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116 The Dynamics of Tumor Microenvironment and Therapeutic Targets
TABLE6.1
Relation Between Potential for Repurposed Drug Candidates and Hallmarks
of Cancer That They Are Signifying to Target*
Hallmark of Cancer Drug Repurposing (Potential Candidates) Therapy
Tumor promoting/enhancing
inammation
NSAIDs, aspirin, dexamethasone,
thalidomide, ruxolitinib, statin,
thiocolchicoside
Combinatorial
Chemoresistance Monensin, chloroquine
Activating invasion and
metastasis
Acetylsalicylic acid, warfarin, berberine,
doxycycline, metformin, niclosamide,
ritonavir
Combinatorial
Evasion of growth suppressors Quinacrine, ritonavir Combinatorial
Induction of angiogenesis Artesunate, itraconazole, diclofenac,
disulram, ibuprofen, becaplermin,
nelnavir, thalidomide
Combinatorial
Resisting programmed cell death Auranon, cardiac glycosides, artemisinin,
disulram, itraconazole, chloroquine,
naproxen
Monotherapy
Enabling replicative immortality Curcumin, genistein Combinatorial
Deregulating cellular metabolism/
reprogramming energy
metabolism
Auranon, metformin, disulram, ritonavir Monotherapy
Genome instability and mutation Spironolactone, mebendazole Combinatorial
Sustainment of proliferative
signals
Diclofenac, prazosin, metformin,
indomethacin, doxycycline, thalidomide,
rapamycin,
Monotherapy
Evasion of immune destruction Infectious disease vaccine Monotherapy
Inducing/accessing vasculature Enalapril, captopril, trandolapril Monotherapy
Senescent cell Dasatinib, setin, quercetin, and navitoclax Combinatorial
Unlocking phenotypic plasticity Paclitaxel, cisplatin, docetaxel, etoposide,
getinib, gemcitabine, methotrexate,
sorafenib, and sunitinib
Combinatorial
Nonmutational epigenetic
reprogramming
Vidaza, Dacogen, Epidaza, Farydak Combinatorial
*(https://www.aacr.org/blog/2022/01/21/new-dimensions-in-cancer-biology-updated-hallmarks-of-
cancer-published/; Ribeiro et al 2023; da Silva Costa et al 2023; Correia et al 2021; Hatem et al 2018;
Zhang et al 2020)
This complex entity also comprises neoplastic cells at different phase of differentia-
tion, including cancer stem cells (CSCs), stromal (like cancer-associated broblasts
(CAFs)) and epithelial cells, various penetrating immune cells, and the extracellular
matrix (ECM) and its noncellular components. Amultifaceted cascade of recipro-
cal signaling pathways among all of these interfaces comprises a dynamic immu-
nosuppressive tumor niche, which stimulates tumor growth and proliferation and
117Drug Repurposing and Tumor Microenvironment in Cancer
opposition to therapy (Jin and Jin 2020). The antitumor immunity generated in the
niche changes the fate of cancer cells. The TME niche differentially varies according
to type and stages of cancer. Therefore, TME components were directly correlated
with the clinical outcome of cancer patients. Thus, it is more relevant to dissect the
TME niche to predict the treatment responses. Consequently, a big revelation is to
procure new therapeutic approaches that are able to manage the versatile crosstalk
among immune cells within the TME niche for competent blocking of immunosup-
pressive pathways. In this phase, this chapter provides an impression of the main
constituents that drive tumor advancement and scrutinizes the versatile crosstalk
among tumor, associated stromal cells, and their end-products playing a vital role in
determining the recruitment, constituents, and role of immune-inltrating cells (Jin
and Jin 2020). Lastly, the major immunotherapeutic strategies that are designed to
target active TME signaling pathways for reversing immunosuppression into antitu-
mor resistance will be dissected (Zhang et al 2020).
