Feeds:
Posts
Comments

Posts Tagged ‘heterogeneity’


Single-cell RNA-seq helps in finding intra-tumoral heterogeneity in pancreatic cancer

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

 

Pancreatic cancer is a significant cause of cancer mortality; therefore, the development of early diagnostic strategies and effective treatment is essential. Improvements in imaging technology, as well as use of biomarkers are changing the way that pancreas cancer is diagnosed and staged. Although progress in treatment for pancreas cancer has been incremental, development of combination therapies involving both chemotherapeutic and biologic agents is ongoing.

 

Cancer is an evolutionary disease, containing the hallmarks of an asexually reproducing unicellular organism subject to evolutionary paradigms. Pancreatic ductal adenocarcinoma (PDAC) is a particularly robust example of this phenomenon. Genomic features indicate that pancreatic cancer cells are selected for fitness advantages when encountering the geographic and resource-depleted constraints of the microenvironment. Phenotypic adaptations to these pressures help disseminated cells to survive in secondary sites, a major clinical problem for patients with this disease.

 

The immune system varies in cell types, states, and locations. The complex networks, interactions, and responses of immune cells produce diverse cellular ecosystems composed of multiple cell types, accompanied by genetic diversity in antigen receptors. Within this ecosystem, innate and adaptive immune cells maintain and protect tissue function, integrity, and homeostasis upon changes in functional demands and diverse insults. Characterizing this inherent complexity requires studies at single-cell resolution. Recent advances such as massively parallel single-cell RNA sequencing and sophisticated computational methods are catalyzing a revolution in our understanding of immunology.

 

PDAC is the most common type of pancreatic cancer featured with high intra-tumoral heterogeneity and poor prognosis. In the present study to comprehensively delineate the PDAC intra-tumoral heterogeneity and the underlying mechanism for PDAC progression, single-cell RNA-seq (scRNA-seq) was employed to acquire the transcriptomic atlas of 57,530 individual pancreatic cells from primary PDAC tumors and control pancreases. The diverse malignant and stromal cell types, including two ductal subtypes with abnormal and malignant gene expression profiles respectively, were identified in PDAC.

 

The researchers found that the heterogenous malignant subtype was composed of several subpopulations with differential proliferative and migratory potentials. Cell trajectory analysis revealed that components of multiple tumor-related pathways and transcription factors (TFs) were differentially expressed along PDAC progression. Furthermore, it was found a subset of ductal cells with unique proliferative features were associated with an inactivation state in tumor-infiltrating T cells, providing novel markers for the prediction of antitumor immune response. Together, the findings provided a valuable resource for deciphering the intra-tumoral heterogeneity in PDAC and uncover a connection between tumor intrinsic transcriptional state and T cell activation, suggesting potential biomarkers for anticancer treatment such as targeted therapy and immunotherapy.

 

References:

 

https://www.ncbi.nlm.nih.gov/pubmed/31273297

 

https://www.ncbi.nlm.nih.gov/pubmed/21491194

 

https://www.ncbi.nlm.nih.gov/pubmed/27444064

 

https://www.ncbi.nlm.nih.gov/pubmed/28983043

 

https://www.ncbi.nlm.nih.gov/pubmed/24976721

 

https://www.ncbi.nlm.nih.gov/pubmed/27693023

 

Read Full Post »


Variability of Gene Expression and Drug Resistance

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

New Data Suggest Extreme Genetic Diversity of Tumors May Impart Drug Resistance

NEW YORK (GenomeWeb) – Researchers from the University of Chicago and the Beijing Institute of Genomics have undertaken one of the most extensive analyses of the genome of a single tumor and found far greater genetic diversity than anticipated. Such variation, they said, may enable even small tumors to resist treatment.

“With 100 million mutations, each capable of altering a protein in some way, there is a high probability that a significant minority of tumor cells will survive, even after aggressive treatment,” Chung-I Wu, a University of Chicago researcher and senior author of the study, said in a statement. “In a setting with so much diversity, those cells could multiply to form new tumors, which would be resistant to standard treatments.”

