Pathogenic variant profile in DNA damage response genes correlates with metastatic breast cancer progression-free survival in a Mexican-mestizo population

IntroductionMetastatic breast cancer causes the most breast cancer-related deaths around the world, especially in countries where breast cancer is detected late into its development. Genetic testing for cancer susceptibility started with the BRCA 1 and 2 genes. Still, recent research has shown that variations in other members of the DNA damage response (DDR) are also associated with elevated cancer risk, opening new opportunities for enhanced genetic testing strategies.MethodsWe sequenced BRCA1/2 and twelve other DDR genes from a Mexican-mestizo population of 40 metastatic breast cancer patients through semiconductor sequencing.ResultsOverall, we found 22 variants –9 of them reported for the first time– and a strikingly high proportion of variations in ARID1A. The presence of at least one variant in the ARID1A, BRCA1, BRCA2, or FANCA genes was associated with worse progression-free survival and overall survival in our patient cohort.DiscussionOur results reflected the unique characteristics of the Mexican-mestizo population as the proportion of variants we found differed from that of other global populations. Based on these findings, we suggest routine screening for variants in ARID1A along with BRCA1/2 in breast cancer patients from the Mexican-mestizo population

Amplified Genes May Be Overexpressed, Unchanged, or Downregulated in Cervical Cancer Cell Lines

Several copy number-altered regions (CNAs) have been identified in the genome of cervical cancer, notably, amplifications of 3q and 5p. However, the contribution of copy-number alterations to cervical carcinogenesis is unresolved because genome-wide there exists a lack of correlation between copy-number alterations and gene expression. In this study, we investigated whether CNAs in the cell lines CaLo, CaSki, HeLa, and SiHa were associated with changes in gene expression. On average, 19.2% of the cell-line genomes had CNAs. However, only 2.4% comprised minimal recurrent regions (MRRs) common to all the cell lines. Whereas 3q had limited common gains (13%), 5p was entirely duplicated recurrently. Genome-wide, only 15.6% of genes located in CNAs changed gene expression; in contrast, the rate in MRRs was up to 3 times this. Chr 5p was confirmed entirely amplified by FISH; however, maximum 33.5% of the explored genes in 5p were deregulated. In 3q, this rate was 13.4%. Even in 3q26, which had 5 MRRs and 38.7% recurrently gained SNPs, the rate was only 15.1%. Interestingly, up to 19% of deregulated genes in 5p and 73% in 3q26 were downregulated, suggesting additional factors were involved in gene repression. The deregulated genes in 3q and 5p occurred in clusters, suggesting local chromatin factors may also influence gene expression. In regions amplified discontinuously, downregulated genes increased steadily as the number of amplified SNPs increased (p<0.01, Spearman's correlation). Therefore, partial gene amplification may function in silencing gene expression. Additional genes in 1q, 3q and 5p could be involved in cervical carcinogenesis, specifically in apoptosis. These include PARP1 in 1q, TNFSF10 and ECT2 in 3q and CLPTM1L, AHRR, PDCD6, and DAP in 5p. Overall, gene expression and copy-number profiles reveal factors other than gene dosage, like epigenetic or chromatin domains, may influence gene expression within the entirely amplified genome segments

The distribution of high-risk human papillomaviruses is different in young and old patients with cervical cancer.

Despite numerous human papillomavirus (HPV) frequency studies in women with cervical cancer (CC), little is known of HPV frequency trends according to patient age. In this work, we compare the mean age and frequency distribution by age of CC patients positive for different HPVs. This study included 462 CC patients. HPVs were detected by PCR and typed using DNA sequencing. A total of 456 patients (98.7%) were positive for HPV: 418 (90.5%) had single and 38 (8.2%) had double HPV infections. HPV16 (46.5%), HPV18 (10.4%), HPV45 (6.7%), and HPV31 (4.1%) were the most frequent viral types in single-infected patients. The mean ages of single-infected patients with HPV16 (49.2±13.3), HPV18 (47.9±12.2), HPV45 (47.9±11.7), or HPV39 (42.6±8.9) were significantly lower than the mean ages of patients singly (53.9±12.7; p<0.001, t-test) or doubly (55.4±12.7; p<0.05, t-test) infected with the remaining HPVs. Three different trends were identified: one for HPV16, another for HPVs18/45/39, and a third for the rest of HPVs. The frequency trend of HPV16 shows two peaks. The first (63.2%) was found in the youngest women (≤35 years), followed by a decreasing trend until the age of 55-60 years (31.1%). The second peak arose at 61-65 years (52.5%), followed by a decreasing trend. The trend for HPVs18/45/39 declined from the youngest (19.3%) to the oldest (>70 years; 12.8%) women. In contrast, the trend for the remaining HPVs increased from the youngest (15.8%) to the oldest (46.2%) women. Unlike other life-style factors, low-risk sexual behavior was associated with late onset of CC independent of low-oncogenic HPV types (p<0.05, Wald chi-square statistic). The data indicate that most CCs in young women depend on the presence of high-oncogenic HPVs. In contrast, almost half of CCs in older patients had low-oncogenic HPVs, suggesting they could depend on the presence of other factors

Impact of gene dosage on gene expression, biological processes and survival in cervical cancer: a genome-wide follow-up study.

