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Posts Tagged ‘HER2’

An Intelligent DNA Nanorobot to Fight Cancer by Targeting HER2 Expression

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

3.2.9

3.2.9   An Intelligent DNA Nanorobot to Fight Cancer by Targeting HER2 Expression, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair

HER2 is an important prognostic biomarker for 20–30% of breast cancers, which is the most common cancer in women. Overexpression of the HER2 receptor stimulates breast cells to proliferate and differentiate uncontrollably, thereby enhancing the malignancy of breast cancer and resulting in a poor prognosis for affected individuals. Current therapies to suppress the overexpression of HER2 in breast cancer mainly involve treatment with HER2-specific monoclonal antibodies. However, these monoclonal anti-HER2 antibodies have severe side effects in clinical trials, such as diarrhea, abnormal liver function, and drug resistance. Removing HER2 from the plasma membrane or inhibiting the gene expression of HER2 is a promising alternative that could limit the malignancy of HER2-positive cancer cells.

DNA origami is an emerging field of DNA-based nanotechnology and intelligent DNA nanorobots show great promise in working as a drug delivery system in healthcare. Different DNA-based nanorobots have been developed as affordable and facile therapeutic drugs. In particular, many studies reported that a tetrahedral framework nucleic acid (tFNA) could serve as a promising DNA nanocarrier for many antitumor drugs, owing to its high biocompatibility and biosecurity. For example, tFNA was reported to effectively deliver paclitaxel or doxorubicin to cancer cells for reversing drug resistance, small interfering RNAs (siRNAs) have been modified into tFNA for targeted drug delivery. Moreover, the production and storage of tFNA are not complicated, and they can be quickly degraded in lysosomes by cells. Since both free HApt and tFNA can be diverted into lysosomes, so,  combining the HApt and tFNA as a novel DNA nanorobot (namely, HApt-tFNA) can be an effective strategy to improve its delivery and therapeutic efficacy in treating HER2-positive breast cancer.

Researchers reported that a DNA framework-based intelligent DNA nanorobot for selective lysosomal degradation of tumor-specific proteins on cancer cells. An anti-HER2 aptamer (HApt) was site-specifically anchored on a tetrahedral framework nucleic acid (tFNA). This DNA nanorobot (HApt-tFNA) could target HER2-positive breast cancer cells and specifically induce the lysosomal degradation of the membrane protein HER2. An injection of the DNA nanorobot into a mouse model revealed that the presence of tFNA enhanced the stability and prolonged the blood circulation time of HApt, and HApt-tFNA could therefore drive HER2 into lysosomal degradation with a higher efficiency. The formation of the HER2-HApt-tFNA complexes resulted in the HER2-mediated endocytosis and digestion in lysosomes, which effectively reduced the amount of HER2 on the cell surfaces. An increased HER2 digestion through HApt-tFNA further induced cell apoptosis and arrested cell growth. Hence, this novel DNA nanorobot sheds new light on targeted protein degradation for precision breast cancer therapy.

It was previously reported that tFNA was degraded by lysosomes and could enhance cell autophagy. Results indicated that free Cy5-HApt and Cy5-HApt-tFNA could enter the lysosomes; thus, tFNA can be regarded as an efficient nanocarrier to transmit HApt into the target organelle. The DNA nanorobot composed of HApt and tFNA showed a higher stability and a more effective performance than free HApt against HER2-positive breast cancer cells. The PI3K/AKT pathway was inhibited when membrane-bound HER2 decreased in SK-BR-3 cells under the action of HApt-tFNA. The research findings suggest that tFNA can enhance the anticancer effects of HApt on SK-BR-3 cells; while HApt-tFNA can bind to HER2 specifically, the compounded HER2-HApt-tFNA complexes can then be transferred and degraded in lysosomes. After these processes, the accumulation of HER2 in the plasma membrane would decrease, which could also influence the downstream PI3K/AKT signaling pathway that is associated with cell growth and death.

However, some limitations need to be noted when interpreting the findings: (i) the cytotoxicity of the nanorobot on HER2-positive cancer cells was weak, and the anticancer effects between conventional monoclonal antibodies and HApt-tFNA was not compared; (ii) the differences in delivery efficiency between tFNA and other nanocarriers need to be confirmed; and (iii) the confirmation of anticancer effects of HApt-tFNA on tumors within animals remains challenging. Despite these limitations, the present study provided novel evidence of the biological effects of tFNA when combined with HApt. Although the stability and the anticancer effects of HApt-tFNA may require further improvement before clinical application, this study initiates a promising step toward the development of nanomedicines with novel and intelligent DNA nanorobots for tumor treatment.

References:

https://pubs.acs.org/doi/10.1021/acs.nanolett.9b01320

https://www.ncbi.nlm.nih.gov/pubmed/27939064

https://www.ncbi.nlm.nih.gov/pubmed/11694782

https://www.ncbi.nlm.nih.gov/pubmed/27082923

https://www.ncbi.nlm.nih.gov/pubmed/25365825

https://www.ncbi.nlm.nih.gov/pubmed/26840503

https://www.ncbi.nlm.nih.gov/pubmed/29802035

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New Risk Stratification for Breast Cancer

Larry H. Bernstein, MD, FCAP, Curator

LPBI

Updated 01/26/2021

Invasive Lobular Breast Cancer May Have Worse Prognosis than Ductal Cancer

— Analysis highlights need for further research, says Megan Kruse, MD

Source: https://www.medpagetoday.com/meetingcoverage/sabcsvideopearls/90531

An analysis of the largest recorded cohort of patients with invasive lobular breast cancer (ILBC) demonstrates that outcomes are significantly worse when compared with invasive ductal breast cancer, highlighting a significant need for more research and clinical trials on patients with ILBC. The findings were presented at the virtual 2020 San Antonio Breast Cancer Symposium.

In this exclusive MedPage Today video, Megan Kruse, MD, of the Cleveland Clinic, explains the multi-institutional study and the insights in provides for future prognostic research.

This work was spearheaded by clinicians who are interested in lobular breast cancer, and trying to figure out how lobular breast cancer is different than ductal breast cancer in a way that would be meaningful for patient care. And so since lobular breast cancer is about 10-15% of all the breast cancers we see, we knew that this work would have to be done on a multi-institution basis.
What we ultimately found was that for lobular cancer patients, those tumors were often diagnosed at a higher stage — meaning larger tumor size and greater lymph node involvement. These were also diagnosed in patients who were of older age compared to the ductal cancer patients, and the patients in the lobular cancer group were less likely to be HER2-positive and less likely to receive chemotherapy.

MD Anderson Researchers Develop New Breast Cancer Staging System

https://www.genomeweb.com/cancer/md-anderson-researchers-develop-new-breast-cancer-staging-system

NEW YORK (GenomeWeb) – Researchers at the University of Texas MD Anderson Cancer Center have developed a new breast cancer staging system that incorporates tumor biology as a critical prognostic indicator for women who undergo neoadjuvant therapy.

Published this week in JAMA Oncology, the Neo-Bioscore staging system incorporates HER2/ERBB2 status, which allows for more precise prognostic stratification of all breast cancer subtypes.

To date, breast cancer patient staging involved considering the size of the primary tumor, metastasis, or disease in the lymph nodes at the time of presentation as the primary factors.However, this fails to take into account the biology of the tumor, which has shown to be critically important, Elizabeth Mittendorf, associate professor of Breast Surgical Oncology at MD Anderson and corresponding author on the study, said in a statement.

The new system builds on the development of an earlier breast cancer staging system developed by MD Anderson, CPS+EG, that incorporates preclinical stage, estrogen receptor status, grade, and post-treatment pathologic stage. While it was an improvement from previous methods, it is no longer a sufficient staging system because it predates the routine use of trastuzumab in the neoadjuvant setting and therefore had a limited ability to provide prognostic information for HER2/ERBB2-positive patients, Mittendorf said.

To develop the staging system, the researchers conducted a retrospective study that evaluated 2,377 MD Anderson breast cancer patients who all had non-metastatic invasive breast cancer and were treated with neoadjuvant chemotherapy.

Each patient’s clinicopathologic data were recorded, including age, clinical and pathological stage, ER status, HER2/ERBB2 status, and nuclear grade. Patients’ ER status was recorded as a percentage of cells staining positive under immunohistochemical analysis. Their ERBB2 status was defined as positive at a reading of 3+ on immunohistochemical analysis or when gene amplification was shown on fluorescence in situ hybridization.

All patients received an anthracycline and/or taxane-based neoadjuvant chemotherapy regimen. Patients with HER2/ERBB2-positive disease routinely completed one year of trastuzumab therapy. After completing chemotherapy, patients underwent either breast-conserving therapy or mastectomy with axillary evaluation with or without post-mastectomy irradiation.

Patients’ CPS+EG score was determined according to the previously published staging system and was calculated twice (once using 1 percent or higher as the cutoff for ER positivity and again using 10 percent or higher as the cutoff).

Their disease-specific survival (DSS) was also calculated using multiple staging systems: AJCC clinical stage, AJCC pathologic stage, CPS+EG (1 percent cutoff), and CPS+EG (10 percent cutoff). Within each staging system, DSS among subgroups was compared using the log-rank test.

After the researchers determined a CPS+EG score for each patient, they added the patient’s respective HER2/ERBB2 status to the model. They then constructed the novel staging system by adding a point to the CPS+EG score for HER2-negative tumors. In the study cohort, 591 patients were HER2/ERBB2 positive.

The researchers found that in addition to validating previous findings that CPS+EG score improved prognostication of patients, the Neo-Bioscore created a more refined stratification in approximately 75 percent of the study cohort. This shift reflects the number of HER2/ERBB2-negative tumors in the study and demonstrated that adding HER2/ERBB2 standards created a highly significant improvement.

“With this tool, I can give my patients the precise information they are looking for: a more refined prognosis. Also, with this data, we will know which patients are in greatest need of additional therapy,” Mittendorf said. “Hopefully these findings will result in more informed conversations between doctor and patient.”

The Neo-Bioscore Update for Staging Breast Cancer Treated With Neoadjuvant ChemotherapyIncorporation of Prognostic Biologic Factors Into Staging After Treatment 

Elizabeth A. Mittendorf, MD, PhD1; Jose Vila, MD1; Susan L. Tucker, PhD2; ….; W. Fraser Symmans, MD6; Aysegul A. Sahin, MD6; Gabriel N. Hortobagyi, MD3; Kelly K. Hunt, MD
JAMA Oncol. Published online March 17, 2016.              http://dx.doi.org:/10.1001/jamaoncol.2015.6478

Importance  We previously described and validated a breast cancer staging system (CPS+EG, clinical-pathologic scoring system incorporating estrogen receptor–negative disease and nuclear grade 3 tumor pathology) for assessing prognosis after neoadjuvant chemotherapy using pretreatment clinical stage, posttreatment pathologic stage, estrogen receptor (ER) status, and grade. Development of the CPS+EG staging system predated routine administration of trastuzumab in patients with ERBB2-positive disease (formerly HER2 or HER2/neu).

Objective  To validate the CPS+EG staging system using the new definition of ER positivity (≥1%) and to develop an updated staging system (Neo-Bioscore) that incorporates ERBB2 status into the previously developed CPS+EG.

Design, Setting, and Participants  Retrospective review of data collected prospectively from January 2005 through December 2012 on patients with breast cancer treated with neoadjuvant chemotherapy at The University of Texas MD Anderson Cancer Center.

Main Outcomes and Measure  Prognostic scores were computed using 2 versions of the CPS+EG staging system, one with ER considered positive if it measured 10% or higher, the other with ER considered positive if it measured 1% or higher. Fits of the Cox proportional hazards model for the 2 sets of prognostic scores were compared using the Akaike Information Criterion (AIC). Status of ERBB2 was added to the model, and the likelihood ratio test was used to determine improvement in fit.

Results  A total of 2377 patients were included; all were women (median age, 50 years [range, 21-87 years]); ER status was less than 1% in 28.9%, 1% to 9% in 8.3%, and 10% or higher in 62.8%; 591 patients were ERBB2 positive. Median follow-up was 4.2 years (range, 0.5-11.7 years). Five-year disease-specific survival was 89% (95% CI, 87%-90%). Using 1% or higher as the cutoff for ER positivity, 5-year disease-specific survival estimates determined using the CPS+EG stage ranged from 52% to 98%, thereby validating our previous finding that the CPS+EG score facilitates more refined categorization into prognostic subgroups than clinical or final pathologic stage alone. The AIC value for this model was 3333.06, while for a model using 10% or higher as the cutoff for ER positivity, it was 3333.38, indicating that the model fits were nearly identical. The improvement in fit of the model when ERBB2 status was added was highly significant, with 5-year disease-specific survival estimates ranging from 48% to 99% (P < .001). Incorporating ERBB2 into the staging system defined the Neo-Bioscore, which provided improved stratification of patients with respect to prognosis.

Conclusions and Relevance  The Neo-Bioscore improves our previously validated staging system and allows its application in ERBB2-positive patients. We recommend that treatment response and biologic markers be incorporated into the American Joint Committee on Cancer staging system.

