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Anticancer drugs repurposed for Alzheimer’s disease: a systematic review

Abstract

Background

The relationship between cancer and dementia is triggering growing research interest. Several preclinical studies have provided the biological rationale for the repurposing of specific anticancer agents in Alzheimer’s disease (AD), and a growing number of research protocols are testing their efficacy and safety/tolerability in patients with AD.

Methods

The aim of the present systematic review was to provide an overview on the repurposing of approved anticancer drugs in clinical trials for AD by considering both ongoing and completed research protocols in all phases. In parallel, a systematic literature review was conducted on PubMed, ISI Web, and the Cochrane Library to identify published clinical studies on repurposed anticancer agents in AD.

Results

Based on a structured search on the ClinicalTrials.gov and the EudraCT databases, we identified 13 clinical trials testing 11 different approved anticancer agents (five tyrosine kinase inhibitors, two retinoid X receptor agonists, two immunomodulatory agents, one histone deacetylase inhibitor, and one monoclonal antibody) in the AD continuum. The systematic literature search led to the identification of five published studies (one phase I, three phase II, and one phase IIb/III) reporting the effects of antitumoral treatments in patients with mild cognitive impairment or AD dementia. The clinical findings and the methodological characteristics of these studies are described and discussed.

Conclusion

Anticancer agents are triggering growing interest in the context of repurposed therapies in AD. Several clinical trials are underway, and data are expected to be available in the near future. To date, data emerging from published clinical studies are controversial. The promising results emerging from preclinical studies and identified research protocols should be confirmed and extended by larger, adequately designed, and high-quality clinical trials.

Background

Cancer and dementia, including Alzheimer’s disease (AD), represent two of the leading causes of mortality and disability worldwide [1]. Although these pathological conditions have traditionally been associated with distinct pathophysiological mechanisms and phenotypic manifestations, a growing body of research has recently been focused on their possible mutual relationship [2, 3].

Some studies suggested an inverse relationship between cancer and dementia (mostly of the AD type), with cancer history decreasing the risk of AD and patients with AD having a lower probability of developing cancer [4]. However, it is crucial to clarify the either genetic or molecular mechanisms that could be somehow at crossroads between these two conditions and sustain their possible negative association. In contrast, other studies provided preliminary evidence that cancer and AD may share some common pathways. In this regard, a recent study analyzed all biological hallmarks of cancer in the AD literature and concluded that not all cancer etiopathogenetic events run the opposite direction in AD [5]. Moreover, since Hanahan and Weinberg updated their research on the hallmarks of cancer [6, 7], there is accumulating evidence that these key molecular pathways may also affect the risk, onset, and progression of AD and that some specific hallmarks can actually be common to these diseases [8].

For instance, it has been shown that some oncoproteins, such as protein kinases, are dysregulated in AD, since hyperphosphorylation of neurofibrillary tangles is one of the distinctive features of AD [8]. Another cancer hallmark, namely inflammation [6, 7, 9], is also increasingly invoked to explain the neuropathological changes leading to AD. Indeed, the activation of microglia and astrocytes and the resulting neuroinflammation are currently considered as major events in the pathophysiology of this neurodegenerative condition [10, 11] and it is demonstrated that amyloid plaques are surrounded by activated microglia both in early and late stages of the disease [12]. Targeting these immune responses could therefore represent an alternative therapeutic strategy in AD [13, 14]. Finally, other biological processes and abnormalities, such as genome instability and deregulation of cellular energetics, probably constitute common underlying mechanisms [5].

The therapeutic implications of the complex relationship between cancer and dementia have instead been poorly investigated yet. Given the current therapeutic gap in AD, the scientific community is growingly investigating whether drugs approved for other diseases may be repurposed to slow down or even hamper AD course [15, 16]. In this regard, some anticancer drugs have been shown to have a good permeability through the blood-brain barrier (BBB), thus potentially exerting relevant effects against AD pathology [17, 18]. A recent retrospective study of approximately 3.5 million older American veterans showed that cancer treatment was independently associated with decreased AD risk and that those who received chemotherapy had a lower risk than those who did not [19]. Accordingly, in a study of nearly 62,000 older women diagnosed with breast cancer, the risk of developing AD and other dementias was significantly lower in patients receiving chemotherapy [20]. In addition, some studies suggest that anticancer drugs may also act as disease-modifying therapies once the AD-related neurodegenerative process has already started [21]. Based on these preliminary findings, a growing number of research protocols are testing the efficacy and safety of approved anticancer agents in patients with AD.

Hence, the aim of the present systematic review was to provide an overview on the repurposing of approved anticancer drugs in clinical trials for AD. Both ongoing research protocols and published studies were considered for this purpose. Furthermore, attention was paid to methodological and reporting quality.

Materials and methods

Systematic review of ongoing research protocols

Two databases were used as sources for the present study: (i) the ClinicalTrials.gov for studies registered in the USA and (ii) the EudraCT (European Union Drug Regulating Authorities Clinical Trials Database) for all interventional studies registered in the European Union. The two databases were investigated in December 2020, to identify ongoing research protocols testing anticancer agents in the AD continuum by using both the following search terms: “Alzheimer OR Dementia.” No restriction was applied for recruitment phase/status, study design, and study phase. Two reviewers (AA, EL) independently selected protocols deemed to be eligible for the review topic. Specifically, only studies (i) investigating pharmacological compounds approved by national or international drug agencies (e.g., Food and Drugs Administration, European Medicines Agency) as anticancer agents and (ii) recruiting patients with a clinical diagnosis of AD or mild cognitive impairment (MCI) or assessing AD biomarkers in subjects with preclinical AD and healthy volunteers were selected. Trials focusing on neurodegenerative dementias other than AD (i.e., Lewy body dementia, Parkinson’s disease dementia, frontotemporal dementias) were instead not considered for the present analysis. Any disagreement in the protocols’ selection was resolved by discussion between the authors. For each selected trial, the main methodological and clinical information (IDs, status, duration, intervention, sample size, sociodemographic and clinical characteristics of participants, relevant inclusion and exclusion criteria, diagnosis at the baseline, primary and secondary endpoints) were extracted in standardized forms. Along with this information, it was investigated whether the tested drugs were used as disease-modifying or as symptomatic treatments.

