Abstract
New research from the University of California, Berkeley, USA, suggests that special AT-rich sequence binding protein 1 (SATB1), a nuclear protein known for its role in regulating chromatin architecture in developing T-cells, is responsible for reprogramming gene expression to promote breast tumor growth and metastasis.
During the study, expression of SATB1 was studied in both metastatic and non-metastatic cell lines grown in vitro. The researchers found that SATB1 protein and messenger RNA were detected only in the metastatic cells lines. “Our findings suggest a new paradigm in tumor progression, in which SATB1 functions as a genome organizer during tumorigenesis…,” the authors write in the journal Nature.
“…SATB1 reprogrammes the genome to change the expression of hundreds of genes, promoting tumor growth and metastasis.”
Using microarray analysis, the researchers demonstrated that, in highly aggressive cancer cells, RNA-interference-mediated knockdown of SATB1 resulted in altered expression of more than 1000 genes, many of which are known to be involved in oncogenic pathways, such as vascular endothelial growth factors, matrix metalloproteases, transforming growth factor-β1 and epidermal growth factors. A reversal of tumorigenesis was also observed by restoration of breast-like acinar polarity and inhibition of tumor growth and metastasis in vivo.
Furthermore, ectopic expression of SATB1 in nonaggressive cells resulted in gene expression patterns that were consistent with those seen in aggressive tumor phenotypes, acquiring metastatic activity in vivo.
Using archived tumor samples of 1318 women with breast cancer, for whom full clinical follow-up data was available, the researchers undertook Kaplan–Meir analysis and determined a significant correlation between higher SATB1 expression levels and shorter overall survival. “In breast tumors, SATB1 reprogrammes the genome to change the expression of hundreds of genes, promoting tumor growth and metastasis,” explains lead study author, Terumi Kohwi-Shigematsu. “What we have found is a new model of altered gene regulation during the progression of tumors, which depends on SATB1's reprogramming of the gene expression profile. What results is an aggressive cancer phenotype that promotes tumor growth and metastasis.”
“This fascinating piece of research suggests that the way DNA is arranged within cells may contribute to cancer.”
While it remains unclear exactly how SATB1 is able to elicit the results observed in this study, the researchers note that this is an important area for further research and hypothesize that the chromatin remodeling function of SATB1 may be involved, as well as its ability to tether multiple genomic loci to its regulatory network and assemble transcription factors.
In terms of when these findings can be incorporated into therapeutic strategies for breast cancer, the authors are uncertain. Kohwi-Shigematsu comments, “We cannot speculate this accurately because we need to first develop a special delivery system for SATB1 inhibitors to breast cancer cells. Once this is achieved, of course SATB1 would be a remarkable target.”
Sarah Cant, Policy Manager at Breakthrough Breast Cancer, UK, is hopeful about the future for this research but cautions that it is still in the early stages, “This is a very interesting study, which provides us with new information about how aggressive breast cancer tumors may grow and spread. However, it is important to remember that this research looked at cancer cells grown in the lab and is at a very early stage. She adds, “Understanding more about the role of the protein SATB1 in breast cancers in patients could help clinicians to better determine a patient's prognosis and might even lead to future new treatments for women with advanced or metastatic breast cancer.”
“…it (SATB1) could provide an exciting lead for treating breast cancer in the future.”
Commenting on the study, Kat Arney, senior science information officer at Cancer Research UK, enthused, “This fascinating piece of research suggests that the way DNA is arranged within cells may contribute to cancer. We've known for some time that SATB1 can reorganize DNA and alter patterns of gene activity, and now it seems that if this molecule behaves inappropriately, it could cause changes that lead to cancer. Even more interesting is the fact that removing SATB1 apparently reverses these changes, which suggests that it could provide an exciting lead for treating breast cancer in the future.”
Source: Han HJ, Russo J, Kohwi Y, Kohwi-Shigematsu T: SATB 1 reprogrammes gene expression to promote breast tumour growth and metastasis. Nature 452(7184), 187–193 (2008).
in brief…
Dubsky P, Sevelda P, Jakesz R et al.: Clin. Cancer Res. 14(7), 2082–2087 (2008).