Transforming Breast Cancer Treatment

Landmark preclinical study cured lung metastases in 50 percent of breast cancers by making nanoparticles inside the tumor.

http://www.technologynetworks.com/news.aspx?ID=189462

A team of investigators from Houston Methodist Research Institute may have transformed the treatment of metastatic triple negative breast cancer by creating the first drug to successfully eliminate lung metastases in mice.

The majority of cancer deaths are due to metastases to the lung and liver, yet there is no cure. Existing cancer drugs provide limited benefit due to their inability to overcome biological barriers in the body and reach the cancer cells in sufficient concentrations. Houston Methodist nanotechnology and cancer researchers have solved this problem by developing a drug that generates nanoparticles inside the lung metastases in mice.

In this study, 50 percent of the mice treated with the drug had no trace of metastatic disease after eight months. That’s equivalent to about 24 years of long-term survival following metastatic disease for humans.

Due to the body’s own defense mechanisms, most cancer drugs are absorbed into healthy tissue causing negative side effects, and only a fraction of the administered drug actually reaches the tumor, making it less effective, said Mauro Ferrari, Ph.D, president and CEO of the Houston Methodist Research Institute. This new treatment strategy enables sequential passage of the biological barriers to transport the killing agent into the heart of the cancer. The active drug is only released inside the nucleus of the metastatic disease cell, avoiding the multidrug resistance mechanism of the cancer cells. This strategy effectively kills the tumor and provides significant therapeutic benefit in all mice, including long-term survival in half of the animals.

This finding comes 20 years after Ferrari started his work in nanomedicine. Ferrari and Haifa Shen, M.D., Ph.D., are co-senior authors on the paper, which describes the action of the injectable nanoparticle generator (iNPG), and how a complex method of transporting a nano-version of a standard chemotherapy drug led to never before seen results in mice models with triple negative breast cancer that had metastasized to the lungs.

“This may sound like science fiction, like we’ve penetrated and destroyed the Death Star, but what we discovered is transformational. We invented a method that actually makes the nanoparticles inside the cancer and releases the drug particles at the site of the cellular nucleus. With this injectable nanoparticle generator, we were able to do what standard chemotherapy drugs, vaccines, radiation, and other nanoparticles have all failed to do,” said Ferrari.

Houston Methodist has developed good manufacturing practices (GMP) for this drug and plans to fast-track the research to obtain FDA-approval and begin safety and efficacy studies in humans in 2017.

“I would never want to overpromise to the thousands of cancer patients looking for a cure, but the data is astounding,” said Ferrari, senior associate dean and professor of medicine, Weill Cornell Medicine. “We’re talking about changing the landscape of curing metastatic disease, so it’s no longer a death sentence.”

The Houston Methodist team used doxorubicin, a cancer therapeutic that has been used for decades but has adverse side effects to the heart and is not an effective treatment against metastatic disease. In this study, doxorubicin was packaged within the injectable nanoparticle generator that is made up of many components.

Shen, a senior member of the department of nanomedicine at Houston Methodist Research Institute, explains that each component has a specific and essential role in the drug delivery process. The first component is the nanoporous silicon material that naturally degrades in the body. The second component is a polymer made up of multiple strands that contain doxorubicin. Once inside the tumor, the silicon material degrades, releasing the strands. Due to natural thermodynamic forces, these strands curl-up to form nanoparticles that are taken up by the cancer cells. Once inside the cancer cells, the acidic pH close to the nucleus causes the drug to be released from the nanoparticles. Inside the nucleus, the active drug acts to kill the cell.

“If this research bears out in humans and we see even a fraction of this survival time, we are still talking about dramatically extending life for many years. That’s essentially providing a cure in a patient population that is now being told there is none,” said Ferrari, who holds the Ernest Cockrell Jr. Presidential Distinguished Chair and is considered one of the founders of nanomedicine and oncophysics (physics of mass transport within a cancer lesion).

The Houston Methodist team is hopeful that this new drug could help cancer physicians cure lung metastases from other origins, and possibly primary lung cancers as well.

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Rapid regression of HER2 breast cancer

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Anti-HER2 Combo Shrunk Breast Tumors in Under 2 Weeks

Translating genetic drivers into new targeted therapies for breast cancer
Speaker: D. Tripathy (USA)
Key Objectives

Translating Genetic Drivers into New Targeted Therapies for Breast Cancer

Key Objectives

Objective 1: To review critical genomic drivers of breast carcinogenesis

Objective 2: To describe resistance drivers and evolutionary changes that develop under treatment pressure

Objective 3: To understand the rationale, early results, and future clinical applications of targeted biological therapies for breast cancer

 

The role of tumour typing and grading
Speaker: M.P. Foschini (Italy)
Key Objectives

1) Explain the importance of histotyping, with special focus on low grade tumours and on triple negative low grade tumours.
2) Explain the prognostic importance of correct grading on surgical specimens.
3) Explain the value and limits of grading and histotyping on pre-operative biopsies.

 

“This has groundbreaking potential because it allows us to identify a group of patients who, within 11 days, have had their tumors disappear with anti-HER2 therapy alone and who potentially may not require subsequent chemotherapy,” said researcher Nigel Bundred, MD, professor of surgical oncology at the University of Manchester in the United Kingdom, in a statement. “This offers the opportunity to tailor treatment for each individual woman.”

Following initial news reports of the EPHOS-B trial, the authors earlier today issued a statement urging caution in interpreting the results: “While we do not wish to downplay the significance of the findings,” they wrote, “we wish to emphasize that our research has shown this treatment to be suitable for a group of women with a particular type of breast cancer. We have no evidence that it would be effective for anything other than patients with newly diagnosed, HER2-positive breast tumors.”

The trial was split into two parts and included 257 newly diagnosed, operable, HER2-positive breast cancer patients.

In the first part of the trial, 130 patients were randomized to a control group that received no pre-operative treatment, or to one of three treatment arms that received therapy for 11 days prior to surgery: trastuzumab alone, lapatinib alone, or the combination of trastuzumab and lapatinib. All patients were treated with standard of care after surgery.

In the second part of the trial, 127 patients were randomized to receive trastuzumab alone (n = 32), the combination of trastuzumab and lapatinib (n = 66), or a control group that received no pre-operative treatment (n = 29). Results from this part of the trial showed that in patients who received the combination treatment, 11% had a pathologic complete response (pCR) and 17% had minimal residual disease (MRD). In patients who received trastuzumab alone, none had a pCR and only 3% had MRD. No patient in the control group had either a pCR or MRD. Patients in the combination treatment arm also had a reduction in Ki67, a marker of apoptosis.

Median age of patients in the trial was 52 years, 48% of women had tumors greater than 2 cm, and 51% were grade 3 as assessed by biopsy.

“These results show that we can get an early indication of pathologic response within 11 days, in the absence of chemotherapy, in these patients on combination treatment. Most previous trials have only looked at the pathologic response after several months of treatment,” said Judith Bliss, MD, of the Institute of Cancer Research in London and Vice-Chair of the UK Breast Intergroup, who took part in the clinical trial, at a press conference.

The study researchers emphasized that these results need to be confirmed in larger trials.

“This study proposes a simple way to identify those patients very early on, which could help spare them unnecessary chemotherapy. What is now indispensable is to confirm if these early responses translate into better or equal long-term survival,” said Fatima Cardoso, MD, chair of EBCC-10 and director of the breast unit at the Champalimaud Clinical Centre in Lisbon, in a statement.

The EPHOS-B trial was funded by Cancer Research UK and GlaxoSmithKline.

 

Breast Cancer Drug Combination Could Shrink Tumors in Days

Seth Augenstein, Digital Reporter    http://www.biosciencetechnology.com/news/2016/03/breast-cancer-drug-combination-could-shrink-tumors-days

A combination of breast cancer drugs administered before surgery could drastically shrink particular tumors within days – and potentially eliminate the need for chemotherapy in some patients, according to British researchers.

Herceptin (trastuzumab) in concert with lapatinib on tumors that are HER-2 positive can shrink or even destroy tumors within just 11 days before surgery, according to The Institute of Cancer Research in London.

Some 20 percent of all breast cancers are HER-2 positive, according to analysis by the Mayo Clinic.

The theory was the two drugs would work as a one-two punch: the Herceptin would block the HER-2 proteins on which the tumors rely, and then the lapatinib would inhibit other enzymes that may potentially remain unaffected by the other drug.

The study observed the tumor size in 257 women in the days-long window between diagnosis and removal of the tumors.

The participants were initially split up into three groups – one each getting one of the drugs, and a third getting no treatment for the 11 days before the surgery, according to the scientists.

However, other trials had indicated the drug combination could have a dramatic effect, so additional women were put in the lapatinib group and also given the Herceptin.

Roughly a quarter of the 66 women who got both drugs had tumors that were too small for the second measurement before surgery, they found.

“Our trial set out to try to use the window between diagnosis and surgery to find clues that combined treatment with (Herceptin) and lapatinib was having a biological effect on HER-2 positive tumors,” said Judith Bliss, director of the Cancer Research Clinical Trials and Statistics Unit at the Institute of Cancer Research. “So it was unexpected to see quite such dramatic responses to the (Herceptin) and lapatinib within 11 days.”

The results were presented at the European Breast Cancer Conference on Thursday.

“These results are very promising if they stand up in the long run and could be the starting step of finding a new way to treat HER-2 positive breast cancers,” said Arnie Purushotham, senior clinical adviser at Cancer Research UK.

 

Breast cancer cells stained for DNA (red), NFkB (green), and a reactive oxygen species probe (blue). Julia Sero the ICR, 2011

Breast cancer cells stained for DNA (red), NFkB (green), and a reactive oxygen species probe (blue) (photo: Julia Sero/the ICR)

 

A drug combination – of lapatinib and trastuzumab (Herceptin) – before surgery shrinks and may even destroy tumours in women with HER2 positive disease within 11 days, according to new research.

The EPHOS B trial, led by researchers at The Institute of Cancer Research, London, the University of Manchester and University Hospital of South Manchester NHS Foundation Trust, studied 257 women with HER2 positive breast cancer in the short gap between initial diagnosis and surgery to remove their tumours.

The research may lead to fewer women needing chemotherapy.

The results, from a Cancer Research UK-funded trial, are being presented at the 10th European Breast Cancer Conference (EBCC10) today (Thursday).

In the trial, women were split into three groups and treated for 11 days before their surgery. Initially, women were randomised to receive either trastuzamab, or lapatinib or no treatment – but halfway through the trial, after evidence emerged from other trials of the effectiveness of the combination, the design was altered so that additional women allocated to the lapatinib group were also prescribed trastuzumab.

Official 10th European Breast Cancer Conference (EBCC-10)

Statement on EPHOS-B (lapatinib/trastuzumab combination) trialLead researchers: Prof. Judith Bliss, Prof. Nigel  Bundred, Prof. David Cameron

We wish to emphasise that our research has shown this treatment to be suitable for a group of women with a particular type of breast cancer. We have no evidence that it would be effective for anything other than patients with newly-diagnosed, HER2 positive breast tumours. In addition, we do not yet know what effect the treatment will have on long-term survival.  While we do not wish to downplay the significance of the findings, we also urge caution in their interpretation.  Further trials will be needed before we can confirm these results, even in HER2 positive patients.

 

Breast Cancer Vaccines and Checkpoint-Inhibitor Immunotherapy

Q&A | March 15, 2016 | MBCC 2016, Breast Cancer
By Elizabeth A. Mittendorf, MD, PhD

Elizabeth A. Mittendorf, MD, PhD
As part of our coverage of the 33rd Annual Miami Breast Cancer Conference, held March 10-13 in Miami Beach, Florida, we spoke with Elizabeth A. Mittendorf, MD, PhD, associate professor at the department of breast surgical oncology at the University of Texas MD Anderson Cancer Center in Houston, Texas, who presented at the meeting on cancer vaccines and checkpoint inhibitors.
Cancer Network: How has being both a surgeon and immunologist, shaped your views of the potential clinical roles of cancer vaccines?

Dr. Mittendorf: As a surgeon, I see and treat patients with early-stage breast cancer that is potentially curable. Unfortunately, despite our best treatment—surgery, chemotherapy when indicated, radiation if required—we still see recurrences in up to 20% of these patients. I think it is not unreasonable to hypothesize that this recurrence is in part attributable to a failure of the immune response against the cancer—hence my enthusiasm for vaccines that could potentially augment that antitumor immunity, thereby decreasing the risk of recurrence.

Cancer Network: In what settings do breast cancer vaccines show the most promise?

Dr. Mittendorf: Secondary prevention. There is currently one vaccine that is being investigated in a phase III trial—NeuVax—which is made up of an immunogenic peptide combined with an immunoadjuvant. The trial is vaccinating patients in the adjuvant setting with the goal being to determine if vaccination can decrease the risk of recurrence.

Cancer Network: Is there reason for optimism that cancer vaccines might prove useful against advanced breast cancers?

Dr. Mittendorf: In my opinion, vaccines as monotherapy are not likely to be successful in advanced breast cancer. With that said, it is possible that vaccines could be administered as part of a combination strategy with other drugs that could augment the immune response such as certain chemotherapy regimens, trastuzumab, or other immunomodulatory drugs such as the checkpoint blockade agents.

