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Analysis of p53 mutation status in human cancer cell lines: A paradigm for cell line cross-contamination


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Cancer cell lines are essential tools used in many areas of biomedical research. Using the last release of the UMD_p53 database (2007) (, we analysed the p53 status of 1,211 cell lines published between 1989 and 2007. p53 mutations in cell lines from various types of cancers display a striking similarity in the distribution of mutations and in the pattern of mutational events compared to tumors, indicating that they are representative of the cells from which they were derived. Analysis of the residual transcriptional activity of p53 mutants identified in cell lines that displayed two different p53 mutations show that there is a high frequency of weak mutations that are paired with more potent mutations suggesting a driver/passenger configuration. Strikingly, we found discrepancies in the p53 status for 23% (88/384) of cell lines, for which the p53 status was established independently in two laboratories. Using the NCI-60 cell line panel as a model widely used in the literature, the p53 status could not be ascertained for 13 cell lines due to a lack of homogeneous data in the literature. Our study clearly confirms that misidentified cell lines are still a silent and neglected danger and that extreme care should be taken as a wrong p53 status could lead to disastrous experimental interpretations. The p53 web site has been updated with new sections describing the p53 status in the majority of cell lines and a special section devoted to cell lines with controversial p53 status.
Content may be subject to copyright. Cancer Biology & Therapy 699
Cancer cell lines are essential tools used in many areas of
biomedical research. Using the last release of the UMD_p53
database (2007) (, we analysed the p53 status
of 1,211 cell lines published between 1989 and 2007. p53 muta-
tions in cell lines from various types of cancers display a striking
similarity in the distribution of mutations and in the pattern of
mutational events compared to tumors, indicating that they are
representative of the cells from which they were derived. Analysis
of the residual transcriptional activity of p53 mutants identified
in cell lines that displayed two different p53 mutations show that
there is a high frequency of weak mutations that are paired with
more potent mutations suggesting a driver/passenger configura-
tion. Strikingly, we found discrepancies in the p53 status for 23%
(88/384) of cell lines, for which the p53 status was established
independently in two laboratories. Using the NCI-60 cell line
panel as a model widely used in the literature, the p53 status could
not be ascertained for 13 cell lines due to a lack of homogeneous
data in the literature. Our study clearly confirms that misidentified
cell lines are still a silent and neglected danger and that extreme
care should be taken as a wrong p53 status could lead to disastrous
experimental interpretations. The p53 web site has been updated
with new sections describing the p53 status in the majority of cell
lines and a special section devoted to cell lines with controversial
p53 status.
Continuous cell lines derived from human tumors are widely
used in laboratory research. They can be used for drug screening
(the NCI-60 panels), for production of various macromolecules, for
modelling human tumors or, most frequently, as biological test tubes
for a large variety of experiments.
To draw valid conclusions from
such experiments, it is essential for cell lines to be clearly characterized
at the molecular level. For a long time, these genetic characterizations
were performed by studies focusing on one gene and the informa-
tion was scattered in the literature. Recently, the Sanger Institute
developed a Catalog Of Somatic Mutations In Cancer (COSMIC)
that gathers information on genetic alterations in human tumor cell
To date, data in the COSMIC cell line database is a mix of
information taken from the literature and in-house sequencing.
Cell line cross-contamination (CLCC) is not a novel problem,
as it was discovered as early as 1974 that one in three cell lines were
contaminated, mostly by HeLa cells.
Despite the tremendous work
conducted by Nelson-Rees et al., this problem is still a silent and
neglected danger”, as a recent study indicates a CLCC of 18% at a
German cell line repository.
CLCC is not trivial, as the use of
wrong cell lines can lead to erroneous conclusions associated with
years of wasted time and effort.
p53 mutation is the most common genetic abnormality found in
human cancer.
In cell lines, loss of p53 activity is usually linked
with several specific landmarks such as defect in growth arrest or
apoptosis after DNA damage and lack of induction of p53-regulated
The p53 status is also a key factor for the sensitivity
to anticancer agents and multiple studies have focused on this
Although the majority of studies found a correlation
between loss of p53 function and p53 alteration, a few publications
report opposite results.
This situation is complicated by the
observation that some mutant p53 proteins expressed in cell lines
have only a partial loss of activity or present a temperature-sensitive
transcriptional activity.
For more than 17 years, we have collected and compiled p53
mutations in human tumors and cell lines.
Although numerous
studies on p53 mutations in human tumors have been published, no
systematic analysis of the p53 status of cell lines is currently avail-
able. In the course of updating the various versions of the UMD
p53 database, we have noticed a number of discrepancies in the p53
status of several cell lines. The situation has recently been worsened,
as these discrepancies have been randomly published in the literature,
a situation that can lead to serious problems of data analysis. Many
drug sensitivity studies are based on the p53 status reported in the
literature without any new genetic analysis.
In the present study, using the UMD-p53 database as a frame-
work, we performed a precise and thorough analysis of p53 status
in 1,211 tumor cell lines. Our analysis shows that p53 mutations in
cell lines from various types of cancers display a striking similarity in
Research Paper
Analysis of p53 mutation status in human cancer cell lines
A paradigm for cell line cross-contamination
Hanna Berglind,
Yudi Pawitan,
Shunsuke Kato,
Chikashi Ishioka
and Thierry Soussi
Karolinska Institute; Department of Oncology-Pathology; Cancer Center Karolinska (CCK); Stockholm, Sweden;
Karolinska Institute; Department of Medical Epidemiology and
Biostatistics; Stockholm, Sweden;
Department of Clinical Oncology; Institute of Development, Aging and Cancer; Tohoku University; Sendai, Japan;
Université Pierre et Marie
Curie-Paris6; Paris, France
Key words: p53 mutations, cancer, human cancer cell lines, NCI-60 panel, cell lines cross contaminations
*Correspondence to: Thierry Soussi; Karolinska Institute; Deptartment of Oncology-
Pathology; Cancer Center Karolinska (CCK); Stockholm SE-171 76 Sweden; Email:
Submitted: 01/25/08; Revised: 02/11/08; Accepted: 02/11/08
Previously published online as a Cancer Biology & Therapy E-publication:
[Cancer Biology & Therapy 7:5, 699-708; May 2008]; ©2008 Landes Bioscience
p53 mutation status in human cancer cell lines
700 Cancer Biology & Therapy 2008; Vol. 7 Issue 5
the distribution of mutations and in the pattern of mutational events
when compared to tumors indicating that they are representative
of the cells from which they were derived. Surprisingly, we found
discrepancies in the p53 status in 23% of cell lines, some of which
are widely used, such as MOLT-4 or CAPAN-1.
Results and Discussion
p53 mutations in cell lines versus tumors. The pattern of p53
mutations can be analysed in two informative ways, either by exam-
ining the distribution of p53 mutations in the p53 protein or by
scoring the various mutational events that lead to these mutations.
Both types of analysis have been very informative when applied
to various types of human tumors.
These studies demonstrate
a link between exposure to various types of carcinogens and the
development of specific cancers. The most striking example is that
of tandem mutations, specifically induced by ultraviolet radia-
tion, which are only observed in skin cancers.
The relationships
between GT transversion and lung cancer in smokers or muta-
tion of codon 249 observed in aflatoxin B1-induced liver cancers
are also very demonstrative.
The distribution of p53 mutations
along the p53 protein is similar in tumors and cell lines, indicating
that there is no bias in the selection of specific mutant p53 during
establishment of a cell culture (Fig. 1A and data not shown). The
only exception concerns colorectal cancer cell lines. p.R175H is one
of the most frequent p53 mutations in tumors, but is very rare in
colorectal cancer cell lines (Suppl. Fig.). This finding is specific for
p.R175H and it is not observed for the other two hot spots at codons
248 and 273. The reason for this bias is not known. Comparison
of the various mutational events in cell lines and tumors has been
performed for all cancers together or for 8 cancer types (Fig. 1A and
B and Suppl. Figs.). As previously observed, the pattern of mutations
differs between various types of cancers, but there is a striking simi-
larity when comparing tumors and cell lines from the same origin.
In colorectal and brain cancer, there is a predominance of GCAT
transition at CpG dinucleotides, whereas in lung cancer or head
and neck SCC, the frequency of GCTA transversion is 30% and
20%, respectively, with only a few transitions at CpG dinucleotides.
This high frequency of transversion in these cancers has been shown
to be associated with tobacco smoking and will not be discussed in
more detail here.
This similarity in the pattern of p53 mutations
in primary tumors and cell lines is a strong argument suggesting that
these p53 mutations did not occur de novo during the establishment
of these cell lines. It also supports the small number of studies that
have found matched p53 mutations in primary tumors that were
used to establish cell lines and confirms that analysis of the spectrum
of mutations in oncogenes or tumor suppressor genes in human cell
lines accurately reflects the situation observed in primary tumors.
Analysis of p53 mutant activity in cell lines. Analysis of p53
mutations in human tumors has led to the discovery that at least
5% to 10% of published p53 mutations could be due to PCR or
sequencing artefacts.
However, these mutations are not randomly
distributed among the 2,500 publications reporting p53 mutations.
A meta-analysis identified about 30 publications (1,600 p53 muta-
tions) with a high concentration of unusual p53 mutations that shared
the following properties: (i) multiple p53 mutations in the same
tumor (3 to 14); (ii) a high frequency of synonymous mutations; (iii)
a low frequency of mutations at hot spot codons; (iv) most of these
mutations retained either partial or total transactivational activity.
The vast majority of these studies were associated with the use of
nested PCR for amplification and analysis of the p53 gene. Analysis
of p53 mutations in cell lines provides several advantages over anal-
ysis of tumors to minimize artefactual data: (i) DNA extracted from
cell lines is available in large quantities. Analysis requires neither
nested PCR nor excessive numbers of PCR cycles and can be easily
repeated; (ii) The high quality of the DNA avoids PCR problems
associated with DNA extracted from paraffin-embedded tissue; (iii)
DNA is not contaminated by normal DNA from stroma or cells or
infiltrating lymphocytes.