 

Extremely high genetic diversity in a single tumor points to prevalence of non-Darwinian cell evolution

Shaoping Linga,1Zheng Hua,1Zuyu Yanga,1Fang Yanga,1Yawei LiaPei LinbKe ChenaLili DongaLihua CaoaYong TaoaLingtong HaoaQingjian ChenbQiang Gonga, et al.

Shaoping Ling,  PNAS   http://dx.doi.org:/10.1073/pnas.1519556112      http://www.pnas.org/content/early/2015/11/11/1519556112

A tumor comprising many cells can be compared to a natural population with many individuals. The amount of genetic diversity reflects how it has evolved and can influence its future evolution. We evaluated a single tumor by sequencing or genotyping nearly 300 regions from the tumor. When the data were analyzed by modern population genetic theory, we estimated more than 100 million coding region mutations in this unexceptional tumor. The extreme genetic diversity implies evolution under the non-Darwinian mode. In contrast, under the prevailing view of Darwinian selection, the genetic diversity would be orders of magnitude lower. Because genetic diversity accrues rapidly, a high probability of drug resistance should be heeded, even in the treatment of microscopic tumors.

The prevailing view that the evolution of cells in a tumor is driven by Darwinian selection has never been rigorously tested. Because selection greatly affects the level of intratumor genetic diversity, it is important to assess whether intratumor evolution follows the Darwinian or the non-Darwinian mode of evolution. To provide the statistical power, many regions in a single tumor need to be sampled and analyzed much more extensively than has been attempted in previous intratumor studies. Here, from a hepatocellular carcinoma (HCC) tumor, we evaluated multiregional samples from the tumor, using either whole-exome sequencing (WES) (n = 23 samples) or genotyping (n = 286) under both the infinite-site and infinite-allele models of population genetics. In addition to the many single-nucleotide variations (SNVs) present in all samples, there were 35 “polymorphic” SNVs among samples. High genetic diversity was evident as the 23 WES samples defined 20 unique cell clones. With all 286 samples genotyped, clonal diversity agreed well with the non-Darwinian model with no evidence of positive Darwinian selection. Under the non-Darwinian model,MALL (the number of coding region mutations in the entire tumor) was estimated to be greater than 100 million in this tumor. DNA sequences reveal local diversities in small patches of cells and validate the estimation. In contrast, the genetic diversity under a Darwinian model would generally be orders of magnitude smaller. Because the level of genetic diversity will have implications on therapeutic resistance, non-Darwinian evolution should be heeded in cancer treatments even for microscopic tumors.

Semantically Related Articles

 

 

 

The findings, which appeared in the Proceedings of the National Academy of Sciences this week, also call into question the widely held view that evolution at the cellular level is driven by Darwinian selection, revealing a level of rapid and extensive genetic diversity beyond what would be expected under this model.

In the study, the researchers focused on a single hepatocellular carcinoma tumor, roughly the size of a ping pong ball. They sampled 286 regions from a single slice of the tumor, studying each one with either whole-exome sequencing or genotyping under both the infinite-site and infinite-allele models of population genetics.

Based on their analyses, the team estimated more than 100 million coding region mutations in what they called an “unexceptional” tumor — more mutations than would ordinarily be expected by orders of magnitude, according to Wu.

This extreme genetic diversity, the study’s authors wrote, implies evolution under the non-Darwinian mode, which is driven by random mutations largely unaffected by natural selection. It also raises the question of why there is so little apparent Darwinian selection in the tumor.

The scientists speculated that in solid tumors, cells remain together and do not migrate, “so that when an advantageous mutation indeed emerges, cells carrying it are competing mostly with themselves. These mutations may confer advantages in fighting for space or extracting nutrients, but they are stifled by their own advantages,” they wrote.

Beneficial mutations may emerge on occasion, but in solid tumors the cell populations are “so structured that selection may often be blunted,” they stated. “The physiological effect has to be very strong to overcome those constraints.” Cancer drugs could remove those constraints, loosening up a cell population and allowing competition to occur, the investigators added.

Wu and his colleagues see the presence of so many mutations in a tumor as creating problems when it comes to treatment. “It almost guarantees that some cells will be resistant,” study co-author and University of Chicago oncologist Daniel Catenacci said in the statement. “But it also suggests that aggressive treatment could push tumor cells into a more Darwinian mode.”