Drug repurposing (or drug repositioning, reproling, drug redesigning) is an
approach to sh out new candidate drug (off-patent drugs) from existing licensed
shelved medications (cancer or noncancer) with known targets, rather than from de
novo procurement of new molecules. This approach widened target-specic applica-
bility, high on safety (with regulatory standards) and non-toxicity (known toxicologi-
cal prole), and minimized treatment time, easy availability and low cost (Pantziarka
et al 2014; Bertolini et al 2015) with no clinical trials. As all the clinical trial phases
were already completed, so it has known efcacy, pharmacokinetics, and known
drug-drug interactions (Ishida et al 2016).
6.2 CANCER AND THE TME: AWEB OF INTERACTIONS
Cancer is a complex disease that metastasizes through different lymph nodes, blood
vessels, or transcoelomic seeding, dissected by nerves, and involves the contribution
of the whole living being. Tumor is a concoction of neoplastic and stromal cells form-
ing a complex tissue. The TME is a unique, complex, and dynamic ecosystem. The
TME has a convenience relationship with carcinogenesis but also provides breeding
ground for tumor development and metastasis. The TME has both extracellular and
cellular components. The cellular components include stromal and immune cells,
whereas extracellular components include extracellular matrix and cell secreted pro-
teins (Zhang et al 2020).
Tumor cells coexist with different immune cells (like macrophages, dendritic
cells, mast cells, natural killer cells, polymorphonuclear cells, T and B lympho-
cytes), blood vessels, extracellular matrix lymphatic vessels, the microbiome, other
non-immune cells (like endothelial cells and stromal cells). The stromal cells/non-
immune inammatory cells include mesenchymal stem cells (MSCs), CAFs, vascu-
lar endothelial cells, broblasts, inammatory cells or immune cells, neuroendocrine
cells, smooth muscle cells, pericytes, endothelial cells, and adipocytes.
The surrounding normal cells were reprogrammed and recruited by the TME
for efcient local invasion, tumor progression, rapid proliferation, and metastases to
nally form an organ-like structure. The surrounding normal cells acts as supporting
118 The Dynamics of Tumor Microenvironment and Therapeutic Targets
cells. Cells of the TME were recruited to the primary tumor site to create soluble
paracrine signals for tumor progression and development.
The interactions established by different cells determine the progression and pro-
liferation of the tumor. The different immune cells are invasive and metastatic in
nature and are more fundamental in determining tumor’s fate in the TME. In-house
immune cells of the TME are also intervened or inltrated by a large number of immune
cells, whose organization and composition prospect the clinical outcome of cancer
patients. Thus, different immunological parameters were designed for clinical analy-
sis of cancer patients based on functioning and interaction between immune cells.
But in cancer treatment, the TME is not the only true comprehensive situation. For
effective therapy, other interrelated factors need to be dissected. The TME always
acts as a promoter for cancer progression, not just a bystander.
The knowledge about the complexity of the cancer niche, the dynamic and recip-
rocal interactions between all immune and nonimmune components has continu-
ously evolving and has changed the perspective of tumor in cancer survival, local
invasion, and metastatic innervations. The surrounding microbiota and the nontumor
and tumor cellular components form an integrated model to shape the TME. To
overcome an acidic and hypoxic microenvironment, the TME stimulate angiogenesis
in the ecosystem to restore nutrient and oxygen supply in the niche and to excrete
metabolic waste.
Two main research strategies relate to cancer therapy includes physicochemi-
cal characteristics (like acidic pH, hypoxia, enhanced vascular permeability, and
improper nutrient partitioning) of the TME and the other is the crosstalk between
its components specially the cellular components. The interactions between cel-
lular components are maintained by chemokines and cytokines. Chemokines and
cytokines are related to pro-inammation, tumor progression and enhancement, and
immunotherapy resistance.
All immune cell types create a complex neoplastic immune microenvironment
stuffed with these cells and different molecules (like inhibitory ligands or cytokines)
that they express. Immune cells are diverse, based on cancer type, and their evolu-
tion, growth, and inltration capability to metastasize the cancer tissues depends on
their inherent functions. Molecules secreted/expressed/released by immune cells are
blocked by monoclonal antibodies targeting inhibitory receptors to attain immune
checkpoint blockade in efcacious therapies to treat different advanced cancer.