We investigated the role of tumor copy number (CN)-altered genome (CN-AG) in the carcinogenesis of cervical cancer (CC), especially its effect on gene expression, biological processes, and patient survival. Fifty-nine human papillomavirus 16 (HPV16)-positive CCs were investigated with microarrays-31 for mapping CN-AG and 55 for global gene expression, with 27 CCs in common. Five-year survival was investigated in 55 patients. Deletions and amplifications >2.5 Mb were defined as CN alterations. The %CN-AG varied from 0 to 32.2% (mean = 8.1±8.9). Tumors were classified as low (mean = 0.5±0.6, n = 11), medium (mean = 5.4±2.4, n = 10), or high (mean = 19.2±6.6, n = 10) CN. The highest %CN-AG was found in 3q, which contributed an average of 55% of all CN alterations. Genome-wide, only 5.3% of CN-altered genes were deregulated directly by gene dosage. In contrast, the rate in fully duplicated 3q was twice as high. Amplification of 3q explained 23.2% of deregulated genes in whole tumors (r2 = 0.232, p = 0.006; analysis of variance), including genes located in 3q and other chromosomes. A total of 862 genes were deregulated exclusively in high-CN tumors, but only 22.9% were CN altered. This suggests that the remaining genes are not deregulated directly by gene dosage, but by mechanisms induced in trans by CN-altered genes. Anaphase-promoting complex/cyclosome (APC/C)-dependent proteasome proteolysis, glycolysis, and apoptosis were upregulated, whereas cell adhesion and angiogenesis were downregulated exclusively in high-CN tumors. The high %CN-AG and upregulated gene expression profile of APC/C-dependent proteasome proteolysis were associated with poor patient survival (p<0.05, log-rank test). Along with glycolysis, they were linearly associated with FIGO stage (r>0.38, p<0.01, Spearman test). Therefore, inhibition of APC/C-dependent proteasome proteolysis and glycolysis could be useful for CC treatment. However, whether they are indispensable for tumor growth remains to be demonstrated

Age distribution of patients with cervical cancer (CC).

<p>The age distribution of CC patients divided into 5-year intervals according to tumor histological type (A). The frequency of patients by age, divided into three groups: <41 years, 41–55 years, and>55 years, according to FIGO staging (B). IND, undifferentiated; ASCC, adenosquamous cell carcinoma; ACC, adenocarcinoma; SCC, squamous cell carcinoma.</p

Mean age of cervical cancer patients according to HPV type (n = 462).

<p>a. S.D.  =  standard deviation.</p><p>b. Other HPVs included HPV6, HPV26, HPV39Like, HPV42, HPV51Like, HPV53, HPV61, HPV66, HPV68, HPV69, HPV70, HPV73, HPV82, HPV82Like.</p><p>The mean±S.D.(n) in the whole sample was 50.6±13.0 (462)</p><p>Mean age of cervical cancer patients according to HPV type (n = 462).</p

Frequency of single and double HPV infections in cervical cancer patients (n = 462).

a<p>Includes HPV68, HPV51Like, HPV66, HPV26, HPV39Like, HPV42, HPV61, HPV70, HPV73, HPV82, HPV82Like.</p><p>Frequency of single and double HPV infections in cervical cancer patients (n = 462).</p

HPV types distribution by 5-years age intervals in the whole sample of CC patients.

<p>The figure shows the frequency distribution of HPV16 single infections (blue circles), pooled frequency of HPV18, HPV45, and HPV39 single infections (green circles), and the pooled frequency of other HPV types (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109406#pone-0109406-g002" target="_blank">Figure 2</a>) plus HPV31 and all double infections (orange circles) over 5-years age intervals in the whole CC patients (n = 462).</p

Frequencies of different HPV types in CC patients according to age and FIGO staging.

<p>The figure shows the relative frequency (%) of HPV types in CC patients grouped by age in ≤40, between 41 and 55 and>55 years old. Panel A included the patients with FIGO I/II, and panel B patients with FIGO III/IV. Bars labeled as HPV16, HPV18, HPV45, HPV31 and HPV39 include only single infections. Other HPVs group include single infection of HPV types 6, 11, 26, 33, 35, 42, 51, 52, 53, 56, 58, 59, 61, 66, 68, 69, 70, 73, 82, 39-like, 51-like, 82-like and all double infections.</p

Association of life-style factors and HPV types with delayed onset of cervical cancer.

a<p>Patient group ≤40 yrs was taken as reference group and odds ratios were calculated using a logistic regression model including all significant variables of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109406#pone-0109406-t003" target="_blank">table 3</a>; reference variable (OR = 1), p value and 95% confidence interval are shown.</p>b<p>Other HPVs includes single infections other than HPV16/18/45/39 and double infections.</p>c<p>Information of six patients was missed.</p>d<p>Include nulliparous (3.4% of total cases).</p>e<p>Patients that have been assisted at least once to Pap screening.</p><p>*Lower-risk factor or reference factor for CC.</p><p>Association of life-style factors and HPV types with delayed onset of cervical cancer.</p