The UMD p53 mutation database includes functional infor-
mation about the majority of p53 missense mutants, as originally
published by Kato et al.,
(see also material and methods).
Quantitative data concerning the transcriptional activity of each
missense p53 mutation has been extremely useful to classify and
analyse p53 mutations in the p53 database.
The mean and
95% confidence interval (CI) of the remaining activity of all mutant
p53 proteins found in cell lines or in tumors was calculated by using
the activity measured on the p21WAF1 promoter (similar results
were obtained with the activity measured on seven other promoters
of transcription, data not shown). The analysis shows that the mean
activity was situated between -1 and -1.2. This value corresponds to a
residual transcriptional activity of about 10% compared to wild-type
p53. The narrower 95% CI in tumors compared to cell lines is due
to the greater number of tumors used in the analysis (Fig. 2A). In the
majority of cancers, residual p53 activity was lower in cell lines than
in tumors, but this difference was only marginally significant in head
and neck, breast and SCLC, p = 0.03). On the other hand, residual
p53 activity has a wider distribution in tumors compared to cell lines
(variance analysis, Fig. 2B). A large number of mutant p53 retain
wild-type activity in tumors, but this feature is rarely observed in cell
lines. This difference was highly significant for all cancer types (p <
0.0001) except for brain cancers and haematological malignancies.
Two non-exclusive explanations can be proposed for this difference
between tumors and cell lines. First, it is possible that only tumors
with fully inactivated p53 are preferentially selected to establish cell
lines. This hypothesis could also explain why the frequency of p53
mutations is always higher in cell lines than in tumors. It is also
possible that this profile of p53 inactivation in cell lines is more
representative of the true pattern of p53 inactivation and that the
tumor p53 database contains passenger mutations and/or artefactual
mutations with partial or fully active p53.
During the course of these analyses, we also observed that 82 cell
lines displayed two p53 missenses mutations. Preliminary observa-
tions suggested that the two mutations may not have the same
importance and that only one mutation was the driving force selected
during transformation.
In order to obtain more information, clus-
tering analysis was performed on cell lines with either single (SM
cell lines) or double mutations (DM cell lines). Three clusters were
obtained for the two populations, corresponding to mutant p53 with
wild-type activity (cluster I), intermediate residual activity (cluster
II) or no activity (cluster III) (Table 1). The number of mutants in
clusters I and II was significantly higher in DM cell lines than in SM
cell lines, whereas mutations with total loss of activity were more
frequent in SM cell lines (p < 0.0001, Table 1). Mutations in DM
cell lines were further analysed to determine how paired mutations
p53 mutation status in human cancer cell lines Cancer Biology & Therapy 701
Figure 1. Mutation spectrum in tumours and cell lines: (A) Mutational events (left) and distribution of mutations (right) in all tumours (upper part) and cell lines
(lower part). Data were obtained from the UMD p53 database, 2007_R1 release (http://p53/free/fr). (B) mutational events in tumours versus cell lines in
various types of cancer. A similar pattern of mutational events is observed for other cancers (melanoma, ovarian carcinoma, oesophageal carcinoma or
pancreatic carcinoma, data not shown). Transitions at CpG dinucleotides are shown in red.
p53 mutation status in human cancer cell lines
702 Cancer Biology & Therapy 2008; Vol. 7 Issue 5
(two mutations in a single cell line) were associated (Table 2). Only
one of the 41 cell lines presented two mutations in cluster I with wt
activity for the two p53 mutant alleles. This choriocarcinoma cell
line (NUC-1) displays two unusual p53 mutations at codons 17 and
24 that have never been observed in any other cell lines or tumors.
Among the 11 remaining mutations in cluster I, three were paired
with mutations in cluster II and 8 were paired with mutations in
cluster III. Among the 19 mutations in cluster II, two were paired
with a mutation of the same class, 3 with class I mutations and 12
with class III mutations. The majority (30) of the 50 mutations in
cluster III were paired with a mutation of the same class and 12 were
paired with class II mutations (Table 2).
Double mutations can occur in two configurations, either on the
same allele (DMS) or on two different alleles (DMD). Unfortunately,
in the majority of cases, this status is unknown (DMU). In the p53
mutation database based on tumors, the majority of DM with a
known configuration are DMD (about 90%). No cell lines with two
missense mutations in the same allele have been reported and only 10
cell lines with mutations on two different alleles have been reported.
All of these cell lines expressed one class III mutation associated with
either another class III mutation (6), or class II (3) or class I (1)
Altogether, our results indicate that: (i) there is a higher frequency
of weak mutations in DM than in SM mutations and (ii) the
majority of these weak mutations are paired with a more potent
mutation. This suggests that the two mutants do not have the same
contribution to the transforming process. Whether or not these weak
mutations are passenger mutations associated with a driving muta-
tion or true mutations associated with selection of the transforming
phenotype is an unresolved question. One of the main problems
associated with p53 mutations is the possible dominant negative
activity of mutant p53 via hetero-oligomerization making it very
difficult to reach any definitive conclusions concerning weak p53
mutations. Weakening of the second allele could possibly accentuate
the dominant negative activity of p53.
p53 status in human tumor cell lines. The NCI-60 panel is a
good example of a series of cell lines that are widely used for both
basic research and drug discovery.
This panel originally contained
60 cell lines from nine histological origins (Table 3). Several obser-
vations unrelated to p53 status revealed that some cell lines were
either mixed up or were derived from the same donor (Table 3).
At least 100 studies have analysed the p53 status of a subset of the
panel and in 1997, O’Connor et al., reported the p53 status of the
entire NCI-60 panel.
This paper has been used as a reference for
10 years despite discrepancies with other data in the literature. A
second analysis of the entire NCI-60 panel was performed in 2006
and the results are fairly heterogeneous compared to the 1997 study
(Table 3). Inspection of the two studies leads to the detection of 19
apparent differences (Table 3). Three differences were due to typo-
graphical errors in the 1997 report (RPMI-8226, SK-MEL-28 and
Hs-578-T). A more careful examination of four other discrepancies
reveals that they are due to a problem of nomenclature associated
with a different mutation screening strategy. In the 1997 paper, p53
mutations were analysed by cDNA sequencing, while the 2007 anal-
ysis was performed using genomic DNA as starting material. One
of the disadvantages of RNA-based analysis is that it is impossible
to infer whether deletions found in the cDNA are due to splicing
mutations or intragenic deletions in the gene. On the other hand, it
is always difficult to predict the consequence of mutations found in
intron or splice junctions after genomic sequencing. Both methods
are complementary and may be necessary to ensure an accurate
genetic status.
In HOP-62, RNA-based analysis detected an insertion between
codon 212–225 but no information about the insertion sequence
was available. Codon 225 is at the boundary of exon 6 and intron 6
suggesting a splicing defect, as analysis at the genomic level confirms
the presence of a splice mutation in the acceptor signal of exon 6
(Table 3).
In OVCAR-8, the 126–132 deletion detected by the RNA-based
assay concerns the first six residues of exon 5. Genomic analysis
described a mutation in the acceptor site of exon 5 and a splicing
defect leading to a shift of the normal donor site of exon 5 that
skips 18 nucleotides (6 aa residues) in exon 5. Examination of the
DNA sequence at codon 132 reveals an AG dinucleotide sequence
preceded by a pyrimidine tract similar to those found in the splice
donor sequence. The same situation is observed for NCI/ADR-RES
Figure 2. Analysis of the residual p53 activity of mutant p53 in tumors and
cell lines. (A) Points, mean p53 activity as measured by transactivation with
the p21WAF1 promoter; bars, 95% CI. A similar distribution was observed
with other p53 response genes (data not shown). The y-axis corresponds
to p53 transactivation activity, with a value of -1.5 for the negative control
and 2.5 for wild-type p53. (B) Variance of the p21WAF1 promoter activity
in tumors and cell lines. CRC, colorectal carcinoma; NSCLC, non-small cell
lung cancer. Data from cell lines and tumors are displayed in black and red
p53 mutation status in human cancer cell lines Cancer Biology & Therapy 703
that has been recently shown to be an ovarian carcinoma cell line
originating from the same patient as OVCAR-8.
In EKVX, the deletion of codon 187 to 224 detected on
RNA-based analysis corresponds exactly to the deletion of the entire
exon 6, a strong argument for a splicing defect. Genomic analysis
did not reveal a splicing defect but a tandem mutation at codons
203 and 204 in exon 6 (Table 3). If the two cell lines analysed were
really EKVX, this result suggests that a mutation at either codon 203
and/or 204 could affect p53 gene splicing. This observation is not
surprising, as it is now well known that exons contain exonic splicing
enhancers (ESE) that regulate either alternative splicing or normal
These ESE are recognized by the SR proteins that regulate
the various splicing events. Mutations in ESE have been identified
in numerous genes including APC or NF1.
Exonic mutations
that can change p53 splicing have also been described.
together, the contradictions noted in the p53 status of the four cell
lines, HOP-62, OVCAR-8, NCI/ADR-RES and certainly EKVX are
only due to the different strategies used for their analysis and a lack of
homogeneity in the nomenclature used to report p53 mutations. The
problem of the nomenclature of p53 mutations as well as other gene
defects is a recurrent problem in publications.