Immune checkpoint by monoclonal antibodies showed amazing response rates in
several types of hematologic malignancies and solid tumors. Other therapies include
cancer vaccines, adoptive cellular transfer, immune checkpoint inhibitors, and
immune agonists, which are effective for certain patients but remain ineffective for
others due to inherent resistance or quick acquisition of immune resistance.
Therapy response rate depends on proper analysis of the TME. Combination
therapy response or disease-specic novel strategy showed moderate effect in vivo
in comparison to in vitro models. All these indicate a disease-specic resistance
mechanism with its roots down in the TME. Thus, to enhance immunotherapy stra-
tegically, we need to target the TME, not the cancer cells. Drug resistance in cancer
treatment is mediated by tumor-to-tumor communication, direct cell-to-cell interac-
tion, tumor-to-ECM interaction, and tumor-to-stem-cell contact.
119Drug Repurposing and Tumor Microenvironment in Cancer
The accumulation of CAFs in the TME contributes to tumor progression and
development by secreting various cellular factors such as cytokines and interacting
with neuroendocrine cells and immune-inammatory cells to promote angiogenesis.
TGF-β produced from cancer cells activates adjacent CAFs (Meseure et al 2014).
CAFs release several chemokines (CC-chemokine ligand CCL and CXC-chemokine
ligand CXCL) and interleukins (IL-1, IL-6, IL-8, and IL-22), which contribute to
tumor progression.
6.3 CANCER AND TRADITIONAL DRUG
Cancer (or malignant neoplasm) involves abnormal cell growth, invasion, and spread
to other body tissues and thus indicates digression from the coordinated crosstalk
among cells and related organs (Malani 2012; NCI 2020). Cancer is a very common
form of illness and death, including a wide spectrum of stomach, liver, lung, and
bowel cancers. Among females and males, breast and prostate cancers are promi-
nent, respectively (Cancer Research UK 2020).
Cancer is one of leading causes of mortality globally, accounting for almost 10
million deaths in 2020, or approximately one in six deaths (https://www.who.int/
news-room/fact-sheets/detail/cancer). In India, the approximate number of incidence
cases of cancer was found to be 14,61,427 in 2022. The incidence of cases of cancer
is estimated to increase by nearly 12.8 per cent in 2025 as compared to 2020. Nearly
one in nine people in India are likely to develop cancer in his/her life (Sathishkumar
et al 2022). During coronavirus pandemic, within a lag of two to three years, there
was a great negligence in cancer research and treatment. Monotherapy, combina-
tional therapy, and chemotherapy are age-old traditional methods of cancer treat-
ment. To overcome the vast death toll in cancer, modern technology and enhanced
research knowledge were applied in the discovery of new drugs for translational
medical use in clinics. However, drug development and design is much slower than
expected, requiring an average of 13 years of research. For nal production and mar-
keting, it is important to examine the efcacy, toxicity, and pharmacodynamic and
pharmacokinetic proles of drugs used in animal- and cell-based studies. This whole
tedious process of developing a new drug from bench to bedside is quite costly and
time-consuming (Zhang et al 2020; Sobti et al 2023).
CAR-T cells therapy and tumor-inltrating lymphocyte (TIL) therapy are the two
types of T cell transfer therapy (or adoptive cell therapy or immune cell therapy). They
employ the patient’s own immune cells (collected from cancer patients) to attack can-
cer cells (by intravenous injection). In TIL therapy, special lymphocytes are isolated
to recognize tumor cells, then they are reinfused to treat tumors (Zhang et al 2020).
TIL therapy has accomplished good results in melanoma, bile duct cancer, and cervi-
cal squamous cell carcinoma. In many cancers, it is still in the investigational stage.
CAR-T cell therapy uses chimeric antigen receptor (obtained from CAR protein in T
cell) to bind to specic proteins on the cancer cells surface for better attack. CAR-T
cell therapy is mostly used in hematological malignancies (Rosenberg and Restifo
2015; Fesnak et al 2016; June et al 2018; Dudley and Rosenberg 2003; Kalos and
June 2013; Landsberg et al 2012; Gisselbrecht and Van Den Neste 2018; Fraietta et al
2018; Schuster et al 2017). Patient-specic precision medicine based on the patient’s
120 The Dynamics of Tumor Microenvironment and Therapeutic Targets
clinical characteristics can be rationally designed for a better treatment outcome. To
achieve this, focus should be on the drugs’ modus operandi, and its targeted mol-
ecules must be dissected for proper anticancer effect (Malik et al 2022).
