Posts Tagged ‘tumor response’

Improving imaging based assessment of tumours’ response to treatment

Writer: Dror Nir, PhD.

The protocol for imaging-based assessment of cancer patients’ response to oncological drugs is known as the RECIST 1.1 criteria; The Role of Medical Imaging in Personalized Medicine . RECIST is mainly relying on morphological evaluation of tumors’ size . I recently participated to a webinar organised by Oncodesign which presented the potential use of more advanced imaging techniques as tools to improve the assessment of cancer patients’ response during oncological clinical trials.

It’s first part, describes a methodology developed based on the original approach of the DITEP* at the “Institut Gustave Roussy”. A method that takes into account kinetics of tumor growth at the pre-treatment phase and along the entire treatment sequence. The conclusion is that adding Tumor Growth Rate (TGR) assessment in Phase I and Phase III clinical trials is simple and provides clinically relevant information: (i) It allows for an early and precise assessment of the tumor growth, (ii) It reveals drug-specific profiles, suggesting its potential use for the early assessment of drug activity, (iii)TGR is independently associated with prognosis both in early clinical trials and in phase III setting.

The second part  presents two functional imaging modalities based on MRI: diffusion-weighted imaging (Dw-MRI) and Dynamic Contrast-Enhanced MRI (DCE-MRI). Dw-MRI gives measures of tissue architecture at the cellular level, whereas DCE-MRI provides information on the vascular status of tumors. Both methods have been standardized and used extensively as early PD biomarkers of the efficacy of anticancer therapies. The presentation goes through preclinical and clinical case studies illustrating how these two techniques can be used to evaluate the activity of novel drug candidates.

I recommend watching a recording of this webinar on YouTube . Note, the voice recording is not so good but, the effort is worthwhile….


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AMPK Is a Negative Regulator of the Warburg Effect and Suppresses Tumor Growth In Vivo

Reporter-Curator: Stephen J. Williams, Ph.D.

There has been a causal link between alterations in cellular metabolism and the cancer phenotype.  Reorganization of cellular metabolism, marked by a shift from oxidative phosphorylation to aerobic glycolysis for cellular energy requirements (Warburg effect), is considered a hallmark of the transformed cell.  In addition, if tumors are to survive and grow, cancer cells need to adapt to environments high in metabolic stress and to avoid programmed cell death (apoptosis). Recently, a link between cancer growth and metabolism has been supported by the discovery that the LKB1/AMPK signaling pathway as a tumor suppressor axis[1].

LKB1/AMPK/mTOR Signaling Pathway

The Liver Kinase B1 (LKB1)/AMPK  AMP-activated protein kinase/mammalian Target of Rapamycin Complex 1 (mTORC1) signaling pathway links cellular metabolism and energy status to pathways involved in cell growth, proliferation, adaption to energy stress, and autophagy.  LKB1 is a master control for 14 other kinases including AMPK, a serine-threonine kinase which senses cellular AMP/ATP ratios.  In response to cellular starvation, AMPK is allosterically activated by AMP, leading to activation of ATP-generating pathways like fatty acid oxidation and blocking anabolic pathways, like lipid and cholesterol synthesis (which consume ATP).  In addition, AMPK regulates cell growth, proliferation, and autophagy by regulating the mTOR pathway.  AMPK activates the tuberous sclerosis complex 1/2, which ultimately inhibits mTORC1 activity and inhibits protein translation.  This mTOR activity is dis-regulated in many cancers.

LKB1AMPK pathway

LKB1/AMPK in Cancer

  • Somatic mutations of the STK11 gene encoding LKB1 are detected in lung and cervical cancers
  • Therefore LKB1 may be a strong tumor suppressor
  • Pharmacologic activation of LKB1/AMPK with metformin can suppress cancer cell growth

In a recent Cell Metabolism paper[2], Brandon Faubert and colleagues describe how AMPK activity reduces aerobic glycolysis and tumor proliferation while loss of AMPK activity promotes tumor proliferation by shifting cells to aerobic glycolysis and increasing anabolic pathways in a HIF1-dependent manner.