Cancer Network: What insights do epidemiologic studies, such as those regarding childhood infections and cancer risk, offer for cancer immunotherapy?

Dr. Mittendorf: There is epidemiologic data to suggest that individuals who have had childhood infections (ie, chicken pox, pertussis, and other febrile illnesses) have a decreased risk of developing cancer. It is likely that these individuals develop adaptive immune responses against epithelial antigens. These responses could be augmented in the setting of a premalignant condition (ie, a colonic adenoma, or ductal carcinoma in situ), thereby tipping the scales back in favor of the immune response, leading to elimination of the threat of malignancy.

Cancer Network: Are the KEYNOTE trial reports to date reason for optimism about immune checkpoint blockade’s potential against breast cancer?

Dr. Mittendorf: Absolutely. These trials have confirmed that pembrolizumab (anti-PD-1 antibody) is fairly well tolerated by breast cancer patients and suggest some clinical activity. Through the portfolio of KEYNOTE trials, which have enrolled the different subtypes of breast cancer, we’re likely to learn more about which subtypes of breast cancer are most likely to respond to pembrolizumab as monotherapy, which in turn would suggest which subtypes might need additional immune stimulation (ie, a combination strategy) in order for the checkpoint blockade agent to be effective.

Cancer Network: What is the significance of PD-L1 expression in tumor cells vs the tumor microenvironment?

Dr. Mittendorf: Whether PD-L1 expression on the tumor cells is required for response to anti-PD-1 or anti-PD-L1 therapy remains a subject of much discussion. Data from the JAVELIN trial presented at the San Antonio Breast Cancer Symposium in December suggested that PD-L1 expression on the tumor was less important than PD-L1 expression on immune cells in the microenvironment—what they referred to as “immune hotspots.”

Cancer Network: Do you anticipate clinical roles for checkpoint blockade in secondary prevention? Breast cancer treatment in combination with other agents, like trastuzumab? (Are there other promising combinations? Do you anticipate immunotherapy combinations that exploit different immune system pathways?)

Dr. Mittendorf: I see a potential role for checkpoint blockade in the adjuvant setting (effectively secondary prevention) in high-risk patients in whom the risk/benefit ratio favors using these agents, which do have some toxicity associated with them. As an example, the SWOG cooperative group is developing a trial that will evaluate pembrolizumab in patients with triple-negative breast cancer who have at least 1 cm of tumor or positive lymph nodes after neoadjuvant chemotherapy. With respect to using in combination with other agents—yes; in fact the PANACEA trial currently accruing in Europe is combining pembrolizumab with trastuzumab in patients with HER2-positive metastatic breast cancer.

http://www.cancernetwork.com/mbcc-2016/breast-cancer-vaccines-and-checkpoint-inhibitor-immunotherapy#sthash.UenTvjsF.dpuf

 

 

Prognostic DCIS Score: ‘Ready for Prime Time’

News | March 14, 2016 | MBCC 2016, Breast Cancer
By Bryant Furlow
Not all ductal carcinoma in situ (DCIS) is dangerous, and the prognostic genomic Oncotype DX DCIS Score allows for routine risk stratification of patients to avoid unnecessary treatment, reported Patrick I. Borgen, MD, chair of the department of surgery at Maimonides Medical Center in Brooklyn, New York. Dr. Borgen spoke at the 33rd Annual Miami Breast Cancer Conference, held March 10–13 in Miami Beach, Florida.
Recent jumps in DCIS diagnoses have been driven by overdetection. “There’s a reservoir of DCIS in the female breast that was never going to become invasive—or would do so, so slowly that it was never going to threaten our patient,” Dr. Borgen noted.

Graphing the utilization of mammography over time, one sees that it “completely parallels the increase in DCIS diagnoses,” Dr. Borgen said. “There’s a similar slope of percent-change over time for DCIS and mammography screening. That either means the mammograms are causing DCIS, or, much more likely, that some of this [DCIS] was not going to become clinically relevant.”

When more sensitive digital mammography became more widely used, DCIS rates jumped again, he added. “Better imaging, more DCIS.”

The prevalence of occult DCIS in autopsy studies is “about an order of magnitude higher” than what we see in screening studies, Dr. Borgen noted, as further evidence for subclinical DCIS.

Thanks to landmark prospective randomized studies like the National Surgical Adjuvant Breast and Bowel Project (NSABP) B-17 study, the standard of care for DCIS is lumpectomy and radiation. Those studies did not identify subsets of patients who failed to benefit from radiation, but they did find that 80% of patients would do well with surgery alone. “We focus on the 10% who do better with radiotherapy, but 10% recur despite radiotherapy. The challenge is, how do we find the 80% of patients who, much later—15, 20, 25 years later—are going to be well?”

Nomograms “leave significant room for improvement,” he noted. “It is possible that clinical parameters alone are insufficient to predict outcome. We have moved away from morphology—from looking down a microscope to determine whether it’s a bad lesion.”

Instead, the field has turned to prognostic analyses of DCIS genomics.

“The Oncotype DX DCIS Score isn’t a mathematical model and doesn’t require bootstrapping,” he said. “It looks at DCIS genomics in the patient in front of you—a subset of the 21-gene assay that we use routinely.”

It has been validated in the Eastern Cooperative Oncology Group (ECOG) E5194 and Ontario DCIS Cohort studies for recurrence prognostication and risk stratification of women with DCIS who underwent breast-conserving surgery and had negative margins.

“I would argue that it’s ready for prime time” in routine clinical use, Dr. Borgen told attendees.

The DCIS Score divides patients into low, intermediate, and high-risk DCIS categories, with 65% of patients falling into the low-risk group, meaning that at 10 years, they face a 4% chance of developing invasive breast cancer.

Dr. Borgen noted that the addition of radiation doesn’t diminish the DCIS Score’s predictability. “The DCIS Score is associated with the risk of local recurrence in a population of patients with pure DCIS treated with breast-conserving surgery, with or without radiation. It’s almost certain there’s a very high-risk cohort of the disease, as well, and those patients may benefit from an entirely different treatment.”

http://www.cancernetwork.com/mbcc-2016/prognostic-dcis-score-ready-prime-time

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Circulating Protein Breast Carcinoma Biomarkers

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Circulating Protein Biomarkers a Boon to Breast Cancer Management

Immunoassays Are the Gold Standard for Measuring Soluble Breast-Cancer-Related Proteins

Mary F. Lopez, Ph.D

http://www.genengnews.com/insight-and-intelligence/circulating-protein-biomarkers-a-boon-to-breast-cancer-management/77900557/

 

Circulating Protein Biomarkers a Boon to Breast Cancer Management

http://www.genengnews.com/media/images/AnalysisAndInsight/Nov4_2015_MaryLopez_HER2Oncoprotein2272426032.jpg

HER-2 is an oncogene and a member of the human epidermal growth factor receptor (HER/EGFR/ERBB) family. Amplification or overexpression of HER-2 plays an important role in the development and progression of certain aggressive types of breast cancer.

 

Breast cancer patients often display elevated levels of proteins in plasma or serum, and many of these proteins correlate to active or recurrent disease, metastasis, prognosis, and therapeutic response. Several of these markers have demonstrated clinical utility, particularly in the area of monitoring disease recurrence after or during therapeutic treatment in advanced disease.

The application of immunoassays to monitor levels of breast-cancer-related proteins in blood or serum is complementary to other diagnostics such as imaging and can be a valuable part of the routine management of disease. The availability of a group of easily applied blood tests is a convenient and powerful addition to the arsenal of technologies available to physicians for patient management. Immunoassays are available for serum-borne breast-cancer-related markers such as cancer antigen 15-3 (CA 15-3), carcinoembryonic antigen (CEA), tissue inhibitor of metalloproteinases-1 (TIMP-1), and human epidermal growth factor receptor 2 (HER2)—all of which are discussed in this article.

Clinical Utility Considered by Multiple Studies 

While essential for diagnosis and typing, tissue testing during long-term breast cancer management is impractical, costly, and painful for patients. A growing number of studies support serum-based immunoassay testing to monitor drug response, disease progression, and potential for metastases.

In 2012, Tsai et al.1 studied serum levels of HER2 and TIMP-1 in 185 breast cancer patients in Taiwan. They concluded that TIMP-1 was significantly associated with serum HER2-positive status in circulation, as well as poorer disease-free survival—suggesting that monitoring both of these biomarkers may be beneficial.

In the same year, Kontani et al.2 reported that serum HER2 is a useful biomarker not only for detecting breast cancer recurrence but also for predicting tumor responses to trastuzumab. In 2014, Shao et al.3 found that elevated serum HER2 levels were significantly associated with short-term response to trastuzumab treatment. The median progression-free survival was significantly longer in patients with low levels of serum HER2. Furthermore, they found that over time patients with remaining low serum HER2 levels or those who achieved low serum HER2 levels after treatment had significantly longer progression-free survival than those whose levels remained high or converted from low to high.

In 2015, Di Gioia et al.4 reported that they had investigated the combination of CEA, CA 15-3, and serum HER2 in the pretherapeutic serum of 241 patients as biomarkers for prognosis in early breast cancer. Their retrospective analysis confirmed that serum HER-2 and CA15-3 (but not CEA) were independent and better prognostic tools than HER-2 in tissue. However, they concluded that prospective validation is necessary to confirm usefulness in routine clinical practice.

In a review published in 2015, Ravelli et al.5 discussed the advantages, drawbacks, and new insights with respect to measuring circulating breast-cancer-related biomarkers with immunoassays as compared to standard tissue-based biopsies. They suggested that a reliable panel of circulating cancer biomarkers would be helpful for the following tasks:

  1. Screening and diagnostic procedures
  2. Predicting prognosis
  3. Selecting therapeutic options, including experimental ones
  4. Detecting a lack of efficacy of an ongoing therapy and predicting side-effects
  5. Identifying recurrence

In this review, the authors emphasized “classic” markers such as CA 15-3, CEA, and serum HER2. With respect to CA 15-3 and CEA, the authors noted that they might be most useful in combination. “[More] reliable prediction power have been obtained with the combination of the two biomarkers, whereas when measured singularly, both sensitivity and specificity values were drastically decreased,” the authors wrote. “As a result, the association of the two markers may be a useful independent tool in the follow-up of [breast cancer] patients.”

In their discussion of HER2, the researchers pointed out that increased serum HER2 levels have been clearly associated with the tissue HER2 status, the presence and number of metastases, and the levels of CA 15-3 and CEA.

Utility Strongly Suggested by a Large Study  

The review cited a 2014 study that reported how 2,862 primary breast cancer patients had been monitored to demonstrate the correlation between serum HER2 and tissue HER2 overexpression.6This study showed that 15% of tissue-HER2-positive patients also had increased serum HER2 levels and that there was a linear correlation with the increased aggressiveness of tumors. Multivariate analysis confirmed that increased serum HER2 is an independent prognostic factor that can be clinically useful, particularly in patients with tissue-HER2-positive tumors.

The authors of the study concluded that measuring serum HER2 could help oncologists monitor patient response to trastuzumab in the absence of tissue HER2. They added that further clinical validation would be worthwhile.

Summary

Basic immunoassay technology has been in place since the 1950s and has become the gold standard for clinical protein measurement due to high sensitivity and selectivity.7 Growing evidence suggests that these reliable, robust tests can provide valuable insights for physicians managing breast cancer treatment.

 

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Role of Progesterone in Breast Cancer Progression

Author: Tilda Barliya PhD

Breast Cancer has been long discussed herein focusing on different aspects of the diseases: from diagnosis and all the way up to treatment modalities (I). The literature has put a lot of emphasis on the role of Estrogen receptor in the development of breast cancer, yet not much focus was placed on the counterpart partner–Progesterone Receptor.

Progesterone:

Progesterone is secreted by the empty egg follicle after ovulation has occurred. It is highest during the last phases of the menstrual cycle, after ovulation. Progesterone causes the endometrium to secrete special proteins to prepare it for the implantation of a fertilized egg (2). If conception has occurred, progesterone becomes the major hormone supporting pregnancy, with many important functions:

  • Responsible for the growth and maintenance of the endometrium
  • Suppresses further maturation of eggs by preventing release of LH and FSH (Follicle Stimulating Hormone).
  • By relaxing the major muscle of the uterus, progesterone prevents early contractions and birth.
  • It thicken the muscle, helping the body prepare for the hard work of labor.
  • Suppresses prolactin (the primary hormone of milk production), preventing lactation until birth

A recent review by Prof. Cathrin Brisken from ISREC- Swiss Institute for Experimental Cancer Research, summarizes and highlights the important role of progesterone in breast cancer progression (1). So where do we stand?

“The ovarian steroid hormones, 17β‑oestradiol and progesterone, are pivotal in the control of breast development and physiology, and both experimental and  epidemiological studies indicate that the two hormones are intimately linked to mammary carcinogenesis”.