Despite numerous
recommendations, the description of p53 mutations in the litera-
ture is highly heterogeneous and can reach a high degree of fantasy
with tables that are either totally non-informative or with so many
typographical errors that they cannot be interpreted. In a recent
survey, the editors of 80 journals with frequent publications of p53
mutations were contacted in order to stress this problem and define
certain guidelines for the publication of p53 mutations (Soussi T,
Unpublished). Unfortunately, this survey was a complete failure with
less than 10% of replies and no change in the trends of reporting
accurate p53 mutations. In fact, the number of typographical errors
or incomprehensible mutations has increased over the last five years
(Soussi T, unpublished observations).
After eliminating typographical errors and possible splice muta-
tions, the p53 status of 15 cell lines was different between the
two studies. Using the UMD p53 database and the literature, we
checked for other publications that have analysed the p53 status of
these cell lines. For two cell lines, CCRF-CEM and HL-60, suffi-
ciently concordant publications are available to define a consensus
concerning the p53 status (Table 3). For 13 cell lines, analysis of the
literature revealed a very heterogeneous situation and no consensus
could be reached (Table 3, Inconclusive). Cell lines such as MOLT-4
or NCI-H226 represent an extreme situation, as multiple publica-
tions do not show any common p53 mutations. For other cell lines
such as DU-145, which have been shown to display two different
p53 mutations in two different alleles (p.V274F and p.P223L), the
ambiguity concerns the fact that several authors have detected only
one of the two mutations, either p.V274F or p.P223L. It is therefore
possible that during long-term cell culture, one of the two mutant
p53 alleles is lost, as no selection pressure is exerted on cell growth.
A similar situation is observed for other cell lines that do not
belong to the NCI-60 panel, but with many discrepancies (Table 4
and Suppl. Table S1, see also p53 website). In many cell lines, the
p53 status has been analysed in only one or two reports and the
information is subsequently reproduced in the literature. This is a
very dangerous situation as it could lead to erroneous phenotype-
genotype correlations in various types of studies. The pancreatic
carcinoma cell line CAPAN-2 is a good example of the problems
raised by erroneous phenotype. This cell line has been described as
either wt, mutated (p.R273H) or p53 null (Table 4 and reference
within). A Pubmed literature search indicates that all three pheno-
types are used in various studies.
The p53-null” status is used in different ways in the literature.
The two most common meanings are a cell line with a documented
p53 gene deletion (both alleles) or a cell line with a p53 mutation.
We have also observed more “unusual” situations in which this status
is only based on p53 expression (RNA or protein). Unfortunately,
this type of information diffuses rapidly in the literature without any
verification of the original publication. The p53 status of the two cell
lines SK-OV-3 (Ovarian cancer) and FRO (anaplastic thyroid carci-
noma cell line) are a good example of this ambiguity. In the majority
of publications, the p53 status of these two cell line is stated as p53
null”. In fact, close examination of the original manuscript shows
that the p53 gene in SK-OV-3 is not deleted and did not sustain
any gross rearrangement but neither p53 RNA or protein are found.
In these publications, no p53 mutations were found but the recent
analysis performed at the Sanger Institute detected a deletion of a
single nucleotide at position 267 (codon 90).
It is therefore possible
that nonsense-mediated mRNA decay (NMD) eliminates p53 aber-
rant mRNA. NMD has been observed in the human leukaemia cell
line K562 where p53 is also inactivated via a 1 base pair insertion
at nucleotide 136. For the FRO cell line, the original reference for
the analysis of the p53 gene status is always correctly quoted, but a
closer look at this original paper demonstrates a marked decrease of
p53 RNA in the cell but no mutation was detected by sequencing
exons 5 to 8. Either a mutation is situated outside this region leading
to a decrease of RNA expression (frameshift mutation associated with
Nonsense-Mediated mRNA Decay) or the altered p53 expression is
due to another mechanism. Because the whole p53 gene is present,
it is incorrect to define SK-OV-3 or FRO cell lines as p53 null”, as
Table 1 Cluster analysis of p53 mutation activity
Cluster I (wt activity) 27 (3.4%) 13 (15.9%)
Cluster II (low acitivity) 73 (9.3%) 19 (23.2%)
Cluster III (no activity) 687 (87.5%) 50 (61.0%)
Total 787 (100%) 82 (100%)
The table entries are the number (and %) of mutants classified into the three clusters based on k-means
clustering of the promoter activities of p53 target genes. There are significantly more cluster-I and cluster-II
mutations among the double mutations (DM) than among the single mutations (SM) (p= 2e - 10 using
the chi-square test).
Table 2 Discordance table of class assignment of the 82
DM mutations (from 41 pairs)
Cluster I Cluster II Cluster III
Cluster I (wt activity) 1 3 8
Cluster II (low acitivity) 0 2 9
Cluster III (no activity) 2 3 15
Majority of the weak mutations (cluster I and cluster II) are paired with strong mutations (cluster III).
p53 mutation status in human cancer cell lines
704 Cancer Biology & Therapy 2008; Vol. 7 Issue 5
in the case of H1299 or Saos-2 cell lines in which the p53 gene is
entirely deleted. These cell lines are commonly used as recipients to
reintroduce either wild-type of mutant p53. Whether the presence
of an endogenous p53 gene which is still transcriptionally active
in the SK-OV-3 or FRO cell could interfere with this reconstitu-
tion experiment is not known, but should be carefully considered
before conducting this type of experiment. The recent finding of
p53 isoforms that could be expressed by alternative splicing may
also increase the complexity of this problem, as the various delta133
isoforms could be theoretically expressed in this cell line.
Another reason why p53-null” should be used cautiously to describe
cell lines that express mutant p53 is the observation that p53 mutations
are fairly heterogeneous in terms of loss of function and several cell
lines display a normal or partial p53 response. Finally, there is now
ample evidence that some mutant p53 behave as dominant oncogenes
with a gain of function activity. We therefore believe that the p53 null”
status should be used only for cell lines that are totally devoid of p53
gene. Any other situation should be referred to as mutant p53”.
The UMD_p53 database (2007_R1 release) includes p53 muta-
tions in 1,211 cell lines: 827 of these mutations have only been
described once, preventing any verification. A discrepancy was
detected in 88 of the remaining 384 cell lines (23%), in line with
the study by Macleod et al., who showed that 18% of cell lines in
the DSMZ-German Collection of Microorganisms and cell Cultures
Table 3 p53 status in the NCI-60 panel cell lines
p53 mutation status in human cancer cell lines Cancer Biology & Therapy 705
were cross-contaminated.
The p53 status in various cell lines is a
paradigm for CLCC. (i) p53 mutation is sufficiently diverse to allow
comparison of various cell lines. Statuses of other genes with fewer
mutation hot spots (Ha-ras) or a lower frequency of mutations are not
as useful. (ii) Due to its importance in cell phenotype, p53 status has
been analysed in more than 1,200 cell lines. Although p53 mutation
Mutations as reported in the 2007_R1 of the UMD p53 mutation database. The description of the mutations have been left as originally published by the authors;
Mutations described by Ikediobi et al.,
A mutation
consensus was defined for cell lines using the following rules: (i) at least two independent studies reporting sequencing and identifying the same mutation without any contradictory reports; (ii) at least three independent
studies reporting sequencing and identifying the same mutation and one fourth contradictory report. All other possibilities were not considered to be consensual and have been assigned as uncertain. The nomenclature
for TP53 mutation uses either the cDNA (RefSeqNM_000546.2) or the protein (RefSeq NP 000537) as reference: For numbering, +1 is A of the ATG initiation codon in the correct RefSeq (NM_000546.2). Mutations are
described using the international nomenclature
Mutation found independently by multiple authors. Only the first publication is shown;
HL 60(TB) was used for the analysis, but
it is reported to have a p53 deletion similar to HL60;
The status of MOLT-4 is highly heterogeneous in the literature. The report of a wt status could be due to the fact that only exons 5 to 8 (residues 126–306) were
screened in several publications;
Typographical error in the publication;
it is not clear whether these authors checked the p53 status of the cell line or report the mutation described by O’ Connor et al.;
This cell line
has been reported to be null for p53 RNA or protein. Whether this is due to a small DNA rearrangement or RNA-mediated decay associated with a frameshift mutation is unknown.
Table 3 p53 status in the NCI-60 panel cell lines (continued)
p53 mutation status in human cancer cell lines
706 Cancer Biology & Therapy 2008; Vol. 7 Issue 5
analysis cannot replace DNA fingerprinting, our finding is a strong
argument to suggest that CLCC should not be ignored. We are also
very concerned by the observation that the p53 status based on a cell
line (either correct or false) can be reproduced from a single publica-
tion in the literature without any subsequent confirmation. Finally,
we have also noticed a marked heterogeneity in the labelling of cell
lines, a problem that can also lead to confusion between mislabelled
cell lines with similar names.
CLCC includes several situations: (i)
cross-contamination between two cell lines (the best example being
HeLa cells); (ii) cell lines with an incorrect origin (such as the KB
cell line often wrongly described as an oral cancer when it is actually
a cervical cancer); and (iii) cell lines that have been contaminated
during manipulation. We believe that the problem identified in the
present analysis is predominantly related to confusion or incorrect
labelling of cell lines. Although, the material and methods sections
of published articles usually state that cell lines were derived from
cell banks such as ATCC or DMSZ, it is well known that many cell
lines have been exchanged between research groups, a situation that
increases the probability of CLCC. These problems have already been
extensively discussed over the past year, but seem to be ignored by the
scientific community. We strongly encourage all scientists to comply
with the various recently published guidelines for correct handling of
cell lines.
The p53 status in cell lines is now available at the p53 web site
A specific section is devoted to cell lines with a controversial p53
Table 4 Cell lines with controversial p53 mutations
*References correspond to studies in which the p53 gene status was analysed experimentally and not deduced from other reports in the literature.
p53 mutation status in human cancer cell lines Cancer Biology & Therapy 707
status. We invite all scientists to update these tables with their own
findings so that a consensus concerning the p53 status of each cell
line can be reached. Finally, we strongly encourage those involved in
studies dealing with p53 (or other p53 family members) to regularly
check the p53 status of their cell lines.
