This technology has the potential to reliably predict which patients will respond to which treatment and for how long. The use of artificial intelligence is critical to understanding the best applications of precision medicine. Big data sharing is the key to realize early cancer diagnosis and accurate decision-making, and is a key step to realize cancer precision medicine. The use of bioinformatics and large data sets will continue to generate insights into the intersection of drug efficacy and genomics, and will drive the optimization of effective treatments.
Optimize drug development
At present, a new generation of therapies based on precision oncology helps to clarify many key characteristics of the best molecularly targeted drugs. The most important factors include therapeutic index, target selectivity and drug resistance.
A good treatment window to allow the optimal dose is the key to successful treatment. The therapeutic index is the result of comprehensive consideration of drug selectivity, target characteristics and off-target toxicity.
For example, the therapeutic window of EGFR inhibitors is different due to the different selectivity of targeted activating mutations and wild-type EGFR. Many patients who respond well to first- and second-generation EGFR inhibitors ( such as erlotinib, gefitinib, and afatinib ) have L858R mutations and exon 19 deletions. These deletions increase receptor dimerization and reduce ATP binding. Compared with EGFR, the affinity of inhibitors is enhanced.
In contrast, these drugs have a poor therapeutic index in EGFR exon 20 insertion, because the inhibitory effect of exon 20 mutants is not as good as that of wild-type EGFR, which limits the tolerance of these drugs.
Target selectivity can reduce off-target toxicity and allow more effective drug activity, thereby improving efficacy.
For example, changes in activated RET are found in about 2% of lung adenocarcinomas and up to 20% of papillary thyroid carcinomas, and multiple kinase inhibitors ( MKI ) have a certain degree of RET inhibition, such as lenvatinib, vandetanib, cabozatinib, and ponatinib. Shows limited clinical activity in RET-mutated tumors. However, all of these drugs show stronger non-targeted inhibitory effects, typically VEGFR ( KDR ), which determines their dose-limiting toxicity and thus cannot achieve the maximum RET blockade.
In contrast, selective RET inhibitors, including selpercatinib ( LOXO-292 ) and pralsetinib ( BLU-667 ), have been developed to allow effective and sustained targeted inhibition, and have proven to have significant efficacy and good results compared with MKIs Security.
Therefore, a better understanding of the genomic drivers of a single cancer, coupled with advances in structural biology, enables the development of reasonable and suitable drugs for specific purposes. The production of such selective inhibitors is essential for optimizing tolerance and maximizing The effect of chemical treatment is very important.
When designing drugs, the underlying mechanisms of primary and acquired resistance should be considered. Considerations include resistance caused by drug permeability and resistance secondary to molecular changes.
For common cancers with brain metastases, including NSCLC, breast cancer, and melanoma, ensuring that drugs targeting key genome changes in these cancers have sufficient central nervous system ( CNS ) permeability has become a key design parameter. Although the first-generation ALK inhibitor crizotinib can achieve high initial systemic disease control rates, poor brain permeability leads to CNS progression in up to 60% of patients during treatment. A prospective evaluation of a new generation of ALK inhibitors has shown that disease control in the brain has been significantly improved, ultimately helping to improve progression-free survival and overall survival.
In addition to drug resistance determined by drug permeability, drug development increasingly considers the predictive mechanism of targeted acquired drug resistance. For example, successive generations of ALK inhibitors are specifically designed to target mutations to maintain binding efficacy.
New areas of drug development
Isomer and mutation selective inhibitor
Recognizing that more selective treatments tend to have better efficacy and tolerability, some strategies have been used to more specifically and directly suppress carcinogenic drivers, including the development of selective inhibitors of isoforms and mutations.
For example, the PI3K pathway is one of the most common mutation pathways in cancer, but the early use of pan-PI3K inhibitors has only shown limited efficacy. In contrast, subtype-selective PI3K inhibitors show better efficacy than pan-PI3K and dual PI3K/mTOR inhibitors. In addition, isoform-specific inhibitors can minimize the toxicity attributed to “off-target” isoforms.
In recent years, the selectivity of drugs has surpassed the selectivity of isoforms, and has evolved to a single mutant allele. This selectivity allows the suppression of mutated oncogenic proteins while retaining wild-type proteins.
