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Archive for the ‘Cancer Genomics’ Category


Complex rearrangements and oncogene amplification revealed by long-read DNA and RNA sequencing of a breast cancer cell line

Reporter: Stephen J. Williams, PhD

In a Genome Research report by Marie Nattestad et al. [1], the SK-BR-3 breast cancer cell line was sequenced using a long read single molecule sequencing protocol in order to develop one of the most detailed maps of structural variations in a cancer genome to date.  The authors detected over 20,000 variants with this new sequencing modality, whereas most of these variants would have been missed by short read sequencing.  In addition, a complex sequence of nested duplications and translocations occurred surrounding the ERBB2 (HER2) while full-length transcriptomic analysis revealed novel gene fusions within the nested genomic variants.  The authors suggest that combining this long-read genome and transcriptome sequencing results in a more comprehensive coverage of tumor gene variants and “sheds new light on the complex mechanisms involved in cancer genome evolution.”

Genomic instability is a hallmark of cancer [2], which lead to numerous genetic variations such as:

  • Copy number variations
  • Chromosomal alterations
  • Gene fusions
  • Deletions
  • Gene duplications
  • Insertions
  • Translocations

Efforts such as the Cancer Genome Atlas [3], and the International Genome Consortium (2010) use short-read sequencing technology to detect and analyze thousands of commonly occurring mutations however short-read technology has a high false positive and negative rate for detecting less common genetic structural variations {as high as 50% [4]}. In addition, short reads cannot detect variations in close proximity to each other or on the same molecule, therefore underestimating the variation number.

Methods:  The authors used a long-read sequencing technology from Pacific Biosciences (SMRT) to analyze the mutational and structural variation in the SK-BR-3 breast cancer cell line.  A split read and within-read mapping approach was used to detect variants of different types and sizes.  In general, long-reads have better alignment qualities than short reads, resulting in higher quality mapping. Transcriptomic analysis was performed using Iso-Seq.

Results: Using the SMRT long-read sequencing technology from Pacific Biosciences, the authors were able to obtain 71.9% sequencing coverage with average read length of 9.8 kb for the SK-BR-3 genome.

A few notes:

  1. Most amplified regions (33.6 copies) around the locus spanning the ERBB2 oncogene and around MYC locus (38 copies), EGFR locus (7 copies) and BCAS1 (16.8 copies)
  2. The locus 8q24.12 had the most amplifications (this locus contains the SNTB1 gene) at 69.2 copies
  3. Long-read sequencing showed more insertions than deletions and suggests an underestimate of the lengths of low complexity regions in the human reference genome
  4. Found 1,493 long read variants, 603 of which were between different chromosomes
  5. Using Iso-Seq in conjunction with the long-read platform, they detected 1,692,379 isoforms (93%) mapping to the reference genome and 53 putative gene fusions (39 of which they found genomic evidence)

A table modified from the paper on the gene fusions is given below:

Table 1. Gene fusions with RNA evidence from Iso-Seq and DNA evidence from SMRT DNA sequencing where the genomic path is found using SplitThreader from Sniffles variant calls. Note link in table is  GeneCard for each gene.

SplitThreader path

 

# Genes Distance
(bp)
Number
of variants
Chromosomes
in path
Previously observed in references
1 KLHDC2 SNTB1 9837 3 14|17|8 Asmann et al. (2011) as only a 2-hop fusion
2 CYTH1 EIF3H 8654 2 17|8 Edgren et al. (2011); Kim and Salzberg
(2011); RNA only, not observed as 2-hop
3 CPNE1 PREX1 1777 2 20 Found and validated as 2-hop by Chen et al. 2013
4 GSDMB TATDN1 0 1 17|8 Edgren et al. (2011); Kim and Salzberg
(2011); Chen et al. (2013); validated by
Edgren et al. (2011)
5 LINC00536 PVT1 0 1 8 No
6 MTBP SAMD12 0 1 8 Validated by Edgren et al. (2011)
7 LRRFIP2 SUMF1 0 1 3 Edgren et al. (2011); Kim and Salzberg
(2011); Chen et al. (2013); validated by
Edgren et al. (2011)
8 FBXL7 TRIO 0 1 5 No
9 ATAD5 TLK2 0 1 17 No
10 DHX35 ITCH 0 1 20 Validated by Edgren et al. (2011)
11 LMCD1-AS1 MECOM 0 1 3 No
12 PHF20 RP4-723E3.1 0 1 20 No
13 RAD51B SEMA6D 0 1 14|15 No
14 STAU1 TOX2 0 1 20 No
15 TBC1D31 ZNF704 0 1 8 Edgren et al. (2011); Kim and Salzberg
(2011); Chen et al. (2013); validated by
Edgren et al. (2011); Chen et al. (2013)

 

SplitThreader found two different paths for the RAD51B-SEMA6D gene fusion and for the LINC00536-PVT1 gene fusion. Number of Iso-Seq reads refers to full-length HQ-filtered reads. Alignments of SMRT DNA sequence reads supporting each of these gene fusions are shown in Supplemental Note S2.