The cancer stem cells (CSCs) have a tumorigenic role, is responsible for tumor
progression, metastasis formation, and recurrence and resistance mechanisms
against therapeutic agents. CSCs could be an effectively employed to treat cancer.
As CSCs are heterogeneous in nature, stem-cell-specic biomarkers need to be
researched for proper targeting. The multi-target effect of combinational drugs or
drug models could be planted in the cancer treatment landscape to solve the prob-
lems with traditional drugs or stem cell therapy. Employing conventional anticancer
drugs conjugated with repurposed drugs would create a combination drug model to
increase therapeutic efcacy. Moreover, strategic manipulations of drug–drug inter-
actions need to be carefully evaluated in designing combinational drugs or therapies
(Dou 2021).
On the other hand, the genetic heterogeneity, intratumoral heterogeneity, inter-
patient heterogeneity, drug non-nonresponse (one or more drugs), and partial non-
response among cancer patients can be overcome by powerful pharmacological
approach or well-drafted combination therapies (Palmer and Sorger 2017; Law 1952).
It is true that combination therapies are more effective than monotherapies,
depending on the cancer types. Furthermore, patients may respond to one drug and
remain non-respondent to another. The case may be reversed in another patient. So
patient-specic precision medicine is required. When repurposing a drug, it is very
necessary to understand the genetic background of development of the tumor. Most
of the repurposed drugs are based on the study of DNA damage, carcinogenesis
signaling pathways, apoptosis, and expression of cancer-related proteins. Apart from
this, genetic mechanisms need to be evaluated. Transcriptome analysis, mode of
action of any tumor suppressor genes or oncogenes, up-/downregulation of impor-
tant genes, and dissecting the growth-stimulating signaling pathways streamline the
genetic bias of cancer patients (Kumari et al 2017; Webster 2016; Hu et al 2016;
Rodrigues et al 2022).
6.4 DRUG REPURPOSING
Drug repurposing (DR) is also known as drug re-tasking, drug repositioning, drug
reproling, drug recycling, drug rescuing, drug redirection, and therapeutic switch-
ing. It can be dened as a recognition of new pharmacological formulations from
old, existing, investigational, failed, experimental, discontinued, abandoned, already
marketed, and/or FDA-approved drugs/pro-drugs, and the application of new tech-
nology for developing new drugs for diseases other than the old drug’s pre-assigned
therapeutic use (Rudrapal et al 2020).
Traditional drug discovery process is highly laborious, time-consuming, and
expensive and has an increased risk of failure and toxicity issues. Most of these loop-
holes can be overcome by considerable the momentum gained by drug repurposing,
with an increase in annual revenue and different approaches since its accidental dis-
covery in 1920s (Rudrapal et al 2020). The traditional way of drug discovery engages
121Drug Repurposing and Tumor Microenvironment in Cancer
de novo recognition and characterization of new molecular entities (NME), which
comprise ve stages: discovery and preclinical, safety clinical review, FDA regula-
tions, and post-market FDA safety monitoring. On the other hand, in drug reposition-
ing, there are only four stages: compound identication, acquirement, development,
and post-market FDA safety monitoring. With the availability of huge structural and
biological database, use of in silico techniques, use of structure-based drug design
(SBDD), progression of bioinformatics/cheminformatics tools, and articial intel-
ligence, drug repositioning has appreciably decreased the processing time and labor
to a considerable extent (Rudrapal et al 2020).
Momentarily, decreasing drug intake, increasing drug efux, sequestration of
drugs, and enzymatic metabolism of drugs are processes needed for reduced drug
availability in the cells. Additionally, through apoptosis, DNA mutations, increased
target concentration, and stimulation of compensatory pathways, cancer cells can
inhibit the anticancer effects of the drug (Rodrigues et al 2022). The pharmaco-
kinetic and pharmacodynamic proles of repurposed drugs have already been
thoroughly characterized through extensive studies in their application to previous
diseases or disease states. Therefore, further application of the drug to a new disease
reduces both time and cost. But to specify/identify potential repurposing of a specic
drug, not only in pre-clinical studies but also in in vivo, in vitro, and in silico studies,
needs to be validated by epidemiological studies and clinical observations (Kaushik
et al 2021).
