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Commentary on Science, Innovation & New Products with a focus on Oncology, Hematology & Cancer Immunotherapy

Posts from the ‘Biomarkers’ category

T cell activation has been very much to the fore over the last couple of years with many companies looking at different ways to use them against cancer cells, with chimeric antigen receptor (CAR) T cell therapy, vaccines or monoclonal antibodies. There are situations though, where T cells are not necessarily a good thing.

Graft versus Host disease (GvHD) is an area of tremendous unmet medical need that is triggering the interest of a number of biotech and rare disease companies such as Alexion Pharmaceuticals (ALXN).

Houston based Bellicum Pharmaceuticals (BLCM), whose IPO raised around $140M last month, have said they plan to spend most of the funds on bringing to market a new cell therapy that could make stem cell transplants more effective and reduce GvHD. They also have a CAR-T therapy in early development.

Indeed, at last month’s ASH 2014 annual meeting in San Francisco, GvHD was very much a hot topic, with data presented in the plenary session by Dr Wei Li (pictured below) on a novel biomarker for GI GvHD.

Dr Wei Li ASH 2014 GvHD Plenary

This post discusses one of the GvHD oral sessions at ASH 2014, and includes post-presentation commentary from Dr Marcel van den Brink, who is an expert in the area. The related interview Dr Brink kindly gave BSB at the SITC annual meeting is well worth reading if you missed it.

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Today I thought it would be a good idea to answer a question sent in by a premium subscriber.  He asked,

“What’s the deal with TIL and how does that relate to checkpoint inhibitors and PD-L1 expression?”

This is a good question and there were some interesting top-line debates about this at AACR recently, which are well worth discussing and highlighting.

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On Friday, I headed uptown to attend the Miami Breast Cancer Conference (#MBCC14) held at the Fontainebleau Hotel and organised by the Physicians Education Resource (PER).  It was fun to grab a local Deco Bike and furiously cycle over 45 blocks in under half an hour – most probably the only attendee who arrived on two wheels that day!

MBCC14: Dr Lance Liotta

MBCC14: Dr Lance Liotta

Now, I haven’t attended this event since it was at the Loews Hotel in midtown, which was rather low key and fairly small.  Certainly there wasn’t a big exhibition area then, as far I can recall.  Fast forward a decade on and the event is MUCH bigger, with an excellent Academic panel and an interesting mix of didactic talks and case studies.  The stage setting is also much more impressive, as you can see in the photo right.

To give you some basic background, the audience polls at the beginning of the first day were really useful to put things into context:

  1. The majority of attendees (88%) were physicians (mix of Community medical oncologists, radiation oncologists and surgical oncologists)
  2. 49% of respondents treated 1–5 patients with breast cancer per week
  3. 25% of respondents treated 6–10 patients with breast cancer per week

Being a scientist, and having missed the San Antonio Breast Cancer Symposium (SABCS) due to an overlap with the American Society of Hematology (ASH) meeting in December, I was particularly keen to catch up on the new developments in genomics and molecular profiling, with early morning talks from Drs Lance Liotta (George Mason Univ) and Debu Tripathy (USC).  There were also updates on neoadjuvant treatment for breast cancer by Drs Kathy Albain (Loyola) and Hal Burstein (Dana Farber).  Neoadjuvant therapy prior to surgery is an area that is seeing many new trials and potential therapies emerge.

In today’s post, the attention is on the important topic molecular profiling. This is something I believe we will see much more of going forward.  Two separate articles will follow on personalised treatment in advanced breast cancer (including TNBC) and also on neoadjuvant developments.

Genomics can sometimes be a bit of a dry topic, at least to some people, as anyone who has sat through slide after slide of those fuzzy green-red assays in systems biology sessions at AACR will attest. This time, much to my pleasant surprise, it was different…

What I heard blew my mind and changed the way I think about some aspects of breast cancer.

Now I’m not joking or trying to hype progress here, but sometimes you experience an epiphany when you least expect it.

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Lance Liotta always gives well organised presentations and illustrates the key facts on proteomics (a tough subject for many to follow) with critical learning points.  At this year’s MBCC, he focused his talk on a vision for combining genomic mapping with proteomic analysis of the metastatic lesion.  Part of the challenge with using genomics is the sheer heterogeneity and complexity of every single patient’s tumour.  He also had a second talk in the afternoon that was equally interesting, but more about that in another post.

