Issues in Personalized Medicine: Discussions of Intratumor Heterogeneity from the Oncology Pharma forum on LinkedIn

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

WordCloud Image Produced by Adam Tubman

In an earlier post entitled “Issues in Personalized Medicine in Cancer: Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing” the heterogenic nature of solid tumors was discussed.  There resulted an excellent discussion in the Oncology Pharma forum on LinkedIn so I curated the comments (below article) to foster further discussion. To summarize the original post, this was a discussion of Dr. Charles Swanton’s paper[1] in which he and colleagues had noticed that individual biopsies from primary renal tumors displayed a variety of mutations of the same and different tumor suppressor genes (TSG), thereby not only revealing the heterogeneity of individual tumors but also how tumors can evolve.  Thus it was suggested that individual cells of a primary tumor can represent individual clones, each evolving on a distinct pathway to tumorigenicity and metastasis as each clone would have accumulated different passenger mutations.  It is these passenger mutations which have been posited to be responsible for a tumor’s continued growth (as discussed in the following post Rewriting the Mathematics of Tumor Growth; Teams Use Math Models to Sort Drivers from Passengers).  Indeed, as Dr. Swanton mentioned in the posting that it is very likely a solid tumor contains discrete clones with different driver and passenger mutations and possibly different mutated TSG but also this intra-tumor heterogeneity would have great implications for personalized chemotherapeutic strategies, not only against the primary tumor but against resistant outgrowth clones, and to the metastatic disease, as Swanton and colleagues had found that the metastatic disease displayed tremendously increased genomic instability than the underlying primary disease.

Therefore it may behoove the clinical oncologist to view solid tumors as a collection of multiple clones, each having their own mutagenic spectrum and tumorigenic phenotype.  Each of these clones may acquire further mutations which provide growth advantage over other clones in the early primary tumor.  In addition, branched evolution of a clone most likely depends more on genomic instability and epigenetic factors than on solely somatic mutation.

This is echoed in a  report in Carcinogenesis back in 2005[3] Lorena Losi, Benedicte Baisse, Hanifa Bouzourene and Jean Benhatter had shown some similar results in colorectal cancer as their abstract described:

“In primary colorectal cancers (CRCs), intratumoral genetic heterogeneity was more often observed in early than in advanced stages, at 90 and 67%, respectively. All but one of the advanced CRCs were composed of one predominant clone and other minor clones, whereas no predominant clone has been identified in half of the early cancers. A reduction of the intratumoral genetic heterogeneity for point mutations and a relative stability of the heterogeneity for allelic losses indicate that, during the progression of CRC, clonal selection and chromosome instability continue, while an increase cannot be proven.”

Therefore if a tumor had evolved in time closer to the initial driver mutation multiple therapies may be warranted while tumors which had not yet evolved much from their driver mutation may be tackled with an agent directed against that driver, hence the branched evolution as shown in the following diagram:

Cancer Sequencing Unravels clonal evolution. From Carlos Caldas. (2012). Nature Biotechnology V.30 pp 405-410.[2] used with permission.

 

 

 

 

 

 

An article written by Drs. Andrei Krivtsov and Scott Armstron entitled “Can One Cell Influence Cancer Heterogeneity”[4] commented on a study by Friedman-Morvinski[5] in Inder Verma’s laboratory discussed how genetic lesions can revert differentiated neorons and glial cells to an undifferentiated state [an important phenotype in development of glioblastoma multiforme].

In particular it is discussed that epigenetic state of the transformed cell may contribute to the heterogeneity of the resultant tumor.  Indeed many investigators (initially discovered and proposed by Dr. Beatrice Mintz of the Institute for Cancer Research, later to be named the Fox Chase Cancer Center) show the cellular microenvironment influences transformation and tumor development[6-8].