For anticancer therapy, it is imperative to study different targeted signaling path-
ways to determine the anti-neoplastic effects of the candidate drug. But the process
is not always so easy. Some candidate drugs have unknown molecular pathways and
unknown interactions with some cancer hallmarks. This kind of “off-target” effects
of the anticancer drug can result in unanticipated antitumoral effects. The modula-
tion of gene expression (including up- or downregulation of genes) by a candidate
drug for repurposing needs to be studied in cancer-specic ways to identify its mode
of expression for proper therapeutic treatment (Olgen and Kotra 2019).
6.5 THE TME AND DRUG REPURPOSING
Enormous permutation combination of genetic alterations elicits tumorigenesis to
form cancer cells. Cancer therapy mostly revolves around radiotherapy and chemo-
therapy. These two strategies have serious side effects, compromise the patient’s
immune system, and lead consequent therapeutic resistance. Targeting the TME can
be therapeutic for efcient cancer therapy. Stromal cells in the TME is the main con-
tributor of chemoresistance. Targeting the tumor-promoting factors in the TME or
inhibiting signaling pathways hinders cancer development (Yuan et al 2016).
6.6 DRUG REPURPOSING IN CANCER
Cancer is a complex set of disorders with many complications, characterized by
uncontrolled and irregular cell growth, invasiveness, and high clinical burden by
increasing morbidity and mortality (Haberkohn 2007). Drug repurposing in cancer
122 The Dynamics of Tumor Microenvironment and Therapeutic Targets
can lead to low-cost and affordable drugs for other common disorders, such as diabe-
tes, hypercholesterolemia, and hypertension, in oncology treatment modalities. On a
global scale, though the burden of cancer disease is high, the FDA approval for drugs
is declining. FDA regulation also revolves around a tedious preclinical-to-clinical
process, drug identication and optimization, and testing for toxicity, safety, and
efcacy. Drug repurposing can tackle all these drawbacks (Malik et al 2022).
The nonspecic nature of conventional therapies through IV administration causes
a drug to spread to the whole body, affecting both cancer and noncancer cells, which
gradually affects the surrounding microenvironment. Excessive targeting of the TME
also leads to drug resistance as the TME quickly evolves by altering cell–cell signal-
ing. So market-available anticancer drugs mostly lead to multi-drug resistance, have
limited solubility or are hydrophobic, and have low availability and selectivity toward
the TME (Lee et al 2017; Chidambaram et al 2011). Conventional drugs also have
related side effects, like nausea, vomiting, generic pain, and fatigue (Malik et al 2022).
To position a drug for repurposing, it is necessary to collect all clinical data
about the target drug and knowledge on experimentation on animal models at the
preclinical phase. All the biochemical, experimental, systematic examination, and
computational data repository and analysis may be employed. Multiple omics con-
cepts like proteomics, metabolomics, and genomics can be used in drug repurposing.
Data analysis to drug design with molecular modeling, detailed chemical structure
analysis, genotyping, binding assays, dose curve and dose response, drug–target cell
interactions, and drug binding partners are explored (Mahon et al 2022; Nagaraj et al
2018; Luo et al 2017; Palve et al 2021).
Well-known examples of repurposing in cancer therapy are imatinib for gastroin-
testinal stromal tumors, thalidomide for multiple myeloma, and zoledronic acid for
bone metastases (Bertolini 2015). The literature-based approach of the Repurposing
Drugs in Oncology (ReDO) project screens licensed noncancer drugs with recom-
mended anticancer efcacy. In the ReDO database, candidate targeted drugs with at
least one peer-reviewed publication revealing signicant anticancer property have
been recognized. The ReDO database has been made available to access online
(Zhang et al 2020; Pantziarka et al 2018). The primary cause for recurrence, relapse,
and death due to cancer is resistance to conventional chemotherapy. Anticancer drugs
act on the genome, damage the DNA of cancer cells, and consequently inhibit signal
pathways. Resistance leads to dose-limiting side effects. To modulate/ alter the drug
targeted cells; intracellular drug metabolism, efux out mechanism, altered detoxi-
cation mechanisms using drug pumps were imposed by drugs. This alter prolifera-
tion rate of target cell, increase its ability to repair DNA damage, co-opting in the
same TME with altered scenario. This also controls fatty acid synthesis, mitochon-
drial metabolism rate making it less susceptible to apoptosis. Targeted drug changes
the redox metabolism also (Malik et al 2022).