One of the main findings from the SideOut trial (run by TGen and George Mason, sponsored by the Side Out Foundation; reported at ASCO 2013 – download the poster here) a proof-of-concept study, which showed that molecular profiling often yielded a treatment recommendation that was different from the one recommended by the treating physician:

Source: L Liotta, MBCC

Source: L Liotta, MBCC

You can see that some of the regimens mentioned here are quite noticeably different – patient #103 is particularly fascinating, for example.

Here’s my quick summary of some of the main points from his first talk:

  1. Basic concept of SideOut I: map the signaling network of metastatic tumour cells to understand which growth or survival pathways are functionally in use in the tissue microenvironment.
  2. Combine this information with genomic analysis from biopsies to determine true drivers from passengers.
  3. Use a combination of genomics and proteomics to recommend appropriate therapies.
  4. The trial was largely successful at generating good responses to therapy and demonstrating PFS – 40% of patients exceeded the PFS ratio of 1.3 and three pats still continue on therapy for 199, 254 and 816 days.
  5. 60% of patient samples had activation of drug targets in only 3 major clusters i.e.
    1. pan-HER-AKT
    2. EGFR/Src/ERK/mTOR
    3. IGF/RAF/MEK/PLK1
  6. Improved treatment may therefore be facilitated by biomarker-led understanding of subgroup molecular targets, which may predict benefit from currently approved agents and newer targeted drugs.
  7. Subclones are selected out based on selective pressure i.e. survival in a secondary tissue or organ during metastasis or survival in the face of therapy (adaptive resistance).  This is something we need to learn more about as our knowledge of the biology of the disease improves.

Following the success of this trial, SIDEOUT II has now opened in 9 sites looking at metastatic breast cancer patients progressing after 1–3 lines of therapy. The study will investigate genome sequencing, protein pathway mapping and multiplexed IHC before using all of the information available to provide a molecular rationale for individualising therapy.

For the SideOut I study, Liotta gave a nice example of a typical patient case study, as shown below.  The idea was to illustrate how they investigators tackled this difficult case and used the genomic and proteomic data to make better clinical decisions.  Note the patient had TNBC, yet had different findings for HER2 status based on two different tests – this isn’t an uncommon finding with lab results, unfortunately:

Source: L Liotta, MBCC

Source: L Liotta, MBCC

After the proteomic and genomic analysis, this is what they ended up with. Note the recommended treatment regimen that resulted – not something you would normally consider with such a detailed work-up!

Source: L Liotta MBCC

Source: L Liotta MBCC

To put this in better context – consider the attendee poll on what tests the physicians would order based on the biopsy of a metastatic lesion suggested that 60% would run ER, PR and HER2 only, while less than a third would test for ER, PR, HER2 and genomic profiling.  Personally, I was really surprised that so few respondents would consider genomic sequencing in the metastatic setting given the sheer molecular complexity that exists.  Clearly, there is a molecular world beyond hitting ER, PR and HER2.

Ultimately, the proof of the pudding in any clinical trial is outcome – how well did the patients do when molecular profiling was used to guide therapy?  Remember that many of these patients had quite advanced disease and were considered difficult to treat.

The answer is quite well, as this waterfall plot demonstrates:

Sideout waterfall plot

 

We have to wonder how can we possibly expect to treat any patient successfully, if we don’t know what driver mutations and targets exist?  In this respect, lung cancer has truly come out of the shadows and leap-frogged breast cancer in terms of molecular profiling and targeted therapies, at least in Academia.

In the future, it may be possible to better define triple negative breast cancers (TNBC) by what the are, rather than what they’re not i.e. ER, PR, HER2 negative, which is a broad catch-all and a very heterogenous population indeed.

Meanwhile, tomorrow we will continue the personalized theme and cover another mind blowing talk that demonstrated how far we really have to go before we can possibly expect to see major shifts in outcome based on the underlying biology and matching appropriate targeted therapy.

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Sometimes timing can be amusing when writing up data and conferences. Yesterday, while writing about the immuno-oncology developments in renal cell cancer (RCC), I was putting a table of the trials together and absent mindedly noticed that Merck didn’t have much going in this indication compared to BMS and Roche/Genentech.

Oddly, the company fixed that this morning with their announcement that they are expanding their combinations and collaborations for the anti-PD–1 antibody, MK–3475. One of the new trials includes a partnership with Pfizer for axitinib (Inlyta), enabling them to study a PD–1 + VEGF combination in RCC. The table in yesterday’s thought piece has now been updated to include this trial, although it is in the planning stage at present.