The paper’s major findings were as follows:

  • Loss of AMPKα1 cooperates with the Myc oncogene to accelerate lymphomagenesis
  • AMPKα dysfunction enhances aerobic glycolysis (Warburg effect)
  • Inhibiting HIF-1α reverses the metabolic effects of AMPKα loss
  • HIF-1α mediates the growth advantage of tumors with reduced AMPK signaling


AMPK is a metabolic sensor that helps maintain cellular energy homeostasis. Despite evidence linking AMPK with tumor suppressor functions, the role of AMPK in tumorigenesis and tumor metabolism is unknown. Here we show that AMPK negatively regulates aerobic glycolysis (the Warburg effect) in cancer cells and suppresses tumor growth in vivo. Genetic ablation of the α1 catalytic subunit of AMPK accelerates Myc-induced lymphomagenesis. Inactivation of AMPKα in both transformed and nontransformed cells promotes a metabolic shift to aerobic glycolysis, increased allocation of glucose carbon into lipids, and biomass accumulation. These metabolic effects require normoxic stabilization of the hypoxia-inducible factor-1α (HIF-1α), as silencing HIF-1α reverses the shift to aerobic glycolysis and the biosynthetic and proliferative advantages conferred by reduced AMPKα signaling. Together our findings suggest that AMPK activity opposes tumor development and that its loss fosters tumor progression in part by regulating cellular metabolic pathways that support cell growth and proliferation.

Below is the graphical abstract of this paper.

Graphical Abstract FINAL.pptx

(Photo credit reference(2; Faubert et. al) permission from Elsevier)

However, this regulation of tumor promotion by AMPK may be more complicated and dependent on the cellular environment.

Nissam Hay from the University of Illinois College of Medicine, Chicago, Illinois, USA and his co-workers Sang-Min Jeon and Navdeep Chandel were investigating the mechanism through which LKB1/AMPK regulate the balance between cancer cell growth and apoptosis under energy stress[3]. In their system, the loss of function of either of these proteins makes cells more sensitive to apoptosis in low glucose environments, and cells deficient in either AMPK or LKB1 were shown to be resistant to oncogenic transformation.  Whereas previous studies showed (as above) AMPK opposes tumor proliferation in a HIF1-dependent manner, their results showed AMPK could promote tumor cell survival during periods of low glucose or altered redox status.

The researchers incubated LKB1-deficient cancer cells in the presence of either glucose or one of the non-metabolizable glucose analogues 2-deoxyglucose (2DG) and 5-thioglucose (5TG), and found that 2DG, but not 5TG, induced the activation of AMPK and protected the cells from apoptosis, even in cells that were deficient in LKB1.

The authors demonstrated that glucose deprivation depleted NADPH levels, increased H2O2 levels and increased cell death, and that this was accelerated in cells deficient in the enzyme glucose-6-phosphate dehydrogenase. Anti-oxidants were also found to inhibit cell death in cells deficient in either AMPK or LKB1.

Knockdown or knockout of either LKB1 or AMPK in cancer cells significantly increased levels of H2O2 but not of peroxide (O2) during glucose depletion. The glucose analogue 2DG was able to activate AMPK and maintain high levels of NADPH and low levels of H2O2 in these cells.

The nucleotide coenzyme NADPH is generated in the pentose phosphate pathway and mitochondrial metabolism, and consumed in H2O2 elimination and fatty acid synthesis. If glucose is limited mitochondrial metabolism becomes the major source of NADPH, supported by fatty acid oxidation. AMPK is known to be a regulator of fatty acid metabolism through inhibition of two acetyl-CoA carboxylases, ACC1 and ACC2.

Short interfering RNAs (siRNAs) to knock down levels of both ACC1 and ACC2 in A549 cancer cells and found that only ACC2 knockdown significantly increased peroxide accumulation and apoptosis, while over-expression of mutant ACC1 and ACC2 in LKB1-proficient cells increased H2O2 and apoptosis.

Therefore, it was concluded AMPK acts to promote early tumor growth and prevent apoptosis in conditions of energy stress through inhibiting acetyl-CoA carboxylase activity, thus maintaining NADPH levels and preventing the build-up of peroxide in glucose-deficient conditions.

This may appear to be conflicting with the previous report in this post however, it is possible that these reports reflect differences in the way cells respond to various cellular stresses, be it hypoxia, glucose deprivation, or changes in redox status.  Therefore a complex situation may arise:

  • AMPK promotes tumor progression under glucose starvation
  • AMPK can oppose tumor proliferation under a normoxic, HIF1-dependent manner
  • Could AMPK regulation be different in cancer stem cells vs. non-stem cell?


