Identifying clinically relevant drug resistance genes in drug-induced resistant cancer cell lines and post-chemotherapy tissues.

Until recently, few molecular signatures of drug resistance identified in drug-induced resistant cancer cell models can be translated into clinical practice. Here, we defined differentially expressed genes (DEGs) between pre-chemotherapy colorectal cancer (CRC) tissue samples of non-responders and responders for 5-fluorouracil and oxaliplatin-based therapy as clinically relevant drug resistance genes (CRG5-FU/L-OHP). Taking CRG5-FU/L-OHP as reference, we evaluated the clinical relevance of several types of genes derived from HCT116 CRC cells with resistance to 5-fluorouracil and oxaliplatin, respectively. The results revealed that DEGs between parental and resistant cells, when both were treated with the corresponding drug for a certain time, were significantly consistent with the CRG5-FU/L-OHP as well as the DEGs between the post-chemotherapy CRC specimens of responders and non-responders. This study suggests a novel strategy to extract clinically relevant drug resistance genes from both drug-induced resistant cell models and post-chemotherapy cancer tissue specimens.


SUPPLEMENTARY DATA
Two drugs used together is pharmacodynamically synergistic, additive or antagonistic if the therapeutic effect is greater than, equal to, or less than the summed effects of the partner drugs [47]. Drug combinations may also produce pharmacokinetically potentiative or reductive effects such that the therapeutic activity of one drug is enhanced or reduced by another drug [47]. Another type of drug combination is a coalistic combination, in which all of the drugs involved are inactive individually but are active in combination [48]. In this study, we only consider three pharmacodynamical types of drug combinations: synergistic, additive and antagonistic effects.
We define the DEGs between the non-responders and responders of patients treated with drug A and B as CRGs for the combination chemotherapy, denoted as CRG A/B . The DEGs between the non-responders and responders of patients treated with drug A or B alone were defined as CRGs for drug A or CRGs for drug B, denoted as CRG A or CRG B , respectively. If CRG A and CRG B have overlaps, then we define each of the overlapped genes as a synergistic or antagonistic gene if it has the same or opposite deregulation directions (up-regulation or downregulation) in the non-responders compared with the responders) in CRG A and CRG B . Then, we can prove the following conclusions: 1. If a CRG A (CRG B ) is not a CRG B (CRG A ), then it is statistically expected to be detected as a CRG A/B with the same deregulation direction in non-responders compared with responders. 2. For a synergistic gene included in both CRG A and CRG B , it is expected to be included in CRG A/B with the same deregulation direction. 3. For an antagonistic gene, it may or may not be detected as a CRG A/B . If it is also detected as a CRG A/B , then its deregulation direction could be inconsistent with CRG A or CRG B . 4. If the frequency of antagonistic genes in CRG A or CRG B is small, then the consistence score between the CRG A or CRG B and CRG A/B should be significant. 5. The same conclusions can be proven for combination chemotherapy with more than two drugs.
Under the same assumption that the frequency of antagonistic genes is small, we can prove the following conclusion: 6. If two different regimens share one or several drugs, then the overlaps of CRGs for the two different regimens should be the CRGs for the shared drug(s).
Proof. We assume that the non-responders are resistant to all the drugs used together (subtype0) and the responders have three subtypes: sensitive to drug B only(subtype1), sensitive to drug A only(subtype2), and sensitive to both A and B(subtype3). For any of CRG A , denoted as g A , we suppose that expectation of its expression value in subtype i is μ gAi (i = 0,1,2,3). The frequency of subtypes in the non-responder and responder groups for combination chemotherapy is f i (i=0,1,2,3, The four kinds of sample subtypes were displayed in the following table: μ gAi : the expectation of expression value of g A in the non-responder and responder groups(i=0,1,2,3); f i : the frequency of subtypes in the non-responder and responder groups(i=0,1,2,3). According the table above, μ gA0 -μ gA2 and μ gA1 -μ gA3 both represent the difference of g A in the non-responders compared with the responders for drug A, we define Similarly, We further define ∆ A/B (g A ) as the difference of g A in the in the non-responders compared with the responders for combination chemotherapy with drug A and drug B, then, we suppose ∆ A (g A ) > 0, which means g A is up-regulated in the non-responders compared with the responders for drug A.
3. If g A ∈ (CRG A ∩ CRG B ) and ∆ B (g A ) < 0,which means g A is an antagonistic gene, Only when Only when f 2 which represents the sample size of responders who are sensitive to drug A is small enough, then ∆ A/B (g A ) < 0. In fact, accumulated empirical clinical experience showed that cytotoxic drugs given in combination was to achieve additive or synergistic effects [49].
Similarly, the same conclusions can be proven when g A down-regulated in the non-responders compared with the responders for drug A. The mathematical derivations above can be summarized to the following derivations more concisely: G: the whole genes set ∆ X (g): the expection difference of gene g between the sensitive and resistant samples of a drug X.
Similarly,   The number of BD genes (ID genes) of 5-FU overlapped with BD genes (ID genes) of L-OHP; b The consistency score of BD genes (ID genes) of 5-FU and BD genes (ID genes) of L-OHP;  Abbreviations: a ID two-24 genes compared with CRG 5-FU/L-OHP ; b ID two-24 genes compared with ID clinical genes.