Briefly the Friedman-Morvinski study used intra-cerebral ventricular (ICV) injection of lentivirus to introduce oncogenes within the CNS and produced tumors of multiple cell origins including neuronal and glial cell origin (neuroblastoma and glioma).  The important takeaway was differentiated somatic cells which acquire genetic lesions can transform to form multiple tumor types.  As the authors state, “cellular differentiation and specialization are accompanied by gradual changes in epigenetic programs” and that “the cell of origin may influence the epigenetic state of the tumor”.   In essence this means that the success of therapy may depend on the cellular state (whether stem cell, progenitor cell, or differentiated specialized cell) at time of transformation.  In other words tumors arising from cells with an epigenetic state seen in stem cells would be more resistant to therapy unless given an epigenetic therapy, such as azacytididne, retinoic acid or HDAC inhibitors.

 

So as the Oncology Pharma forum on LinkedIn was such an excellent discussion I would like to post the comments for curation purposes and foster further discussion.  I would like to thank everyone’s great comments below.  I would especially like to thank Dr. Emanuel Petricoin from George Mason and Dr. David Anderson for supplying extra papers which will be the subject of a future post. I had curated each comment with inserted LIVE LINKS to make it easier to refer to a paper and/or company mentioned in the comment.

The comments seemed to center on three main themes:

1. 1.      Clinicians pondering the benefit to mutational spectrum analysis to determine personalized therapy and develop biomarkers of early disease
2. 2.      A shift in the clinicians paradigm of cancer development, diagnoses, and treatment from strictly histologic evaluation to a genetic and altered cellular pathway view
3. 3.      Use of proteomics, microarray and epigenetics as an alternative to mutational analysis to determine aberrant cellular networks in various stages of tumor development

 

Victor Levenson • Thanks for posting this! To be honest, I am puzzled by the insistence on sequencing as a tool for tumor analysis – we know that expression patterns rather than mutations in a limited number of genes determine tumor physiology (or, even more, physiology of any tissue). Since the AACR-2012 we know that different tumors have similar or even identical mutations, so >functional< rather than >structural< differences are important. Frankly, I’d be much more excited learning about expression pattern heterogeneity in tumors.Granted that is much more challenging than NGS sequencing, but the value of the data would be incomparable, especially in its application to biomarker development.

Stephen J. Williams, Ph.D. • Dear Dr. Levenson, thanks for your comments. I agree with you and in no way am insisting on the releiance of sequencing mutations in cancer as the sole means for determining therapy. It is extremely true that tumors will show tremendous heterogeneity of mRNA expression. There are a number of studies (one which I will post on pharmaceuticalintelligence.com) that individual tumor cells will have differing expression patterns based on the levels of regional hypoxia within the tumor as well as other microenvironmental factors. I do have two posts on pharmaceuticalintelligence.com on this matter, curating various programs around the world which are using microarray expression analysis of tumors to determine personalized strategies. I believe the reliance on mutational analysis is based on the drugs that have been developed (such as Gleevec and crizotinib) which are based on mutant forms of BCR-Abl and ALK, respectively. However (as per two posts I did based on Mike Martin on our site “Mathematical Models of Driver and Passenger mutations) where he discusses how certain driver mutations will get the senescent cell over the hump to get to fully transformed and contribute to a certain level of growth while subsequent passengers are responsible for the sustained survival and expansion of the tumor.

Victor Levenson • Dr. Williams, thanks for the comments. Driving a senescent cell into proliferative stage is a tremendous change, which >may< begin with a mutation, but involves dramatic restructuring of transcription patterns that will drive the process. Hypoxia will definitely contribute to variations in the patterns, although will probably not be the main driver of the process. As to whether a mutation or a change in transcription pattern initiate the process, I am not sure we will ever be able to determine <grin>.

Vanisree Staniforth • Thanks for posting! Certainly a thought provoking article with regard to the future of personalized cancer therapies.

 

Dr. Raj Batra • If we follow Dr Levenson’s proposed conceptual approach (which we also published in 2009 and 2010), we are MUCH more likely to significantly impact tumor morbidity and mortality.