Literature search of published clinical studies

The literature review was performed following the methodology described in the Cochrane handbook for systematic reviews [22] and was reported based on the PRISMA statement for reporting systematic reviews and meta-analyses [23]. A systematic literature search was conducted in the biomedical databases, i.e., PubMed, ISI Web of Knowledge, and the Cochrane Library to identify published clinical trials testing approved anticancer agents in AD. The search was updated to January 2021. The following terms were used: (Alzheimer* OR dementia*) AND (((cancer* OR neoplas* OR tumor* OR oncolog* OR anticancer* OR anti-cancer* OR anti-neoplas* OR antineoplas* OR tumor* OR antitumor* OR anti-tumor*) AND (drug* OR treatment* OR therap*) AND (“clinical trial” OR “clinical trials” OR “randomized trial” OR “randomised trial” OR “randomized trials” OR “randomised trials”)) OR (bexaroten* OR Nilotinib OR AMN107 OR Dasatinib OR Daratumumab OR Tamibarotene OR OAM80 OR Thalidomide OR Lenalidomide OR Masitinib OR AB1010 OR Bosutinib OR PF-5208763 OR Ski-606 OR Pexidartinib OR PLX3397 OR Vorinostat)). Specific drug names and/or codes included in the search string were selected based on the trials identified by the search in the ClinicalTrial.gov and EudraCT databases.

Studies were independently selected by four reviewers (AA, EL, IB, GR) based on their pertinence with and relevance to the topic of the review. Disagreements were resolved by consensus. Only clinical studies (i) investigating approved anticancer agents and (ii) enrolling patients with a clinical diagnosis of AD (of any severity) or MCI or exploring the effect of anticancer agents on AD biomarkers in participants with preclinical AD or healthy subjects were selected. Preclinical studies, study protocols, and reviews as well as studies recruiting participants without a diagnosis of AD were not considered. Studies that published only trial protocols and/or patients’ baseline features were excluded. Conference proceedings, abstracts, posters, letters, and editorials were also excluded. When trial results were available both from clinical trials databases and publications, data were compared to identify possible discrepancies. A modified PRISMA Flow Diagram was used to report the flow process for study selection (Fig. 1). Then, the Cochrane risk-of-bias tool for randomized trials (RoB) was applied to published trial studies for methodological and quality assessment. The RoB tool is suitable for individually randomized, parallel-group, and cluster-randomized trials. The qualitative assessment of included studies was performed using the software Review Manager, version 5.3, developed by the Cochrane Collaboration.

Fig. 1
figure 1

Modified PRISMA flow diagram for clinical trial selection

Results

Overview of identified research protocols

A total of 3654 protocols registered on ClinicalTrials.gov and 656 protocols registered on EudraCT were identified and screened. Among them, 13 studies fulfilled the selection criteria as they were testing approved anticancer agents in samples of patients in the AD continuum (Fig. 1). Eleven of these studies were only registered in ClinicalTrials.gov. One trial was registered on both databases, and one protocol was registered exclusively in the EU database. Three phase I, one phase I/II, eight phase II, and one phase IIb/III protocols were identified (Table 1).

Table 1 IDs, intervention, main features, and outcomes of selected trial protocols

Overall, 11 different approved anticancer drugs were investigated. Five drugs (bosutinib, dasatinib, masitinib, nilotinib, and pexidartinib) belong to the class of tyrosine kinase inhibitor (TKI) class, two are immunomodulatory agents (lenalidomide and thalidomide), two are retinoid X receptor (RXR) agonists (bexarotene and tamibarotene), one is a monoclonal antibody (daratumumab), and one is a histone deacetylase (HDAC) inhibitor (vorinostat) (Fig. 2). A comprehensive overview of the role of these drugs in cancer, their regulatory approved indications, and the rationale for their therapeutic potential for AD is provided in Table 2 [24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47, 49, 50].

Fig. 2
figure 2

Pie chart of approved anticancer drugs in trials for Alzheimer’s disease

Table 2 Anticancer drug class, mechanism of action, approved indications, and therapeutic rationale for repurposing in Alzheimer’s disease

Five protocols are currently active (nilotinib, lenalidomide, dasatinib, daratumumab, and vorinostat), four are completed (bexarotene and masitinib), one is enrolling by invitation (bosutinib), two are currently in unknown status (tamibarotene, thalidomide), and one is prematurely ended (pexidartinib). In terms of the number of trials identified, bexarotene and masitinib were the most represented agents that are being investigated in two trials each.

Concerning the study design, four studies (vorinostat, bosutinib, dasatinib, and daratumumab) are adopting a single-group assignment (i.e., no placebo) whereas nine are parallel-group, placebo-controlled studies.