“Ever since the 1960s,  pharmacological antagonists of both estrogen and progesterone were developed. PR antagonists failed in the clinic because of severe side effects, such as liver toxicity. By contrast, drugs that interfere with estrogen signalling, such as tamoxifen and aromatase inhibitors have become mainstays of breast cancer therapy; they substantially prolong survival and have saved many lives”.

Agonists for both receptors have been developed and are used for both contraception and hormone replacement therapy (HRT), but there are growing concerns that they may increase breast cancer risk. Women receiving HRT have little or no increase in breast cancer risk when taking estrogens only, in fact there may even be a protective effect (1,3).

“By contrast, a substantial increase in breast cancer risk was noticed in women taking combinations of an estrogen and various synthetic progesterone agonists (progestins). This could be related to the increase in cell proliferation in the breast epithelium that has been reported with combination therapy”. These results however differ between women who took natural progesterone and those who received the synthetic form- progestin, which may be due to the fact that progestin may bound other nuclear receptors (i.e androgen and glucocorticoid receptors). Other factors aside from progesterone may advances this higher risk for HRT-related breast cancer and include for example breast density (fatty pad density).

Cellular Mechanism:

“Across species, ERα and PR are absent from the myoepithelial cells and basal cells and are expressed by 30–50% of the luminal cells. Most cells co-express ERα and PR, which is consistent with PR being an ERα target. A small subset of cells expresses either only ERα or only PR”.  It was found that cells that are either or both hormone receptor(s) positive may affect neighboring cells in a paracrine fashion by secreting signalling and proliferating factors . Some of the attractive target genes of this hormones include but excluded to WNT, fibroblast growth factors (FGF), epidermal growth factor (EGF) as well as direct intercellular signalling mediated by Notch, ephrins or gap junctions.

Hormone Receptor (HR)+ cells seem to act as ‘sensor’ cells that translate the signals encoded by systemic hormones into local paracrine signals. To relay these signals they secrete paracrine factors that bind to receptors on HR–, luminal and basal cells, which act as the ‘secondary responder cells”.

This organizing principle ensures that the signal is amplified and prolonged in time and provides a means of coordinating different biological functions of distinct cell types.

Several experiments in MCF-7 cells showed that if a cell had recently been stimulated by estrogens it would be hormone receptor (HR)–. More so, later experiments showed that the HR expression, rather positive or negative, is a hallmark of a distinct cell type in the mammary epithelium.

There are many alternations in global gene expressions and protein factors during each menstrual cycle and more over in the life time of a woman. The entire sum of changes in the different cell population determine the proliferation and development of breast cancer.

There are two types of proliferation, cell-intrinsic and paracrine proliferation. For example, it was found in mice model, that the cell-intrinsic action of progesterone on HR+ cell proliferation requires cyclin D1. Whereas the proliferation of HR– cells does not (1).

Proliferation of HR– cells on progesterone stimulation requires RANKL, which is a tumour necrosis factor‑α (TNFα) family member. It was further noted that that RANKL is a crucial mediator of PR signalling function.

It is believed that recurrent activation of PR during repeated menstrual cycles and its downstream effectors, cyclin D1, WNT4 and RANKL promotes breast carcinogenesis (Fig.1). It was found for instance, that use of PR agonists or ectopic expression of RANKL induce mammary tumors in mice models.

Therefore, of clinical relevance  for example, soluble RANKL administered intravenously can elicit proliferation in the mammary epithelium, and systemic administration of its decoy receptor osteoprotegerin (OPG) can inhibit proliferation (1). There are obviously other genes associated with these phenotypes and the RANKL was given as an example.

Cathrin Brisken 2011

Novel preventive strategies are envisioned to PR itself and its downstream mediators. The new generation of selective progesterone receptor modulators (SPRMs)  used for gynaecological disorders, have fewer side effects than earlier ones, and are thought to be introduced as potential breast cancer therapy.

Reproductive hormones impinge on breast carcinogenesis at all stages and can determine whether the disease will progress (Fig 1). In particular, PR signalling has a pivotal role in controlling tumour promotion from the in situ stage onwards.

Clinical Aspect

Breast Cancers are generally divided into molecular subtypes which include:

  • Basal-like: ER-, PR- and HER2-; also called triple negative breast cancer (TNBC). Most BRCA1 breast cancers are basal-like TNBC.
  • Luminal A: ER+ and low grade
  • Luminal B: ER+ but often high grade
  • Luminal ER-/AR+: (overlapping with apocrine and so called molecular apocrine) – recently identified androgen responsive subtype which may respond to antihormonal treatment with bicalutamide.  
  • ERBB2/HER2+: has amplified HER2/neu.
  • Normal breast-like
  • Claudin-low: a more recently described class; often triple-negative, but distinct in that there is low expression of cell-cell junction protein including E-cadherin and frequently there is infiltration with lymphocytes.

NCCN 2007

Onitilo et al suggested this subgroups in their 7-year retrospective study(6):

  • ER/PR+, Her2+ = ER+/PR+, Her2+; ER−/PR+, Her2+; ER+/PR−, Her2+

  • ER/PR+, Her2− = ER+/PR+, Her2−; ER−/PR+, Her2−; ER+/PR−, Her2−

  • ER/PR−, Her2+ = ER−/PR−, Her2+

  • ER/PR−, Her2− = ER−/PR−, Her2−

The independent prognostic and predictive role of PR expression irrespective of ER has been a subject of great controversy.

In their study, Onitilo & colleagues have evaluated numerous patients for different factors such as five-year overall and disease-free survival, recurrent site and age, depending on their subgroups (6).

Their study supports other studies which have shown both the triple negative and Her2+/ER− subtypes to have poorer clinical, pathologic and molecular prognoses. The triple negative group has the worst overall and disease-free survival. More so the prognosis according to ER/PR status was found to be:

ER-positive/PR-positive tumors >> ER-positive/PR-negative tumors >>> ER-negative/PR-negative tumors.

But what happens with the ER-negative/PR positive group? How many patients fall into this category and how important that is? Could it be an artifact?

Maleki et al believes that in their study tumor that were initially reported as ER-negative/PR-positive are actually grade I (low grade) ER positive tumors such as infiltrating lobular carcinoma and colloidal carcinoma (7).

Summary:

Reproductive hormones impinge on breast carcinogenesis at all stages and can determine whether the disease will progress. In particular, PR signalling has a pivotal role in controlling tumour promotion from the in situ stage onwards. It will therefore be a good opportunity to design new treatment strategies that include selective progesterone receptor inhibitors. Interfering with the breast-specific effects of increased serum progesterone levels may be an effective way to reduce their risk of dying of breast cancer without blocking all reproductive function.More so, the majority of the physicians and researchers would agree that more studies are necessary to refine IHC classification for better classification and clinical use.

Reference:

1. Cathrin Brisken. Progesterone signalling in breast  cancer: a neglected hormone coming  into the limelight. Nature Reviews Cancer June 2013, (13): 385-396. http://www.nature.com/nrc/journal/v13/n6/full/nrc3518.html

2. Nicole Galan RN. What is Progesterone? http://pcos.about.com/od/normalmenstrualcycle/f/Progesterone.htm

3. Anderson, G. L. et al. Conjugated equine oestrogen and breast cancer incidence and mortality in postmenopausal women with hysterectomy: extended follow-up of the Women’s Health Initiative randomised placebo-controlled trial. Lancet Oncol 2012. 13, 476–486.

4. MJ, Möller MF, DG, Niggemann B, Zänker KS and Entschladen F. Luminal and basal-like breast cancer cells show increased migration induced by hypoxia, mediated by an autocrine mechanism. BMC Cancer 2011, 11:158. http://www.biomedcentral.com/1471-2407/11/158

5. MCU Cheang, J Parker, K DeSchryver, J Snider, T Walsh, S Davies, A Prat, T Vickery, J Reed, B Zehnbauer, S Leung, D Voduc, T Nielsen, E Mardis, P Bernard, C Perou, and M Ellis. Luminal A vs. Basal-like Breast Cancer: time dependent changes in the risk of relapse in the absence of treatment. Cancer Research: December 15, 2012; Volume 72, Issue 24, Supplement 3. http://cancerres.aacrjournals.org/cgi/content/meeting_abstract/72/24_MeetingAbstracts/P6-07-10

6. Onitilo AA., Engel JM., Greenlee RT and Mukesh BN. Breast Cancer Subtypes Based on ER/PR and Her2 Expression: Comparison of Clinicopathologic Features and Survival. Clinical Medicine & Research  2009 June 1 7 (1-2); 4-13. http://www.clinmedres.org/content/7/1-2/4.long

7. Maleki Z., Shariat S., Mokri M and Atri M.  ER-negative /PR-positive Breast Carcinomas or Technical Artifacts in Immunohistochemistry? Arch Iran  Med. 2012; 15(6): 366 – 369. http://www.ams.ac.ir/AIM/NEWPUB/12/15/6/0010.pdf

Other articles from our Open Access Jounal:

I By: Larry Bernstein MD. “recurrence risk for breast cancer”. http://pharmaceuticalintelligence.com/2013/03/02/recurrence-risk-for-breast-cancer/

II. By: Ritu Saxena PhD. “In focus: Triple Negative Breast Cancer”. http://pharmaceuticalintelligence.com/2013/01/29/in-focus-triple-negative-breast-cancer/

III. By: Tilda Barliya PhD. The Molecular pathology of Breast Cancer Progression. http://pharmaceuticalintelligence.com/2013/01/10/the-molecular-pathology-of-breast-cancer-progression/

IV. By: Sudipta Saha PhD. The FEMALE reproductive system and the hypothalamic-pituitary-thyroid axis. http://pharmaceuticalintelligence.com/2012/12/11/the-female-reproductive-system-and-the-hypothalamic-pituitary-thyroid-axis/

V. By: Tilda Barliya PhD. Nanotech Therapy for Breast Cancer. http://pharmaceuticalintelligence.com/2012/12/09/naotech-therapy-for-breast-cancer/

 

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Combining Nanotube Technology and Genetically Engineered Antibodies to Detect Prostate Cancer Biomarkers

Writer, Curator: Stephen J. Williams, Ph.D.

acs nanoFigure of  Carbon Nanotube Transistor design with functionalized antibodies for biomarker detection.  From paper of A.T. Johnson; used with permission from A.T. Johnson)

In a literature review of the current status of the breast cancer biomarker field[2], author Dr. Michael Duffy, from University College Dublin, pondered the clinical utility of breast cancer serum markers and suggested that due to lack of sensitivity and specificity none of available markers is of value for detection of early breast cancer however these biomarkers have been shown useful in monitoring patients with advanced disease. For instance high preoperative CA15-3 is indicative of adverse patient outcome.  According to American Society of Clinical Oncology Expert Panel, however CA 15-3 may lack the sensitivity and disease specificity for breast cancer as a prognostic marker.  For panel suggestions please click on the link below:

http://www.asco.org/sites/www.asco.org/files/breast_tm_2007_changes-final.pdf

The same panel also concurred on the lack of prognostic value of other markers (for example CEA for colon cancer) but did agree that 66-73% of patients with advanced disease, who responded to therapy, showed reduction in these serum markers.  Indeed, CA125, long associated as a biomarker for ovarian cancer, does not have the sensitivity and especially the disease specificity to be a stand-alone prognostic marker[3].  Therefore, although “omics” strategies have suggested multiple possible biomarkers  for various cancers, a major issue in translating a putative biomarker to either:

1)      a clinically validated (panel) of disease-relevant biomarkers or

2)      biomarkers useful for therapeutic monitoring

is obtaining the specificity and sensitivity for detection in bio-specimens.   As discussed below, this is being achieved with the merger of nanotechnology-based sensors and bioengineering of biomolecule.

For ASCO panel suggestions of biomarkers useful in Prostate cancer please see the link below:

http://jco.ascopubs.org/site/misc/specialarticles.xhtml#GENITOURINARY_CANCER

As a side note, since 2010, ASCO has focused on reviewing and producing new guidelines for cancer biomarkers including genome sequencing:

http://www.medscape.com/viewarticle/723349

Osteopontin (OPN) and prostate cancer

Osteopontin is a phosphorylated glycoprotein secreted by activated macrophages, leukocytes, activated T lymphocytes and is present at sites of inflammation (for a review of OPN see [4]).  Osteopontin interacts with several integrins and CD44 (a putative cancer stem cell marker).  Binding of OPN to cell integrins mediates cell-matrix and cell-cell communication, stimulating adhesion, migration (through interaction with urokinase plasminogen activator {uPA}) and cell signaling pathways such as the HGF-Met pathway.  Overexpression is found on a variety of cancers including breast, lung, colorectal, ovarian and melanoma[5].  And although OPN is detected in normal tissue, it is known that OPN over-expression can alter the malignant potential of tumor cells.

Roles of osteopontin in cancer include:

  • Binding to CD44
  • Increase in growth factor signaling (HGF/Met pathway)
  • Increase uPA activity- increase invasiveness
  • Angiogenesis thru binding with αvβ3 integrin and increased VEGF expression
  • Protection against apoptosis: OPN activates nuclear factor Κβ

Some researchers have suggested it could be a prognostic marker for breast and lung cancer while there have been conflicting reports as to whether OPN expression is correlated to malignant potential in prostate cancer[6].  Osteopontin is found on tumor infiltrating macrophages, which may contribute to OPN as a prognostic marker. Breast cancer patients (disseminated carcinomas) have 4-10 times higher serum levels of OPN than found in healthy patients, although there is no difference in pre- or post-menopausal women[7].