Stephen J. Williams, Ph.D. • Thanks Vanisiree and Dr. Batra for your comments. Hopefully we will see, from the future cancer statistics, how personlized therapy have improved outcomes for the solid tumors, like the hematologic cancers. 26 days ago

Emanuel Petricoin • The issue about intra and inter tumor heterogeneity is very important however since it is unknown which mutations are true drivers, an explanation of the results found in these studies simply could be the variances are all in the inconsequential mutations and the commonality is the driver mutations. Moreover, at the end of the day, its not the mRNA expression that we really care about but the functional protein signaling -phosphoprotein driven signaling architecture, that we care about since these are the drug targets directly.

Mohammad Azhar Aziz,PhD • This article addresses the potential complexity of dealing with cancer which is apparently increasing proportionally with the amount of data generated. Intratumor heterogeneity will remain there and even multiple biopsies that are randomly chosen will offer no conclusive solution.Mutations,expression profiles and functional protein signaling (as discussed above) alone can not provide any breakthrough. It will be a composite picture of all these and many other components (e.g. microenvironment, alternative splicing, epigenetics,non-coding RNAs etc.) that will hold the promises in the future. We have made phenomenal advances in understanding each of these aspects separately but definitely lack the tools to integrate all these. Developing tools to integrate all these data may provide some breakthrough in understanding and thus treating cancer.

Emanuel Petricoin • I agree Mohammad in a systems biology approach however the current compendium of drugs largely are kinase inhibitors or enzymatic inhibitors. Since most studies have shown little correlation between gene mutation and protein levels and phosphoprotein levels, for example, it is no wonder why the recent spate of failed trials (e.g. stratification by PIK3CA mutation or PTEN mutation for AKT-mTOR inhibitors) should come as any shock. We will be publishing work using protein pathway activation mapping coupled to laser dissection of a number of intra and inter tumoral analysis that indicates that the signaling architecture appears much more stable.

Stephen J. Williams, Ph.D. • Thank you Dr. Pettricoin for your comments. I eagerly await the publication of your results concerning proteomic evaluation of multiple biopsies of a tumor. I am very interested that you found limited intratuoral heterogeneity of signaling pathways given the diversity of intratumoral microenvironmental stresses (changes in regional hypoxia, blood flow, and populations of cancer stem cells). I agree with you and Mohammed that proteomic profiling will be imperative in determining personalized approaches for targeted therapy. Dr. Swanton had informed me that they had used IHC to determine if mTOR signaling had correlated with the mutational spectrum they had seen. In addition he had mentioned that there was enhanced genomic instability in the metastatic disease relative to the primary tumor and it would be very interesting to see how signaling pathways change in cohorts of matched metastatic and primary tumors. A few years ago we were looking at genes which were completely lost upon transformation of ovarian epithelial cells and worked up one of those genes (CRBP1) in cohorts of human ovarian cancer samples, using expression analysis in conjunction with laser capture microdissection and backed up by IHC analysis, and found that the expression pattern of CRBP1 was uniform in a tumor, either there was a complete loss in all cells in a tumor of CRBP1 or all the cells expressed the protein. Therefore I am curious if intratumor heterogeneity is dependent on the cell lineage and evolution of the transformed cell into a full tumor or a function of a discrete population of stem cells with varied genomic instability. Your results might suggest a more clonal evolution rather than a branched evolution which was found in this paper.
It is interesting that you mention the tough trials with the PTEN/PI3K/AKT axis of inhibitors. In high grade serous ovarian cancer we were never able to find any PI3K, PTEN, nor AKT mutations yet PI3K activity is usually overactive. If feel both your and Mohammed’s assessment that a systems biology approach instead of just relying on DNA mutational analysis will be more important in the future. In addition, there is nice work from Dr. Jefferey Peterson at Fox Chase and the development of a database of kinase inhibitors and activity effects on the kinome, showing the vast amount of crosstalk between once thought linear enzyme systems. If TKI’s will be the brunt of pharma’s development I feel they need to quickly develop as many TKI’s as they can now before we get to a clinical problem (resistance and lack of available therapeutics).