5-FU
ZWINT ZW10 interacting kinetochore protein; The encoded protein is involved in kinetochore function and overexpression of ZWINT stimulates cell growth [1].
TYMS thymidylate synthetase; It is a target for 5-FU.High expression of this gene activates 5-FU resistance [2].

PRC1
protein regulator of cytokinesis 1;This gene encodes a protein that is involved in cytokinesis and acts as both tumor suppressors and oncogenes [3].
NDC80 NDC80 kinetochore complex component;This protein is required for proper chromosome segregation,which might be one of the mechanisms of 5-FU action [4,5].
CCNB1 cyclin B1; The protein encoded by this gene is a regulatory protein involved in mitosis,which could be an anti-cancer drug target [6].

BUB1B
BUB1 mitotic checkpoint serine/threonine kinase B; UNG uracil-DNA glycosylase; UNG initiated base excision repair, which could stimulate the development of be related to L-OHP resistance [7]. DLGAP5 discs, large (Drosophila) homolog-associated protein 5; Up-regulation of DLGAP5 contributes to hepatocellular carcinoma cells tumorigenesis by promoting cell proliferation [8].
TSPAN13 tetraspanin 13; The proteins mediate signal transduction events that play a role in the regulation of cell development, activation, growth and motility.
KIF14 kinesin family member 14;KIF14 knockdown clearly enhanced chemosensitivity to docetaxel in breast cancer and this gene played a role in response to cytotoxic chemotherapy [9]. PAIP1 poly(A) binding protein interacting protein 1; FAM171A1 family with sequence similarity 171, member A1; ESRP1 epithelial splicing regulatory protein 1;ESRP1 is re-expressed in the lymph nodes, where carcinoma cells metastasize and colonize [10].
RFC4 replication factor C (activator 1) 4, 37kDa; This inhibition of RFC4 expression correlated with a decrease in cellular proliferation, increased levels of apoptosis and a sensitizing of the cells to the DNA-damaging chemotherapeutic agents [13].

PSAT1
phosphoserine aminotransferase 1; TTK TTK protein kinase; The encoded protein is associated with cell proliferation and essential for chromosome alignment at the centromere during mitosis [14,15].
SLC35A1 solute carrier family 35 (CMP-sialic acid transporter), member A1;SLC35A1 is a member of solute carriers (SLCs) and its overexpression can activate the process of absorption and transport of cell inhibitors [16].
(Continued ) MCM2 minichromosome maintenance complex component 2;The protein encoded by this gene is involved in replication and promotes tumor cell proliferation [14].
ZWINT ZW10 interacting kinetochore protein; The encoded protein is involved in kinetochore function and overexpression of ZWINT stimulates cell growth [1].

PRC1
protein regulator of cytokinesis 1;This gene encodes a protein that is involved in cytokinesis.

PRIM1
primase, DNA, polypeptide 1 (49kDa); RFC4 replication factor C (activator 1) 4, 37kDa; This inhibition of RFC4 expression correlated with a decrease in cellular proliferation, increased levels of apoptosis and a sensitizing of the cells to the DNA-damaging chemotherapeutic agents [13].
UNG uracil-DNA glycosylase; UNG initiated base excision repair, which could stimulate the development of be related to L-OHP resistance [7].
CDKN3 cyclin-dependent kinase inhibitor 3;The gene plays a keyrole in regulating cell division and tumorigenesis [18].