Piezoelectric sensors have been used by the same group at Fox Chase Cancer Center to detect serum levels of the HER2 protein in breast cancer patients, for the purpose of therapeutic monitoring after anti-HER2 antibody trastuzumab (Herceptin™) therapy.  Lina Loo, in the laboratory of Dr. Gregory Adams showed the utility of using (scFv) to trastuzumab (anti-HER2) with pizo-electric nanotubes to accurately and reproducibly determine levels of serum HER2[8].  This method improved the sensitivity of serum HER2 detection over other methods such as:

  • ELISA {enzyme-linked immunoassay}
  • Luminex platforms

Please watch the following video interview concerning genetically engineered scFV antibody fragments and their use in cancer detection and treatment (with Dr. Matt Robinson and Dr. Greg Adams, from Fox Chase Cancer Center)

PLEASE WATCH VIDEO

However the advent of nanotechnology-based detection system combined with engineered affinity-based biomolecules has increased both the sensitivity and specificity of biomarker detection from complex fluids such as plasma and urine.  The advent of multiple types of biosensors, including

has given the ability to measure, with enhanced sensitivity and specificity,  putative biomarkers of disease in minute volumes of precious bio-samples.

The basic design of a biosensor is made of three components:

  1. A recognition element (I.e. antibodies, nucleic acids, enzymes)
  2. A signal transducer (electrochemical, optical, piezoelectric)
  3. Signal processor (relays and displays)

In the journal ACS Nano Mitchel Lerner from Dr. Charlie Johnson’s laboratory at University of Pennsylvania in collaboration with Fox Chase Cancer researchers in the laboratory of Dr. Matthew Robinson, describe a piezoelectric detection system for quantifying levels of osteopontin (OPN), a putative biomarker for prostate cancer[1].  In this paper Dr. Robinson’s group at Fox Chase, genetically engineered a single chain variable fragment (scFv) protein {the binding portion of the antibody} which had high affinity for OPN.  This scFv was attached to a carbon nanotube field-effect transistor (NT-FET), designed by Dr. Johnson’s group, using a chemical process called chemical functionalization {a process using diazonium salts to covalently attach scFV to NT-FET.

functionalization

Figure. Functionalization scheme for OPN attachment to carbon nanotubes. As figure 1 legend in paper states: “First, sp8 hybridized-sites are created o the nanotube sidewall by incubation in a diazonium salt solution.  The carboxylic acid group is then activated by EDC and stabilized with NHS.ScFv antibody displaces the NHS and forms an amide bond.  OPN epitope is shown in yellow and the C and N-terminuses are in orange and green respectively.” (used by permision for A.T. Charlie Johnson)

This system was then used to determine the selectivity and sensitivity of OPN from complex solutions.

Methods: 

Nanotube (NT) design

  • Grown by catalytic vapor deposition
  • Electrical contacts patterned using photo-lithography
  • Atomic Force microscopy was used to verify structure of nanotube

Chemical Linking of scFv to nanotube

  • Diazonium treatment resulted in activation and subsequent stabilization of amino (NHS) side chain
  • Amine group on lysine of scFV displaced NHS group => covalent attachment of scFV to NT
  • Atomic Force Spectroscopy used to verify linkage of scFv to nanotube

Results showed there was

  • minimal non-specific binding of OPN to the scFv
  • system allowed for detection limit of 1 pg/ml OPN (pictogram/milliliter) or 30 fM (fentomolar) in a phosphate buffered saline solution.
  •  Only a minute volume (10 µl) of sample is needed
  • Sensor able to measure million-fold  range of OPN concentrations ( from 10-3 to 103 ng/mL OPN)

Two experiments were conducted to determine the specificity of OPN to the antibody-detection system.

1st experiment

–          scFv functionalized  sensor was incubated in a solution of high concentration of BSA (450 mg/ml) to approximate nonspecific proteins in patient samples

–           minimal signal was detected

        2nd experiment

–          Functionalized NT-FET devices with a scFv based on the HER2 therapeutic antibody trastuzumab

–          There was no binding of OPN to anti-HER2 devices

–          Therefore anti OPN (23C3) scFv-functionalized carbon nanotube sensors exhibit high levels of specificity to OPN

The authors conclude “the functionalization procedure described here is expected to be generalizable to any antibody containing an accessible amine group, and to result in biosensors appropriate for detection of corresponding complementary proteins at fM concentrations”.

I had the opportunity to speak with co-author Dr. Matthew Robinson, Assistant Professor in the Developmental Therapeutics Program at Fox Chase Cancer Center about the next steps for this work.  Dr. Robinson mentioned that “at this point we have not looked in patient samples yet but our plan is to move in that direction. We need to establish sensitivity/specificity in increasingly complex samples (e.g. spiked normal serum and retrospectively in patient serum with known levels of biomarkers).” 

Cancer patients often present a complex metabolic profile.  The paper notes that OPN has a pI (isoelectric point) of 4.2, which would result in a negative charge at physiologically normal pH of 7.6. I asked Dr. Robinson about if changes in metabolic profile could hinder OPN binding to the NT-FET system would require some preprocessing of blood samples.  Dr. Robinson  agreed “that confounding variables such as additional diseases but even things like diet (i.e. is fasting necessary) need to be addressed before this platform is ready for use in clinical setting.
It is likely that sample prep will be needed to remove albumin, lower salt concentrations, etc. This could end up being problematic for biomarkers that are unstable and would degrade over the time necessary for sample prep. It is also possible that sample prep to remove albumin and other background factors could result in loss of biomarkers. This will need to be determined on a case-by-case basis with validated testing methods.”
One useful advantage of this system is the possibility of measuring multiple biomarkers, clinically important as studies has suggested that

multiple markers result in the higher sensitivity/specificity for many infrequent cancers, such as ovarian. Dr. Robinson agrees “that panels of biomarkers are likely to be better at early detection and diagnosis. In principle the platform that we describe can be set up to allow for detection of  multiple biomarkers at a time. From the biology end of things we have built antibodies against 3 different prostate cancer biomarkers for that purpose.”

Dr. Johnson  commented on the ability of the platform allowed for the simultaneous detection of multiple biomarkers, noting that ”the platform is compatible with the measurement of multiple biomarkers through the use of multiple devices, each functionalized with their own antibody.”

ASCO guidelines Expert Panel on Tumor Biomarkers 2007 Update for Breast Cancer:

http://www.asco.org/sites/www.asco.org/files/breast_tm_2007_changes-final.pdf 

ASCO Guidelines for Genitourinary Cancer:

Screening for Prostate Cancer With Prostate-Specific Antigen Testing: American Society of Clinical Oncology Provisional Clinical Opinion

Published in JCO, Vol. 30, Issue 24 (August 20), 2012: 3020-3025

American Society of Clinical Oncology Clinical Practice Guideline on Uses of Serum Tumor Markers in Adult Males With Germ Cell Tumors

Published in JCO, Vol 28, Issue 20 (July 10), 2010: 3388-3404

American Society of Clinical Oncology Endorsement of the Cancer Care Ontario Practice Guideline on Nonhormonal Therapy for Men With Metastatic Hormone-Refractory (castration-resistant) Prostate Cancer

Published in JCO, Vol 25, Issue 33 (November 20), 2007: 5313-5318

Initial Hormonal Management of Androgen-Sensitive Metastatic, Recurrent, or Progressive Prostate Cancer: 2006 Update of an American Society of Clinical Oncology Practice Guideline

Published in JCO, Vol. 25, Issue 12 (April 20), 2007: 1596-1605

References:

1.            Lerner MB, D’Souza J, Pazina T, Dailey J, Goldsmith BR, Robinson MK, Johnson AT: Hybrids of a genetically engineered antibody and a carbon nanotube transistor for detection of prostate cancer biomarkers. ACS nano 2012, 6(6):5143-5149.

2.            Duffy MJ: Serum tumor markers in breast cancer: are they of clinical value? Clinical chemistry 2006, 52(3):345-351.

3.            Meyer T, Rustin GJ: Role of tumour markers in monitoring epithelial ovarian cancer. British journal of cancer 2000, 82(9):1535-1538.

4.            Rodrigues LR, Teixeira JA, Schmitt FL, Paulsson M, Lindmark-Mansson H: The role of osteopontin in tumor progression and metastasis in breast cancer. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 2007, 16(6):1087-1097.

5.            Brown LF, Berse B, Van de Water L, Papadopoulos-Sergiou A, Perruzzi CA, Manseau EJ, Dvorak HF, Senger DR: Expression and distribution of osteopontin in human tissues: widespread association with luminal epithelial surfaces. Molecular biology of the cell 1992, 3(10):1169-1180.

6.            Thoms JW, Dal Pra A, Anborgh PH, Christensen E, Fleshner N, Menard C, Chadwick K, Milosevic M, Catton C, Pintilie M et al: Plasma osteopontin as a biomarker of prostate cancer aggression: relationship to risk category and treatment response. British journal of cancer 2012, 107(5):840-846.

7.            Brown LF, Papadopoulos-Sergiou A, Berse B, Manseau EJ, Tognazzi K, Perruzzi CA, Dvorak HF, Senger DR: Osteopontin expression and distribution in human carcinomas. The American journal of pathology 1994, 145(3):610-623.

8.            Loo L, Capobianco JA, Wu W, Gao X, Shih WY, Shih WH, Pourrezaei K, Robinson MK, Adams GP: Highly sensitive detection of HER2 extracellular domain in the serum of breast cancer patients by piezoelectric microcantilevers. Analytical chemistry 2011, 83(9):3392-3397.

Other posts from this site on Biomarkers, Cancer, and Nanotechnology include:

Stanniocalcin: A Cancer Biomarker.

Mesothelin: An early detection biomarker for cancer (By Jack Andraka)

Squeezing Ovarian Cancer Cells to Predict Metastatic Potential: Cell Stiffness as Possible Biomarker

PIK3CA mutation in Colorectal Cancer may serve as a Predictive Molecular Biomarker for adjuvant Aspirin therapy

Biomarker tool development for Early Diagnosis of Pancreatic Cancer: Van Andel Institute and Emory University

Early Biomarker for Pancreatic Cancer Identified

In Search of Clarity on Prostate Cancer Screening, Post-Surgical Followup, and Prediction of Long Term Remission

Prostate Cancer Molecular Diagnostic Market – the Players are: SRI Int’l, Genomic Health w/Cleveland Clinic, Myriad Genetics w/UCSF, GenomeDx and BioTheranostics

Early Detection of Prostate Cancer: American Urological Association (AUA) Guideline

A Blood Test to Identify Aggressive Prostate Cancer: a Discovery @ SRI International, Menlo Park, CA

Prostate Cancer Cells: Histone Deacetylase Inhibitors Induce Epithelial-to-Mesenchymal Transition

Prostate Cancer and Nanotecnology

 

Read Full Post »

Diagnostics and Biomarkers: Novel Genomics Industry Trends vs Present Market Conditions and Historical Scientific Leaders Memoirs

Larry H Bernstein, MD, FCAP, Author and Curator

This article has two parts:

  • Part 1: Novel Genomics Industry Trends in Diagnostics and Biomarkers vs Present Market Transient Conditions

and

  • Part 2: Historical Scientific Leaders Memoirs

 

Part 1: Novel Genomics Industry Trends in Diagnostics and Biomarkers vs Present Market Transient Conditions

 

Based on “Forging a path from companion diagnostics to holistic decision support”, L.E.K.

Executive Insights, 2013;14(12). http://www.LEK.com

Companion diagnostics and their companion therapies is defined here as a method enabling

  • LIKELY responders to therapies that are specific for patients with ma specific molecular profile.

The result of this statement is that the diagnostics permitted to specific patient types gives access to

  • novel therapies that may otherwise not be approve or reimbursed in other, perhaps “similar” patients
  • who lack a matching identification of the key identifier(s) needed to permit that therapy,
  • thus, entailing a poor expected response.

The concept is new because:

(1) The diagnoses may be closely related by classical criteria, but at the same time they are
not alike with respect to efficacy of treatment with a standard therapy.
(2) The companion diagnostics is restricted to dealing with a targeted drug-specific question
without regard to other clinical issues.
(3) The efficacy issue it clarifies is reliant on a deep molecular/metabolic insight that is not available, except through
emergent genomic/proteomic analysis that has become available and which has rapidly declining cost to obtain.

The limitation example given is HER2 testing for use of Herceptin in therapy for non-candidates (HER2 negative patients).
The problem is that the current format is a “one test/one drug” match, but decision support  may require a combination of

  • validated biomakers obtained on a small biopsy sample (technically manageable) with confusing results.

While HER2 negative patients are more likely to be pre-menopausal with a more aggressive tumor than postmenopausal,

  • the HER2 negative designation does not preclude treatment with Herceptin.

So the Herceptin would be given in combination, but with what other drug in a non-candidate?