 

 References

 

  1. Nattestad M, Goodwin S, Ng K, Baslan T, Sedlazeck FJ, Rescheneder P, Garvin T, Fang H, Gurtowski J, Hutton E et al: Complex rearrangements and oncogene amplifications revealed by long-read DNA and RNA sequencing of a breast cancer cell line. Genome research 2018, 28(8):1126-1135.
  2. Hanahan D, Weinberg RA: The hallmarks of cancer. Cell 2000, 100(1):57-70.
  3. Kandoth C, McLellan MD, Vandin F, Ye K, Niu B, Lu C, Xie M, Zhang Q, McMichael JF, Wyczalkowski MA et al: Mutational landscape and significance across 12 major cancer types. Nature 2013, 502(7471):333-339.
  4. Sudmant PH, Rausch T, Gardner EJ, Handsaker RE, Abyzov A, Huddleston J, Zhang Y, Ye K, Jun G, Fritz MH et al: An integrated map of structural variation in 2,504 human genomes. Nature 2015, 526(7571):75-81.

 

Other articles on Cancer Genome Sequencing in this Open Access Journal Include:

 

International Cancer Genome Consortium Website has 71 Committed Cancer Genome Projects Ongoing

Loss of Gene Islands May Promote a Cancer Genome’s Evolution: A new Hypothesis on Oncogenesis

Identifying Aggressive Breast Cancers by Interpreting the Mathematical Patterns in the Cancer Genome

CancerBase.org – The Global HUB for Diagnoses, Genomes, Pathology Images: A Real-time Diagnosis and Therapy Mapping Service for Cancer Patients – Anonymized Medical Records accessible to

 

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An Intelligent DNA Nanorobot to Fight Cancer by Targeting HER2 Expression

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

 

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

 

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

 

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

 

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

 

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

 

References:

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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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

 

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scPopCorn: A New Computational Method for Subpopulation Detection and their Comparative Analysis Across Single-Cell Experiments

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

 

Present day technological advances have facilitated unprecedented opportunities for studying biological systems at single-cell level resolution. For example, single-cell RNA sequencing (scRNA-seq) enables the measurement of transcriptomic information of thousands of individual cells in one experiment. Analyses of such data provide information that was not accessible using bulk sequencing, which can only assess average properties of cell populations. Single-cell measurements, however, can capture the heterogeneity of a population of cells. In particular, single-cell studies allow for the identification of novel cell types, states, and dynamics.

 

One of the most prominent uses of the scRNA-seq technology is the identification of subpopulations of cells present in a sample and comparing such subpopulations across samples. Such information is crucial for understanding the heterogeneity of cells in a sample and for comparative analysis of samples from different conditions, tissues, and species. A frequently used approach is to cluster every dataset separately, inspect marker genes for each cluster, and compare these clusters in an attempt to determine which cell types were shared between samples. This approach, however, relies on the existence of predefined or clearly identifiable marker genes and their consistent measurement across subpopulations.

 

Although the aligned data can then be clustered to reveal subpopulations and their correspondence, solving the subpopulation-mapping problem by performing global alignment first and clustering second overlooks the original information about subpopulations existing in each experiment. In contrast, an approach addressing this problem directly might represent a more suitable solution. So, keeping this in mind the researchers developed a computational method, single-cell subpopulations comparison (scPopCorn), that allows for comparative analysis of two or more single-cell populations.

 

The performance of scPopCorn was tested in three distinct settings. First, its potential was demonstrated in identifying and aligning subpopulations from single-cell data from human and mouse pancreatic single-cell data. Next, scPopCorn was applied to the task of aligning biological replicates of mouse kidney single-cell data. scPopCorn achieved the best performance over the previously published tools. Finally, it was applied to compare populations of cells from cancer and healthy brain tissues, revealing the relation of neoplastic cells to neural cells and astrocytes. Consequently, as a result of this integrative approach, scPopCorn provides a powerful tool for comparative analysis of single-cell populations.