Notably, only for one protocol, the study design and findings were already published in a journal [51]. No discrepancies between the registered protocol and the study publication were noticed regarding baseline characteristics, outcomes, and observed adverse events (AEs). A total of 1057 (range 5–721) subjects were planned to be enrolled in the considered protocols. The largest number of participants are expected to be recruited in the two trials with masitinib (n=756). Most studies focused on subjects with a diagnosis of MCI and mild to moderate AD (MMSE range 10–28). Only in one study, healthy volunteers were enrolled (bexarotene, NCT02061878). The duration of the planned interventions ranged between 5 days and 1 year.

Five trials (i.e., daratumumab, tamibarotene, lenalidomide, and both masitinib studies) adopted the Alzheimer’s Disease Assessment Score–Cognitive Subscale (ADAS-Cog) as the primary outcome.

Phase III masitinib and lenalidomide trials indicated the Alzheimer’s Disease Collaborative Study-Activities of Daily Living (ADCS-ADL) as the primary endpoint. The Mini Mental State Examination (MMSE) was indicated as the primary outcome in the lenalidomide study and as the secondary outcome in the daratumumab, tamibarotene, bexarotene, and masitinib studies. The Montreal Cognitive Assessment (MoCA) was used as the secondary endpoint in the dasatinib trial. In the phase I bexarotene study, where healthy volunteers were enrolled, only amyloid biomarkers were considered as both primary and secondary outcomes. No clinical outcomes were defined in phase I and phase I–II studies (vorinostat, bosutinib, bexarotene, and dasatinib).

Overview of published clinical studies

The structured bibliographic searches yielded 2056 records. A total of 10 studies were selected based on their pertinence and relevance to the topic of the review. When applying the predefined inclusion and exclusion criteria, five studies were further excluded, with five studies to be included in the qualitative analysis [48, 51,52,53,54] (Fig. 1). Four phase II and one phase I studies were identified. For one study, results were also posted on ClinicalTrials.gov as mentioned in the previous section. Anticancer drugs for which a publication was available were bexarotene [52, 54], masitinib [51], nilotinib [53], and thalidomide [48]. The main characteristics and outcomes of the identified studies are summarized in Table 3.

Table 3 Main features of published clinical studies: study design, intervention, safety profile, and outcomes

Design and study population

Four studies [48, 51,52,53] enrolled patients with a diagnosis of mild to moderate AD while one study [54] recruited healthy volunteers; four studies enrolled patients older than 50 years [48, 51,52,53], while one study [54] recruited young volunteers [age range 21–50]. In two studies [52, 53], a positive amyloid PET was required as an additional criterion before randomization.

All five studies adopted a randomized, double-blind design. Only one study was a multicenter trial [51]. Allocation ratio, treatment duration, drug, and placebo doses were always described. Four trials [48, 52,53,54] adopted a two-arm design while the remaining one [51] relied on a multi-arm design. All studies reported that the appearance and way of administration of drug and matching placebo were identical. In some cases, packaging and labeling were generated and held by a third-party service to ensure a blinding procedure.

We used the RoB tool for quality analysis of randomized studies (Fig. 3). Our analysis of random sequence generation (selection bias) assessed that three studies had an unclear risk of bias [48, 53, 54] while, for two studies, a low risk was estimated [51, 52]. The enrollment and allocation process were reported in all studies. However, in two studies, the flow diagram of the randomization process was not available [48, 54]. Baseline characteristics and clinical features of participants were reported for both treatment and placebo groups in all studies. Only for one study [51], p-values were presented in tables to highlight between-group differences at the baseline. Only in two studies [52, 53], ethnicity was reported among baseline characteristics with white/Caucasian participants accounting for the overwhelming majority of participants (90–95%).

Fig. 3
figure 3

Risk of bias tool for methodological evaluation of published clinical studies

Apoliprotein E (ApoE) genotype

Information on ApoE genotype was reported only for three studies in summary tables [52,53,54]. In the nilotinib study, all ApoE genotypes identified in both treatment and placebo groups were reported. In the phase II bexarotene study, the frequency of ApoE-ε4 carriers (homozygotes and heterozygotes) and noncarriers was provided. In the phase I bexarotene study, based on theoretical concerns that the ApoE-ε4 allele may confer toxic gain of function and side effects, it was considered as appropriate to enroll only ApoE ε3/ε3 carriers. For two studies [48, 51], genotype profiles were not characterized.

Concomitant treatments and investigational drug dosages

Participants with AD were allowed to continue their treatments with cholinesterase inhibitors and/or memantine if on a stable dose. Investigational drugs were thus administered as adjunct therapies to the standard of care. Regarding drug dose, fixed dosages were assessed in bexarotene studies [52, 54]. Conversely, in the nilotinib trial [53], patients received escalating dose regimens unless safety and tolerability concerns appeared. In the masitinib study [51], blinded dose adjustments were allowed in the case of minimal toxicity or lack of response. In the thalidomide study [48], patients received escalating dose regimens previously adopted in oncological studies. Additional information on therapeutic regimens and posology is provided in Table 3.

Safety profiles

Safety analysis, drug tolerability, and AEs were reported for each study. A low risk of reporting bias was observed in four studies [48, 52,53,54]. In the masitinib study [51], only AEs with an incidence greater or equal to 5% were reported. A comparison between the masitinib’s safety profile observed in patients with AD and that emerged in other masitinib phase II non-oncology studies showed similar findings. A high discontinuation rate occurred in the treatment arm of the masitinib trial as compared to placebo (65% vs 25%). However, a similar frequency of severe AEs occurred was documented in the masitinib and placebo arms (15% vs 13% of patients, respectively). Moreover, only seven out of 26 subjects (27%) discontinued due to AEs while 10 subjects interrupted the treatment for reasons unrelated to the exposure. In the bexarotene studies [52, 54], increased triglyceride and cholesterol levels were observed both in healthy subjects and patients with AD. In the nilotinib study [53], the drug revealed an acceptable safety profile.