1.            Green AS, Chapuis N, Lacombe C, Mayeux P, Bouscary D, Tamburini J: LKB1/AMPK/mTOR signaling pathway in hematological malignancies: from metabolism to cancer cell biology. Cell Cycle 2011, 10(13):2115-2120.

2.            Faubert B, Boily G, Izreig S, Griss T, Samborska B, Dong Z, Dupuy F, Chambers C, Fuerth BJ, Viollet B et al: AMPK is a negative regulator of the Warburg effect and suppresses tumor growth in vivo. Cell metabolism 2013, 17(1):113-124.

3.            Jeon SM, Chandel NS, Hay N: AMPK regulates NADPH homeostasis to promote tumour cell survival during energy stress. Nature 2012, 485(7400):661-665.

 Other posts on this site related to Warburg Effect and Cancer include:

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Author and curator: Ritu Saxena, Ph.D.

This post attempts to integrate three posts and to embed all comments made to all three papers, allowing the reader a critically thought compilation of evidence-based medicine and scientific discourse.

Dr. Dror Nir authored a post on October 16th titled “Knowing the tumor’s size and location, could we target treatment to THE ROI by applying imaging-guided intervention?” The article attracted over 20 comments from readers including researchers and oncologists debating the following issues:

  • imaging technologies in cancer
  • tumor size, and
  • tumor response to treatment.

The debate lead to several new posts authored by:

This post is a compilation of the views of authors representing different specialties including research and medicine. In medicine: Pathology, Oncology Surgery and Medical Imaging, are represented.

Dr. Nir’s post talked about an advanced technique developed by the researchers at Sunnybrook Health Sciences Centre, University of Toronto, Canada for cancer lesions’ detection and image-guided cancer treatment in the specific Region of Interest (ROI). The group was successfully able to show the feasibility and safety of magnetic resonance imaging (MRI) – controlled transurethral ultrasound therapy for prostate cancer in eight patients.

The dilemma of defining the Region of Interest for imaging-based therapy

Dr. Bernstein, one of the authors at, a Fellow of the American College of Pathology, reiterated the objective of the study stating that “Their study’s objective was to prove that using real-time MRI guidance of HIFU treatment is possible and it guarantees that the location of ablated tissue indeed corresponds to the locations planned for treatment.” He expressed his opinion about the study by bringing into focus a very important issue i.e., given the fact that the part surrounding the cancer tissue is in the transition state, challenge in defining a ROI that could be approached by imaging-based therapy. Regarding the study discussed, he states – “This is a method demonstration, but not a proof of concept by any means.  It adds to the cacophany of approaches, and in a much larger study would prove to be beneficial in treatment, but not a cure for serious prostate cancer because it is unlikely that it can get beyond the margin, and also because there is overtreatment at the cutoff of PSA at 4.0. I think that the pathologist has to see the tissue, and the standard in pathology now is for any result that is cancer, two pathologists or a group sitting together should see it. It’s not an easy diagnosis.”

“The crux of the matter in terms of capability is that the cancer tissue, adjacent tissue, and the fibrous matrix are all in transition to the cancerous state. It is taught to resect leaving “free margin”, which is better aesthetically, and has had success in breast surgery. The dilemma is that the patient may return, but how soon?” concludes Dr. Larry.

Dr. Nir responded, “The philosophy behind lumpectomy is preserving quality of life. It was Prof. Veronesi (IEO) who introduced this method 30 years ago noticing that in the majority of cases; the patient will die from something else before presenting recurrence of breast cancer. It is well established that when the resection margins are declared by a pathologist (as good as he/she could be) as “free of cancer”, the probability of recurrence is much lower than otherwise. He explains further, “The worst enemy of finding solutions is doing nothing while using the excuse of looking for the “ultimate solution.” Personally, I believe in combining methods and improving clinical assessment based on information fusion. Being able to predict, and then timely track the response to treatment is a major issue that affects survival and costs!

In this discussion my view is expressed, below.