Material and Methods
Analysis of the biological activity of mutant p53 proteins. Data
analysis. The p53 database used for this study contains 21,717
mutations derived from 1,992 publications (UMD p53 database
(htpp://, 2007_R1 release released in January 2007).
This release contains functional data for the majority of missense
p53 mutants. Mutant p53 activity has been described previously.
Briefly, 2,314 haploid yeast transformants containing p53 muta-
tions and a GFP-reporter plasmid have been constructed. Mutant
p53 activity was tested by measuring the fluorescent intensity of
GFP that is controlled by the p21WAF1 promoter sequence of the
plasmid after 3 days of growth at 37°C. For functional analysis,
frameshift and nonsense mutations were also excluded, as their
biological significance has not been clearly established (see text for
more information). The mean and 95% Confidence Interval (CI)
of the biological activity of all mutants was calculated by using the
transactivational activity measured on the p21WAF1 promoter.
Similar results were obtained with the activity measured on 7 other
promoters of transcription (data not shown).
Statistical analysis. To identify the distinct levels of p53 residual
activities among the mutants we used the k-means clustering,
aim is to partition the data into 3 groups such that the sum of squares
from each mutant to the assigned cluster centres is minimized. Three
clusters were chosen to represent mutants with no, low and wild-
type activity levels. The analysis was based on the measurements
of promoter activities of 8 p53 target genes, including p21WAF1,
MDM2, BAX, v14-3-3-σ, AIP, GADD45, NOXA and p53R2.
We are grateful to B. Zhivotovsky and B. Joseph for reading
this manuscript. This work is supported by Cancerföreningen i
Stockholm and the Swedish Research Council (VR).
Supplementary materials can be found at:
1. Monks A, Scudiero D, Skehan P, Shoemaker R, Paull K, Vistica D, Hose C, Langley J,
Cronise P, Vaigro Wolff A, et al. Feasibility of a high-flux anticancer drug screen using a
diverse panel of cultured human tumor cell lines. J Natl Cancer Inst 1991; 83:757-66.
2. Forbes S, Clements J, Dawson E, Bamford S, Webb T, Dogan A, Flanagan A, Teague J,
Wooster R, Futreal PA, Stratton MR. COSMIC 2005. Br J Cancer 2006; 94:318-22.
3. Ikediobi ON, Davies H, Bignell G, Edkins S, Stevens C, O’Meara S, Santarius T, Avis T,
Barthorpe S, Brackenbury L, Buck G, Butler A, Clements J, Cole J, Dicks E, Forbes S, Gray K,
Halliday K, Harrison R, Hills K, Hinton J, Hunter C, Jenkinson A, Jones D, Kosmidou V,
Lugg R, Menzies A, Mironenko T, Parker A, Perry J, Raine K, Richardson D, Shepherd R,
Small A, Smith R, Solomon H, Stephens P, Teague J, Tofts C, Varian J, Webb T, West S,
Widaa S, Yates A, Reinhold W, Weinstein JN, Stratton MR, Futreal PA, Wooster R.
Mutation analysis of 24 known cancer genes in the NCI-60 cell line set. Mol Cancer Ther
2006; 5:2606-12.
4. Nelson Rees WA, Daniels DW, Flandermeyer RR. Cross-contamination of cells in culture.
Science 1981; 212:446-52.
5. Chatterjee R. Cell biology. When 60 lines dont add up. Science 2007; 315:929.
6. O’Brien, SJ. Cell culture forensics. Proc Natl Acad Sci USA 2001; 98:7656-8.
7. Markovic O, Markovic N. Cell cross-contamination in cell cultures: the silent and neglected
danger. In Vitro Cell Dev Biol Anim 1998; 34:1-8.
8. MacLeod RA, Dirks WG, Matsuo Y, Kaufmann M, Milch H, Drexler HG. Widespread
intraspecies cross-contamination of human tumor cell lines arising at source. Int J Cancer
1999; 83:555-63.
9. Donzelli M, Bernardi R, Negri C, Prosperi E, Padovan L, Lavialle C, Brison O, Scovassi AI.
Apoptosis-prone phenotype of human colon carcinoma cells with a high level amplification
of the c-myc gene. Oncogene 1999; 18:439-48.
10. Liscovitch M, Ravid D. A case study in misidentification of cancer cell lines: MCF-7/AdrR
cells (re-designated NCI/ADR-RES) are derived from OVCAR-8 human ovarian carcinoma
cells. Cancer Lett 2007; 245:350-2.
11. Caron de Fromentel C, Nardeux PC, Soussi T, Lavialle C, Estrade S, Carloni G,
Chandrasekaran K, Cassingena R. Epithelial HBL-100 cell line derived from milk of
an apparently healthy woman harbours SV40 genetic information. Exp Cell Res 1985;
12. Soussi T, Beroud C. Assessing TP53 status in human tumors to evaluate clinical outcome.
Nat Rev Cancer 2001; 1:233-40.
13. Oren M. Decision making by p53: life, death and cancer. Cell Death Differ 2003;
14. Harris SL, Levine AJ. The p53 pathway: positive and negative feedback loops. Oncogene
2005; 24:2899-908.
15. El Deiry WS. The role of p53 in chemosensitivity and radiosensitivity. Oncogene 2003;
16. O’Connor PM, Jackman J, Bae I, Myers TG, Fan S, Mutoh M, Scudiero DA, Monks A,
Sausville EA, Weinstein JN, Friend S, Fornace AJJ, Kohn KW. Characterization of the
p53 tumor suppressor pathway in cell lines of the National Cancer Institute anticancer
drug screen and correlations with the growth-inhibitory potency of 123 anticancer agents.
Cancer Res 1997; 57:4285-300.
17. Shi LM, Myers TG, Fan Y, O’Connor PM, Paull KD, Friend SH, Weinstein JN. Mining
the National Cancer Institute Anticancer Drug Discovery Database: cluster analysis of
ellipticine analogs with p53-inverse and central nervous system-selective patterns of activity.
Mol Pharmacol 1998; 53:241-51.
18. Brachman DG, Beckett M, Graves D, Haraf D, Vokes E, Weichselbaum RR. p53 mutation
does not correlate with radiosensitivity in 24 head and neck cancer cell lines. Cancer Res
1993; 53:3667-9.
19. Shiraishi K, Kato S, Han SY, Liu W, Otsuka K, Sakayori M, Ishida T, Takeda M, Kanamaru R,
Ohuchi N, Ishioka C. Isolation of temperature-sensitive p53 mutations from a comprehen-
sive missense mutation library. J Biol Chem 2004; 279:348-55.
20. Caron de Fromentel C, Soussi T. TP53 tumor suppressor gene: a model for investigating
human mutagenesis. Genes Chromosomes Cancer 1992; 4:1-15.
21. Soussi T, Ishioka C, Claustres M, Beroud C. Locus-specific mutation databases: pitfalls and
good practice based on the p53 experience. Nat Rev Cancer 2006; 6:83-90.
22. Soussi T, Kato S, Levy PP, Ishioka C. Reassessment of the TP53 mutation database in
human disease by data mining with a library of TP53 missense mutations. Hum Mutat
2005; 25:6-17.
23. Kato S, Han SY, Liu W, Otsuka K, Shibata H, Kanamaru R, Ishioka C. Understanding the
function-structure and function-mutation relationships of p53 tumor suppressor protein by
high-resolution missense mutation analysis. Proc Natl Acad Sci USA 2003; 100:8424-9.
24. Hartigan J, Wong M. A K-means clustering algorithm. Applied Statistics 1979; 28:100-8.
25. Wang XW, Harris CC. p53 tumor-suppressor gene: clues to molecular carcinogenesis. J Cell
Physiol 1997; 173:247-55.
26. Brash DE, Rudolph JA, Simon JA, Lin A, McKenna GJ, Baden HP, Halperin AJ, Ponten J.
A role for sunlight in skin cancer: UV-induced p53 mutations in squamous cell carcinoma.
Proc Natl Acad Sci USA 1991; 88:10124-8.
27. Denissenko MF, Pao A, Tang M, Pfeifer GP. Preferential formation of benzo[a]pyrene
adducts at lung cancer mutational hotspots in P53. Science 1996; 274:430-2.
28. Toyooka S, Tsuda T, Gazdar AF. The TP53 gene, tobacco exposure, and lung cancer. Hum
Mutat 2003; 21:229-39.
29. Soussi T, Asselain B, Hamroun D, Kato S, Ishioka C, Claustres M, Beroud C. Meta-analysis
of the p53 mutation database for mutant p53 biological activity reveals a methodologic bias
in mutation detection. Clin Cancer Res 2006; 12:62-9.
30. Fairbrother WG, Yeh RF, Sharp PA, Burge CB. Predictive identification of exonic splicing
enhancers in human genes. Science 2002; 297:1007-13.
31. Aretz S, Uhlhaas S, Sun Y, Pagenstecher C, Mangold E, Caspari R, Moslein G, Schulmann K,
Propping P, Friedl W. Familial adenomatous polyposis: aberrant splicing due to missense or
silent mutations in the APC gene. Hum Mutat 2004; 24:370-80.
32. Zatkova A, Messiaen L, Vandenbroucke I, Wieser R, Fonatsch C, Krainer AR, Wimmer K.
Disruption of exonic splicing enhancer elements is the principal cause of exon skipping
associated with seven nonsense or missense alleles of NF1. Hum Mutat 2004; 24:491-501.
33. Varley JM, Attwooll C, White G, McGown G, Thorncroft M, Kelsey AM, Greaves M,
Boyle J, Birch JM. Characterization of germline TP53 splicing mutations and their genetic
and functional analysis. Oncogene 2001; 20:2647-54.