Today, I want to switch horses a little bit and talk about another immuno-oncology therapy, namely, ipilimumab (Yervoy).  Dr Charles Drake (Johns Hopkins) presented an update on the post chemotherapy trial (CA184–083) in CRPC at ASCO GU this weekend, which we wrote about from ESMO last Fall when the data was first presented (see here).  What’s interesting is that the trial, although negative, only just missed its endpoint.

Last week I came across some interesting new developments relating to ipilimumab that are well worth discussing here, particularly in relation to biomarkers, as they may have significant implications for the drug clinically.

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The 2013 Molecular Targets and Cancer Therapeutics Conference (twitter #targets13) takes place in Boston from October 19-23 at the Hynes Convention Center. It’s a “must attend” meeting for anyone with an interest in cancer drug development and I’m really looking forward it. Boston is an exciting place for cancer research!

Molecular Targets Meeting AppJointly organized by the American Association for Cancer Research (AACR), European Organization for Research and Treatment of Cancer (EORTC) and National Cancer Institute (NCI), it alternates each year between Europe the United States.

The molecular targets meeting program and abstracts are now available online. There’s also a meeting App that’s well worth downloading if you plan to be there.

As for what’s interesting at the meeting – the three media briefings give a flavor of what to expect:

Sunday, Oct. 20, 10 a.m. “Emerging Therapeutics,” including research on investigational drugs AZD9291 and PF-06463922, which have the potential to overcome drug resistance in some lung cancers.

Monday, Oct. 21, 9 a.m. “Overcoming Resistance and Hard-to-Treat Cancers,” including research on a new antibody-drug conjugate MLN0264 for pancreatic cancer and a new nanopharmaceutical CRLX101 for cancers resistant to antiangiogenic drugs.

Tuesday, October 22, 9 a.m. “Guiding Treatment for BRAF- and BRCA-related Cancers,” including updated data on the clinical benefit of the PARP inhibitor BMN 673 and a new diagnostic platform to rapidly identify BRAF mutations.

The AACR press team led by Jeremy Moore have done a good job of identifying some of the exciting new drugs in development.

Readers of blog premium content have already read about the potential of AZD9291 in T790M resistant lung cancer from ECCO 2013 in Amsterdam.  While it looks like the ECCO late-breaker did steal some of the thunder from the molecular targets meeting, there’s going to be more granularity on the compound at AACR, and hopefully some updated clinical data.

There are three AZD9291 posters at the meeting, and I’ll be covering all of these while in Boston:

Sunday, Oct 20, 2013, 12:30 PM – 3:00 PM  A109: AZD9291: an irreversible, potent and selective third generation tyrosine kinase inhibitor (TKI) targeting EGFR activating (EGFRm+) and resistance (T790M) mutations in advanced lung adenocarcinoma.

Monday, Oct 21, 2013, 12:30 PM – 3:00 PM  B212: Integrating the pre-clinical pharmacokinetic, pharmacodynamics, and efficacy data for AZD9291, an oral, irreversible inhibitor of EGFR activating (EGFRm+) and resistant (EGFRm+/T790M) mutations and an active metabolite to predict the human pharmacokinetics and potential efficacious dose in patients.

Monday, Oct 21, 2013, 12:30 PM – 3:00 PM B94 Discovery of and first disclosure of the clinical candidate AZD9291, a potent and selective third-generation EGFR inhibitor of both activating and T790M resistant mutations that spares the wild type form of the receptor.

Another compound that I have been following with data at Molecular Targets is ABT-199/GDC-199.

You’ll find me in the poster halls every afternoon, so if you are going to be in Boston for Molecular Targets, I look forward to seeing you there!

AB Science confirms the filing for the Marketing Authorization Application to the European Medicines Agency of Masitinib in the treatment of Pancreatic Cancer.

AB Science LogoParis based biopharmaceutical company AB Science announced in an October 16 news release that the company has applied to the European Medicines Agency (EMA) for approval of masitinib in pancreatic cancer.

Masitinib is a tyrosine kinase inhibitor of PDGF, PDGFR, FGFR, FAK, c-KIT. A phase 3 clinical trial (NCT00789633) in pancreatic cancer is underway that compares masitinib with gemcitabine to placebo with gemcitabine.  The trial started in November 2008 with an estimated enrollment of 320 patients at 68 study locations. As far as I am aware no data has yet been presented for this trial.