Emanuel Petricoin • Thanks Steven- yes, we are working with Charlie Swanton and Marco on the renal sets- our other studies are from breast and colon cancers. I think one of the things we do that really no one else is doing, unfortunately, is to laser capture microdissect the tumor cells from these specimens so that we have a more pure and accurate view of the signaling architecture. One confounder from the proteomic stand-point is the fact that pre-analytical variables such as post-excision delay times where the tissue is a hypoxic wound and signaling changes fluctuating as the tissue reacts to the ex-vivo condition can really effect things. When we look at tissue sets where the tissue is biopsied and immediately frozen we really dont see big differences in the signaling – the within tumor architecture is much more similar then between. We use the reverse phase array technology we invented to provide quantitative analysis on hundreds of phosphoproteins at once – so a nice view of the functional protein activation network. Your results of CRBP1 in ovarian tumors and the IHC data are very interesting. We will see how this all plays out. Of course once other confounder with the mutational data is that we really dont know what are the drivers and what are the passengers…
Yes I know Jeff Peterson’s work- its fantastic. In the end the hope I think- and in my personal opinion- will be rationally combined therapeutics based on the signaling architecture of each individual patient.

Incidentally, we just published a paper that you may be interested in from a “systems biology” standpoint-

SYSTEMS ANALYSIS OF THE NCI-60 CANCER CELL LINES BY ALIGNMENT OF PROTEIN PATHWAY ACTIVATION MODULES WITH “-OMIC” DATA FIELDS AND THERAPEUTIC RESPONSE SIGNATURES.

Federici G, Gao X, Slawek J, Arodz T, Shitaye A, Wulfkuhle JD, De Maria R, Liotta LA, Petricoin EF 3rd. Mol Cancer Res. 2013 May

also- we published a paper that speaks directly to your point where we compared the signaling network activation of patient-matched primary colorectal cancers and synchronous liver mets. indeed there is huge systemic differences in the liver metastasis compared to the primary. there is no doubt in my mind that we will need to biopsy the metastasis to know how to treat. Looking at the primary tumor as a guide for therapy is a fools errand. here is the paper reference:

Protein pathway activation mapping of colorectal metastatic progression reveals metastasis-specific network alterations.

Silvestri A, Calvert V, Belluco C, Lipsky M, De Maria R, Deng J, Colombatti A, De Marchi F, Nitti D, Mammano E, Liotta L, Petricoin E, Pierobon M.

Clin Exp Metastasis. 2013 Mar;30(3):309-16. doi: 10.1007/s10585-012-9538-5. Epub 2012 Sep 29.

Center for Applied Proteomics and Molecular Medicine, George Mason University, 10900 University Blvd., Manassas, VA, 20110, USA.

Abstract

The mechanism by which tissue microecology influences invasion and metastasis is largely unknown. Recent studies have indicated differences in the molecular architecture of the metastatic lesion compared to the primary tumor, however, systemic analysis of the alterations within the activated protein signaling network has not been described. Using laser capture microdissection, protein microarray technology, and a unique specimen collection of 34 matched primary colorectal cancers (CRC) and synchronous hepatic metastasis, the quantitative measurement of the total and activated/phosphorylated levels of 86 key signaling proteins was performed. Activation of the EGFR-PDGFR-cKIT network, in addition to PI3K/AKT pathway, was found uniquely activated in the hepatic metastatic lesions compared to the matched primary tumors. If validated in larger study sets, these findings may have potential clinical relevance since many of these activated signaling proteins are current targets for molecularly targeted therapeutics. Thus, these findings could lead to liver metastasis specific molecular therapies for CRC.

Adrian Anghel • I think both patterns (protein phosphorylation and mRNA) should be important in this complicated equation of heterogeneity. Let’s not forget the so-called functional miRNA-mRNA regulatory modules (FMRMs). Also I think we have different patterns of this heterogeneity for different evolutive stages of the tumour.