Poor safety was reported in the thalidomide study [48]. Based on our judgments, attrition bias was low in four studies [48, 52,53,54], since equal loss of participants occurred both in treatment and control arms.

Results for reported outcomes

Safety and tolerability were assessed as primary outcomes in three studies [48, 53, 54]. Biological outcomes associated with the reduction of CNS amyloid markers were evaluated in three studies [52,53,54]. In the proof-of-mechanism study [54], only low nanomolar levels of bexarotene were found in CSF and poor CNS penetration in the brain of healthy subjects was documented. However, the authors cautioned that the BBB of healthy human subjects would show lower permeability. The study on thalidomide [48] showed that poor safety and high toxicity hampered the use of a potentially therapeutic dose. Conversely, bexarotene, masitinib, and nilotinib showed more favorable safety profiles.

All four studies on patients with AD assessed cognitive and/or functional and/or neuropsychiatric changes through the administration of clinical tools (ADAS-Cog, ADCS-ADL, MMSE, MoCA, CDR-SB, CIBIC-Plus, and NPI). No study used a comprehensive neuropsychological test battery to measure cognitive modifications. Three studies [48, 52, 53] did not report any significant cognitive improvement, while the masitinib study [51] showed significant efficacy results measured with a decrease greater or equal to four points of the ADAS-Cog score at 12 and 24 weeks (6% of participants in the masitinib group experienced a cognitive decline as compared with 50% of those receiving placebo, p=0.040 and p=0.046, respectively).

Nilotinib achieved relevant CSF concentrations. Furthermore, it significantly reduced amyloid burden in the frontal lobe, measured by florbetaben PET at 12 months, and attenuated hippocampal volume loss. No significant result was observed for the explorative clinical outcomes.

Discussion

To the best of our knowledge, the present study is the first attempt to systematically collect and discuss available data on the clinical use of approved anticancer agents in AD. Based on the present analysis, the possibility of modifying the AD pathophysiology and clinical course through the use of anticancer agents is increasingly investigated. The results of several randomized controlled trials have already been published and shared with the scientific community [48, 51,52,53,54], while further studies are currently underway and are expected to be completed in the next few years, thus generating additional evidence in the field.

Three out of five published randomized controlled trials, two bexarotene studies [52, 54] and a thalidomide study, [48] did not show any promising results, mainly for reasons related to toxicity and poor CNS penetration. Explorative clinical outcomes in the nilotinib [53] study showed promising results that should be confirmed in larger and longer studies. Masitinib was found to slow down the rate of cognitive decline in AD [51]. It is noteworthy that a larger phase IIb/III study on masitinib has recently been completed on more than seven hundred patients and, according to the statement of AB Science (the industry that developed the drug) [55], the drug met the primary endpoint by significantly improving both cognition and functional abilities. Although masitinib is currently approved for veterinary use, it is also currently under evaluation in humans for the treatment of diverse conditions including malignant melanoma, mastocytosis, multiple myeloma, gastrointestinal and pancreatic cancers, and multiple sclerosis [30].

Drug repurposing may consent to optimize the efforts to develop new treatments for AD by exploring the AD-related effects of agents already approved for other clinical indications [16]. This approach is promising since many approved pharmacological agents have shown AD-relevant effects in animal models. Moreover, it may significantly reduce the times and costs of drug development given that the repurposed drugs have already been tested in terms of safety/tolerability, thus rendering the conduction of further preclinical studies unnecessary [16]. In 2020, 53 clinical trials involving 58 FDA-approved agents acting on multiple therapeutic targets (e.g., neuroinflammation, neuroprotection, neurotransmitter modification) were registered in the ClinicalTrials.gov database, accounting for 39% of the overall AD pipeline [16]. In parallel, since 2019, the number of phase III studies targeting Aβ dropped by 20% [56].

In the last decades, in vitro and animal studies have provided promising evidence supporting the repurposing of anticancer agents for AD [21, 26, 57, 58]. In particular, agents acting as TKIs are attracting special attention. Emerging evidence justifies TKI utilization in AD [26,27,28,29,30,31, 33,34,35,36,37,38,39,40,41]. The inhibition of several kinases has been associated with lower Aβ deposition and tau phosphorylation [26, 57] and hampered amyloidogenic APP processing in AD neurons [58]. RXR agonists have also provided promising preclinical results [42,43,44,45]. Particularly, bexarotene was found to enhance the clearance of soluble Aβ within hours in an ApoE-dependent manner, to inhibit Aβ42 aggregation and reduce neuroinflammation, and to revert cognitive deficits [42,43,44] (Table 2). These promising preclinical results were not confirmed in humans mainly due to poor CNS penetration and deficient cerebrospinal fluid concentrations. Moreover, frequent serious AEs (i.e., elevated triglycerides) were observed [54]. Other anticancer drugs such as thalidomide, lenalidomide, and pexidartinib have been shown to exert neuroprotective effects and attenuate neuroinflammation in experimental models [37,38,39,40, 46, 59]. Masitinib, as well, showed promising anti-neuroinflammatory effects through the modulation of microglia and amyloidosis, or with a synaptoprotective action in relation with mast cell inhibition [30,31,32,33,34]. Overall, targeting several actors implicated in neuroinflammation, together with the reduction of brain amyloid burden, currently represents the primary therapeutic rationale for the repurposing of anticancer drugs in AD [49, 50, 60,61,62].