 

This scPopCorn is basically a computational method for the identification of subpopulations of cells present within individual single-cell experiments and mapping of these subpopulations across these experiments. Different from other approaches, scPopCorn performs the tasks of population identification and mapping simultaneously by optimizing a function that combines both objectives. When applied to complex biological data, scPopCorn outperforms previous methods. However, it should be kept in mind that scPopCorn assumes the input single-cell data to consist of separable subpopulations and it is not designed to perform a comparative analysis of single cell trajectories datasets that do not fulfill this constraint.

 

Several innovations developed in this work contributed to the performance of scPopCorn. First, unifying the above-mentioned tasks into a single problem statement allowed for integrating the signal from different experiments while identifying subpopulations within each experiment. Such an incorporation aids the reduction of biological and experimental noise. The researchers believe that the ideas introduced in scPopCorn not only enabled the design of a highly accurate identification of subpopulations and mapping approach, but can also provide a stepping stone for other tools to interrogate the relationships between single cell experiments.

 

References:

 

https://www.sciencedirect.com/science/article/pii/S2405471219301887

 

https://www.tandfonline.com/doi/abs/10.1080/23307706.2017.1397554

 

https://ieeexplore.ieee.org/abstract/document/4031383

 

https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0927-y

 

https://www.sciencedirect.com/science/article/pii/S2405471216302666

 

 

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Can Elephants Help Fight Cancer?

Reporter: Gail S. Thornton, M.A.

 

 

This paragraph is excerpted from the American Technion Society Facebook page.

Professor Avi Schroeder and Dr. Josh Schiffman of the The University of Utah are working with elephants at Utah’s Hogle Zoo on a possible new tool to fight against lung, bone, breast, and other cancers. Dr. Schiffman found that p53, a cancer-suppressing protein, is far more prevalent in elephants, which rarely develop cancer. Prof. Schroeder is now working to manufacture the protein in nanoparticles to begin preclinical testing.


This article is excerpted from The Salt Lake Tribune, May 2, 2019.

Earth’s biggest, smallest, oddest life forms are getting new attention from scientists. A Utah author explores what they’re learning.

Published: May 2, 2019

Researchers have long ignored superlative life forms — the biggest, the tiniest, ones that can survive extremes — as outliers, Utah author Matthew D. LaPlante says.

But they’re now realizing the value of studying nature’s “oddballs,” he adds, which are helping scientists discover how to better fight disease and aging, understand the history of life on this planet and how we might reach others.

LaPlante’s new book, “Superlative: The Biology of Extremes” was released this week. On Friday at 7 p.m., the associate professor of journalistic writing at Utah State University will read from “Superlative” and talk about his work at The King’s English Bookshop, 1511 S. 1500 East, Salt Lake City. The event is free and open to the public.

The co-writer of several books on the intersection of scientific discovery and society, LaPlante now is working with Harvard geneticist David Sinclair on a book about human longevity. “Superlative” from BenBella Books is the first solo book by LaPlante, a former reporter for The Salt Lake Tribune.

As he surveys unusual life around the earth, there are stops in Utah — from Pando, the aspen clone in Sevier County believed to be the single most massive living organism known on Earth, to pop-up appearances by researchers at the University of Utah and elephants at Hogle Zoo in Salt Lake City.

Vast sequences of the genetic coding that humans share with elephants still perform similar functions in each species, LaPlante explains. And long after the two diverged, both developed the same genetic solution for the oxygen needs of a larger brain.

So there’s reason to believe that responses elephants have evolved — such as rarely developing cancer — might be spurred in humans.

The potential within a genome for such new traits to develop is at the heart of comparative genomics — and at the work of Utah pediatric oncologist Josh Schiffman.

This excerpt from “Superlative” explains how Schiffman began working with Hogle Zoo’s African elephants — the largest living land mammals — to fight cancer.

It all started in the summer of 2012, when [pediatric oncologist Josh] Schiffman’s beloved dog, Rhody, passed away [due] to histiocytosis, a condition that attacks the cells of skin and connective tissue. “It was the only time my wife has ever seen me cry,” he told me. “Rhody was like our first child.”

Schiffman had heard dogs like his had an elevated risk of cancer, but it wasn’t until after Rhody’s death that he learned just how elevated it was. Bernese mountain dogs who live to the age of ten have a 50 percent risk of dying from cancer.