The phase 2 trial results for mastinib in pancreatic cancer were, however, extremely promising.

Alain Moussy, CEO of AB Science in an interview on Pharma Strategy Blog, A leap of faith: AB Science & mastinib in pancreatic cancer, stated that masitinib “is unique its ability to resensitize the pancreatic cell that has become resistant to gemcitabine.

Strangely, the AB Science news release today offers no top line results, and merely states the “communication of results was delayed to allow the filing for patent applications aimed at extending the period of marketing exclusivity.

The presumption from the filing and today’s announcement is that the data for mastinib in pancreatic cancer is positive, which is good news for patients. I look forward to hearing more about the overall survival benefit for masitinib when more data becomes available.

This news also adds to the excitement building in pancreatic cancer, with the Celgene Abraxane data expected before year end.

Update November 1, 2012: Phase 3 Trial Results Announced

In an October 30, 2012 news release, AB Science finally shared the data for their Phase 3 clinical trial (NCT00789633): A Study to Compare Efficacy and Safety of Masitinib in Combination With Gemcitabine, to Placebo in Combination With Gemcitabine, in Treatment of Patients With Advanced/Metastatic Pancreatic Cancer.

I don’t plan to rehash the self-explanatory news release, but the results are mixed. The Principal Investigator, and leading pancreatic cancer experts I contacted (who were not involved with the trial) did not respond to requests for comment. This suggests that we will have to wait till the data is presented at the ASCO GI symposium in San Francisco next year to fully understand the implications for clinical practice.

Bad news: Study failed to meet it’s primary endpoint of showing that masitinib increased overall survival (patients lived longer) when used in combination with gemcitinabine versus gemcitabine alone.

  • Median OS was 7.7 months in the masitinib plus gemcitabine treatment arm versus 7.0 months in the placebo plus gemcitabine treatment arm (p=0.74; hazard ratio=0.90).

The company news release states:

“This finding of a non significant survival improvement in the overall population is explained by the fact that masitinib is not indicated when Gemzar® is highly efficient.”

However, there is some positive news for AB Science, and that is a subset of the 320 patients in the study did significantly live longer with masitinib.

Good news: a subset of pancreatic cancer patients with a novel genetic biomarker for tumor aggressiveness, identified using RNA expression from whole blood samples, lived significantly longer with masitinb.

  • Patients in the subset with this biomarker (65% of the study population) had a median overall survival (OS) of 5 months on gemcitabine alone, while those on masitinib and gemcitabine had an OS of 11.0 months (hazard ratio of 0.29, p=0.000038).

A survival advantage of 6 months with mastinib is a dramatic result!

If mastinib can be used in conjunction with a predictive biomarker that identifies those patients who may likely respond, it is hard not to imagine that some form of regulatory approval would be forthcoming, despite the failure of the trial to meet it’s primary endpoint. However, more clinical data and another clinical trial may be needed to validate the biomarker, if as it appears, the biomarker was identified retrospectively.

There are also many unanswered questions:

  • what is the technology needed to detect the biomarker?
  • is this a test that can be routinely performed?
  • is there a diagnostic kit available?
  • How might such a genetic biomarker be used in clinical practice by non-academic physicians?
  • What is the extent to which the biomarker has been shown to be valid and reproducible?

I look forward to hearing more about the masitinib data at the ASCO GI 2013 meeting.

Update November 6, 2012: Skuldtech identified as diagnostics partner

Another piece of the jigsaw has been provided in a November 3 news release from AB Science that french company, Skuldtech is the company they are working with on a companion diagnostic test for masitinib in pancreatic cancer. As usual, I found the news out first on Twitter:

The AB Science news release states that:

Skuldtech and AB Science plan to exploit these new markers for commercialization of a future companion test associated with masitinib, a molecule developed by AB science for treating pancreatic cancer.

It goes on to say:

“From a simple drop of blood, Skuldtech and AB Science were able to identify specific markers – transcriptomic markers – that can distinguish between the different populations treated during the phase III study and select the predictive markers for pancreatic cancer survival associated with masitinib treatment.”

We await further information on the cost, availability and validation of the companion diagnostic.

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Drug development for neurodegenerative brain diseases such as Parkinson’s or dementia, of which Alzheimer’s is the most common form, needs to focus on patients early in the disease, not those where brain damage has already occurred.