  • The paper that discusses imaging technique had the objective of finding out whether real-time MRI guidance of treatment was even possible and if yes, whether the treatment could be performed in accurate location of the ROI? The data reveals they were pretty successful in accomplishing their objective and of course that gives hope to the imaging-based targeted therapies.
  • Whether the ROI is defined properly and if it accounts for the real tumor cure, is a different question. Role of pathologists and the histological analysis and what they bring to the table cannot be ruled out, and the absence of a defined line between the tumor and the stromal region in the vicinity is well documented. However, that cannot rule out the value and scope of imaging-based detection and targeted therapy. After all, it is seminal in guiding minimally invasive surgery.
  • As another arm of personalized medicine-based cure for cancer, molecular biologists at MD Anderson have suggested molecular and genetic profiling of the tumor to determine genetic aberrations on the basis of which matched-therapy could be recommended to patients.
  • When phase I trial was conducted, the results were encouraging and the survival rate was better in matched-therapy patients compared to unmatched patients. Therefore, every time there is more to consider when treating a cancer patient and who knows a combination of views of oncologists, pathologists, molecular biologists, geneticists, surgeons would device improvised protocols for diagnosis and treatment. It is always going to be complicated and generalizations would never give an answer. Smart interpretations of therapies – imaging-based or others would always be required!

To read additional comments, including those from Dr. Williams, Dr. Lev-Ari, refers to:

Knowing the tumor’s size and location, could we target treatment to THE ROI by applying imaging-guided intervention? Author and Reporter: Dror Nir, Ph.D.

Dr. Lev-Ari in her paper linked three fields that bear weight in the determination of Tumor Response to Therapy:

  • Personalized Medicine
  • Cancer Cell Biology, and
  • Minimally Invasive Surgery (MIS)

Her objectives were to address research methodology, the heterogeneity innate to Cancer Cell Biology and Treatment choice in the Operating Room — all are related to the topic at hand: How to deliver optimal care with least invasive intervention course.

Any attempt aimed at approaching this desirable result, called Personalized Medicine,  involves engagement in three strategies:

  • prediction of Patient’s reaction to Drug induction
  • design of Clinical Trials to validate drug efficacy on small subset of patients predicted to react favorable to drug regimen, increasing validity and reliability
  • Genetical identification of patients at no need to have a drug administered if non sensitivity to the drug has been predicted

These method are to be applied to a list of 56 leading Cancer types.

While the executive task of the clinician remains to assess the differentiation in Tumor Response to Treatment, pursuit of  individualized histopathology, as well as tumor molecular, genetic and functional characteristics has to take into consideration the “total” individual patients’ characteristics: age, co-morbidities, secondary risks and allergies to drugs.

In Dr. Lev-Ari’s paper Minimally Invasive Treatment (MIT) is compared with Minimally Invasive Surgery (MIS) applied for tumor resection.  In many cases MIS is not the right surgical decision, yet, it is applied for a corollary of patient-centered care considerations. At present, facing the unknown of the future behavior of the tumor as its response to therapeutics bearing uncertainty related to therapy outcomes.

Forget me not – says the ‘Stroma’

Dr. Brücher, the author of review on tumor response criteria, expressed his views on the topic. He remembers that 10 years ago, every cancer researcher stated – “look at the tumor cells only – forget the stroma”. However, the times have changed, “now, everyone knows that it is a system we are looking at, and viewing and analyzing only tumor cells is really not enough.”

He went on to state “if we would be honest, we would have to declare that all data, which had been produced 8-13 years ago, dealing with laser capture microdissection, would need a rescrutinization, because the influence of the stroma was ‘forgotten’.”

He added, “the surgeon looks at the ‘free margin’ in a kind of reductionable model, the pathologist is more the control instance. I personally see the pathologist as ‘the control instance’ of surgical quality. Therefore, not the wish of the surgeon is important, the objective way of looking into problems or challenges. Can a pathologist always state if a R0-resection had been performed?”

What is the real RO-resection?

There have been many surrogate marker analysis, says Dr. Brücher, and that a substantially well thought through structured analysis has never been done: mm by mm and afterwards analyzing that by a ROC analysis. For information on genetic markers on cancer, refer to the following post by Dr. Lev-Ari’s: Personalized Medicine: Cancer Cell Biology and Minimally Invasive Surgery (MIS)

He also stated that there is no gold standard to compare the statistical ROC analysis to. Often it is just declared and stated but it is still not clear what the real RO-resection is?

He added, “in some organs it is very difficult and we all (surgeons, pathologists, clinicians) that we always get to the limit, if we try interpreting the R-classification within the 3rd dimension.”