“Suddenly it dawned on me there was this whole other world, this young field of comparative oncology,” he said, “and I was pulled into the idea of being a pioneer and maybe a leader to help move things along.”

Schiffman had long been intrigued by the fact that size doesn’t appear to correlate to cancer rates — a phenomenon known as “Peto’s Paradox,” named for Oxford University epidemiologist Richard Peto. But when Schiffman took his children on an outing to Utah’s Hogle Zoo — the same place I sometimes go to have lunch with my elephant friend, Zuri — everything came together.

A keeper named Eric Peterson had just finished giving a talk to a crowd of visitors, mentioning in passing that the zoo’s elephants have been trained to allow the veterinary staff to take small samples of blood from a vein behind their ears. As the crowd dispersed, an angular, excited man approached him.

“I’ve got a strange question,” Schiffman said.

“We’ve heard them all,” Peterson replied.

“OK then — how do I get me some of that elephant blood?” Schiffman asked.

Peterson contemplated calling security. Instead, after a bit of explanation from Schiffman, the zookeeper told the inquisitive doctor he’d look into it. Two and a half months later, the zoo’s institutional review board gave its blessing to Schiffman’s request.

Things moved fast after that.

(Steve Griffin | Tribune file photo) Lab specialists Lauren Donovan Cristhian Toruno, Lisa Abegglen and researcher Joshua Schiffman, from left, are testing the effects of elephant gene p53 (EP53) in human cancer cells at the Huntsman Cancer Institute.
(Steve Griffin | Tribune file photo) Lab specialists Lauren Donovan Cristhian Toruno, Lisa Abegglen and researcher Joshua Schiffman, from left, are testing the effects of elephant gene p53 (EP53) in human cancer cells at the Huntsman Cancer Institute.

Cancer develops in part because cells divide. During each division the cells must make a copy of their DNA, and once in a while, for various reasons, those copies include a mistake. The more cells divide, the greater the odds of an error, and the more prone an error is to be duplicated again and again.

And elephant cells? Those things are dividing like crazy. Based on the number of cell divisions elephants need to get from Zuri’s size when we met to the size she is now, in just a few short years, it stands to reason they should get lots of cancer. Yet they almost never do.

“Going from 300 pounds as a calf to more than 10,000 pounds, gaining three-plus pounds a day, they’re growing so quickly, so big and so fast — baby elephants really shouldn’t make it to adulthood,” Schiffman said. “They should have 100 times the cancer. Just by chance alone, elephants should be dropping dead all over the place.” Indeed, he said, they should probably die of cancer before they’re even old enough to reproduce. “They should be extinct!”

Already, comparative oncologists suspected the exceptionally low rate of cancer in elephants had something to do with p53, a gene whose human analog is a known cancer suppressor. Most humans have one copy — two alleles — of the gene. Those with an inherited condition known as Li–Fraumeni syndrome, however, have just one allele — and a nearly 100 percent chance of getting cancer. The logical conclusion is more p53 alleles mean a better chance of staving off cancer. And elephants, it turns out, have twenty of them.

The big find that came from Schiffman’s exploration of the elephant blood he got at the zoo, though, was not just that there were more of these genes in elephants, but that the genes behaved a little bit differently, too.

In humans, the gene’s first approach for suppressing tumor growth is to try to repair faulty cells — the sort that cause cancer. So, at first, Schiffman’s team assumed having more p53 genes meant elephants had bigger repair crews. With the goal of watching those crews in action, the researchers exposed the elephant cells to radiation, causing DNA damage. But they noticed that, instead of trying to fix what was broken, the elephant cells seemed to grow something of a conscience.

To understand this, it’s helpful to think about how you’d respond in a zombie apocalypse. Of course you’d fight long and hard to keep from being infected, right? But if a zombie was about to chomp down on your arm, and there was nothing you could do to stop it, and if you had but one bullet remaining in your gun —and a few moments to consider what you might do to your fellow humans as a part of the legion of the undead — what would you do?

That’s what elephant cells do, too. Under the directive of p53, mutated cells don’t put up a fight. Upon recognizing the inevitability of malignant mutation, they take their own lives in a process known as apoptosis.

And they don’t just do this for one kind of cancer. The p53 gene apparently programs cells to do this in response to all kinds of malignantly mutated cells in elephants—a finding that flies in the face of the conventional assumption that there is no one singular cure for the complex group of disorders we call cancer.