 

Alvin L. Beers, Jr., M.D. • This is a great study, but bad news for attempting to tailor treatment based on molecular markers. Dr. Swanton’s comment: “herterogeneity is likely to complicate matters” is an understatement. Intratumoral heterogeneity, branched, instead of linear, evolution of mutational events portends a nightmare in trying to predict location and volume of biopsies. I am reminded of a series of articles in Nature 491 (22 November 2012) “Physical Scientists take on Cancer”. There is a great comment by Jennie Dusheck: “Cancer researchers now recognize that taming wild cancer cells – populations of cells that evolve, cooperate, and roam freely through the body-demand a wider-angle view than molecular biology has been able to offer. Cross-disciplinary collaborations can approach cancer a greater spatial and temporal scales, using mathematical methods more typical of engineering, physics, ecology and evolutionary biology. The sense of failure so evident five years ago is giving way to the excitement of a productive intellectual partnership.” I’m not certain how well the “productive partnership” is going, but this Swanton study confirms the limitations of molecular biology.

Stephen J. Williams, Ph.D. • Thanks Dr. Beers for adding in your comment and adding in Jennie’s comment. Certainly it is something to be aware of if a cancer center’s strategy is to rely solely on gene arrays to genotype tumors. I think Dr. Pettricoin’s work on using proteomics might give some resolution to the matter however, in communicating with Dr. Swanton, I did not get the feeling of an “all hope is lost” but just that, in the case of solid tumors like renal, that careful monitoring of tumors after treatment may be warranted and, more interestingly, from a scientific standpoint, is the genetic complexity surrounding the origin of the disease, and not simple mutational spectrum of a single clone.

Burke Lillian • This is clinically a very important issue. Right now, sequencing or massive approaches such as pan-phosphorylation studies are helpful because, although we know many of the drivers, these studies are actually identifying new genes or new pathways that are activated. After a few (or several years), we truly will know which genes are typically activated and there will be panels to look for these.

Emanuel Petricoin • yes, I agree. In fact, the company that I co-founded, Theranostics Health, Inc– is launching a CLIA based protein pathway activation mapping test at ASCO that measures actionable drug targets (e.g. phospho HER2, EGFR, HER3, AKT, ERK, JAK, STAT, p70S6) and total HER2, EGFR, HER3 and PTEN. So these tests are coming even now.

 

Alvin L. Beers, Jr., M.D. • I do not think that “all hope is lost” nor did I have the impression that Dr. Swanton feels that way with regards to molecular profiling of cancer. I certainly applaud further research into the molecular aspects of cancer biology. But I do not believe that this will be sufficient. Integrating physicial sciences into cancer biology makes perfect sense toward better understanding of this complex disease.

Eleni Papadopoulos-Bergquist • I have enjoyed reading these comments and different ideas regarding genetic testing and profiling. As a nurse and researcher at heart, this is information that will make a huge impact on drug protocols, therefore allowing the best and most specific treatment to each individual rather than having a standard treatment protocol. Even with the scientific complexity of specifying genotypes of particular cancers, there is still the question of each individuals body responding to treatment. I’d love to have some dialogue regarding immune response.

Bradford Graves • I too have enjoyed reading this discussion. I am not a clinician but as a drug discovery researcher I have been struck by some parallels to the concept of virus fitness in virology – particularly as applied to HIV. Drug discovery cannot wait for the final answers to the many important questions being addressed in the discussion initiated by Dr. Williams. The best we can do is to pursue a broad range of therapeutics that will give the clinicians the armament they will need to either cure a given cancer or to at least turn it into a chronic as opposed to an acute disease. There has been a measure of success in the HIV field and it seems like it will be achievable for cancer. Obviously, to the extent that the labels of driver and passenger mutations can be correctly applied will help to prioritize the targets we address.

David W. Anderson • I would suggest that you look at the following publications:

Horn and Pao, (2009) JCO 26: 4232-4234.

Bunn and Doebele (2011) JCO:29:1-3

Boguski et al. (2009) Customized care 2020: how medical sequencing and network biology will enable personalized medicine. F1000 Bio Report 1:7.

Jones, S et al. (2010). Evolution of an adenocarcinoma in response to selection by targeted kinase inhibitors. Genome Biology. 11:R82. Marco Marra’s group in Toronto.

Also look at how companies and organizations like Foundation Medicine, Caris, Clarient, and CollabRx who are using genomics and sequencing on a large scale to address cancer from a personalized/individual approach.