Overall, the findings highlight the need to consider non-Darwinian evolution and the vast genetic diversity it can confer as factors when developing treatment strategies, even for small tumors, the researchers concluded.

Read Full Post »


Reporter and Curator: Ritu Saxena, PhD

Magnetic Resonance Imaging (MRI) is increasingly used in clinical diagnostics, for a rapidly growing number of indications. The MRI technique is non-invasive and can provide information on the anatomy, function and metabolism of tissues in vivo (Strijkers GJ, et al, Anticancer Agents Med Chem, May 2007;7(3):291-305). Basic contrast in the MRI image scans is as a result of contrast generated by differences in the relaxation times between different regions. Since the intrinsic contrast generated between regions is limited to allow clear and specific diagnosis, MRI contrast agents administered intravenously are increasingly being used to alter image contrast.

Gadoxetic acid, a gadolinium-based compound, is a recently developed hepatobiliary-specific contrast material for MRI that has high sensitivity in the detection of malignant liver tumors. Its salt, gadoxetate disodium, is marketed as Primovist in Europe and Eovist in the United States by Bayer HealthCare Pharmaceuticals. Gadoxetic acid is taken up by hepatocytes and then excreted into the bile ducts (Schuhmann-Giampieri G, et al, Radiology, Apr 1992;183(1):59-64). Therefore, hepatic focal lesions without normal hepatobiliary function are depicted as hypointense areas compared with the well-enhanced hyperintense background liver in the hepatobiliary phase of gadoxetic acid–enhanced MR imaging. In addition, gadoxetic acid can be used in the same way as gadopentetate dimeglumine to evaluate the hemodynamics of hepatic lesions in the dynamic phase after an intravenous bolus injection (Kitao A, et al, Radiology, Sep 2010;256(3):817-26).

Recently, researchers from Kanazawa University Graduate School of Medical Science, (Kanazawa, Japan) analyzed the correlation among biologic features, tumor marker production, and signal intensity at gadoxetic acid-enhanced MR imaging in hepatocellular carcinomas (HCCs). The findings were published in Radiology journal. The research was supported in part by a Grant-in-Aid for Scientific Research (21591549) from the Ministry of Education, Culture, Sports, Science and Technology; and by Health and Labor Sciences Research Grants for “Development of novel molecular markers and imaging modalities for earlier diagnosis of hepatocellular carcinoma.”

Research significance: HCC is the most frequent primary malignant tumor of liver and is the third most common cause of cancer death worldwide. It is the most Hepatocellular.

The accurate detection and characterization of HCC focal lesions is crucial for improving prognosis of patients with HCC.

Research problem: Gadoxetic acid–enhanced MR imaging is highly accurate for diagnosing HCC lesions. As discussed earlier, in this imaging process, hepatic focal lesions without normal hepatobiliary are hypointense as compared with the well-enhanced hyperintense background liver. However, approximately 6%–15% of hypervascular HCCs demonstrate isointensity or hyperintensity (Kitao A, et al, Eur Radiol, Oct 2011;21(10):2056-66).

Hypothesis: The reason for hyperintensity in some HCC lesions was previously shown to be due to overexpression of organic anion transporting polypeptide 8 (OATP8) (Kitao A, et al, Radiology, Sep 2010;256(3):817-26). The authors speculated that there might be a correlation of the tumor marker production and signal intensity (SI) on hepatobiliary phase images, which would reflect distinct genomic and proteomic expression of HCC. Thus, authors stated that “the purpose of this study was to analyze the correlation among the pathologic and biologic features, tumor marker production, with signal intensity (SI) on hepatobiliary phase gadoxetic acid–enhanced MR images of HCC” (Kitao A, et al, Radiology, Dec 2012;265(3):780-9).

Experimental design: From April 2008 to September 2011, 180 surgically resected HCCs in 180 patients (age, 65.0 years ± 10.3 [range, 34–83 years]; 138 men, 42 women) were classified as either hypointense (n = 158) or hyperintense (n = 22) compared with the signal intensity of the background liver on hepatobiliary phase gadoxetic acid–enhanced MR images (Abstract of the study).