As part of an adjuvant Phase III trial comparing chemotherapy with adjuvant hormone therapy in addition to local radiotherapy, 424 premenopausal women with early-stage breast cancer and hormone receptor-expressing tumors were treated with intravenous cyclophosphamide/methotrexate/ 5-fluorouracil (CMF). The influence of anemia (defined as hemoglobin <12 g/dl) on local relapse-free, relapse-free and overall survival (LRFS, RFS and OS, respectively) was evaluated in a retrospective analysis. A total of 18.2% of patients developed anemia on CMF chemotherapy. After a median follow-up period of 5 years, 8.9% of nonanemic patients had experienced local relapse compared with 19.6% of anemic patients. Age, lymph node status and hemoglobin were all shown to have an independent significant influence on LRFS. Compared with nonanemic patients, patients who developed anemia during the study had a significantly worse LFRS, with a relative risk of 2.96.
Finning K, Martin P, Summers J, Massey E, Poole G, Daniels G: Br. Med. J. (2008) (Epub ahead of print). A recent study assessed the feasibility of using an automated robotic technique to predict the fetal RhD phenotype in pregnant RhD-negative women. Researchers conducted a prospective comparison of fetal RhD genotype determined from fetal DNA in maternal plasma with the serologically determined fetal RhD phenotype from cord blood. Samples were taken at or before the 28 week antenatal visit from 1997 RhD-negative pregnant women of known gestation. Genotyping tests predicted the correct phenotype in 95.7% of samples. Results were either unobtainable or inconclusive in 3.4% of samples. A false-positive result was obtained in 0.8% of cases, possibly due to unexpressed or weakly expressed fetal RhD genes. False-negative results were obtained in 0.2% of samples. The authors conclude that high-throughput RhD genotyping of fetuses in all RhD-negative women is feasible and would substantially reduce unnecessary administration of anti-RhD immunoglobulin to RhD-negative pregnant women with an RhD-negative fetus.
Research supports role of hypofractionation in breast cancer radiotherapy
In the treatment of early-stage breast cancer, the international radiotherapy schedule delivers 25 daily fractions of 2.0 Gy; it is thought that this regimen limits the damage caused to normal tissue, whilst maximizing the level of tumor control. However, there is a history of nonstandard regimens that deliver a lower total dose by using fewer, larger fractions (so-called hypofractionation). Indeed, authors of the UK Standardization of Breast Radiotherapy (START) trials believe that there is “mounting evidence that hypofractionation is a safe and effective approach to breast cancer radiotherapy.”
Results of the trials suggest that breast cancer patients in receipt of hypofractionation demonstrate similar recurrence rates and fewer adverse side effects than those in receipt of the standard regimen. A total of 2236 women with early breast cancer from 17 centers in the UK were enrolled in the START A’ trial. Of these, 749 women were randomly assigned to receive the international standard radiotherapy regimen, while 1487 received 13 fractions of either 41.6 Gy (n = 750) or 39 Gy (n = 737) administered in doses of 3.2 and 3.0 Gy, respectively, over 5 weeks.
A median follow-up of 5.1 years demonstrated a local-regional tumor relapse rate of 3.6% after 50 Gy, 3.5% after 41.6 Gy and 5.2% after 39 Gy. The groups receiving 41.6 and 50 Gy demonstrated similar late adverse effects and local tumor relapse rates; however, photographic and patient self-assessments were suggestive of lower rates of late adverse effects after 39 Gy, compared with 50 Gy.
In the START ‘B’ trial, a further 1105 women were assigned to receive the standard radiotherapy regimen while 1110 received a lower dose of 40 Gy in 15 fractions of 2.67 Gy over a shorter duration of 3 weeks. After 5 years of follow-up, the rate of local-regional relapse was 2.2% in the 40 Gy group compared with 3.3% in the 50 Gy group. Further photographic and patient self-assessment also demonstrated fewer later adverse effects to be associated with the 40 Gy regimen.
Despite these promising results supporting the use of radiotherapy hypofractionation in early breast cancer, the researchers warn that longer follow-up data will be required to further investigate any late-occurring events.
Source: START Trialists' Group, Bentzen SM, Agrawal RK, Aird EG et al.: The UK Standardisation of Breast Radiotherapy (START) Trial A of radiotherapy hypofractionation for treatment of early breast cancer: a randomised trial. Lancet Oncol. 9(4), 331–341 (2008).
START Trialists' Group, Bentzen SM, Agrawal RK, Aird EG et al.: The UK Standardisation of Breast Radiotherapy (START) Trial B of radiotherapy hypofractionation for treatment of early breast cancer: a randomised trial. Lancet 371(9618), 1098–1107 (2008).