Diagnosing and treating patients more effectively earlier will, even if you aren’t able to instigate a cure, offer the ability to modify the disease progression and slow or delay when brain damage occurs.  In the case of Alzheimer’s, once the amyloid plaques (tangles of misshapen proteins) have accumulated in nervous tissue, it has so far been impossible to untangle or remove them.

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Last year, I interviewed Dr Todd Sherer, (then the Chief Program Officer) and now the CEO of the Michael J. Fox Foundation, who told me that: “biomarkers are a real focus of the foundation.” Sherer went on to say that:

“Parkinson’s is a difficult disease to diagnose, there is no definitive diagnostic test, so it ends up a clinical diagnosis.  Getting a biomarker that could help better confirm the diagnosis would allow people to get the correct treatment earlier in their disease”

Which is why I was interested to see new research published earlier this week in the journal Archives of Neurology (online first, August 27, 2012), by Sara Hall and colleagues at Lund University, University of Gothenburg and Skåne University Hospital in Malmo, Sweden.

Hall and colleagues describe how a panel of five cerebrospinal fluid (CSF) biomarkers allowed the differential diagnosis of common dementia from Parkinsonian disorders:

  • Beta-amyloid 42
  • Total tau
  • Phosphorylated tau
  • Alpha-synuclein
  • Neurofilament light chain

Patients with early symptoms of neurodegenerative diseases can be hard to diagnose.  Misdiagnosis can occur, which means patients may not respond to treatment or they could be enrolled into a clinical trial, and end up skewing the results.

Ensuring that we have the right patients in clinical trials is important as we seek to alter disease progression.  In other words it’s important to see whether new drugs or treatments are impacting the disease course.  If you have a wrongly diagnosed patient in a trial, then the drug may show no effect, not because it’s not effective, but that patient’s disease is not responsive.

Multivariate analysis indicated that the panel of 5 CSF biomarkers could accurately differentiate Alzheimer’s disease (AD) from Parkinson disease with dementia (PDD), and dementia with Lewy bodies (DLB). The Neurofilament light chain biomarker alone could differentiate PD from atypical Parkinson disease, Hall and colleagues noted.

Whilst the panel was not able to distinguish all forms of dementia, in an accompanying editorial Richard J. Perrin MD, PhD from the University of Washington, stated that this research “represents a significant step forward.” Perrin concluded that:

“Implementation of CSF biomarker panels such as this one should improve the efficiency of clinical trials and accelerate the evaluation and discovery of new effective treatments for neurological diseases.”

Summary

Developing biomarkers that assist in the ability to diagnose Alzheimer’s, Parkinson and dementia patients correctly, and then be able to monitor their subsequent disease progression, should be a key focus of those biotechnology and pharmaceutical companies that want to do innovative and rational drug development.

References

ResearchBlogging.orgSara Hall, MD, Annika Ohrfelt, PhD, Radu Constantinescu, MD, Ulf Andreasson, PhD, Yulia Surova, MD, Fredrik Bostrom, MD, Christer Nilsson, MD, PhD, Hakan Widner, MD, PhD, Hilde Decraemer, Katarina Nagga, MD, PhD, Lennart Minthon, MD, PhD, Elisabet Londos, MD, PhD, Eugeen Vanmechelen, PhD, Bjorn Holmberg, MD, PhD, Henrik Zetterberg, MD, PhD, Kaj Blennow, MD, PhD, & Oskar Hansson, MD, PhD (2012). Accuracy of a Panel of 5 Cerebrospinal Fluid Biomarkers in the Differential Diagnosis of Patients With Dementia and/or Parkinsonian Disorders Arch Neurol. DOI: 10.1001/archneurol.2012.1654

Richard J. Perrin, MD, PhD (2012). Cerebrospinal Fluid Biomarkers for Clinical Trials Arch Neurol. (August 27 Online First) DOI: 10.1001/archneurol.2012.2353

What is a Biomarker?

According to the Biomarkers Definitions Working Group, a biomarker is:

“a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.”

An example of a common biomarker is blood pressure. High blood pressure is a surrogate for cardiovascular disease and risk of stroke.

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Why are Biomarkers important?

Biomarkers can be used for diagnosis and for monitoring the safety and effectiveness of treatments. They are increasingly becoming important in the selection of patients for clinical trials, and as potential surrogates for clinical endpoints that may take a long time to occur e.g. measuring how long someone will live in a cancer trial (overall survival).