Promisingly, most of the completed and ongoing clinical studies testing anticancer agents in the continuum of AD are adopting a randomized, placebo-controlled design. Moreover, a sizeable proportion of these protocols is already assessing meaningful clinical outcomes (e.g., cognitive and functional improvement) besides exploring the safety/tolerability profiles of the investigational interventions and their effects on specific biomarkers. These methodological features enhance the clinical relevance of the findings that will emerge from these trials. At the same time, much remains to be done in this field. Moreover, several methodological shortcomings still limit the overall quality of the available evidence. Indeed, most studies are recruiting very small populations of patients, with heterogeneous clinical manifestations (e.g., at different dementia stages); are conducted in single clinical sites; and are at the earlier phases of drug development.

Several limitations of the present study are worth to be acknowledged and discussed. First, besides ClinicalTrials.gov and EudraCT, there are other registries for research protocols (in particular, for those conducted outside the USA and EU). Therefore, our study should not be regarded as an exhaustive overview on the topic. Moreover, such databases only collect a limited amount of data on the methodology of the ongoing studies. In addition, eventual protocol amendments and updates may not be timely reported. A further limitation of the present study is the lack of a quantitative analysis of the reviewed evidence. However, identified studies did not focus on the same research question and adopted different methodological designs (e.g., different disease severity, interventions, comparators, and outcomes), thus hampering the conduction of a metanalysis and quantitative comparisons. On the contrary, the main strength of this study is the choice of merging available evidence coming from both ongoing research protocols and completed clinical trials. This approach has allowed us to provide a comprehensive perspective on the repurposing of anticancer agents for AD. However, to have an exhaustive overview of the efficacy and safety of anticancer drugs currently underway for AD, we encourage the scientific community to disclose trial data, even when results do not seem promising, thereby preventing publication bias.

Conclusions

In conclusion, based on the present overview, the repurposing of anticancer agents for the treatment of AD is triggering growing interest. The promising results emerging from preclinical studies and identified research protocols should be confirmed and extended by larger, adequately designed, and high-quality clinical trials.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Αβ:

Amyloid-beta

AD:

Alzheimer’s disease

ADAS-Cog:

Alzheimer’s Disease Assessment Scale–Cognitive Subscale

ADCS-ADL:

Alzheimer’s Disease Cooperative Study-Activities of Daily Living

AE:

Adverse event

ApoE:

Apoliprotein E

BBB:

Blood-brain barrier

CIBIC-Plus:

Clinician’s Interview-Based Impression of Change Plus Caregiver Input

CDR-SB:

Clinical dementia rating–sum of boxes

CNS:

Central nervous system

CSF:

Cerebrospinal fluid

MCI:

Mild cognitive impairment

MMSE:

Mini Mental State Examination

MoCA:

Montreal Cognitive Assessment

NPI:

The Neuropsychiatric Inventory

SAE:

Serious adverse event

TKI:

Tyrosine kinase inhibitor

References

  1. World Health Organization. Available online: https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death. Accessed 3 Jan 2021

  2. Roe CM, Fitzpatrick AL, Xiong C, et al. Cancer linked to Alzheimer disease but not vascular dementia. Neurology. 2010;74(2):106–12 https://doi.org/10.1212/WNL.0b013e3181c91873.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Driver JA, Beiser A, Au R, et al. Inverse association between cancer and Alzheimer’s disease: results from the Framingham Heart Study. BMJ. 2012;344:e1442 Published 2012 Mar 12. https://doi.org/10.1136/bmj.e1442.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Shafi O. Inverse relationship between Alzheimer’s disease and cancer, and other factors contributing to Alzheimer’s disease: a systematic review. BMC Neurol. 2016; https://doi.org/10.1186/s12883-016-0765-2.

  5. Nudelman KNH, et al. Biological hallmarks of cancer in Alzheimer’s disease. Mol Neurobiol. 2019;56(10):7173–87 https://doi.org/10.1007/s12035-019-1591-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Hanahan D, Weinberg RA. The hallmarks of cancer. Cell. 2000;100(1):57–70 https://doi.org/10.1016/s0092-8674(00)81683-9.

    Article  CAS  PubMed  Google Scholar 

  7. Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144(5):646–74 https://doi.org/10.1016/j.cell.2011.02.013.

    Article  CAS  PubMed  Google Scholar 

  8. Martin L, Latypova X, Wilson CM, et al. Tau protein kinases: involvement in Alzheimer’s disease. Ageing Res Rev. 2013;12(1):289–309 https://doi.org/10.1016/j.arr.2012.06.003.

    Article  CAS  PubMed  Google Scholar 

  9. Diakos CI, et al. Cancer-related inflammation and treatment effectiveness. Lancet Oncol. 2014;15(11):e493–503 https://doi.org/10.1016/S1470-2045(14)70263-3.

    Article  PubMed  Google Scholar 

  10. McGeer PL, McGeer EG. Glial cell reactions in neurodegenerative diseases: pathophysiology and therapeutic interventions. Alzheimer Dis Assoc Disord. 1998;12(Suppl 2):S1–6.

    CAS  PubMed  Google Scholar 

  11. McGeer PL, Rogers J, McGeer EG. Inflammation, antiinflammatory agents, and Alzheimer’s disease: the last 22 years. J Alzheimers Dis. 2016;54(3):853–7 https://doi.org/10.3233/JAD-160488.

