The Lymphoma Research Foundation (LRF) is pleased to announce that the 2009 Millennium Pharmaceuticals, Inc./Lymphoma Research Foundation Clinical Investigator Career Development Award has been awarded to Kai Fu, MD, PhD, Associate Professor at the Nebraska Medical Center in Omaha, Nebraska. Lymphoma, the most common type of blood cancer, is broadly categorized into Hodgkin lymphoma (HL) and non-Hodgkin lymphoma (NHL).

The most comprehensive analysis yet of the genome of childhood acute myeloid leukemia (AML) found only a few mistakes in the genetic blueprint, suggesting the cancer arises from just a handful of missteps, according to new findings from St. Jude Children’s Research Hospital. The research appears in the July 27 online edition of the Proceedings of the National Academy of Sciences.

IntroductionA major challenge in developing more effective therapeutic strategies for the treatment of breast cancer patients is confronting the heterogeneity of the disease, recognizing that breast cancer is not one disease but multiple disorders with distinct underlying mechanisms. Gene expression profiling studies have been used to dissect this complexity and our previous studies have identified a series of intrinsic subtypes of breast cancer that define distinct populations of patients with respect to survival. Additional work has also used signatures of oncogenic pathway deregulation to dissect breast cancer heterogeneity as well as to suggest therapeutic opportunities linked to pathway activation.
Methods:
We use genomic analyses to identify relationships between breast cancer subtypes, pathway deregulation, and drug sensitivity. For these studies, we use three independent breast cancer gene expression datasets to measure an individual tumor’s phenotype. Correlation between pathway status and subtype are examined, and linked to predictions for response to conventional chemotherapies.
Results:
We reveal patterns of pathway activation characteristic of each molecular breast cancer subtype, including within the more aggressive subtypes where novel therapeutic opportunities are critically needed. While some oncogenic pathways have high correlation to breast cancer subtype (RAS, CTNNB1, p53, HER1), others have high variability of activity within a specific subtype (MYC, E2F3, SRC), reflecting biology independent of common clinical factors. Additionally, we have combined these analyses with predictions of sensitivity to commonly used cytotoxic chemotherapies to provide additional opportunities for therapeutics specific to the intrinsic subtype that might be better aligned with the characteristics of the individual patient.
Conclusions:
Genomic analyses can be used to dissect the heterogeneity of breast cancer. We use an integrated analysis of breast cancer that combines independent methods of genomic analyses to highlight the complexity of signaling pathways underlying different breast cancer phenotypes, and to identify optimal therapeutic opportunities.

IntroductionTo determine whether the levels of expression of 17 candidate genes were associated with loco-regional control after breast conserving treatments of early-stage breast cancers in young, premenopausal women.
Methods:
Gene expression was measured using RT-PCR in the breast tumors of a series of 53 young (<40 years), premenopausal patients. All treatments consisted in primary breast conserving surgery followed by whole-breast radiotherapy (+/- regional lymph nodes) with or without systemic treatments (chemotherapy +/- hormone-therapy). The median follow-up was 10 years.
Results:
The 10-year loco-regional control rate was 70% (95% CI 57%-87%). In univariate analysis, no clinical/pathological prognostic factors were found to be significantly associated with a decreased loco-regional control. Expression of three genes was found to be significantly associated with an increased loco-regional recurrence rate: low estrogen receptor beta, low aromatase, high GATA3. Two others were associated with only a trend (P<0.10): low HER1 and SKP2. In multivariate analysis only the absence of aromatase was significantly associated with an increased loco-regional recurrence rate (P=0.003, Relative Risk =0.49 95% CI [0.29-0.82]).
Conclusions:
Recent data give credit to the fact that breast cancer in young women is a distinct biological entity driven by special oncogenic pathways. Our results highlight the role of estrogen signalling pathways (mainly CYP19/aromatase, GATA3 and ER beta) in the risk of loco-regional recurrence of breast cancer in young women. Confirmation in larger prospective studies is needed.

Breakthrough Breast Cancer scientists have taken a significant step towards personalising cancer treatment by developing a method to predict a patient’s response to the drug Herceptin. Scientists based in Edinburgh are the first to use computer modelling to predict individual responses to cancer treatment. The results are published in the journal Cancer Research on 28 July 2009.

Researchers at The University of Queensland have helped identify genes that could hold the key to treating a common and deadly type of breast cancer. The discovery suggests a vaccine could be developed for ER negative breast cancer, which accounts for a third of all breast cancer cases, has a generally poor prognosis and few therapy options.

Acceleron Pharma, Inc., a biopharmaceutical company developing novel therapeutics that modulate the growth of cells and tissues including red blood cells, bone and muscle, and Celgene Corporation (NASDAQ: CELG) announced the initiation of a second Phase 2 clinical study of ACE-011. This Phase 2 clinical trial is a randomized, double-blind, placebo-controlled study designed to evaluate the potential of ACE-011 to treat chemotherapy-induced anemia in patients with metastatic breast cancer.

Breakthrough Breast Cancer scientists have taken a significant step towards personalising cancer treatment by developing a new method to predict a patient’s response to the drug Herceptin. Scientists based in Edinburgh are the first to use computer modelling to predict individual responses to cancer treatment. The results are published in the journal Cancer Research on 28 July 2009.

When doctors are managing care for women with breast cancer, the information available to them profoundly influences the type of care they recommend. Knowing whether a woman’s cancer has metastasized, for instance, directly affects how her doctors will approach treatment — which may in turn influence the outcome of that treatment. Determining whether a tumor has metastasized is not always straightforward, however.

Cancer researchers are turning to mathematical models to help answer important clinical questions, and a new paper in Cancer Research, a journal of the American Association for Cancer Research, illustrates how the technique may answer questions about Herceptin resistance. Sofia Merajver, M.D., Ph.D.