Pathologic features were analyzed.

Serum analysis and immunohistochemical staining was performed and following were compared:

  1. Alpha fetoprotein (AFP) – is a main tumor marker of HCCs. AFP is the most abundant plasma protein found in the human fetus and plasma levels decrease rapidly after birth. A level above 500 nanograms/milliliter of AFP in adults can be indicative of hepatocellular carcinoma, germ cell tumors, and metastatic cancers of the liver.
  2. Absence of protein induced by vitamin K or antagonist-II (PIVKA-II) – is a clinically important serum tumor marker. PIVKAII is an incomplete coagulation factor prothrombin II whose production is related to the absence of vitamin K or the presence of the antagonist of vitamin K, which is the cofactor of g carboxylase that converts precursor into prothrombin.

Serum levels of both AFP and PIVKA-II correlate with HCC malignancy and prognosis (Miyaaki H, et al, J Gastroenterol, Dec 2007;42(12):962-8).

Results: The hyperintense HCCs showed significantly higher differentiation grade than the hypointense HCCs (P = .028). There was a significant difference in the proliferation pattern between the hypointense and hyperintense HCCs (P < .001) and the hyperintense HCCs showed a significantly lower rate of portal vein invasion than that of hypointense HCCs (P = .039). The serum levels of tumor markers AFP, AFP-L3, and PIVKA-II were significantly lower in the patients with hyperintense HCCs than in those with

hypointense HCCs (P = .003, .004, and .026). In addition, immunohistochemical analysis revealed that the expression of FP and PIVKA-II was lower in hyperintense than in hypointense HCCs (both P < .001). Also, hyperintense HCCs showed lower recurrence rate than hypointense HCCs (P = .039).

Conclusion: Variation was observed within differently stained lesions of HCC in the hepatobiliary phase gadoxetic acid–enhanced MR images as evident in tumor marker expression, proliferation pattern, differentiation grade, immunohistochemical analysis and recurrence.  The results lead to the hypothesis that hyperintense HCCs in the hepatobiliary phase gadoxetic acid–enhanced MR images might represent a particular type of HCC that is hypervascular and biologically less aggressive as compared to hypovascular HCCs. Interestingly, this research is another great example where tumor heterogeneity has been brought to light (similar to genetic heterogeneity in triple negative breast cancer deciphered by Lehmann BD, et al, 2011). The heterogeneity might be the basis of answers to why a particular therapy fails in a certain tumor type and fortifying evidence for appropriate analysis of the tumor for obtaining the desired tumor response from a particular drug.

Reference:

Kitao A, et al, Radiology, Dec 2012;265(3):780-9

Strijkers GJ, et al, Anticancer Agents Med Chem, May 2007;7(3):291-305

Schuhmann-Giampieri G, et al, Radiology, Apr 1992;183(1):59-64

Kitao A, et al, Radiology, Sep 2010;256(3):817-26

Kitao A, et al, Eur Radiol, Oct 2011;21(10):2056-66

Kitao A, et al, Radiology, Sep 2010;256(3):817-26

Miyaaki H, et al, J Gastroenterol, Dec 2007;42(12):962-8

Lehmann BD, et al, J Clin Invest, 2011;121(7):2750–2767

Read Full Post »


Reporter: Ritu Saxena, Ph.D.

With the number of cancer cases plummeting every year, there is a dire need for finding a cure to wipe the disease out. A number of therapeutic drugs are currently in use, however, due to heterogeneity of the disease targeted therapy is required. An important criteria that needs to be addressed in this context is the –‘tumor response’ and how it could be predicted, thereby improving the selection of patients for cancer treatment. The issue of tumor response has been addressed in a recent editorial titled “Tumor response criteria: are they appropriate?” published recently in Future Oncology.

The article talks about how the early tumor treatment response methods came into practice and how we need to redefine and reassess the tumor response.