    Article  PubMed  Google Scholar 

  12. McGeer PL, McGeer EG. The amyloid cascade-inflammatory hypothesis of Alzheimer disease: implications for therapy. Acta Neuropathol. 2013;126(4):479–97 https://doi.org/10.1007/s00401-013-1177-7.

    Article  CAS  PubMed  Google Scholar 

  13. Ahmad MH, Fatima M, Mondal AC. Influence of microglia and astrocyte activation in the neuroinflammatory pathogenesis of Alzheimer’s disease: rational insights for the therapeutic approaches. J Clin Neurosci. 2019;59:6–11 https://doi.org/10.1016/j.jocn.2018.10.034.

    Article  CAS  PubMed  Google Scholar 

  14. Shadfar S, Hwang CJ, Lim MS, Choi DY, Hong JT. Involvement of inflammation in Alzheimer’s disease pathogenesis and therapeutic potential of anti-inflammatory agents. Arch Pharm Res. 2015;38(12):2106–19 https://doi.org/10.1007/s12272-015-0648-x.

    Article  CAS  PubMed  Google Scholar 

  15. Appleby BS, Nacopoulos D, Milano N, Zhong K, Cummings JL. A review: treatment of Alzheimer’s disease discovered in repurposed agents. Dement Geriatr Cogn Disord. 2013;35(1-2):1–22 https://doi.org/10.1159/00034579.

    Article  CAS  PubMed  Google Scholar 

  16. Bauzon J, Lee G, Cummings J. Repurposed agents in the Alzheimer’s disease drug development pipeline. Alzheimers Res Ther. 2020;12(1):98 Published 2020 Aug 17. https://doi.org/10.1186/s13195-020-00662-x.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Ryu JK, McLarnon JG. Thalidomide inhibition of perturbed vasculature and glial-derived tumor necrosis factor-alpha in an animal model of inflamed Alzheimer’s disease brain. Neurobiol Dis. 2008;29(2):254–66 https://doi.org/10.1016/j.nbd.2007.08.019.

    Article  CAS  PubMed  Google Scholar 

  18. Cramer PE, Cirrito JR, Wesson DW, et al. ApoE-directed therapeutics rapidly clear β-amyloid and reverse deficits in AD mouse models. Science. 2012;335(6075):1503–6 https://doi.org/10.1126/science.1217697.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Frain L, Swanson D, Cho K, et al. Association of cancer and Alzheimer’s disease risk in a national cohort of veterans. Alzheimers Dement. 2017;13(12):1364–70 https://doi.org/10.1016/j.jalz.2017.04.012.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Du XL, Xia R, Hardy D. Relationship between chemotherapy use and cognitive impairments in older women with breast cancer: findings from a large population-based cohort. Am J Clin Oncol. 2010;33(6):533–43 https://doi.org/10.1097/COC.0b013e3181b9cf1b.

    Article  PubMed  Google Scholar 

  21. Advani D, Gupta R, Tripathi R, Sharma S, Ambasta RK, Kumar P. Protective role of anticancer drugs in neurodegenerative disorders: a drug repurposing approach. Neurochem Int. 2020;140:104841 https://doi.org/10.1016/j.neuint.2020.104841.

    Article  CAS  PubMed  Google Scholar 

  22. Higgins JPT, Green S. Cochrane handbook for systematic reviews of interventions version 51.0: The Cochrane Collaboration; 2011. Available:www.cochrane-handbook.org. Accessed 28 Jan 2021

    Google Scholar 

  23. Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ. 2009;339:b2700 Published 2009 Jul 21. https://doi.org/10.1136/bmj.b2700.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Cuadrado-Tejedor M, Garcia-Barroso C, Sanzhez-Arias J, et al. Concomitant histone deacetylase and phosphodiesterase 5 inhibition synergistically prevents the disruption in synaptic plasticity and it reverses cognitive impairment in a mouse model of Alzheimer’s disease. Clin Epigenetics. 2015;7:108 Published 2015 Oct 8. https://doi.org/10.1186/s13148-015-0142-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Richon V. Cancer biology: mechanism of antitumour action of vorinostat (suberoylanilide hydroxamic acid), a novel histone deacetylase inhibitor. Br J Cancer. 2006;95:S2–6 https://doi.org/10.1038/sj.bjc.6603463.

    Article  CAS  PubMed Central  Google Scholar 

  26. Fowler AJ, Hebron M, Missner AA, et al. Multikinase Abl/DDR/Src inhibition produces optimal effects for tyrosine kinase inhibition in neurodegeneration. Drugs R D. 2019;19(2):149–66 https://doi.org/10.1007/s40268-019-0266-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Lonskaya I, Hebron ML, Selby ST, Turner RS, Moussa CE. Nilotinib and bosutinib modulate pre-plaque alterations of blood immune markers and neuro-inflammation in Alzheimer’s disease models. Neuroscience. 2015;304:316–27 https://doi.org/10.1016/j.neuroscience.2015.07.070.

    Article  CAS  PubMed  Google Scholar 

  28. Sheridan GK, Wdowicz A, Pickering M, et al. CX3CL1 is up-regulated in the rat hippocampus during memory-associated synaptic plasticity. Front Cell Neurosci. 2014;8:233 Published 2014 Aug 12. https://doi.org/10.3389/fncel.2014.00233.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Williamson R, Scales T, Clark BR, et al. Rapid tyrosine phosphorylation of neuronal proteins including tau and focal adhesion kinase in response to amyloid-beta peptide exposure: involvement of Src family protein kinases. J Neurosci. 2002;22(1):10–20 https://doi.org/10.1523/JNEUROSCI.22-01-00010.2002.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Folch J, Petrov D, Ettcheto M, et al. Masitinib for the treatment of mild to moderate Alzheimer’s disease. Expert Rev Neurother. 2015;15(6):587–96 https://doi.org/10.1586/14737175.2015.1045419.

