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Kumar et al. Cancer Drug Resist 2019;2:161-77 I http://dx.doi.org/10.20517/cdr.2018.27 Page 171

against cisplatin and 5-fluorouracil [130] . MIEN1 showed increased expression in lapatinib-sensitive breast
cancer cells compared to lapatinib-resistant breast cancer cells [131] . Colony growth in soft agar, invasion
into collagen matrix and formation of large acinar structures in three-dimensional cell cultures experiment
demonstrated that increased MIEN1 expression is highly associated with cell transformation including
epithelial to mesenchymal transition and reduced expression of E-cadherin and keratin-8 [132] . This study also
demonstrated that cell transformation was dependent on Syk kinases.

Sphingolipids
Membrane lipids family comprises sphingolipids, a fatty acid derivative of sphingosine which constructs
lipid bilayer structure and maintains their fluidity [133] . Sphingolipids includes sphingosine 1-phosphate
(S1P), ceramide, glucosylceramide (GlcCer) and sphingosine that regulates various biological events such
as proliferation, apoptosis, inflammation, senescence and cell migration in cancer cells [133,134] . Alteration
of sphingolipid metabolism, as well as ceramide accumulation, is reported as a major factor for resistance
development against chemotherapy in cancer cells [135] . Ceramide metabolism vastly produces GlcCer
as a product due to higher glucosylceramide synthase (GCS) enzyme activity in tumor cells [136] . Studies
have demonstrated that GCS overexpression and its activity, positively correlated with ABC transporter
facilitating drug resistance [137,138] . GCS knockdown significantly reduces the MDR1 expression, a gene
that encodes for ABC transporter protein [137,138] . ABC family transporters also transport sphingolipids,
phospholipids, and glucosylceramide across the lipid bilayer.

Sphingosine kinase 1 (SK1) and S1P metabolism regulate drug sensitivity against cancer cells because
overexpression of these molecules provides shelter to cancer cells from drug treatment. A study reported
its increased levels in camptothecin resistant prostate cancer cells [139] . Another in vivo study demonstrated
that SK1 and S1P inflection results in cisplatin sensitivity toward the cellular slime mold Dictyostelium
[141]
discoideum, a powerful non-mammalian model for drug target discovery and resistance [140] . Baran et al.
reported that imbalance between C18-ceramide and S1P is associated with SK1 overexpression and BCR-
ABL upregulation which ultimately leads to imatinib resistance in human chronic myeloid leukemia K562
cells. Downregulation of SK1 levels enhanced the imatinib drug sensitivity and induces the apoptosis in
these cells. Another in vivo study demonstrated that silencing of sphingosine 1 phosphate phosphatase 1
through miR-95, endorses S1P-dependent resistance to radiation in breast/prostate tumors [142] .

Future perspectives
Drug resistance in cancer, either intrinsic or acquired, substantially reduces the efficacy of chemotherapeutic
drugs with poor prognosis in cancer patients. To achieve higher likelihood of therapeutic success, a complete
understanding of the mechanisms underlying chemo-resistance is needed. Recent development of high-
throughput screening technologies has enhanced the identification of intrinsic and extrinsic cellular
pathways that may be targeted to prevent or reverse drug resistance. Other evolving techniques including
open reading frame screens, RNA interference, genome editing, and proteomics analysis of drug resistant cell
lines and tissues will provide important information and identification of novel targets to overcome tumor
drug resistance. In addition, smarter means to deliver anticancer drugs through targeted nanotechnology
approach is being tested. This knowledge will be extremely helpful for the development of precision therapies
based on the prediction of tumor cell response to the currently available chemotherapeutic agents and also
the discovery of novel therapeutic strategies to treat cancer or reverse tumor chemo-resistance. Further
work is required to determine which subset of cancer patients are suitable candidates for a particular multi-
targeted therapy or combination regimen affecting multiple targets. Additional research or modeling is also
needed to identify what combination of targets can be expected to optimize therapy for particular cancer
types. Such new knowledge will be translated into the development of innovative cancer therapeutics to
overcome drug resistance.