Examples of the use of biomarkers include:

  • Diagnosis: high blood pressure is used as a biomarker for cardiovascular disease and risk of stroke.
  • Treatment Selection: CSF biomarkers that correlate with neurodegenerative diseases may help select the most appropriate treatment
  • Drug Effectiveness: biomarkers can be used to monitor treatment or drug effectiveness e.g. use of cholesterol levels as a measure of cardiovascular disease
  • Surrogate Clinical Endpoint: a biomarker based on scientific evidence that predicts or correlates with clinical benefit could be used as a surrogate for a clinical endpoint that may take a while to detect e.g. how long a patient lives or survives, and in the process speed up drug development. Recent prostate cancer trials sought to show that circulating tumor cell (CTC) counts correlated with the survival benefits seen. However, validation of a biomarker needs to take place before regulatory agencies will accept it as a surrogate endpoint in clinical trials.

Biomarkers can be divided into those which are prognostic and those that are predictive.

Prognostic Biomarker: a marker that provides information on the likely course of a disease in an untreated individual.

Prognostic biomarkers are used to identify high-risk cancer patients who should, therefore, receive adjuvant therapy.

Predictive Biomarker: a marker that provides information on how likely you are to respond to a particular therapy.

Predictive biomarkers are used to guide treatment choices i.e. selecting the therapy with the highest likelihood of success.

In breast cancer, estrogen and progesterone receptors are biomarkers that predict sensitivity to endocrine therapy, while HER2 levels predict response to Herceptin treatment. In colorectal cancer (CRC) patients, KRAS mutations have been shown to be a biomarker of resistance to EGFR targeting drugs such as cetuximab and panitumumab.

Predictive biomarkers allow expensive new cancer treatments to be given only to those patients who are likely to respond. As we move forward into the era of personalized medicine the aim is to develop more highly predictive biomarkers that will allow better detection, diagnosis and treatment of disease.

In addition, there’s also a need to develop biomarkers that can distinguish between subgroups of patients to separate those who might benefit from a therapy and those who have developed resistance. Biomarkers for resistance to cancer therapy is an increasingly important area of research.

For those readers interested in cancer biomarkers, the joint ASCO-EORTC-NCI “Markers in Cancer” 2012 meeting in Hollywood, FL (near Fort Lauderdale) from October 11-13 has an agenda that holds promise.

Some of the presentations that caught my attention and ones I particularly look forward to watching remotely via the “Virtual Meeting” include:

  • Biomarkers of Resistance to EGFR-Targeted Therapies in Lung Cancer
    Enriqueta Felip, MD, PhD – Vall d’Hebron University Hospital
  • Resistance Mechanisms to BRAF Inhibition in Melanoma
    Jeffrey Sosman, MD – Vanderbilt-Ingram Cancer Center
  • Complexities of Identifying Non-Mutational Biomarkers of Resistance:
    The VEGF Pathway Example
    Michael B. Atkins, MD – Georgetown University
  • Development of Biomarkers for PI3K Pathway Targeting
    Sherene Loi, MD, PhD – Jules Bordet Institute, Brussels
  • Emerging Functional Imaging Biomarkers
    Annick D. Van Den Abbeele, MD – Dana-Farber Cancer Institute

The next post in this mini-series will discuss new research that shows how a panel of 5 CSF biomarkers can be used to differentiate between neurodegenerative diseases that might otherwise be misdiagnosed. This is particularly important for clinical trial recruitment where early symptomatic patients could potentially be recruited in error if given the wrong diagnosis, and placed in trials that they will not respond to.

A standing room only audience at the recent annual meeting of the American Association for Cancer Research (AACR) heard from several distinguished speakers on what the future of cancer drug therapy is likely to look like: combinations of novel cancer agents.

This AACR session was one of the highlights of the meeting and would have merited from being part of the plenary program.

Jeffrey Engelman from MGH persuasively presented on why we need combination therapies to overcome resistance. He noted that:

  • Most cancers are not sensitive to currently available single-agent therapies
  • Even when sensitive to single-agent therapies, cancers develop resistance, often necessitating combinations

One of the challenges of this approach will be “identifying effective combinations,” he said.

Roy Herbst from Yale, presented on some of the practical challenges involved with the early phase testing of two drugs, and challenged the audience with a critical question:

“Do we possess the necessary translational tools that will help us identify the right drug combinations, ratios and schedules with the right patient?”