Tumor cells that survive the drug effects persist further to grow into a resistant
clone population, causing severe clinical prognosis or death (Roberts et al 2019).
Apart from drug resistance, intra- and intertumoral heterogeneity among tumor cells
can be reduced by personalized targeted therapy (Malik et al 2022).
The highest tolerated dose administered to patients creates continuous pres-
sure on tumor cells, and those cells that tolerate the pressure turn out to be resistant.
Immunotherapy, new synthetic analogues of existing drugs, combinational drugs,
123Drug Repurposing and Tumor Microenvironment in Cancer
multi-targeting drugs, and curating the TME can overcome the resistance (Sodani et al
2012). Surgery (by excision of the primary affected tumor), radiation therapy, and phar-
macotherapy are the conventional or standard mode of treatment (Correia et al 2021).
In pharmacotherapy, selective killing of the neoplastic cells is done. But to dif-
ferentiate between normal cells and neoplastic cells is quite difcult to achieve. Also,
the growth factors, different growth parameters, sensitivity to drugs, and degree of
activation of signaling pathways may also vary in normal and tumor cells. Apart
from these, risk factors, including age, gender, family history of cancer, obesity,
unsafe alcohol or tobacco use, past radiation exposure, and regular drug abuse, may
cause resistance to drugs. Most of the repurposed drugs were previously validated
successfully in other diseases, as shown in Table6.2.
TABLE6.2
Noncancer Drug Repurposing in Cancer Treatment (Langley et al. 2011;
Sleire et al 2017; Zhang et al 2020; Rudrapal et al 2020; Sobti et al 2023)
Candidate Drug/
Category of
Pharmacology
Type of Cancer (as a New
Indication)
Old Indication
(Disease or disease
State) Development Status
Fluorouracil,
anticancer,
antimetabolite
Breast cancer Cancer Already developed
Digoxin (Lanoxin) Non-small-cell lung cancer
cells
Heart condition Already developed
Metformin,
antidiabetic DM
(type 2)
Breast cancer DM (type 2) Under development
Disulram (Antabuse) Prostate and other cancer Alcoholism Already developed
Nelnavir (acts as an
antiviral agent)
Breast cancer HIV/AIDS Under development
Nitroxoline,
antibacterial
Breast
cancers
UTI Under development
Doxycycline Breast
cancers
Bacterial infections Already developed
Penuridol/pimozide,
antipsychotics
Breast cancer Psychiatric illness Under development
Itraconazole
(Sporanox)
Colon cancer Fungal infections Already developed
Everolimus,
immunosuppressant
Pancreatic
Neuroendocrine
tumors
Immune suppressant Already developed
Leunomide (Lunava) Lung adenocarcinoma,
cervical cancer, and
melanomas
Rheumatism Already developed
Sunitinib, TKI
(anticancer)
Pancreatic and
neuroendocrine
tumors
Imatinib-resistant
GIST, RCC
Already developed
(Continued)
124 The Dynamics of Tumor Microenvironment and Therapeutic Targets
Candidate Drug/
Category of
Pharmacology
Type of Cancer (as a New
Indication)
Old Indication
(Disease or disease
State) Development Status
Lithium (lithium
carbonate)
Colorectal cancer Depression Under development
Isoniazid,
antitubercular
Certain types of
tumors
Tuberculosis Already developed
Orlistat, anti-obesity
agent
Cancer Obesity Already developed
Mebendazole
(Vermox)
Colorectal cancer Worm infection Under development
Retinoic acid Acute leukemia Acne Already developed
Ribavirin, antiviral Leukemias and
lymphomas
RSV (viral infection),
hepatitis C, infections
Under development
Simvastatin,
hypolipidemic
Lung cancer CVDs Already developed
Aspirin (acetylsalicylic
acid)
Lung, colorectal, and breast
cancer
Pain, fever,
inammation
Already developed
Quinacrine Non-small-cell lung cancer Malaria Under development
Arsenic Acute promyelocytic
leukemia
Tuberculosis and
syphilis
Under development
Artesunate (Artex) Leukemia, breast cancer,