Cancer is/will be a chronic disease requiring individualized/combinatorial therapies in many cases.

Alvin L. Beers, Jr., M.D. • David. These are excellent articles by Paul Bunn and Mark Boguski regarding integrating molecular markers into diagnostic evaluation, and I’ve seen other papers of similiar elk, and likely there will be more to come. Particularly in NSC lung cancer, the SOC is to use these markers up front. Diagnosis based on histology alone can no longer be recommended. The challenge for the future is how to integrate other aspects of cell biology with these markers. It remains daunting that not only do we see heterogeneity in molecular within tumors at a particularly point in time, but that there is often an evolution of markers over time, ie, a “plasticity” of markers, whether treatment is given or not. We know that targeted agents, TKI’s, enzyme inhibitors are not curative, but do give an improvement in PFS. A great deal of this resistance has to do with this “moving target” aspect of cancer cell biology..

 

References:

1.         Gerlinger M, Rowan AJ, Horswell S, Larkin J, Endesfelder D, Gronroos E, Martinez P, Matthews N, Stewart A, Tarpey P et al: Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. The New England journal of medicine 2012, 366(10):883-892.

2.         Caldas C: Cancer sequencing unravels clonal evolution. Nature biotechnology 2012, 30(5):408-410.

3.         Losi L, Baisse B, Bouzourene H, Benhattar J: Evolution of intratumoral genetic heterogeneity during colorectal cancer progression. Carcinogenesis 2005, 26(5):916-922.

4.         Krivtsov AV, Armstrong SA: Cancer. Can one cell influence cancer heterogeneity? Science 2012, 338(6110):1035-1036.

5.         Friedmann-Morvinski D, Bushong EA, Ke E, Soda Y, Marumoto T, Singer O, Ellisman MH, Verma IM: Dedifferentiation of neurons and astrocytes by oncogenes can induce gliomas in mice. Science 2012, 338(6110):1080-1084.

6.         Mintz B, Cronmiller C: Normal blood cells of anemic genotype in teratocarcinoma-derived mosaic mice. Proceedings of the National Academy of Sciences of the United States of America 1978, 75(12):6247-6251.

7.         Watanabe T, Dewey MJ, Mintz B: Teratocarcinoma cells as vehicles for introducing specific mutant mitochondrial genes into mice. Proceedings of the National Academy of Sciences of the United States of America 1978, 75(10):5113-5117.

8.         Mintz B, Cronmiller C, Custer RP: Somatic cell origin of teratocarcinomas. Proceedings of the National Academy of Sciences of the United States of America 1978, 75(6):2834-2838.

 

 

Other articles on this site on “PERSONALIZED MEDICINE” and “CANCER” and “OMICS” include:

Personalized medicine-based diagnostic test for NSCLC

Personalized medicine and Colon cancer

Helping Physicians identify Gene-Drug Interactions for Treatment Decisions: New ‘CLIPMERGE’ program – Personalized Medicine @ The Mount Sinai Medical Center

Systems Diagnostics – Real Personalized Medicine: David de Graaf, PhD, CEO, Selventa Inc.

Issues in Personalized Medicine in Cancer: Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing

Personalized Medicine: Clinical Aspiration of Microarrays

Understanding the Role of Personalized Medicine

Directions for Genomics in Personalized Medicine

Paradigm Shift in Human Genomics – Predictive Biomarkers and Personalized Medicine – Part 1

Rewriting the Mathematics of Tumor Growth; Teams Use Math Models to Sort Drivers from Passengers

Diagnosing Diseases & Gene Therapy: Precision Genome Editing and Cost-effective microRNA Profiling

Breast Cancer: Genomic profiling to predict Survival: Combination of Histopathology and Gene Expression Analysis

Proteomics and Biomarker Discovery

 

 Also please see our upcoming e-book “Genomics Orientations for Individualized Medicine” in our Medical E-book Series at http://pharmaceuticalintelligence.com/biomed-e-books/genomics-orientations-for-personalized-medicine/volume-one-genomics-orientations-for-personalized-medicine/