    Article  CAS  PubMed  Google Scholar 

  31. Dubreuil P, Letard S, Ciufolini M, et al. Masitinib (AB1010), a potent and selective tyrosine kinase inhibitor targeting KIT. PLoS One. 2009;4(9):e7258 Published 2009 Sep 30. https://doi.org/10.1371/journal.pone.0007258.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Pittoni P, Piconese S, Tripodo C, Colombo MP. Tumor-intrinsic and -extrinsic roles of c-Kit: mast cells as the primary off-target of tyrosine kinase inhibitors. Oncogene. 2011;30(7):757–69 https://doi.org/10.1038/onc.2010.494.

    Article  CAS  PubMed  Google Scholar 

  33. Harcha PA, Garcés P, Arredondo C, Fernández G, Sáez JC, van Zundert B. Mast cell and astrocyte hemichannels and their role in Alzheimer’s disease, ALS, and harmful stress conditions. Int J Mol Sci. 2021;22(4):1924 Published 2021 Feb 15. https://doi.org/10.3390/ijms22041924.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Li T, Martin E, Abada YS, et al. Effects of chronic masitinib treatment in APPswe/PSEN1dE9 transgenic mice modeling Alzheimer’s disease. J Alzheimers Dis. 2020;76(4):1339–45 https://doi.org/10.3233/JAD-200466.

    Article  CAS  PubMed  Google Scholar 

  35. Zhang P, Kishimoto Y, Grammatikakis I, et al. Senolytic therapy alleviates Aβ-associated oligodendrocyte progenitor cell senescence and cognitive deficits in an Alzheimer’s disease model. Nat Neurosci. 2019;22(5):719–28 https://doi.org/10.1038/s41593-019-0372-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Keating GM. Dasatinib: A review in chronic myeloid leukaemia and Ph+ acute lymphoblastic leukaemia. Drugs. 2017;77(1):85–96 https://doi.org/10.1007/s40265-016-0677-x.

    Article  CAS  PubMed  Google Scholar 

  37. Bennett RE, Bryant A, Hu M, Robbins AB, Hopp SC, Hyman BT. Partial reduction of microglia does not affect tau pathology in aged mice. J Neuroinflammation. 2018;15(1):311 Published 2018 Nov 9. https://doi.org/10.1186/s12974-018-1348-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Sosna J, Philipp S, Albay R 3rd, et al. Early long-term administration of the CSF1R inhibitor PLX3397 ablates microglia and reduces accumulation of intraneuronal amyloid, neuritic plaque deposition and pre-fibrillar oligomers in 5XFAD mouse model of Alzheimer’s disease. Mol Neurodegener. 2018;13(1):11 Published 2018 Mar 1. https://doi.org/10.1186/s13024-018-0244-x.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Dagher NN, Najafi AR, Kayala KM, et al. Colony-stimulating factor 1 receptor inhibition prevents microglial plaque association and improves cognition in 3xTg-AD mice. J Neuroinflammation. 2015;12:139 Published 2015 Aug 1. https://doi.org/10.1186/s12974-015-0366-9.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Spangenberg EE, Lee RJ, Najafi AR, et al. Eliminating microglia in Alzheimer’s mice prevents neuronal loss without modulating amyloid-β pathology. Brain. 2016;139(Pt 4):1265–81 https://doi.org/10.1093/brain/aww016.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Qu L, Tang X. Bexarotene: a promising anticancer agent. Cancer Chemother Pharmacol. 2010;65(2):201–5 https://doi.org/10.1007/s00280-009-1140-4 Epub 2009 Sep 24. PMID: 19777233.

    Article  CAS  PubMed  Google Scholar 

  42. Muñoz-Cabrera JM, Sandoval-Hernández AG, Niño A, et al. Bexarotene therapy ameliorates behavioral deficits and induces functional and molecular changes in very-old triple transgenic mice model of Alzheimer’s disease. PLoS One. 2019;14(10):e0223578 Published 2019 Oct 9. https://doi.org/10.1371/journal.pone.0223578.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Casali BT, Reed-Geaghan EG, Landreth GE. Nuclear receptor agonist-driven modification of inflammation and amyloid pathology enhances and sustains cognitive improvements in a mouse model of Alzheimer’s disease. J Neuroinflammation. 2018;15(1):43 Published 2018 Feb 15. https://doi.org/10.1186/s12974-018-1091-y.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  44. Habchi J, Arosio P, Perni M, et al. An anticancer drug suppresses the primary nucleation reaction that initiates the production of the toxic Aβ42 aggregates linked with Alzheimer’s disease. Sci Adv. 2016;2(2):e1501244 Published 2016 Feb 12. https://doi.org/10.1126/sciadv.1501244.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  45. Fukasawa H, Nakagomi M, Yamagata N, et al. Tamibarotene: a candidate retinoid drug for Alzheimer’s disease. Biol Pharm Bull. 2012;35(8):1206–12 https://doi.org/10.1248/bpb.b12-00314.