34. Holmila R, Fouquet C, Cadranel J, Zalcman G, Soussi T. Splice mutations in the p53 gene:
case report and review of the literature. Hum Mutat 2003; 21:101-2.
35. Horaitis O, Cotton RG. The challenge of documenting mutation across the genome: the
human genome variation society approach. Hum Mutat 2004; 23:447-52.
36. Shimada Y. Researchers should have respect for the originator of the cell lines. Clin Cancer
Res 2005; 11:4634.
p53 mutation status in human cancer cell lines
708 Cancer Biology & Therapy 2008; Vol. 7 Issue 5
37. Buehring GC, Eby EA, Eby MJ. Cell line cross-contamination: how aware are Mammalian
cell culturists of the problem and how to monitor it? In Vitro Cell Dev Biol Anim 2004;
38. Yoshino K, Iimura E, Saijo K, Iwase S, Fukami K, Ohno T, Obata Y, Nakamura Y. Essential role
for gene profiling analysis in the authentication of human cell lines. Hum Cell 2006; 19:43-8.
39. Cheng J, Haas M. Frequent mutations in the p53 tumor suppressor gene in human leuke-
mia T-cell lines. Mol Cell Biol 1990; 10:5502-9.
40. Wolf D, Rotter V. Major deletions in the gene encoding the p53 tumor antigen cause lack
of p53 expression in HL-60 cells. Proc Natl Acad Sci USA 1985; 82:790-4.
41. Neubauer A, He M, Schmidt CA, Huhn D, Liu ET. Genetic alterations in the p53 gene
in the blast crisis of chronic myelogenous leukemia: analysis by polymerase chain reaction
based techniques. Leukemia 1993; 7:593-600.
42. Murai Y, Hayashi S, Takahashi H, Tsuneyama K, Takano Y. Correlation between DNA
alterations and p53 and p16 protein expression in cancer cell lines. Pathol Res Pract 2005;
43. Rodrigues NR, Rowan A, Smith ME, Kerr IB, Bodmer WF, Gannon JV, Lane DP. p53
mutations in colorectal cancer. Proc Natl Acad Sci USA 1990; 87:7555-9.
44. Teoh G, Tai YT, Urashima M, Shirahama S, Matsuzaki M, Chauhan D, Treon SP, Raje N,
Hideshima T, Shima Y, Anderson KC. CD40 activation mediates p53-dependent cell cycle
regulation in human multiple myeloma cell lines. Blood 2000; 95:1039-46.
45. Lehman TA, Bennett WP, Metcalf RA, Welsh JA, Ecker J, Modali RV, Ullrich S, Romano JW,
Appella E, Testa JR, et al. p53 mutations, ras mutations, and p53-heat shock 70 protein
complexes in human lung carcinoma cell lines. Cancer Res 1991; 51:4090-6.
46. Mitsudomi T, Steinberg SM, Nau MM, Carbone D, D’Amico D, Bodner S, Oie HK,
Linnoila RI, Mulshine JL, Minna JD, et al. p53 gene mutations in non-small-cell lung can-
cer cell lines and their correlation with the presence of ras mutations and clinical features.
Oncogene 1992; 7:171-80.
47. Takahashi T, Nau MM, Chiba I, Birrer MJ, Rosenberg RK, Vinocour M, Levitt M, Pass H,
Gazdar AF, Minna JD. p53: a frequent target for genetic abnormalities in lung cancer.
Science 1989; 246:491-4.
48. Kastrinakis WV, Ramchurren N, Rieger KM, Hess DT, Loda M, Steele G, Summerhayes IC.
Increased incidence of p53 mutations is associated with hepatic metastasis in colorectal
neoplastic progression. Oncogene 1995; 11:647-52.
49. Gayet J, Zhou XP, Duval A, Rolland S, Hoang JM, Cottu P, Hamelin R. Extensive charac-
terization of genetic alterations in a series of human colorectal cancer cell lines. Oncogene
2001; 20:5025-32.
50. Liu Y, Bodmer WF. Analysis of P53 mutations and their expression in 56 colorectal cancer
cell lines. Proc Natl Acad Sci USA 2006; 103:976-81.
51. Nigro JM, Baker SJ, Preisinger AC, Jessup JM, Hostetter R, Cleary K, Bigner SH, Davidson N,
Baylin S, Devilee P, et al. Mutations in the p53 gene occur in diverse human tumor types.
Nature 1989; 342:705-8.
52. Chen P, Iavarone A, Fick J, Edwards M, Prados M, Israel MA. Constitutional p53 mutations
associated with brain tumors in young adults. Cancer Genet Cytogenet 1995; 82:106-15.
53. Fujiwara T, Mukhopadhyay T, Cai DW, Morris DK, Roth JA, Grimm EA. Retroviral-
mediated transduction of p53 gene increases TGF-beta expression in a human glioblastoma
cell line. Int J Cancer 1994; 56:834-9.
54. Haapajarvi T, Kivinen L, Heiskanen A, des Bordes C, Datto MB, Wang XF, Laiho M. UV
radiation is a transcriptional inducer of p21(Cip1/Waf1) cyclin-kinase inhibitor in a p53-
independent manner. Exp Cell Res 1999; 248:272-9.
55. Concin N, Zeillinger C, Tong D, Stimpfl M, Konig M, Printz D, Stonek F, Schneeberger C,
Hefler L, Kainz C, Leodolter S, Haas OA, Zeillinger R. Comparison of p53 mutational
status with mRNA and protein expression in a panel of 24 human breast carcinoma cell
lines. Breast Cancer Res Treat 2003; 79:37-46.
56. Perego P, Giarola M, Righetti SC, Supino R, Caserini C, Delia D, Pierotti MA, Miyashita T,
Reed JC, Zunino F. Association between cisplatin resistance and mutation of p53 gene and
reduced bax expression in ovarian carcinoma cell systems. Cancer Res 1996; 56:556-62.
57. Yaginuma Y, Westphal H. Abnormal structure and expression of the p53 gene in human
ovarian carcinoma cell lines. Cancer Res 1992; 52:4196-9.
58. De Feudis P, Debernardis D, Beccaglia P, Valenti M, Graniela Sire E, Arzani D, Stanzione S,
Parodi S, D’Incalci M, Russo P, Broggini M. DDP-induced cytotoxicity is not influenced by p53
in nine human ovarian cancer cell lines with different p53 status. Br J Cancer 1997; 76:474-9.
59. Ogretmen B, Safa AR. Expression of the mutated p53 tumor suppressor protein and its
molecular and biochemical characterization in multidrug resistant MCF-7/Adr human
breast cancer cells. Oncogene 1997; 14:499-506.
60. Isaacs WB, Carter BS, Ewing CM. Wild-type p53 suppresses growth of human prostate
cancer cells containing mutant p53 alleles. Cancer Res 1991; 51:4716-20.
61. Gurova KV, Rokhlin OW, Budanov AV, Burdelya LG, Chumakov PM, Cohen MB, Gudkov AV.
Cooperation of two mutant p53 alleles contributes to Fas resistance of prostate carcinoma
cells. Cancer Res 2003; 63:2905-12.
62. Kashii T, Mizushima Y, Monno S, Nakagawa K, Kobayashi M. Gene analysis of K-, H-ras,
p53, and retinoblastoma susceptibility genes in human lung cancer cell lines by the poly-
merase chain reaction/single-strand conformation polymorphism method. J Cancer Res
Clin Oncol 1994; 120:143-8.
63. Bartek J, Iggo R, Gannon J, Lane DP. Genetic and immunochemical analysis of mutant p53
in human breast cancer cell lines. Oncogene 1990; 5:893-9.
64. Kovach JS, McGovern RM, Cassady JD, Swanson SK, Wold LE, Vogelstein B, Sommer SS.
Direct sequencing from touch preparations of human carcinomas: analysis of p53 mutations
in breast carcinomas. J Natl Cancer Inst 1991; 83:1004-9.
65. den Dunnen JT, Antonarakis SE. Nomenclature for the description of human sequence
variations. Hum Genet 2001; 109:121-4.
66. Cooper MJ, Haluschak JJ, Johnson D, Schwartz S, Morrison LJ, Lippa M, Hatzivassiliou G,
Tan J. p53 mutations in bladder carcinoma cell lines. Oncol Res 1994; 6:569-79.
67. Grimm MO, Jurgens B, Schulz WA, Decken K, Makri D, Schmitz Drager BJ. Inactivation
of tumor suppressor genes and deregulation of the c-myc gene in urothelial cancer cell lines.
Urol Res 1995; 23:293-300.
68. Rieger KM, Little AF, Swart JM, Kastrinakis WV, Fitzgerald JM, Hess DT, Libertino JA,
Summerhayes IC. Human bladder carcinoma cell lines as indicators of oncogenic change
relevant to urothelial neoplastic progression. Br J Cancer 1995; 72:683-90.
69. Sharma S, Schwarte Waldhoff I, Oberhuber H, Schafer R. Functional interaction of wild-
type and mutant p53 transfected into human tumor cell lines carrying activated ras genes.
Cell Growth Differ 1993; 4:861-9.
70. Warenius HM, Jones M, Gorman T, McLeish R, Seabra L, Barraclough R, Rudland P.
Combined RAF1 protein expression and p53 mutational status provides a strong predictor
of cellular radiosensitivity. Br J Cancer 2000; 83:1084-95.
71. Williamson MP, Elder PA, Knowles MA. The spectrum of TP53 mutations in bladder
carcinoma. Genes Chromosomes Cancer 1994; 9:108-18.
72. Takahashi M. [Analyses of p53 mutations in breast cancers with a combined use of yeast func-
tional assay and immunohistochemical staining]. Hokkaido Igaku Zasshi 1998; 73:275-86.