The point that L.E.K. makes is that providing highly validated biomarkers linked to approved therapies, it is necessary to pursue more holistic decision support tests that interrogate multiple biomarkers (panels of companion diagnostic markers) and discovery of signatures for treatments that are also used with a broad range of information, such as,

  • traditional tests,
  • imaging,
  • clinical trials,
  • outcomes data,
  • EMR data,
  • reimbursement and coverage data.

A comprehensive solution of this nature appears to be a distance from realization.  However, is this the direction that will lead to tomorrows treatment decision support approaches?

 Surveying the Decision Support Testing Landscape

As a starting point, L.E.K. characterized the landscape of available tests in the U.S. that inform treatment decisions compiled from ~50 leading diagnostics companies operating in the U.S. between 2004-2011. L.E.K. identified more than 200 decision support tests that were classified by test purpose, and more specifically,  whether tests inform treatment decisions for a single drug/class (e.g., companion diagnostics) vs. more holistic treatment decisions across multiple drugs/classes (i.e., multiagent response tests).

 Treatment Decision Support Tests

Companion Diagnostics
Single drug/class
Predict response/safety or guide dosing of a single drug or class

HercepTest   Dako
Determines HER2 protein overexpression for Herceptin treatment selection

Multiple drugs/classes

Vysis ALK Break
Apart FISH
Abbott Labs Predicts the NSCLC patient response to Xalkori

Other Decision Support
Provide prognostic and predictive information on the benefit of treatment

Oncotype Dx    Genomic Health, Inc.
Predicts both recurrence of breast cancer and potential patient benefit to chemotherapy regimens

PML-RARα     Clarient, Inc.
Predicts response to all-trans retinoic acid (ATRA) and other chemotherapy agents

TRUGENE    Siemens
Measures resistence to multiple  HIV-1 anti-retroviral agents

Multi-agent Response

Inform targeted therapy class selection by interrogating a panel of biomarkers
Target Now  Caris Life Sciences
Examines tumor’s molecular profile to tailor treatment options

ResponseDX: Lung    Response Genetics, Inc.
Examines multiple biomarkers to guide therapeutic treatment decisions for NSCLC patients

Source: L.E.K. Analysis

Includes IVD and LDT tests from

  1. top-15 IVD test suppliers,
  2. top-four large reference labs,
  3. top-five AP labs, and
  4. top-20 specialty reference labs.

For descriptive purposes only, may not map to exact regulatory labeling

Most tests are companion diagnostics and other decision support tests that provide guidance on

  • single drug/class therapy decisions.

However, holistic decision support tests (e.g., multi-agent response) are growing the fastest at 56% CAGR.
The emergence of multi-agent response tests suggests diagnostics companies are already seeing the need to aggregate individual tests (e.g., companion diagnostics) into panels of appropriate markers addressing a given clinical decision need. L.E.K. believes this trend is likely to continue as

  • increasing numbers of  biomarkers become validated for diseases and multiplexing tools
  • enabling the aggregation of multiple biomarker interrogations into a single test

to become deployed in the clinic.

Personalized Medicine Partnerships

L.E.K. also completed an assessment of publicly available personalized medicine partnership activity from 2009-2011 for ~150 leading organizations operating in the U.S. to look at broader decision support trends and emergence of more holistic solutions beyond diagnostic tests.

Survey of partnerships deals was conducted for

  • top-10 academic medical centers research institutions,
  • top-25 biopharma,
  • top-four healthcare IT companies,
  • top-three healthcare imaging companies,
  • top-20 IVD manufacturers,
  • top-20 laboratories,
  • top-10 payers/PBMs,
  • top-15 personalized healthcare companies,
  • top-10 regulatory/guideline entities, and
  • top-20 tools vendors for the period of 01/01/2009 – 12/31/2011.
    Source: Company websites, GenomeWeb, L.E.K. analysis

Across the sample we identified 189 publicly announced partnerships of which ~65% focused on more traditional areas (biomarker discovery, companion diagnostics and targeted therapies). However, a significant portion (~30%) included elements geared towards creating more holistic decision support models.

Partnerships categorized as holistic decision support by L.E.K. were focused on

  • mining large patient datasets (e.g., from payers or providers),
  • molecular profiling (e.g., deploying next-generation sequencing),
  • creating information technology (IT) infrastructure needed to enable holistic decision support models and
  • integrating various datasets to create richer decision support solutions.

Interestingly, holistic decision support partnerships often included stakeholders outside of biopharma and diagnostics such as

  • research tools,
  • payers/PBMs,
  • healthcare IT companies as well as
  • emerging personalized healthcare (PHC) companies (e.g., Knome, Foundation Medicine and 23andMe).

This finding suggests that these new stakeholders will be increasingly important in influencing care decisions going forward.

Holistic Treatment Decision Support

Holistic Decision   Support Focus

Technology Provider Partners
Stakeholder Deploying the Solution

Holistic Decision
Support Activities
Molecular Profiling

Life Technologies

TGEN/US
Oncology

Sequencing of triple-negative breast  cancer patients to identify potential treatment strategies

Foundation Medicine

Novartis

Deployment of cancer genomics analysis platform to support Novartis clinical research efforts
Predictive genomics

Clarient, Inc.
(GE Healthcare)

Acorn
Research

Biomarker profiling of patients within Acorn’s network of providers to support clinical research efforts

GenomeQuest

Beth Israel Deaconess
Medical Center

Whole genome analysis and to guide patient management
Outcomes Data Mining

AstraZeneca

WellPoint

Evaluate comparative effectiveness of selected marketed therapies

23andMe

NIH

Leverage information linking drug response and CYP2C9/CYP2C19 variation

Pfizer

Medco

Leverage patient genotype, phenotype and outcome for treatment decisions and target therapeutics
Healthcare IT Infrastructure

IBM

WellPoint

Deploy IBM’s Watson-based solution to evidence-based healthcare decision-making support

Oracle

Moffitt Cancer Center

Deploy Oracle’s informatics platform to store and manage patient medical information
Data Integration

Siemens Diagnostics

Susquehanna Health

Integration of imaging and laboratory diagnostics

Cernostics

Geisinger
Health

Integration of advanced tissue diagnostics, digital pathology, annotated biorepository and EMR
to create solutions
next-generation treatment decision support solutions

CardioDx

GE Healthcare

Integration of genomics with imaging data in CVD

Implications

L.E.K. believes the likely debate won’t center on which models and companies will prevail. It appears that the industry is now moving along the continuum to a truly holistic capability.
The mainstay of personalized medicine today will become integrated and enhanced by other data.

The companies that succeed will be able to capture vast amounts of information

  • and synthesize it for personalized care.

Holistic models will be powered by increasingly larger datasets and sophisticated decision-making algorithms.
This will require the participation of an increasingly broad range of participants to provide the

  • science, technologies, infrastructure and tools necessary for deployment.

There are a number of questions posed by this study, but only some are of interest to this discussion:

Group A.    Pharmaceuticals and Devices

  •  How will holistic decision support impact the landscape ?
    (e.g., treatment /testing algorithms, decision making, clinical trials)

Group B.     Diagnostics and   Decision Support

  •   What components will be required to build out holistic solutions?

– Testing technologies

– Information (e.g., associations, outcomes, trial databases, records)

– IT infrastructure for data integration and management, simulation and reporting

  •  How can various components be brought together to build seamless holistic  decision support solutions?

Group C.      Providers and Payers

  •  In which areas should models be deployed over time?
  • Where are clinical and economic arguments  most compelling?

Part 2: Historical Scientific Leaders Memoirs – Realtime Clinical Expert Support

Gil David and Larry Bernstein have developed, in consultation with Prof. Ronald Coifman,
in the Yale University Applied Mathematics Program,

A software system that is the equivalent of an intelligent Electronic Health Records Dashboard that

  • provides empirical medical reference and
  • suggests quantitative diagnostics options.

The current design of the Electronic Medical Record (EMR) is a linear presentation of portions of the record

  • by services
  • by diagnostic method, and
  • by date, to cite examples.

This allows perusal through a graphical user interface (GUI) that partitions the information or necessary reports

  • in a workstation entered by keying to icons.

This requires that the medical practitioner finds the

  • history,
  • medications,
  • laboratory reports,
  • cardiac imaging and
  • EKGs, and
  • radiology in different workspaces.

The introduction of a DASHBOARD has allowed a presentation of

  • drug reactions
  • allergies
  • primary and secondary diagnoses, and
  • critical information

about any patient the care giver needing access to the record.

The advantage of this innovation is obvious.  The startup problem is what information is presented and

  • how it is displayed, which is a source of variability and a key to its success.

We are proposing an innovation that supercedes the main design elements of a DASHBOARD and utilizes

  • the conjoined syndromic features of the disparate data elements.

So the important determinant of the success of this endeavor is that

  • it facilitates both the workflow and the decision-making process with a reduction of medical error.

Continuing work is in progress in extending the capabilities with model datasets, and sufficient data because

  • the extraction of data from disparate sources will, in the long run, further improve this process.

For instance, the finding of  both ST depression on EKG coincident with an elevated cardiac biomarker (troponin), particularly in the absence of substantially reduced renal function. The conversion of hematology based data into useful clinical information requires the establishment of problem-solving constructs based on the measured data.

The most commonly ordered test used for managing patients worldwide is the hemogram that often incorporates

  • the review of a peripheral smear.

While the hemogram has undergone progressive modification of the measured features over time the subsequent expansion of the panel of tests has provided a window into the cellular changes in the

  • production
  • release
  • or suppression

of the formed elements from the blood-forming organ into the circulation. In the hemogram one can view

  • data reflecting the characteristics of a broad spectrum of medical conditions.

Progressive modification of the measured features of the hemogram has delineated characteristics expressed as measurements of

  • size
  • density, and
  • concentration,

resulting in many characteristic features of classification. In the diagnosis of hematological disorders

  • proliferation of marrow precursors, the
  • domination of a cell line, and features of
  • suppression of hematopoiesis

provide a two dimensional model.  Other dimensions are created by considering

  • the maturity of the circulating cells.

The application of rules-based, automated problem solving should provide a valid approach to

  • the classification and interpretation of the data used to determine a knowledge-based clinical opinion.

The exponential growth of knowledge since the mapping of the human genome enabled by parallel advances in applied mathematics that have not been a part of traditional clinical problem solving.

As the complexity of statistical models has increased

  • the dependencies have become less clear to the individual.

Contemporary statistical modeling has a primary goal of finding an underlying structure in studied data sets.
The development of an evidence-based inference engine that can substantially interpret the data at hand and

  • convert it in real time to a “knowledge-based opinion”

could improve clinical decision-making by incorporating

  • multiple complex clinical features as well as duration of onset into the model.

An example of a difficult area for clinical problem solving is found in the diagnosis of SIRS and associated sepsis. SIRS (and associated sepsis) is a costly diagnosis in hospitalized patients.   Failure to diagnose sepsis in a timely manner creates a potential financial and safety hazard.  The early diagnosis of SIRS/sepsis is made by the application of defined criteria by the clinician.

  • temperature
  • heart rate
  • respiratory rate and
  • WBC count

The application of those clinical criteria, however, defines the condition after it has developed and

  • has not provided a reliable method for the early diagnosis of SIRS.

The early diagnosis of SIRS may possibly be enhanced by the measurement of proteomic biomarkers, including

  • transthyretin
  • C-reactive protein
  • procalcitonin
  • mean arterial pressure

Immature granulocyte (IG) measurement has been proposed as a

  • readily available indicator of the presence of granulocyte precursors (left shift).

The use of such markers, obtained by automated systems

  • in conjunction with innovative statistical modeling, provides
  • a promising approach to enhance workflow and decision making.

Such a system utilizes the conjoined syndromic features of

  • disparate data elements with an anticipated reduction of medical error.

How we frame our expectations is so important that it determines

  • the data we collect to examine the process.

In the absence of data to support an assumed benefit, there is no proof of validity at whatever cost.
This has meaning for

  • hospital operations,
  • for nonhospital laboratory operations,
  • for companies in the diagnostic business, and
  • for planning of health systems.

The problem stated by LL  WEED in “Idols of the Mind” (Dec 13, 2006): “ a root cause of a major defect in the health care system is that, while we falsely admire and extol the intellectual powers of highly educated physicians, we do not search for the external aids their minds require”.  HIT use has been

  • focused on information retrieval, leaving
  • the unaided mind burdened with information processing.

We deal with problems in the interpretation of data presented to the physician, and how through better

  • design of the software that presents this data the situation could be improved.

The computer architecture that the physician uses to view the results is more often than not presented

  • as the designer would prefer, and not as the end-user would like.

In order to optimize the interface for physician, the system would have a “front-to-back” design, with
the call up for any patient ideally consisting of a dashboard design that presents the crucial information

  • that the physician would likely act on in an easily accessible manner.

The key point is that each item used has to be closely related to a corresponding criterion needed for a decision.

Feature Extraction.

This further breakdown in the modern era is determined by genetically characteristic gene sequences
that are transcribed into what we measure.  Eugene Rypka contributed greatly to clarifying the extraction
of features in a series of articles, which

  • set the groundwork for the methods used today in clinical microbiology.