    Article  CAS  PubMed  Google Scholar 

  46. He P, Cheng X, Staufenbiel M, Li R, Shen Y. Long-term treatment of thalidomide ameliorates amyloid-like pathology through inhibition of β-secretase in a mouse model of Alzheimer’s disease. PLoS One. 2013;8(2):e55091 https://doi.org/10.1371/journal.pone.0055091.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Holstein SA, Suman VJ, McCarthy PL. Update on the role of lenalidomide in patients with multiple myeloma. Ther Adv Hematol. 2018;9(7):175–90 https://doi.org/10.1177/2040620718775629.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Decourt B, Drumm-Gurnee D, Wilson J, et al. Poor safety and tolerability hamper reaching a potentially therapeutic dose in the use of thalidomide for Alzheimer’s disease: results from a double-blind, placebo-controlled trial. Curr Alzheimer Res. 2017;14(4):403–11 https://doi.org/10.2174/1567205014666170117141330.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Guerreiro S, Privat AL, Bressac L, Toulorge D. CD38 in neurodegeneration and neuroinflammation. Cells. 2020;9(2):471 Published 2020 Feb 18. https://doi.org/10.3390/cells9020471.

    Article  CAS  PubMed Central  Google Scholar 

  50. Blacher E, Dadali T, Bespalko A, et al. Alzheimer’s disease pathology is attenuated in a CD38-deficient mouse model. Ann Neurol. 2015;78(1):88–103 https://doi.org/10.1002/ana.24425.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Piette F, Belmin J, Vincent H, et al. Masitinib as an adjunct therapy for mild-to-moderate Alzheimer’s disease: a randomised, placebo-controlled phase 2 trial. Alzheimers Res Ther. 2011;3(2):16 Published 2011 Apr 19. https://doi.org/10.1186/alzrt75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Cummings JL, Zhong K, Kinney JW, et al. Double-blind, placebo-controlled, proof-of-concept trial of bexarotene Xin moderate Alzheimer’s disease. Alzheimers Res Ther. 2016;8:4 Published 2016 Jan 29. https://doi.org/10.1186/s13195-016-0173-2.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Turner RS, Hebron ML, Lawler A, et al. Nilotinib effects on safety, tolerability, and biomarkers in Alzheimer’s disease. Ann Neurol. 2020;88(1):183–94 https://doi.org/10.1002/ana.25775.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Ghosal K, Haag M, Verghese PB, et al. A randomized controlled study to evaluate the effect of bexarotene on amyloid-β and apolipoprotein E metabolism in healthy subjects. Alzheimers Dement (N Y). 2016;2(2):110–20 Published 2016 Jun 17. https://doi.org/10.1016/j.trci.2016.06.001.

    Article  Google Scholar 

  55. GlobeNewswire. Available online: https://www.globenewswire.com/news-release/2020/12/16/2145869/0/en/AB-Science-announces-that-Phase-2B-3-study-evaluating-oral-in-Alzheimer-s-disease-met-its-primary-endpoint.html. Accessed 30 Jan 2021

  56. Huang LK, Chao SP, Hu CJ. Clinical trials of new drugs for Alzheimer disease. J Biomed Sci. 2020;27(1):18 Published 2020 Jan 6. https://doi.org/10.1186/s12929-019-0609-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Schweig JE, Yao H, Beaulieu-Abdelahad D, et al. Alzheimer’s disease pathological lesions activate the spleen tyrosine kinase. Acta Neuropathol Commun. 2017;5(1):69 Published 2017 Sep 6. https://doi.org/10.1186/s40478-017-0472-2.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. Iannuzzi F, Sirabella R, Canu N, Maier TJ, Annunziato L, Matrone C. Fyn tyrosine kinase elicits amyloid precursor protein Tyr682 phosphorylation in neurons from Alzheimer’s disease patients. Cells. 2020;9(8):1807 Published 2020 Jul 30. https://doi.org/10.3390/cells9081807.

    Article  CAS  PubMed Central  Google Scholar 

  59. Decourt B, Wilson J, Ritter A, et al. MCLENA-1: a phase II clinical trial for the assessment of safety, tolerability, and efficacy of lenalidomide in patients with mild cognitive impairment due to Alzheimer’s disease. Open Access J Clin Trials. 2020;12:1–13 https://doi.org/10.2147/oajct.s221914.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Heneka MT, Carson MJ, El Khoury J, et al. Neuroinflammation in Alzheimer’s disease. Lancet Neurol. 2015;14(4):388–405 https://doi.org/10.1016/S1474-4422(15)70016-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Dong Y, Li X, Cheng J, Hou L. Drug development for Alzheimer’s disease: microglia induced neuroinflammation as a target? Int J Mol Sci. 2019;20(3):558 Published 2019 Jan 28. https://doi.org/10.3390/ijms20030558.

    Article  CAS  PubMed Central  Google Scholar 

  62. Hickman SE, Allison EK, El Khoury J. Microglial dysfunction and defective beta-amyloid clearance pathways in aging Alzheimer’s disease mice. J Neurosci. 2008;28(33):8354–60 https://doi.org/10.1523/JNEUROSCI.0616-08.2008.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Conceptualization, N.V. and M.Ca.; methodology, E.L. and A.A.; software, E.L.; validation, E.L., N.V., and M.Ca.; formal analysis, A.A. and E.L.; investigation, A.A., G.R., G.S., I.B., and P.P.; data curation, A.A.; writing and original draft preparation, A.A.; writing, review, and editing, M.Ca., G.R., E.L., P.P., I.B., M.Co., and N.V.; supervision, N.V. and M.Ca. All authors have read and agreed to the published version of the manuscript.

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Ancidoni, A., Bacigalupo, I., Remoli, G. et al. Anticancer drugs repurposed for Alzheimer’s disease: a systematic review. Alz Res Therapy 13, 96 (2021). https://doi.org/10.1186/s13195-021-00831-6

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