Stuart Lutzker from Genentech described their experiences of clinical trials with rational drug combination of trastuzumab and pertuzumab for HER2+ breast cancer.  He concluded that:

“Rational drug combinations have begun to yield exciting Phase III results and should be preferred over empiric drug combinations.”

The Pharma Strategy Blog video interview with Gordon Mills from ECCO/ESMO 2011 in Stockholm offers some interesting insights into how MD Anderson are helping to facilitate academia-industry combination trials with novel compounds from different companies in order to achieve more rational drug design and improve outcomes for people with cancer.

http://youtu.be/FXkcSry6EtQ

If two or more novel cancer drugs are required to interrupt key pathways or to avoid adaptive resistance, what does this mean for the regulatory strategy?

Janet Woodcock addressed some of these challenges in her AACR presentation, and discussed how the:

“FDA would not want to approve a combination regimen with two new agents unless each contributed to the effect.”

Draft guidance on “Codevelopment of Two or More Unmarketed Investigational Drugs for Use in Combination” was published by the Agency in December 2010. Click here for a PDF copy.

The document gives examples of a number of different phase II trial designs that can be used to demonstrate the contribution each drug makes to the combination, and the additive effect seen.

As an example, if each drug in a combination has activity and can be administered individually then the guidance document suggests a multi-arm phase II trial may be needed that compares the impact of either drug alone versus the combination and standard of care.  An adaptive trial may also be used if appropriate.

Dr Woodcock noted that future cancer drug development is likely to include increasing use of combinations, adaptive trials to evaluate various drug and diagnostic combinations and increasing attention to the use of novel biomarkers.

The message I took home from the AACR annual meeting is that the future of cancer therapy is in combinations, and we can expect more clinical trials with two unapproved agents (novel-novel combinations) in the future.

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There was so much good science on display at the recent 2012 annual meeting of the American Association for Cancer Research (AACR) in Chicago that any blog posts are but a personal snapshot or postcard.

Bill Sellers VP Global Head Oncology Novartis Institutes for BioMedical ResearchOne enduring image I have from the plenary presentation on “The Genetic Basis for Cancer Therapy” by Bill Sellers, VP/Global Head Oncology at Novartis Institutes for BioMedical Research was the video he showed of the robots that are used for automated cell profiling.

Imagine the advertisements that show robots being used to build cars, but now the robots are undertaking automated laboratory work in pursuit of new cancer compounds. Wow!

During his presentation, Sellers described how Novartis have built a robust preclinical translational infrastructure.

He went on to say that, “many experiments we have done in the past, and even many molecules that were put in the human, really were only profiled against a limited number of preclinical models such as one cell line.”

In order to make preclinical data more reproducible, Novartis had the goal to move from testing against one cell line to testing against an encyclopedia of cell lines.

This has now become a reality with the launch of the Cancer Cell Line Encyclopedia (CCLE) in collaboration with the Broad Institute. The CCLE was recently announced by Novartis in a media release, and details were published online on March 28, 2012 in a letter to “Nature” (doi:10.1038/nature11003).

The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity

As described in “Nature”:The Cancer Cell Line Encyclopedia (CCLE) is a compilation of gene expression, chromosomal copy number and massively parallel sequencing data from 947 human cancer cell lines.

When coupled with pharmacological profiles for 24 anticancer drugs across 479 of the cell lines, this collection allowed identification of genetic, lineage, and gene-expression-based predictors of drug sensitivity.

Sellers noted in his AACR plenary presentation that the key to using the CCLE is for profiling and to:

“identify subsets of cancer cell lines that are sensitive to a given therapeutic versus those that are not. And then better yet to identify the markers of sensitivity that are differentially expressed or present in the sensitive versus insensitive cell lines.”

Novartis Institute for Biomedical Research Automated Robotic Drug DiscoveryTo do this, Sellers described how Novartis have built a robotic system that e.g. automates cell profiling.  In approx 3 months with this system we can profile 600 cell lines for about 1500 compounds, he said.

This type of preclinical automation is speeding up cancer drug discovery through the ability to more rapidly identify those compounds that are associated with and have activity against different mutations.

In my view, this will drive innovation through the effective and efficient screening of potential new cancer compounds, with the result that only those compounds with demonstrable promise progress.

AACR have made Bill Sellers plenary presentation available as a free webcast from the 2012 annual meeting (along with several others).  I encourage anyone interested in how cancer biology is driving cancer drug development to watch this.

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