gastrointestinal tumors
Malaria Already developed
Auranon (Ridaura) Breast and lung cancer Rheumatoid arthritis Under development
Prazosin Benign prostatic
hyperplasia
Hypertension,
Raynaud disease,
congestive heart
failure
Under development
Metformin,
antidiabetic
Colon cancer, CVDs DM (type 2) Under development
Indomethacin Colorectal cancer Rheumatic disease Under development
Nitroxoline,
antibacterial
Bladder
cancers
UTI Under development
Nitroxoline,
antibacterial
Pancreatic cancers UTI Under development
Rapamycin Acute myeloid leukemia,
drug-resistant chronic
myelogenous leukemia
Preventing kidney
transplant rejection
Under development
Thalidomide, immune
modulator
Multiple myeloma Immunomodulation,
morning sickness
(withdrawn)
Already developed
DM: diabetes mellitus; CVDs: cardiovascular diseases; HIV/AIDS: human immunodeciency virus/
acquired immunodeciency syndrome; GIST: gastrointestinal stromal tumor; UTI: urinary tract infec-
tion; RCC: renal cell carcinoma.
TABLE6.2 (Continued)
Noncancer Drug Repurposing in Cancer Treatment (Langley et al. 2011;
Sleire et al 2017; Zhang et al 2020; Rudrapal et al 2020; Sobti et al 2023)
125Drug Repurposing and Tumor Microenvironment in Cancer
For drug chemo-informatics- or pharmaco-informatics-based repurposing, data min-
ing of the candidate drug followed by high level computational analysis and computa-
tional intelligence is required. Off-target analysis is mostly required for repurposing.
In pharmacological therapy, off-target effects (OTEs), therapeutic mechanism of
action (MoA), mechanisms of action of targeting, and additional targets apart from
the intended one are needed for compounds and drugs employed in drug repurposing
strategies. In combination therapy, OTEs along with systemic MoAs gives the per-
fect partner against cancer. Fishing out the relevant data from the currently available
large datasets on drugs, their applicability in MoAs, and their off-targets and specic
targets helps in narrowing down the available options, to speed up the process of
repurposing. This allows researchers/clinicians to select from just a handful alterna-
tives instead of searching for a few options among thousands (Barratt and Frail 2012;
Hernández-Lemus and Martínez-García 2020; Lamb 2007).
6.7 DISCUSSION
The identication of candidate clinically approved drugs with familiar safety char-
acteristics and known pharmacokinetic indications is the key to drug repurposing.
There is always a dearth of proper medicines/therapies (mono or combinational) for
type-specic (with varied genetic heterogeneity) cancers. To overcome drug resistance,
with effective, precise, and durable cancer cure, it is necessary to move toward the
promising eld of drug repurposing. The repurposing of noncancer drugs as effective
molecular targets adds more dimensions to this eld, from standard treatment to pre-
cision oncology therapy. Individual patients’ specic treatment modalities can be out-
lined as novel treatment strategies. Asynergistic therapeutic effect can be created by
combinational therapy (a permutation of two or three candidate drugs of low potency)
with anticancer agents to minimize side effects and nullify detrimental drug–drug
interactions. Multi-omics approach/analysis, articial intelligence, machine learning
approaches, and multifactorial data analysis of effectiveness of all concerned drugs
may open new vista with signature anticancer molecule. Information from multi-
omics and machine learning can be reimposed in molecular docking of such a drug
for improvement in its efcacy. This will help to streamline the drug–target interac-
tions also. But data extracted from these elds are always limited, and the application
of a drug to another disease always needs new sets of parameters.
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