Defining ‘tumor response’ has always been a challenge

WHO defines a response to anticancer therapy as 50% or more reduction in the tumor size measured in two perpendicular diameters. It is based on the results of experiments performed by Moertel and Hanley in 1976 and later published by Miller et al in 1981. Twenty years later, in the year 2000, the US National Cancer Institute, with the European Association for Research and Treatment of Cancer, proposed ‘new response criteria’ for solid tumors; a replacement of 2D measurement with measurement of one dimen­sion was made. Tumor response was defined as a decrease in the largest tumor diameter by 30%, which would translate into a 50% decrease for a spherical lesion. However, response criteria have not been updated after that and there a structured standardization of treatment response is still required especially when several studies have revealed that the response of tumors to a therapy via imaging results from conventional approaches such as endoscopy, CT scan, is not reliable. The reason is that evaluating the size of tumor is just one part of the story and to get the complete picture inves­tigating and evaluating the tissue is essential to differentiate between treatment-related scar, fibrosis or micro­scopic residual tumor.

In clinical practice, treatment response is determined on the basis of well-established parameters obtained from diagnostic imaging, both cross-sectional and functional. In general, the response is classified as:

  • Complete remission: If a tumor disappears after a particular therapy,
  • Partial remission: there is residual tumor after therapy.

For a doctor examining the morphology of the tumor, complete remission might seem like good news, however, mission might not be complete yet! For example, in some cases, with regard to prognosis, patients with 0% residual tumor (complete tumor response) had the same prognosis com­pared with those patients with 1–10% residual tumor (subtotal response).

Another example is that in patients demonstrating complete remission of tumor response as observed with clinical, sonographic, functional (PET) and histopathological analysis experience recur­rence within the first 2 years of resection.

Adding complexity to the situation is the fact that the appropriate, clinically relevant timing of assess­ment of tumor response to treatment remains undefined. An example mentioned in the editorial is – for gastrointestinal (GI) malignancies, the assessment timing varies considerably from 3 to 6 weeks after initia­tion of neoadjuvant external beam radiation. Further, time could vary depending upon the type of radiation administered, i.e., if it is external beam, accelerated hyperfractionation, or brachytherapy.

Abovementioned examples remind us of the intricacy and enigma of tumor biol­ogy and subsequent tumor response.

Conclusion

Owing to the extraordinary het­erogeneity of cancers between patients, and pri­mary and metastatic tumors in the same patients, it is important to consider several factors while determining the response of tumors to different therapie in clinical trials. Authors exclaim, “We must change the tools we use to assess tumor response. The new modality should be based on individualized histopathology as well as tumor molecular, genetic and functional characteristics, and individual patients’ charac­teristics.”

Future perspective

Editorial points out that the oncologists, radiotherapists, and immunologists all might have a different opinion and observation as far as tumor response is considered. For example, surgical oncologists might determine a treatment to be effective if the local tumor control is much better after multimodal treatment, and that patients post-therapeutically also reveal an increase of the rate of microscopic and macroscopic R0-resection. Immunologists, on the other hand, might just declare a response if immune-competent cells have been decreased and, possibly, without clinical signs of decrease of tumor size.

What might be the answer to the complexity to reading tumor response is stated in the editorial – “an interdisciplinary initiative with all key stake­holders and disciplines represented is imperative to make predictive and prognostic individualized tumor response assessment a modern-day reality. The integrated multidisciplinary panel of international experts need to define how to leverage existing data, tissue and testing platforms in order to predict individual patient treatment response and prog­nosis.”

Sources:

Editorial : Björn LDM Brücher et al Tumor response criteria: are they appropriate? Future Oncology August 2012, Vol. 8, No. 8, 903-906.

Miller AB, Hoogstraten B, Staquet M, Winkler A. Reporting results of cancer treatment. Cancer 1981, 47(1),207–214.

Related articles to this subject on this Open Access Online Scientific Journal:

See comment written for :

Knowing the tumor’s size and location, could we target treatment to THE ROI by applying

https://pharmaceuticalintelligence.com/2012/10/16/knowing-the-tumors-size-and-location-could-we-target-treatment-to-the-roi-by-applying-imaging-guided-intervention/imaging-guided intervention?

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

https://pharmaceuticalintelligence.com/2012/12/01/personalized-medicine-cancer-cell-biology-and-minimally-invasive-surgery-mis/

Read Full Post »