KRAS is one of the most common mutated oncogenes in cancer, but although it is considered a key carcinogenic driver, it has long been considered unmedicable, partly due to the lack of targetable binding sites. However, the latest design allows it to react with the mutant cysteine of KRAS G12C, forming an irreversible binding and locking the protein in its inactive binding state. In the absence of this mutant cysteine, these covalent inhibitors will not react with wild-type KRAS, thereby protecting normal tissues. The early results of the KRAS G12C inhibitor phase I trial proved the effectiveness and safety of this targeted mutation.
Antibody Conjugation (ADC)
Another way to improve the therapeutic index is to use antibody-conjugated drugs. By directly linking the cytotoxic payload to the targeting antibody, ADC is designed to expand the therapeutic window of traditional cytotoxic drugs.
At present, many such drugs have begun to be used clinically. For example, the ADC drug trastuzumab deruxtecan ( DS8201 ) is composed of the cytotoxic topoisomerase I inhibitor deruxtecan coupled to the anti-HER2 antibody trastuzumab. This drug has shown unprecedented activity in HER2-driven cancers, including HER2+ breast cancer and gastric cancer, as well as in breast cancers with low HER2 expression. In this type of patients, HER2 targeted therapy is effective It is often ineffective to a large extent. Identifying tumor-specific targets suitable for ADC development and optimizing the safety of these engineered drugs will be the key to their further development and utilization.
Traditionally, most small molecule inhibitors target the ATP binding site. Recently, advances in structure-based drug design, computational chemistry with dynamic simulation, and high-throughput drug screening methods have jointly contributed to the development of non-ATP-competitive inhibitors that incorporate new allosteric sites.
These allosteric inhibitors can overcome target drug resistance mediated by mutations in the active site of the validated target, and can inhibit previously untreatable proteins. For example, asciminib ( ABL001 ), an allosteric inhibitor targeting BCR-ABL fusion positive, has entered the clinic and has proven efficacy in refractory drug-resistant AML patients who have been treated with a variety of ATP-competitive inhibitors. Another method being actively explored is the combined application of selective ATP competitive inhibitors and allosteric inhibitors, which may jointly delay or even completely prevent the development of acquired drug resistance.
Allosteric inhibitors can also target treatments that were previously untargetable. For example, phosphatase SHP2 and SOS1 together play an important role in facilitating nucleotide exchange, allowing RAS to cycle between its inactive GDP-bound state and activated GTP-bound state. Phosphatase was previously considered to be an unattractive drug target, but allosteric inhibitors can change the conformation of SHP2 and eliminate its activity. This has proven efficacy in preclinical animal models. Currently, some clinical trials are underway .
Proteolytic targeting chimera (PROTACS)
Another emerging method to target key cancer drivers is PROTACS. This method usually uses bifunctional molecules to bring the target protein close to the ubiquitin ligase, which ultimately leads to the degradation of the target protein.
The application of this technology in cancer treatment is still in its infancy. Like allosteric inhibitors of key oncogenes, this technology may overcome target drug resistance mediated by mutations in the active site of the validated target. Inhibits previously unmedicable proteins. Many key drivers of cancer, including transcription factors, cannot be targeted by currently available treatments, either because they are not expressed on the cell surface and therefore inaccessible to antibodies, or because they lack a binding capsule to which small molecule inhibitors can attach . PROTACs can overcome these challenges by simultaneously binding the target and E3 ubiquitin ligase to utilize the cell’s endogenous protein degradation mechanism to promote protein degradation.
ARV-110 is the first drug to enter phase I clinical trials, which links the E3 ubiquitin ligase and androgen receptor in patients with prostate cancer ( NCT03888612 ). This new method of reducing cellular protein levels can effectively target many previously untreatable targets.
By shaping the protein conformation to restore the natural function of the mutant protein, thereby reactivating the lost activity, such small molecule drugs are currently being developed.
This strategy has been proven successful in the treatment of cystic fibrosis. Cystic fibrosis is a non-tumor hereditary disease characterized by mutations in the gene encoding cystic fibrosis transmembrane conductance regulator ( CFTR ). Lead to excessive mucus secretion. By re-enabling CFTR to reach the cell surface and perform a function similar to that of wild-type protein, protein renaturation drugs reduce the clinical sequelae of cystic fibrosis.