The method he describes is termed S-clustering, and

  • will have a significant bearing on how we can view laboratory data.

He describes S-clustering as extracting features from endogenous data that

  • amplify or maximize structural information to create distinctive classes.

The method classifies by taking the number of features

  • with sufficient variety to map into a theoretic standard.

The mapping is done by

  • a truth table, and each variable is scaled to assign values for each: message choice.

The number of messages and the number of choices forms an N-by N table.  He points out that the message

  • choice in an antibody titer would be converted from 0 + ++ +++ to 0 1 2 3.

Even though there may be a large number of measured values, the variety is reduced

  • by this compression, even though there is risk of loss of information.

Yet the real issue is how a combination of variables falls into a table with meaningful information. We are concerned with accurate assignment into uniquely variable groups by information in test relationships. One determines the effectiveness of each variable by

  • its contribution to information gain in the system.

The reference or null set is the class having no information.  Uncertainty in assigning to a classification is

  • only relieved by providing sufficient information.

The possibility for realizing a good model for approximating the effects of factors supported by data used

  • for inference owes much to the discovery of Kullback-Liebler distance or “information”, and Akaike
  • found a simple relationship between K-L information and Fisher’s maximized log-likelihood function.

In the last 60 years the application of entropy comparable to

  • the entropy of physics, information, noise, and signal processing,
  • has been fully developed by Shannon, Kullback, and others, and has been integrated with modern statistics,
  • as a result of the seminal work of Akaike, Leo Goodman, Magidson and Vermunt, and work by Coifman.

Gil David et al. introduced an AUTOMATED processing of the data available to the ordering physician and

  • can anticipate an enormous impact in diagnosis and treatment of perhaps half of the top 20 most common
  • causes of hospital admission that carry a high cost and morbidity.

For example: anemias (iron deficiency, vitamin B12 and folate deficiency, and hemolytic anemia or myelodysplastic syndrome); pneumonia; systemic inflammatory response syndrome (SIRS) with or without bacteremia; multiple organ failure and hemodynamic shock; electrolyte/acid base balance disorders; acute and chronic liver disease; acute and chronic renal disease; diabetes mellitus; protein-energy malnutrition; acute respiratory distress of the newborn; acute coronary syndrome; congestive heart failure; disordered bone mineral metabolism; hemostatic disorders; leukemia and lymphoma; malabsorption syndromes; and cancer(s)[breast, prostate, colorectal, pancreas, stomach, liver, esophagus, thyroid, and parathyroid].

Rudolph RA, Bernstein LH, Babb J: Information-Induction for the diagnosis of myocardial infarction. Clin Chem 1988;34:2031-2038.

Bernstein LH (Chairman). Prealbumin in Nutritional Care Consensus Group.

Measurement of visceral protein status in assessing protein and energy malnutrition: standard of care. Nutrition 1995; 11:169-171.

Bernstein LH, Qamar A, McPherson C, Zarich S, Rudolph R. Diagnosis of myocardial infarction: integration of serum markers and clinical descriptors using information theory. Yale J Biol Med 1999; 72: 5-13.

Kaplan L.A.; Chapman J.F.; Bock J.L.; Santa Maria E.; Clejan S.; Huddleston D.J.; Reed R.G.; Bernstein L.H.; Gillen-Goldstein J. Prediction of Respiratory Distress Syndrome using the Abbott FLM-II amniotic fluid assay. The National Academy of Clinical Biochemistry (NACB) Fetal Lung Maturity Assessment Project.  Clin Chim Acta 2002; 326(8): 61-68.

Bernstein LH, Qamar A, McPherson C, Zarich S. Evaluating a new graphical ordinal logit method (GOLDminer) in the diagnosis of myocardial infarction utilizing clinical features and laboratory data. Yale J Biol Med 1999; 72:259-268.

Bernstein L, Bradley K, Zarich SA. GOLDmineR: Improving models for classifying patients with chest pain. Yale J Biol Med 2002; 75, pp. 183-198.

Ronald Raphael Coifman and Mladen Victor Wickerhauser. Adapted Waveform Analysis as a Tool for Modeling, Feature Extraction, and Denoising. Optical Engineering, 33(7):2170–2174, July 1994.

R. Coifman and N. Saito. Constructions of local orthonormal bases for classification and regression. C. R. Acad. Sci. Paris, 319 Série I:191-196, 1994.

Realtime Clinical Expert Support and validation System

We have developed a software system that is the equivalent of an intelligent Electronic Health Records Dashboard that provides empirical medical reference and suggests quantitative diagnostics options.

The primary purpose is to

  1. gather medical information,
  2. generate metrics,
  3. analyze them in realtime and
  4. provide a differential diagnosis,
  5. meeting the highest standard of accuracy.

The system builds its unique characterization and provides a list of other patients that share this unique profile, therefore utilizing the vast aggregated knowledge (diagnosis, analysis, treatment, etc.) of the medical community. The

  • main mathematical breakthroughs are provided by accurate patient profiling and inference methodologies
  • in which anomalous subprofiles are extracted and compared to potentially relevant cases.

As the model grows and its knowledge database is extended, the diagnostic and the prognostic become more accurate and precise. We anticipate that the effect of implementing this diagnostic amplifier would result in

  • higher physician productivity at a time of great human resource limitations,
  • safer prescribing practices,
  • rapid identification of unusual patients,
  • better assignment of patients to observation, inpatient beds,
    intensive care, or referral to clinic,
  • shortened length of patients ICU and bed days.

The main benefit is a real time assessment as well as diagnostic options based on

  • comparable cases,
  • flags for risk and potential problems

as illustrated in the following case acquired on 04/21/10. The patient was diagnosed by our system with severe SIRS at a grade of 0.61 .

Graphical presentation of patient status

The patient was treated for SIRS and the blood tests were repeated during the following week. The full combined record of our system’s assessment of the patient, as derived from the further hematology tests, is illustrated below. The yellow line shows the diagnosis that corresponds to the first blood test (as also shown in the image above). The red line shows the next diagnosis that was performed a week later.

Progression changes in patient ICU stay with SIRS

Chemistry of Herceptin [Trastuzumab] is explained with images in

http://www.chm.bris.ac.uk/motm/herceptin/index_files/Page450.htm

 

REFERENCES

The Cost Burden of Disease: U.S. and Michigan CHRT Brief. January 2010.
@www.chrt.org

The National Hospital Bill: The Most Expensive Conditions by Payer, 2006. HCUP Brief #59.

Rudolph RA, Bernstein LH, Babb J: Information-Induction for the diagnosis of myocardial infarction. Clin Chem 1988;34:2031-2038.

Bernstein LH, Qamar A, McPherson C, Zarich S, Rudolph R. Diagnosis of myocardial infarction: integration of serum markers and clinical descriptors using information theory. Yale J Biol Med 1999; 72: 5-13.

Kaplan L.A.; Chapman J.F.; Bock J.L.; Santa Maria E.; Clejan S.; Huddleston D.J.; Reed R.G.; Bernstein L.H.; Gillen-Goldstein J. Prediction of Respiratory Distress Syndrome using the Abbott FLM-II amniotic fluid assay. The National Academy of Clinical Biochemistry (NACB) Fetal Lung Maturity Assessment Project.  Clin Chim Acta 2002; 326(8): 61-68.

Bernstein LH, Qamar A, McPherson C, Zarich S. Evaluating a new graphical ordinal logit method (GOLDminer) in the diagnosis of myocardial infarction utilizing clinical features and laboratory data. Yale J Biol Med 1999; 72:259-268.

Bernstein L, Bradley K, Zarich SA. GOLDmineR: Improving models for classifying patients with chest pain. Yale J Biol Med 2002; 75, pp. 183-198.

Ronald Raphael Coifman and Mladen Victor Wickerhauser. Adapted Waveform Analysis as a Tool for Modeling, Feature Extraction, and Denoising. Optical Engineering 1994; 33(7):2170–2174.

  1. Coifman and N. Saito. Constructions of local orthonormal bases for classification and regression. C. R. Acad. Sci. Paris, 319 Série I:191-196, 1994.

W Ruts, S De Deyne, E Ameel, W Vanpaemel,T Verbeemen, And G Storms. Dutch norm data for 13 semantic categories and 338 exemplars. Behavior Research Methods, Instruments, & Computers 2004; 36 (3): 506–515.

De Deyne, S Verheyen, E Ameel, W Vanpaemel, MJ Dry, WVoorspoels, and G Storms.  Exemplar by feature applicability matrices and other Dutch normative data for semantic concepts.  Behavior Research Methods 2008; 40 (4): 1030-1048

Landauer, T. K., Ross, B. H., & Didner, R. S. (1979). Processing visually presented single words: A reaction time analysis [Technical memorandum].  Murray Hill, NJ: Bell Laboratories. Lewandowsky, S. (1991).

Weed L. Automation of the problem oriented medical record. NCHSR Research Digest Series DHEW. 1977;(HRA)77-3177.

Naegele TA. Letter to the Editor. Amer J Crit Care 1993:2(5):433.

Retinal prosthetic strategy with the capacity to restore normal vision, Sheila Nirenberg and Chethan Pandarinath

http://www.pnas.org/content/109/37/15012

 

Other related articles published in http://pharmaceuticalintelligence.com include the following:

 

  • The Automated Second Opinion Generator

Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2012/08/13/the-automated-second-opinion-generator/

 

  • The electronic health record: How far we have travelled and where is journeys end

Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2012/09/21/the-electronic-health-record-how-far-we-have-travelled-and-where-is-journeys-end/

 

  • The potential contribution of informatics to healthcare is more than currently estimated.

Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2013/02/18/the-potential-contribution-of-informatics-to-healthcare-is-more-than-currently-estimated/

 

  • Clinical Decision Support Systems for Management Decision Making of Cardiovascular Diseases

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https://pharmaceuticalintelligence.com/2013/05/04/cardiovascular-diseases-decision-support-systems-for-disease-management-decision-making/

 

  • Demonstration of a diagnostic clinical laboratory neural network applied to three laboratory data conditioning problems

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https://pharmaceuticalintelligence.com/2012/08/13/demonstration-of-a-diagnostic-clinical-laboratory-neural-network-agent-applied-to-three-laboratory-data-conditioning-problems/

 

  • CRACKING THE CODE OF HUMAN LIFE: The Birth of BioInformatics & Computational Genomics

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https://pharmaceuticalintelligence.com/2014/08/30/cracking-the-code-of-human-life-the-birth-of-bioinformatics-computational-genomics/

 

  • Genetics of conduction disease atrioventricular AV conduction disease block gene mutations transcription excitability and energy homeostasis

Aviva Lev-Ari, PhD, RN

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https://pharmaceuticalintelligence.com/2012/12/10/identification-of-biomarkers-that-are-related-to-the-actin-cytoskeleton/

 

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https://pharmaceuticalintelligence.com/2012/08/02/diagnostic-evaluation-of-sirs-by-immature-granulocytes/

 

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https://pharmaceuticalintelligence.com/2012/12/17/big-data-in-genomic-medicine/

 

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  • FDA Pending 510(k) for The Latest Cardiovascular Imaging Technology

Aviva Lev-Ari, PhD, RN 1/28/2013

https://pharmaceuticalintelligence.com/2013/01/28/fda-pending-510k-for-the-latest-cardiovascular-imaging-technology/

 

  • PCI Outcomes, Increased Ischemic Risk associated with Elevated Plasma Fibrinogen not Platelet Reactivity

Aviva Lev-Ari, PhD, RN 1/10/2013

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  • The ACUITY-PCI score: Will it Replace Four Established Risk Scores — TIMI, GRACE, SYNTAX, and Clinical SYNTAX

Aviva Lev-Ari, PhD, RN 1/3/2013

https://pharmaceuticalintelligence.com/2013/01/03/the-acuity-pci-score-will-it-replace-four-established-risk-scores-timi-grace-syntax-and-clinical-syntax/

 

  • Coronary artery disease in symptomatic patients referred for coronary angiography: Predicted by Serum Protein Profiles

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  • New Definition of MI Unveiled, Fractional Flow Reserve (FFR)CT for Tagging Ischemia

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Treatment for Metastatic HER2 Breast Cancer

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Word Cloud By Danielle Smolyar

Reporter: Larry H Bernstein, MD, FCAP
Leaders in Pharmaceutical Innovation
http://pharmaceuticalintelligence.com/2013/03/03/9680/Treatment for Metastatic HER2 Breast Cancer 

FDA Approves New Treatment for Metastatic HER2 Breast Cancer (antibody-drug conjugate)
T-DM1 is indicated for patients who were previously treated with the anti-HER2 therapy trastuzumab (Herceptin, Genentech) and a taxane chemotherapy.

The US Food and Drug Administration (FDA) today approved ado-trastuzumab emtansine (Kadcyla, Genentech), also known as T-DM1, for the treatment of patients with HER2-positive metastatic breast cancer.
T-DM1 is indicated for patients who were previously treated with

  • the anti-HER2 therapy trastuzumab (Herceptin, Genentech) and a taxane chemotherapy.