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Obesity during pregnancy could have “substantial economic implications,” claim US researchers
New research has highlighted the impact of obesity during pregnancy on the use of healthcare services, with findings that depict a marked increase on the use of healthcare services, such as duration of hospital stay. Obesity heightens the obstetrical risks of pregnancy and it is estimated that a quarter of births in the US are to obese mothers and, as such, the researchers claim that just a small increase in healthcare costs for this group may have “substantial economic implications.”
The findings are based on data of 13,422 pregnancies from a US health insurance organization. Women were categorized as underweight (BMI <18.5), normal (BMI 18.5–24.9), overweight (BMI 25.0–29.9), obese (BMI 30.0–34.9), very obese (BMI 35.0–39.9) or extremely obese (BMI 40.0).
After adjustment for age, race or ethnic group, level of education and parity, the results showed that, overall, 60% of obese women stayed in hospital at least 4 days after delivery, compared with 40% of their normal-weight counterparts.
“Almost all of the increase in use of services was related to (…) obese pregnant women.”
It was also shown that a higher than normal BMI was associated with an increased number of prenatal tests, ultrasounds, medication, telephone calls to the department of obstetrics and gynecology and prenatal visits with physicians.
The average number of physician visits was six for extremely obese women, compared with four for their normal-weight peers. The former group also showed an increased number of fetal tests, with an average of 3.8 tests compared with 1.3 tests for women of normal weight.
“Almost all of the increase in use of services was related to the increased rates of cesarean delivery, gestational diabetes mellitus, pre-existing diabetes mellitus, and hypertensive disorders among obese pregnant women,” the study authors conclude.
Source: Chu SY, Bachman DJ, Callaghan WM et al.: Association between obesity during pregnancy and increased use of health care. N. Engl. J. Med. 358(14), 1444–1453 (2008).
New model may allow a more refined prognosis for early-stage breast cancer
Researchers from Duke University (NC, USA) have developed a novel prognostic tool for breast cancer that incorporates gene-expression signatures with established clinical and pathological risk factors. The study authors believe that their model is more practical than the existing global gene predictors and, thus, may ameliorate the therapeutic strategies currently available for women with early stage disease. “We envision that the genomic information from an individual patient could easily be incorporated within the context of the clinicopathological prognostic model, to provide a basis for more refined prognosis,” Chaitanya Archarya and co-authors comment in the Journal of the American Medical Association.
A total of 964 clinically annotated breast tumor samples were analyzed from women with early-stage breast carcinoma who were candidates for adjuvant chemotherapy. With the use of the computer model, Adjuvant! Online, women were divided into three groups according to their risk for relapse: low-risk, intermediate-risk and high-risk. Age, comorbidities, estrogen-receptor status, tumor grade, tumor size and lymph node status are amongst the factors taken into account by the model, which, the researcher note, has become popular among physicians for assisting with clinical decisions.
Using gene microarray analysis, several validated gene expression signatures based on panels of genes known to be involved in various malignant processes, such as invasiveness, epigenetic stem cell specification and tumor necrosis factor activation, were applied within the context of the Adjuvant clusters. This allowed the Adjuvant prognostic categories to be further defined into six subclusters.
The researchers found that patients of different subclusters demonstrated a significant difference in their relapse-free survival. In the low-risk cohort, of six prognostically significant clusters, the median relapse-free survival for patients in cluster four was found to be 16 months less than patients in cluster one and 19 months less than patients in cluster five. Patients in different subclusters were also found to vary in their sensitivity to chemotherapy agents. Multivariate analysis was used to confirm the independent prognostic value of the genomic clusters.
Chiang-Ching Huang and Markus Bredel from Feinberg School of Medicine (Chicago, IL, USA) write, in an accompanying editorial, “In an attempt to tailor risk estimation, these investigators shy away from pure metagene predictors but instead focus on genes with mechanistic implication in breast cancer. Because these genes represent potential targets for specific molecular therapy, this approach represents an advance in the changing landscape of oncology toward individualized patient management.”
The researchers conclude that this study represents preliminary evidence for the benefits of incorporating gene expression signatures into clinical risk stratification and call for further prospective studies to examine its value in personalizing therapy.
Source: Archaya CR, Hsu DS, Anders CK et al.: Gene expression signatures, clinicopathological features, and individualized therapy in breast cancer. JAMA 299(13), 1574–1587 (2008).