The application of protein renaturation in cancer is currently being explored, and it represents a new method for targeting mutant tumor suppressors. The loss-of-function mutation of the tumor suppressor TP53 is the most common mutation in cancer. However, there is currently no specific treatment for TP53 mutant cancers, and small molecules that restore the activity of mutant TP53 through protein renaturation are under development. In addition to expanding the number of possible drug targets, this approach also provides additional benefits, such as reduced toxicity.
Optimize the use of drugs
In order to maximize the degree of genomic play drive oncology benefits, we must optimize the use of existing therapies.
Reasonable treatment sequence and development of a synergistic and tolerable combination, and giving new treatments at the most appropriate time in the treatment process of patients may improve the efficacy.
Apply as soon as possible to reduce resistance
New treatments are usually tested on patients with diseases that benefit the most from existing standard treatments. However, the experience of using EGFR and ALK inhibitors shows that applying our best drugs as early as possible before the emergence of resistance may improve the efficacy.
More than 50% of EGFR-mutant NSCLC patients treated with first- and second-generation EGFR tyrosine kinase inhibitors ( TKIs ) acquired EGFR T790M mutations. Osimertinib was developed to overcome the T790M mutation and was initially performed in patients who had advanced TKIs.
However, recent evidence shows that compared with patients treated with first-generation EGFR TKIs, when patients receive osimertinib as first-line treatment, it effectively prevents T790M-mediated resistance and significantly increases overall survival. Therefore, the drug development model should encourage early patient testing of next-generation inhibitors.
Adjuvant and neoadjuvant therapy
Most precision treatments are aimed at patients with recurrent or metastatic cancer. The goal of such patients is often to prolong life and do not expect a cure. On the contrary, the greatest opportunity for precision treatment may be patients with early disease, and effective treatment may increase the cure rate.
In patients with HER2-positive breast cancer, adding the HER2 monoclonal antibody trastuzumab to chemotherapy can significantly improve the 10-year survival rate.
Adjuvant targeted therapy is also the standard treatment for patients with stage 3 BRAF V600E mutant melanoma and KIT expressing gastrointestinal stromal tumors. The benefit of disease-free survival has been demonstrated based on the phase 3 trial.
For targeted therapies with high response rates, neoadjuvant therapy can be used to convert unresectable tumors into surgically resectable diseases, thereby providing a chance of cure.
For example, although larotrectinib was developed for advanced TRK fusion-positive cancers that do not respond to standard treatments, neoadjuvant larotrectinib has been successfully used in pediatric sarcoma patients to shrink tumors and allow complete resection.
Although further research is needed to determine the application of this new adjuvant method, it is clear that early use of effective drugs may significantly improve the prognosis of some patients.
Combination therapy can be used to improve efficacy, reduce toxicity, and/or prevent the emergence of drug resistance. In BRAF V600 mutant melanoma, compared with BRAF alone inhibition, combined inhibition of BRAF and MEK can prolong survival and reduce skin toxicity.
In addition to preventing primary drug resistance, a reasonable combination can effectively treat secondary drug resistance. As biopsies become more common after progress, more and more reports of off-target drug resistance have emerged.
When the acquired change itself is targeted, the sequencing data provides an opportunity for a reasonable combination of treatments for both the main and acquired driving factors.
For example, in the TATTON clinical trial, patients with acquired MET-amplified EGFR-mutant NSCLC were treated with osimertinib and the MET inhibitor savolitinib. Savolitinib can restore sensitivity to osimertinib.
The analysis of the molecular characteristics of tumors has enabled us to develop successful targeted therapies, benefiting countless patients.
However, molecular-targeted research also emphasizes the complexity of predicting which patients may respond to treatment.
In addition, many genomic drivers are still “not druggable” or cannot be effectively targeted due to the tolerance of current treatments.
Therefore, we must learn lessons from previous successes and failures to optimize drug design, develop innovative new treatment methods, and continue to improve the matching method between patients and treatments, to achieve more effective precision targeted therapy, and create a more accurate treatment for tumors. New Era.
1. Towards a more precise future for oncology. Cancer Cell. 2020 Apr 13; 37(4): 431–442.
2. Blueprint for cancer research:Critical gaps and opportunities. CA Cancer J Clin. 2020 Dec 16.
Challenges and future of precision tumor treatment.
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