73. Gaidano G, Ballerini P, Gong JZ, Inghirami G, Neri A, Newcomb EW, Magrath IT,
Knowles DM, Dalla Favera R. p53 mutations in human lymphoid malignancies: association
with Burkitt lymphoma and chronic lymphocytic leukemia. Proc Natl Acad Sci USA 1991;
74. Gomez Manzano C, Fueyo J, Kyritsis AP, Steck PA, Roth JA, McDonnell TJ, Steck KD,
Levin VA, Yung WK. Adenovirus-mediated transfer of the p53 gene produces rapid and
generalized death of human glioma cells via apoptosis. Cancer Res 1996; 56:694-9.
75. Jia LQ, Osada M, Ishioka C, Gamo M, Ikawa S, Suzuki T, Shimodaira H, Niitani T, Kudo T,
Akiyama M, Kimura N, Matsuo M, Mizusawa H, Tanaka N, Koyama H, Namba M,
Kanamaru R, Kuroki T. Screening the p53 status of human cell lines using a yeast functional
assay. Mol Carcinog 1997; 19:243-53.
76. Russell SJ, Ye YW, Waber PG, Shuford M, Schold SCJ, Nisen PD. p53 mutations, O6-
alkylguanine DNA alkyltransferase activity, and sensitivity to procarbazine in human brain
tumors. Cancer 1995; 75:1339-42.
77. Smardova J, Pavlova S, Svitakova M, Grochova D, Ravcukova B. Analysis of p53 status in
human cell lines using a functional assay in yeast: detection of new non-sense p53 mutation
in codon 124. Oncol Rep 2005; 14:901-7.
78. Stratton MR, Moss S, Warren W, Patterson H, Clark J, Fisher C, Fletcher CD, Ball A,
Thomas M, Gusterson BA, et al. Mutation of the p53 gene in human soft tissue sarcomas:
association with abnormalities of the RB1 gene. Oncogene 1990; 5:1297-301.
79. D’Amico D, Carbone D, Mitsudomi T, Nau M, Fedorko J, Russell E, Johnson B,
Buchhagen D, Bodner S, Phelps R, et al. High frequency of somatically acquired p53 muta-
tions in small-cell lung cancer cell lines and tumors. Oncogene 1992; 7:339-46.
80. Zolzer F, Hillebrandt S, Streffer C. Radiation induced G
-block and p53 status in six human
cell lines. Radiother Oncol 1995; 37:20-8.
81. Mihara K, Miyazaki M, Kondo T, Fushimi K, Tsuji T, Inoue Y, Fukaya K, Ishioka C, Namba
M. Yeast functional assay of the p53 gene status in human cell lines maintained in our
laboratory. Acta Med Okayama 1997; 51:261-5.
82. Gelfi C, Righetti SC, Zunino F, Della Torre G, Pierotti MA, Righetti PG. Detection
of p53 point mutations by double-gradient, denaturing gradient gel electrophoresis.
Electrophoresis 1997; 18:2921-7.
83. Ruggeri B, Zhang SY, Caamano J, DiRado M, Flynn SD, Klein Szanto AJ. Human pancre-
atic carcinomas and cell lines reveal frequent and multiple alterations in the p53 and Rb-1
tumor-suppressor genes. Oncogene 1992; 7:1503-11.
84. Rodicker F, Putzer BM. p73 is effective in p53-null pancreatic cancer cells resistant to wild-
type TP53 gene replacement. Cancer Res 2003; 63:2737-41.
... Cell culture MCF-7 breast cancer cells express p53 wild-type, are estrogen (ER) and progesterone receptor (PR) positive and express low levels of human epidermal growth factor receptor 2 (HER2) [46,47]. MDA-MB-231 breast cancer cells that were originally isolated from a human breast cancer pleural effusion express a p53-mutation (R280K), are negative for ER and PR and express no amplification of HER2 [46,48]. Both breast cancer cell lines were a kind gift of Göran Landberg (Sahlgrenska Cancer Center, University of Gothenburg, Gothenburg, Sweden) and were initially purchased from ATCC (Catalogue number: CRL-3435 and HTB-26). ...
... The primary colon cancer cell line HT-29 was isolated in 1964 by Fogh and Trempe. HT-29 cells carry a p53 mutation (R273H) and are deregulated for c-MYC [48]. HT-29 was a kind gift from Karsten Parczyk (Bayer AG) and initially purchased from ATCC (Catalogue number: HTB-38). ...
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Background: Despite an improvement of prognosis in breast and colon cancer, the outcome of the metastatic disease is still severe. Microevolution of cancer cells often leads to drug resistance and tumor-recurrence. To target the driving forces of the tumor microevolution, we focused on synergistic drug combinations of selected compounds. The aim is to prevent the tumor from evolving in order to stabilize disease remission. To identify synergisms in a high number of compounds, we propose here a three-step concept that is cost efficient, independent of high-throughput machines and reliable in its predictions. Methods: We created dose response curves using MTT- and SRB-assays with 14 different compounds in MCF-7, HT-29 and MDA-MB-231 cells. In order to efficiently screen for synergies, we developed a screening tool in which 14 drugs were combined (91 combinations) in MCF-7 and HT-29 using EC25 or less. The most promising combinations were verified by the method of Chou and Talalay. Results: All 14 compounds exhibit antitumor effects on each of the three cell lines. The screening tool resulted in 19 potential synergisms detected in HT-29 (20.9%) and 27 in MCF-7 (29.7%). Seven of the top combinations were further verified over the whole dose response curve, and for five combinations a significant synergy could be confirmed. The combination Nutlin-3 (inhibition of MDM2) and PX-478 (inhibition of HIF-1α) could be confirmed for all three cell lines. The same accounts for the combination of Dichloroacetate (PDH activation) and NHI-2 (LDH-A inhibition). Our screening method proved to be an efficient tool that is reliable in its projections. Conclusions: The presented three-step concept proved to be cost- and time-efficient with respect to the resulting data. The newly found combinations show promising results in MCF-7, HT-29 and MDA-MB231 cancer cells.
... Since our previous study showed that RNF187 played tumor suppressor roles in triple-negative breast cancer, we further investigated its role in luminal-type breast cancer [27]. MCF-7, MDA-MB-175, and ZR751 cells, all of which are ER alpha-positive and P53 wild type [28], were utilized as the models in this study [28]. The CCK-8 assay showed that RNF187 depletion significantly inhibited the growth of MCF-7, MDA-MB-175, and ZR751 cells ( Fig. 1E-G). ...
... Since our previous study showed that RNF187 played tumor suppressor roles in triple-negative breast cancer, we further investigated its role in luminal-type breast cancer [27]. MCF-7, MDA-MB-175, and ZR751 cells, all of which are ER alpha-positive and P53 wild type [28], were utilized as the models in this study [28]. The CCK-8 assay showed that RNF187 depletion significantly inhibited the growth of MCF-7, MDA-MB-175, and ZR751 cells ( Fig. 1E-G). ...
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The tumor suppressor P53 plays critical role in preventing cancer. P53 is rarely mutated and remains functional in luminal-type breast cancer(1). According to current knowledge, wild-type P53 function is tightly controlled by posttranslational modifications, such as ubiquitination. Several ubiquitin ligases have been shown to regulate P53 ubiquitination and protein stability. Here, we report that RNF187, a RING family ubiquitin ligase, facilitates breast cancer growth and inhibits apoptosis by modulating P53 signaling. RNF187 expression was elevated in breast cancer and correlated with breast cancer survival only in the P53 wild-type groups. Bioinformatic analysis showed that the expression of RNF187 was negatively correlated with the expression of P53 target genes, such as IGFBP3 and FAS, in breast cancer. RNF187 depletion inhibited breast cancer growth and facilitated cell death. RNA sequencing analysis indicated that RNF187 could be an important modulator of P53 signaling. Further experiments showed that RNF187 interacts with P53 and promotes its degradation by facilitating its polyubiquitination in breast cancer cells. Interestingly, the in vitro ubiquitin assay showed that RNF187 can directly ubiquitinate P53 in a manner independent of MDM2. These findings reveal a novel direct P53 regulator and a potential therapeutic target for breast cancer.
... ERK1/2 can also bind to and stabilize p53 in different ways, thus augmenting p53 expression, which is required for the ERK1/2-induced apoptosis under certain conditions [20]. In line with that, p53-deficient PC-3 cells are also resistant to treatment with chrysosplenol d [33], whereas NSCLC A549 expressing wild type p53 (p53 wt ) are particularly sensitive to chrysosplenol d. However, the p53 status alone does not suffice to explain the differential sensitivity of cancer cell types to chrysosplenol d. ...
... However, the p53 status alone does not suffice to explain the differential sensitivity of cancer cell types to chrysosplenol d. Thus, MCF7 breast cells are also p53 wt and are relatively resistant to chrysosplenol d, whilst MDA-MB-231, which express gain of function p53 mut that promotes tumor growth independent from classical downstream targets of p53 [33,34], are relatively sensitive to treatment. Also, MIA PaCa-2 harbor a gain of function mutation of p53 [35], but are relatively resistant to chrysosplenol d treatment. ...
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... PTGS2 can also mediate cell proliferation, angiogenesis, apoptosis, invasion, and immunosuppression to increase tumor progression [24]. e p53 protein is the product of TP53, a pivotal tumor suppressor gene, whose inactivation can result in gastric carcinogenesis [25,26]. CCL2/MCP1 is an important indicator of an enhanced immune response [27][28][29]. ...