Dr. Brücher explains regarding resectability classification, “If lymph nodes are negative it does not mean, lymph nodes are really negative. For example, up to 38% upper GI cancers have histological negative lymph nodes, but immunohistochemical positive lymph nodes. And, Stojadinovic et al have also shown similar observations at el in colorectal cancer. So the 4th dimension of cancer – the lymph nodes / the lymphatic vessel invasion are much more important than just a TNM classification, which unfortunately does often not reflect real tumor biology.”

The discussion regarding the transition state of the tumor surrounding tissue and the ‘free margin’ led to a bigger issue, the heterogeneity of tumors.

Dr. Bernstein quoted a few lines from the review article titled “Tumor response criteria: are they appropriate?, authored by Dr Björn LDM Brücher et al published in Future Oncology in 2012.

  • Tumor heterogeneity is a ubiquitous phemomenon. In particular, there are important differences among the various types of gastrointestinal (GI) cancers in terms of tumor biology, treatment response and prognosis.
  • This forms the principal basis for targeted therapy directed by tumor-specific testing at either the gene or protein level. Despite rapid advances in our understanding of targeted therapy for GI cancers, the impact on cancer survival has been marginal.
  • Can tumor response to therapy be predicted, thereby improving the selection of patients for cancer treatment?
  • In 2000, the NCI with the European Association for Research and Treatment of Cancer, proposed a replacement of 2D measurement with a decrease in the largest tumor diameter by 30% in one dimension. Tumor response as defined would translate into a 50% decrease for a spherical lesion
  • We must rethink how we may better determine treatment response in a reliable, reproducible way that is aimed at individualizing the therapy of cancer patients.
  • We must change the tools we use to assess tumor response. The new modality should be based on empirical evidence that translates into relevant and meaningful clinical outcome data.
  • This becomes a conundrum of sorts in an era of ‘minimally invasive treatment’.
  • Integrated multidisciplinary panel of international experts – not sure that that will do it.

Dr. Bernstein followed up by authoring a separate post on tumor response. His views on tumor response criteria have been quoted in the following paragraphs:

Can tumor response to therapy be predicted?

The goal is not just complete response. Histopathological response seems to be related post-treatment histopathological assessment but it is not free from the challenge of accurately determining treatment response, as this method cannot delineate whether or not there are residual cancer cells. Functional imaging to assess metabolic response by 18-fluorodeoxyglucose PET also has its limits, as the results are impacted significantly by several variables:

• tumor type
• sizing
• doubling time
• anaplasia?
• extent of tumor necrosis
• type of antitumor therapy and the time when response was determined.

The new modality should be based on individualized histopathology as well as tumor molecular, genetic and functional characteristics, and individual patients’ characteristics, a greater challenge in an era of ‘minimally invasive treatment’.

This listing suggests that for every cancer the following data has to be collected (except doubling time). If there were five variables, the classification based on these alone would calculate to be very sizable based on Eugene Rypka’s feature extraction and classification.

But looking forward, time to remission and disease free survival are additionally important. Treatment for cure is not the endpoint, but the best that can be done is to extend the time of survival to a realistic long term goal and retain a quality of life.

For detailed discussion on the topic of tumor response and comments refer to the following posts:

What can we expect of tumor therapeutic response?

Author: Larry H. Bernstein, MD, FCAP

Judging ‘Tumor response’-there is more food for thought

Reporter: Ritu Saxena, Ph.D.

Additional Sources:

Research articles:

Brücher BLDM  et al. Tumor response criteria: are they appropriate? Future Oncol. August Vol. 8, No. 8, Pages 903-906 (2012).

Brücher BLDM, Piso P, Verwaal V et al. Peritoneal carcinomatosis: overview and basics. Cancer Invest.30(3),209–224 (2012).

Brücher BLDM, Swisher S, Königsrainer A et al. Response to preoperative therapy in upper gastrointestinal cancers. Ann. Surg. Oncol.16(4),878–886 (2009).

Miller AB, Hoogstraten B, Staquet M, Winkler A. Reporting results of cancer treatment. Cancer47(1),207–214 (1981).

Therasse P, Arbuck SG, Eisenhauer EA et al. New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada. J. Natl Cancer Inst.92(3),205–216 (2000).

Brücher BLDM, Becker K, Lordick F et al. The clinical impact of histopathological response assessment by residual tumor cell quantification in esophageal squamous cell carcinomas. Cancer106(10),2119–2127 (2006).

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