This product offers a new twist on an older product; it is an antibody–drug conjugate in which the

  • HER2-targeted antibody trastuzumab
  • is chemically linked to the cytotoxin mertansine (DM1).

The antibody homes in on HER2 breast cancer cells, delivering the chemotherapy directly to the tumor, which reduces the risk for toxicity.  According to Richard Pazdur, MD, at the FDA Center for Drug Evaluation and Research, T-DM1 carries the drug-conjugate

  • directly to the cancer site
  • to shrink the tumor,
  • slow disease progression, and
  • prolong survival .

It is the fourth drug approved that targets the HER2 protein. Apart from lapatinib, which is marketed by GlaxoSmithKline, all the other HER2-targeted products have been developed and are marketed by Genentech/Roche. For T-DM1, the proprietary technology involved in the DM1 portion of the product was developed by ImmunoGen, working in collaboration with Genentech/Roche.

In the pivotal phase 3 EMILIA study, patients receiving T-DM1 survived nearly 6 months longer than patients receiving the standard therapy of

  • lapatinib (Tykerb) plus capecitabine (Xeloda) (median overall survival, 30.9 vs 25.1 months).

There were fewer grade 3 or higher (severe) adverse events with TDM-1 than with standard therapy

  • 43.1% vs. 59.2%)

The approval represents a “momentous” day in breast cancer, said Kathy Miller, MD, from Indiana University in Indianapolis, in her Miller on Oncology Medscape blog.

  • HER2-positive patients with metastatic disease have a therapy that offers prolonged disease control with less toxicity

 T-DM1 was more effective in EMILIA than standard therapy on every outcome:

  • overall response rate,
  • disease-free survival,
  • progression-free survival, and
  • overall survival.

Herceptin Fab (antibody) - light and heavy chains

Herceptin Fab (antibody) – light and heavy chains (Photo credit: Wikipedia)

Ribbon diagram of the Fab fragment of , a , bo...

Ribbon diagram of the Fab fragment of , a , bound to the extracellular domain of HER2. Created using Accelrys DS Visualizer Pro 1.6 and . ; Legend Trastuzumab Fab fragment, Trastuzumab Fab fragment, HER2, extracellular domain (Photo credit: Wikipedia)

Breast cancer (Infiltrating ductal carcinoma o...

Breast cancer (Infiltrating ductal carcinoma of the breast) assayed with anti HER-2 (ErbB2) antibody. (Photo credit: Wikipedia)

English: Breast cancer incidence by age in wom...

English: Breast cancer incidence by age in women in the United Kingdom 2006-2008. Reference: Excel chart for Figure 1.1: Breast Cancer (C50), Average Number of New Cases per Year and Age-Specific Incidence Rates, UK, 2006-2008 at Breast cancer – UK incidence statistics at Cancer Research UK. Section updated 18/07/11. (Photo credit: Wikipedia)

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Author, reporter: Tilda Barliya PhD

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Word Cloud By Danielle Smolyar

Breast cancer is the second most common cancer worldwide after lung cancer, the fifth most  common cause of cancer death, and the leading  cause of cancer death in women. the global burden of  breast cancer exceeds all other cancers and the incidence  rates of breast cancer are increasing (1,2).

The heterogeneity of breast cancers makes them both a fascinating and challenging solid tumor to diagnose and treat. Here is a great review of the molecular pathology of breast cancer progression (3).

The molecular pathology of breast cancer progression” by Alessandro Bombonati  and Dennis C Sgroi.

Breast cancer is the most frequent carcinoma in females and the second most common cause of cancer related mortality in women. Approximately 54 000 and 207 000 new cases of in situ and invasive breast carcinoma, respectively. Overall, breast cancer incidence rates have levelled off since 1990, with a decrease of 3.5%/year from 2001 to 2004.  Most notably, during this same time period, breast cancer mortality rates have declined 24%, with the largest impact among young women and women with estrogen receptor (ER)-positive disease.

The decline in breast cancer mortality has been attributed to the combination of early detection with screening programmes and the advent of more efficacious adjuvant progression have aided in the discovery of novel pathway-specific targeted therapeutics, and the emergence of such effective therapeutics is currently driving the need for molecular-based, ‘patient-tailored’ treatment planning.

Proposed models of human breast cancer progression

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Epidemiological and morp

hological observations led to the formulation of several linear models of breast cancer initiation, transformation and

progression. Figure 1

The ductal and lobular subtypes constitute the majority of all breast cancers worldwide, with the ductal subtype accounting for 40–75% of all diagnosed cases.

The classic model of breast cancer progression of the ductal type proposes thatneoplastic evolution initiates in normal epithelium (normal), progresses to flat epithelial atypia (FEA), advances to atypical ductalhyperplasia (ADH), evolves to ductal carcinoma in situ (DCIS) and culminates as invasive ductal carcinoma (IDC).

The model of lobular neoplasia proposes a multi-step progression from normal epithelium to atypicallobular hyperplasia, lobular carcinoma in situ (LCIS) and invasive lobular carcinoma (ILC).

The cell of origin of breast cancer: the clonal and stem cell hypotheses

The two leading models accounting for breast carcinogenesis are the sporadic clonal evolution model and the cancer stem cell (cSC) model. According to the sporadic clonal evolution hypothesis, any breast epithelial cell can be the target of random mutations. The cells with advantageous genetic and epigenetic alterations are selected over time to contribute to tumour progression. The third alternative cSC model postulates that only stem and progenitor cells (representing a small fraction of the tumor cells within the cancer) can initiate and maintain tumor progression. Figure 2.

Normal breast stem cells (nBSCs) are long-lived, tissue-resident cells capable of self-renewal activity and multi-lineage differentiation that can recapitulate the breast tubulolobular architecture that is composed of luminal and myoepithelial cells.

As normal breast cancer stem cells are long-time tissue residents, it has been proposed that such cells are candidates for accumulating genetic and epigenetic modifications. It has been further proposed that such molecular alterations result in deregulation of normal self-renewal, leading to the development of a cancer stem cell (cSC).

It is believed that the cSC undergoes asymmetrical division, maintaining the stem cell population while at the same time differentiating into committed progenitor(s) cells that give rise to the different breast cancer subtypes.

A second scenario, as it relates to breast cancer development, is one in which the cancer-initiating cells are derived from committed progenitor cells that spawn different breast cancer subtypes. Both scenarios are highly supported.

Molecular analysis of the different stages of breast cancer progression

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Genomic and transcriptomic data in combination with morphological and immunohistochemical data stratify the majority of breast cancers into a “low-grade-like” molecular pathway and a “high-grade-like” molecular pathway. Figure 3. The low-grade-like pathway (left hand side) is characterized by recurrent chromosomal loss of 16q, gains of 1q, a low-grade-like gene expression signature, and the expression of estrogen and progesterone receptors (ER+ and PR+). The progression (vertical arrows) along this pathway (green rectangles) culminates with the formation of low and intermediate grade invasive ductal, (LG IDC and IG IDC) and invasive lobular carcinomas including both the classic (ILC) and the pleomorphic variant (pILC). The tumors arising from the low grade pathway are classified as luminal consisting of a continuum of gene expression frequently associated with the absence (luminal A) or presence of HER2 expression (luminal B). The vast majority of ILCs and pILCs and their precursors cluster together within the luminal subtype. The high grade-like gene expression molecular pathway (right hand side) is characterized by recurrent gain of 11q13 (+11q13), loss of 13q (13q−), expression of a high-grade-like gene expression signature, amplification of 17q12 (17q12AMP), and lack of estrogen and progesterone receptors expression (ER− and PR−). The progression along this pathway (red rectangles) includes intermediate and high grade ductal carcinomas that are stratified as HER2, or basal-like, depending on the expression/amplification of HER2. The molecular apocrine subtype, characterized by the lack of ER expression and presence of AR expression, arises from the high grade pathway. The model also depicts intra-pathway tumor grade progression (horizontal arrows).

Although the genomic and transcriptomic data presented in this review support the divergent model of breast cancer progression, the clinical experience indicates that tumors within each pathway are still fairly heterogeneous with respect to clinical outcome suggesting that even this advanced molecular progression scheme is oversimplified.

The future application of massively parallel sequencing technologies to the preinvasive stages of breast cancer will assist in assessing intratumoral heterogeneity during the transition from preinvasive to invasive breast cancer, and may assist in identifying early tumor initiating genetic events.

Summary:

Over the past decade the integration of numerous genomic and transcriptomic analyses of the various stages of breast cancer has generated multiple novel insights in the complex process of breast cancer progression.

  • First, human breast cancer appears to progress along two distinct molecular genetic pathways that strongly associate with tumor grade.
  • Second, in the epithelial and non-epithelial components of the tumor microenvironment, the greatest molecular alterations (at the gene expression level) occur prior to local invasion.
  • Third, in the epithelial compartment, no major additional gene expression changes occur between the preinvasive and invasive stages of breast cancer.
  • Fourth, the non-epithelial compartment of the tumor micromilieu undergoes dramatic epigenetic and gene expression alterations occur during the transition form preinvasive to invasive disease. Despite these significant advances, we have only begun to scratch the surface of this multifaceted biological process. With the advent of additional novel high-throughput genetic, epigenetic and proteomic technologies, it is anticipated that the next decade of breast cancer research will gain an equally paralleled appreciation for the complexity breast cancer progression. It is with great hope that knowledge gained from such studies will provide for more effective strategies to not only treat, but also prevent breast cancer.

Ref:

1. http://www.nature.com/nrclinonc/journal/v7/n12/pdf/nrclinonc.2010.192.pdf

2. Jemal, a. et al. CA Cancer J. Clin. 60, 277–300; 2010

3. Alessandro Bombonati and Dennis C Sgro. The molecular pathology of breast cancer progression. J Pathol 2011; 223: 307–317.

http://onlinelibrary.wiley.com/doi/10.1002/path.2808/pdf

http://pubmedcentralcanada.ca/pmcc/articles/PMC3069504/

4. Rodney C. Richie and John O. Swanson. Breast Cancer: A Review of the Literature. J Insur Med 2003;35:85–101.

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Author and Reporter: Anamika Sarkar, Ph.D.

Targeted therapies are proven approaches in Cancer and other complicated diseases. Degrees of activation of measured EGFR and ERB2/HER2 in cancer cells are thought of one of the ways to identify the scale of aggressiveness of cancer in tissues.  There are drugs, mostly for breast cancer, which targets inhibition of these receptors. Lapatinib (Tykerb, GSK – see Source for other targeted drugs) is the first drug which inhibits both EGFR and ERB2/HER2 gave hope to cancer patients, especially advanced ERB2-postive or metastatic breast cancer patients. Despite of proven high efficacy, Lapatinib didn’t show promising results in clinical responses due to acquired resistance.

Komurov et. al. (Mol. Systems.Biol., 2012) used network analysis along with experimental findings on cultured human breast cancer cell lines (SKBR3) and showed that a large part of acquired resistance to Lapatinib is due to  increased levels of activated states of glucose deprivation signaling network. The authors cultured ERB2-positive SKBR3 cells with increasing doses of Lapatinib, to make the control cell lines for analyzing their experimental results in comparison with (SKBR3- R),SKBR3-Resistant cells. Their Western Blot analysis showed that Lapatinib was successful to inhibit down signaling pathways to ERB2 and EGFR in both control and resistant cells however fails to induce apoptotic pathways in resistant cells when compared with the controlled cells.

To identify other factors which can influence the differential effects of Lapatinib on controlled and resistant cell lines, Komurov et. al. used a data biased random walk network analysis method called Netwalk (Komurov et. al. PLOS Comp Biol., 2010). Their method is data driven and based on comparative network analysis of gene expressions at different conditions rather than network analysis at one gene level. Their network analysis identified presence of high levels of genes which act as compensatory mechanisms for glucose deprivation (as shown in Figure 2 of the paper Komurov et. al. (2012) Figure 2). They showed validation of their network analysis findings using Western Blot analysis (as shown in Figure 3 of the paper Komurov et.al. (2012) Figure 3).

 

The authors’ results not only show a nice elegant way of finding new information using network analysis and experimental techniques together, but also points out an important concept which can be future of cancer therapy. Their results show that along with targeting mutated Oncogenes eg., EGFR and ERB2/HER2 as in case of Lapatinib, additional way of controlling the pathway of deprivation of glucose, can achieve better clinical responses for cancer patients with aggressive levels of cancer. Targeting glucose or pathways of glucose can be tricky, because of its ubiquitous links to many physiological functions, including metabolism. However, the levels at which these pathways need to be targeted to achieve certain positive responses at in-vitro, supported by systems biology methods, and then in-vivo studies can be informative.  Moreover, targeting many parts in the network in smaller amounts, along with targeted cancer drugs, may produce interesting results.

Sources:

Komurov et.al. (2012) : http://www.ncbi.nlm.nih.gov/pubmed/22864381

A News and Views on Lapatinib (2005) : http://www.emilywaltz.com/Herceptin.pdf

Komurov et.al. (2010) – Article published on methods of Netwalk : http://www.ncbi.nlm.nih.gov/pubmed/20808879

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