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Although modified Liu Jun Zi decoction (MLD) has favorable outcomes for chronic atrophic gastritis (CAG) in clinics, the identification of its active ingredients and the molecular mechanism of pharmacology are still unknown and need to be solved urgently. In the study, we screened 170 active components of MLD based on oral bioavailability ≥30% and drug-likeness ≥0.18 via the TCMSP platform. We further establish a dataset containing 315 CAG targets from PharmGkb, GeneCard, OMIM, DrugBank database, and Therapeutic Target database. Network pharmacology found that there are 110 active components of MLD and 26 potential targets for CAG in the “ingredient-target” network. The results of gene ontology analysis show that these targets are involved mainly in reactive oxygen species metabolic process, regulation of vasculature development, and T cell activation. KEGG pathways analysis indicates that these signaling pathways in the treatment of CAG include HIF-1 signaling pathway, neurodegeneration-multiple diseases pathway, MAPK signaling pathway, and PI3K-Akt signaling pathway. Finally, docking of the active component quercetin and clinical medicine Omeprazole with the core targets was carried out. We found that quercetin, a crucial active ingredient in MLD, has good binding activity with potential targets of CAG, and its molecular conformation is stable, which is better than the binding energy of Omeprazole. So, the active ingredients of MLD exhibit good potential drugs for the treatment of CAG.
... In TP53 mutant tumors, ATF3 induction and TP63+ squamous differentiation following ARID1A loss could be a compensatory mechanism that partially restores p53 pathway function. It is worth noting that these genetic mechanisms are difficult to explore in cell culture models, as the majority of immortalized cell lines have impaired p53 signaling, whether that be through inherent mutation [119], selection during culture [120], or immortalization techniques like SV40 large T antigen [121]. In fact, half of the 30 endometrial cancer cell lines profiled by CCLE are TP53/ARID1A co-mutant [122]. ...
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TP53 and ARID1A are frequently mutated across cancer but rarely in the same primary tumor. Endometrial cancer has the highest TP53-ARID1A mutual exclusivity rate. However, the functional relationship between TP53 and ARID1A mutations in the endometrium has not been elucidated. We used genetically engineered mice and in vivo genomic approaches to discern both unique and overlapping roles of TP53 and ARID1A in the endometrium. TP53 loss with oncogenic PIK3CA H1047R in the endometrial epithelium results in features of endometrial hyperplasia, adenocarcinoma, and intraepithelial carcinoma. Mutant endometrial epithelial cells were transcriptome profiled and compared to control cells and ARID1A/PIK3CA mutant endometrium. In the context of either TP53 or ARID1A loss, PIK3CA mutant endometrium exhibited inflammatory pathway activation, but other gene expression programs differed based on TP53 or ARID1A status, such as epithelial-to-mesenchymal transition. Gene expression patterns observed in the genetic mouse models are reflective of human tumors with each respective genetic alteration. Consistent with TP53-ARID1A mutual exclusivity, the p53 pathway is activated following ARID1A loss in the endometrial epithelium, where ARID1A normally directly represses p53 pathway genes in vivo , including the stress-inducible transcription factor, ATF3. However, co-existing TP53-ARID1A mutations led to invasive adenocarcinoma associated with mutant ARID1A-driven ATF3 induction, reduced apoptosis, TP63+ squamous differentiation and invasion. These data suggest TP53 and ARID1A mutations drive shared and distinct tumorigenic programs in the endometrium and promote invasive endometrial cancer when existing simultaneously. Hence, TP53 and ARID1A mutations may co-occur in a subset of aggressive or metastatic endometrial cancers, with ARID1A loss promoting squamous differentiation and the acquisition of invasive properties.
... In contrast, in H23 cells P21 and Cyclin D1 were down-regulated while Cyclin B1was noticeably up-regulated. The difference may result from the status of the p53 gene which is mutated in H23 cells 26,27 . It has been reported that lack of wild-type p53 protein can lead to bypassing of G1 checkpoint and to G2/ M arrest phenotype instead [28][29][30] . ...
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In this study, we report a novel function of FCN3 (Ficolin 3), a secreted lectin capable of activating the complement pathway, as a tumor suppressor of lung adenocarcinoma (LUAD). First, the expression of FCN3 was strongly down-regulated in cancer tissues compared to matched normal lung tissues, and down-regulation of FCN3 was shown to be significantly correlated with increased mortality among LUAD patients. Interestingly, while ectopic expression of FCN3 led to cell cycle arrest and apoptosis in A549 and H23 cells derived from LUAD, the secreted form of the protein had no effect on the cells. Rather, we found evidence indicating that activation of the unfolded protein response from endoplasmic reticulum (ER) stress is induced by ectopic expression of FCN3. Consistently, inhibition of ER stress response led to enhanced survival of the LUAD cells. Of note, the fibrinogen domain, which is not secreted, turned out to be both necessary and sufficient for induction of apoptosis when localized to ER, consistent with our proposed mechanism. Collectively, our data indicate that FCN3 is a tumor suppressor gene functioning through induction of ER stress.
... We next want to figure out whether the P53 status impacts the DPP4-induced ferroptosis in ccRCC cells. Two ccRCC cell lines 786-O (mutant P53) and Caki-1 (wild-type P53) were used in our study and both cell lines showed ferroptosis after SUV39H1 depleted, which indicated that the regulation role of DPP4 is independent of P53 status in ccRCC cells 34 . Together, our data indicate that SUV39H1 deficiency upregulate the expression of membrane and nucleus DPP4, which is P53-independent in ccRCC. ...
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Clear cell renal cell carcinoma (ccRCC) is a common kidney malignancy characterized by a poor prognosis. Suppressor of variegation 3–9 homolog 1 (SUV39H1), which encodes a histone H3 lysine 9 methyltransferase, has been reported to act as an oncogene in many cancers. However, it is unclear whether SUV39H1 is involved in ccRCC. Here, we report that SUV39H1 expression is frequently upregulated in ccRCC tumors and is significantly correlated with ccRCC progression. SUV39H1 expression level is an independent risk factor for cancer prognosis, and integration with several known prognostic factors predicted ccRCC patient prognosis with improved accuracy than the conventional SSIGN (stage, size, grade and necrosis) prognostic model. Mechanistically, we discovered that siRNA knockdown or pharmacological inhibition of SUV39H1 induced iron accumulation and lipid peroxidation, leading to ferroptosis that disrupted ccRCC cell growth in vitro and in vivo. We also show that SUV39H1 deficiency modulated the H3K9me3 status of the DPP4 (dipeptidyl-peptidase-4) gene promoter, resulting in upregulation of its expression that contributes to ferroptosis. Taken together, our findings provide the mechanistic insight into SUV39H1-dependent epigenetic control of ccRCC tumor growth and indicate that SUV39H1 may serve as a potential therapeutic target for ccRCC treatment.
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Blocking the pyrimidine nucleotide de novo synthesis pathway by inhibiting dihydroorotate dehydrogenase (DHODH) results in the cell cycle arrest and/or differentiation of rapidly proliferating cells including activated lymphocytes, cancer cells, or virally infected cells. Emvododstat (PTC299) is an orally bioavailable small molecule that inhibits DHODH. We evaluated the potential for emvododstat to inhibit the progression of acute myeloid leukemia (AML) using several in vitro and in vivo models of the disease. Broad potent activity was demonstrated against multiple AML cell lines, AML blasts cultured ex vivo from patient blood samples, and AML tumor models including patient-derived xenograft models. Emvododstat induced differentiation, cytotoxicity, or both in primary AML patient blasts cultured ex vivo with 8 of 10 samples showing sensitivity. AML cells with diverse driver mutations were sensitive, suggesting the potential of emvododstat for broad therapeutic application. AML cell lines that are not sensitive to emvododstat are likely to be more reliant on the salvage pathway than on de novo synthesis of pyrimidine nucleotides. Pharmacokinetic experiments in rhesus monkeys demonstrated that emvododstat levels rose rapidly after oral administration, peaking about 2 hours post-dosing. This was associated with an increase in the levels of dihydroorotate (DHO), the substrate for DHODH, within 2 hours of dosing indicating that DHODH inhibition is rapid. DHO levels declined as drug levels declined, consistent with the reversibility of DHODH inhibition by emvododstat. These preclinical findings provide a rationale for clinical evaluation of emvododstat in an ongoing Phase 1 study of patients with relapsed/refractory acute leukemias.
Cancer continues to be a growing burden, especially in the resource limited regions of the world, and more effective and affordable therapies are highly desirable. In this study, the effect of X-ray irradiation and four inhibitors, viz. those against epidermal growth factor receptor (EGFR), phosphatidylinositol 3-kinase (PI3K), mammalian target of rapamycin (mTOR) and B-cell lymphoma 2 (Bcl-2) was evaluated in lung, breast, and cervical cancer cell lines, including normal cell lines to determine and compare the potential therapeutic benefit of these treatment modalities. A clonogenic survival assay was used to determine the radiosensitivity and cytotoxicity of inhibitors of EGFR, PI3K/mTOR, and Bcl-2 in the cell lines. From the data, the equivalent dose at which 50% of the cell populations were killed, for cancer and normal cells, was used to determine the relative cellular sensitivity to X-ray irradiation and inhibitor treatment. It was found that breast cancer cell lines were more sensitive to X-ray irradiation, whilst cervical and lung cancer cell lines were more sensitive to EGFR and PI3K/mTOR inhibitor therapy. These data suggest that patients with breast cancer possessing similar characteristics to MDA-MB-231 and MCF-7 cells may derive therapeutic benefit from X-ray irradiation, whilst EGFR and PI3K/mTOR inhibitor therapy may potentially benefit cancer patients possessing cancers similar to HeLa and A549 cells.
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BACKGROUND Studies have found that many published life sciences research results are irreproducible. Our goal was to provide comprehensive risk estimates of familiar reproducibility deficiencies to support quality improvement in research. MATERIAL AND METHODS Reports included were peer-reviewed, published between 1980 and 2016, and presented frequency data of basic biomedical research deficiencies. Manual and electronic literature searches were performed in seven bibliographic databases. For deficiency concepts with at least four frequency studies and with a sample size of at least 15 units in each, a meta-analysis was performed. RESULTS Overall, 68 publications met our inclusion criteria. The study identified several major groups of research quality defects: study design, cell lines, statistical analysis, and reporting. In the study design group of 3 deficiencies, missing power calculation was the most frequent (82.3% [95% Confidence Interval (CI): 69.9-94.6]). Among the 6 cell line deficiencies, mixed contamination was the most frequent (22.4% [95% CI: 10.4-34.3]). Among the 3 statistical analysis deficiencies, the use of chi-square test when expected cells frequency was <5 was the most prevalent (15.7% [95% CI: -3.2-34.7]). In the reporting group of 12 deficiencies, failure to state the number of tails was the most frequent (65% [95% CI: 39.3-90.8]). CONCLUSIONS The results of this study could serve as a general reference when consistently measurable sources of deficiencies need to be identified in research quality improvement.
HeLa was the first human cell line established (1952) and became one of the most frequently used lines because of its hardiness and rapid growth rate. During the next two decades, the development of other human cell lines Mushroomed. One reason for this became apparent during the 1970s, when it was demonstrated that many of these cell lines hall been overgrown and replaced by fast-growing HeLa cells inadvertently introduced into the original cultures. Although the discovery of these "HeLa contaminants" prompted immediate alarm, how aware are cell culturists today of the threat of cell line cross-contamination? To answer this question, we performed a literature search and conducted a survey of 483 mammalian cell culturists to determine how many were using HeLa contaminants without being aware of their true identity and how many were not using available means to ensure correct identity. Survey respondents included scientists., staff, and graduate students in 48 countries. HeLa cells were used by 32% and HeLa contaminants by 9% Of survey respondents. Most were also using other cell lines; yet, only about a third of respondents were testing their lines for cell identity. Of all the cell lines used, 35% hall been obtained from another laboratory instead of from a repository, thus increasing the risk of false identity. Over 220 publications were found in the PubMed database (1969-2004) in which HeLa contaminants were used as a model for the tissue type of the original cell line. Overall, the results of this study indicate a lack of vigilance in cell acquisition and identity testing. Some researchers are still using HeLa contaminants without apparent awareness of their true identity. The consequences of cell line cross-contamination can be Spurious scientific conclusions: its prevention can save time, resources, and scientific reputations.
We present a panoptic survey of cell line cross-contamination (CLCC) among original stocks of human cell lines, investigated using molecular genetic methods. The survey comprised 252 consecutive human cell lines, almost exclusively tumor-derived, submitted by their originators to the DSMZ and 5 additional cell repositories (CRs), using a combination of DNA profiling (4-locus minisatellite and multilocus microsatellite probes) and molecular cytogenetics, exploiting an interactive database ( Widespread high levels of cross-contaminants (CCs) were uncovered, affecting 45 cell lines (18%) supplied by 27 of 93 originators (29%). Unlike previous reports, most CCs (42/45) occurred intraspecies, a discrepancy attributable to improved detection of the more insidious intraspecies CCs afforded by molecular methods. The most prolific CCs were classic tumor cell lines, the numbers of CCs they caused being as follows: HeLa (n = 11), T-24 (n = 4), SK-HEP-1 (n = 4), U-937 (n = 4) and HT-29 (n = 3). All 5 supposed instances of spontaneous immortalization of normal cells were spurious, due to CLCC, including ECV304, the most cited human endothelial cell line. Although high, our figure for CCs at the source sets a lower limit only as (i) many older tumor cell lines were unavailable for comparison and (ii) circulating cell lines are often obtained indirectly, rather than via originators or CRs. The misidentified cell lines reported here have already been unwittingly used in several hundreds of potentially misleading reports, including use as inappropriate tumor models and subclones masquerading as independent replicates. We believe these findings indicate a grave and chronic problem demanding radical measures, to include extra controls over cell line authentication, provenance and availability. Int. J. Cancer 83:555–563, 1999.
p53 target genesp21Cip1/Waf1cyclin-kinase inhibitor (p21 CKI),GADD45, bax,andcyclin Gand genes affecting the redox state of the cells are implicated in p53 damage control responses. In order to attribute their functions and dependency of p53 in UV-damaged cells we undertook an analysis of UVC responses of fibroblasts derived from p53 knock-out mice. UVC radiation efficiently and rapidly inhibited DNA replication in both p53 −/− and +/+ cells. The arrest was persistent in p53 −/− fibroblasts and cells underwent apoptosis, whereas p53 +/+ cells recovered and reentered the cycle. Protein and mRNA analyses of p21 expression showed that it was induced up to sixfold with similar kinetics both in the presence and in the absence of p53. However, high doses of UV abrogated the p21 response in p53 −/− cells, whereas it was maintained in cells with normal p53. UVC radiation transcriptionally activated p21 expression as demonstrated by luciferase reporter assays using deletion constructs of the p21 promoter. The promoter assays further confirmed the independency of p53-binding sites in the activation and linked UV-responsive transcriptional regulation of p21 to two Sp1 consensus binding sites within −61 bp of the transcription initiation site. A weaker regulation was mediated by elements between −1300 to −500 bp relative to the transcription initiation site. The results suggest that in fibroblasts UVC radiation is a rapid and efficient inducer of p21 expression also in a p53-independent manner.
Transforming growth factor-β (TGF-β) has been implicated as a potent growth regulator; the degree of responses to it, whether positive or negative, generally correlates with the stage of cell differentiation in various cell types. We examined the effect of the p53 gene, which participates in the control of cell-cycle progression, on the expression of human TGF-β. The human glioblastoma cell line SNB-19, which expresses the latent form of TGF-β, was transfected with a retroviral vector containing wild-type p53 (wt-p53) or p53 with a mutation (mut-p53) at codon 273. Stable G418-resistant SNB-19 clones were isolated. The growth kinetics of wt-p53 transfectants were suppressed compared with those of parental cells, vector transfectants, or mut-p53 transfectants, as assayed by growthcurve measurements and H-thymidine incorporation; how-, ever, RNA dot blot and Western blot analyses demonstrated that wt-p53 and mut-p53 transfectants expressed higher amounts of TGF-β1 and TGF-β2 mRNA and intracellular TGF-β isoform proteins, respectively, than parental cells. By means of the biological assay for active TGF-β (MvlLu cell-growth-inhibition assay), we observed that both transfectants produced active TGF-β, whereas the parental cells produced only the latent form. These results suggest that, while only the wt-p53 gene inhibits tumor-cell progression, both wt-p53 and codon 273-mutated p53 can cause increased TGF-β expression.
The role of p53 as a central mediator of the DNA damage and other cellular stress responses is well established. The ultimate growth-suppressive function of p53 in part explains its ability to confer chemosensitivity and radiosensitivity upon tumor cells. Recent work in the field has added complexity to our understanding, in terms of identifying novel regulators of p53 stability and function, elucidation of the importance of the p53 family towards p53 function, a growing list of transcriptional targets as well as transcription-independent apoptotic effects and mechanisms, tissue specificity of the p53 response, a molecular understanding of p53-dependent therapeutic sensitization, and efforts towards molecular targeting of the p53 pathway. p53 remains an attractive target for drug development in cancer because its alteration provides a fundamental difference between normal and cancer cells. Strategies are emerging for the identification of mutant p53-specific therapies, therapies targeted at mutant p53-expressing tumors, as well as therapies that target various aspects of the p53 life cycle to enhance chemosensitization. The tools of molecular imaging are beginning to accelerate the pace of discovery and preclinical testing of p53 in animal models. The future holds promise for specific, individualized targeting of mutant or wild-type p53, or its transcriptional targets, in combination therapies with other cancer-specific drugs, to maximize tumor cell killing while protecting normal cells from toxic side effects.
Abstract Immunohistological staining of primary colorectal carcinomas with antibodies specific to p53 demonstrated gross overexpression of the protein in approximately 50% of the malignant tumors examined. Benign adenomas were all negative for p53 overexpression. To determine the molecular basis for this overexpression we examined p53 protein expression in 10 colorectal cancer cell lines. Six of the cell lines expressed high levels of p53 in ELISA, cell-staining, and immunoprecipitation studies. Direct sequencing
Cell cross-contamination in cell cultures is a common problem during cell culturing and use. Contamination invalidates research results, compromises the comparison of results between laboratories, reduces reproducibility required in industrial production of cell lines, and may lead to unusable therapeutic products. The problem can be solved by increasing the awareness of its seriousness and by introducing regular quality control of cell cross-contamination in every laboratory where cells are grown and used.
Genetic instability is a typical feature of tumor cells. This evidence has stimulated the development of rapid methods for detection of gene mutations. A new, improved protocol for denaturing gradient gel electrophoresis (DGGE), to screen for point mutations in genomic DNA, is reported: double gradient (DG) DGGE. In this technique, to the primary, denaturing gradient (typically 30-80% or 40-80% urea/formamide) a secondary gradient, colinear with the first, is superimposed: a porosity gradient (typically 6.5-12% polyacrylamide). The secondary gradient acts by recompacting smeared and diffuse bands of heteroduplexes, which are often indistinguishable from background fluorescence, and by augmenting the resolution between closely spaced homoduplex zones. This allows proper densitometric quantitation of the ratio of the two homoduplex bands. The reliability of this technique has been documented by detection of a number of mutations in exons 6 and 8 of the p53 gene which had escaped revelation by single-strand conformational polymorphism (SSCP) analysis. Additionally, the precise assessment of ratio of the doublet of homoduplex bands has allowed quantitation of the extent of p53 mutation in a mixed cell population extracted from a tumor specimen.