When I first met Schiffman in 2016, he was brimming with excitement about the potential elephants have to help us understand cancer. He was also very cautious not to suggest he was anywhere near a cure, nor that he ever would be.

Just a few years later, though, Schiffman was speaking openly about his intention to rid the world of cancer. And, to that end, what’s happening in his lab is encouraging, to say the least.

He and his team have been injecting cancer cells with a synthetic version of a p53 protein modeled on the DNA he’s drawn from Zuri and other elephants from around the world. Viewed on time-lapse video, the results are unmistakable and amazing.

Breast cancer. Gone.

bone cancer. Gone.

Lung cancer. Gone.

One by one, each type of cancer cell falls victim to zombie-cell hara-kiri, shriveling and then exploding, and leaving nothing behind to mutate. Schiffman is now working with Avi Schroeder, an expert in nanomedical delivery systems at Technion-Israel Institute of Technology, to create tiny delivery vehicles to take the synthetic elephant protein into mammalian tumors.

If this was all the benefit we ever derived from studying elephants, it would be plenty.

But it’s not. Not at all.

Source:

https://www.sltrib.com/artsliving/2019/05/02/earths-biggest-smallest/?fbclid=IwAR09iwADrhUKkuoXDRMBHFIMstUESU3OBXxKeN0dTKwxapTUASWsv1T_kZI

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Real Time Coverage @BIOConvention #BIO2019: Chat with @FDA Commissioner, & Challenges in Biotech & Gene Therapy June 4 Philadelphia

Reporter: Stephen J. Williams, PhD @StephenJWillia2

 

  • taking patient concerns and voices from anecdotal to data driven system
  • talked about patient accrual hearing patient voice not only in ease of access but reporting toxicities
  • at FDA he wants to remove barriers to trial access and accrual; also talk earlier to co’s on how they should conduct a trial

Digital tech

  • software as medical device
  • regulatory path is mixed like next gen sequencing
  • wearables are concern for FDA (they need to recruit scientists who know this tech

Opioids

  • must address the crisis but in a way that does not harm cancer pain patients
  • smaller pain packs “blister packs” would be good idea

Clinical trial modernization

  • for Alzheimers disease problem is science
  • for diabetes problem is regulatory
  • different diseases calls for different trial design
  • have regulatory problems with rare diseases as can’t form control or placebo group, inhumane. for example ras tumors trials for MEK inhibitors were narrowly focused on certain ras mutants
Realizing the Promise of Gene Therapies for Patients Around the World

103ABC, Level 100

Speakers
Lots of promise, timeline is progressing faster but we need more education on use of the gene therapy
Regulatory issues: Cell and directly delivered gene based therapies have been now approved. Some challenges will be the ultrarare disease trials and how we address manufacturing issues.  Manufacturing is a big issue at CBER and scalability.  If we want to have global impact of these products we need to address the manufacturing issues
 of scalability.
Pfizer – clinical grade and scale is important.
Aventis – he knew manufacturing of biologics however gene therapy manufacturing has its separate issues and is more complicated especially for regulatory purposes for clinical grade as well as scalability.  Strategic decision: focusing on the QC on manufacturing was so important.  Had a major issue in manufacturing had to shut down and redesign the system.
Albert:  Manufacturing is the most important topic even to the investors.  Investors were really conservative especially seeing early problems but when academic centers figured out good efficacy then they investors felt better and market has exploded.  Now you can see investment into preclinical and startups but still want mature companies to focus on manufacturing.  About $10 billion investment in last 4 years.

How Early is Too Early? Valuing and De-Risking Preclinical Opportunities

109AB, Level 100

Speakers
Valuing early-stage opportunities is challenging. Modeling will often provide a false sense of accuracy but relying on comparable transactions is more art than science. With a long lead time to launch, even the most robust estimates can ultimately prove inaccurate. This interactive panel will feature venture capital investors and senior pharma and biotech executives who lead early-stage transactions as they discuss their approaches to valuing opportunities, and offer key learnings from both successful and not-so-successful experiences.
Dr. Schoenbeck, Pfizer:
  • global network of liaisons who are a dedicated team to research potential global startup partners or investments.  Pfizer has a separate team to evaluate academic laboratories.  In Most cases Pfizer does not initiate contact.  It is important to initiate the first discussion with them in order to get noticed.  Could be just a short chat or discussion on what their needs are for their portfolio.

Question: How early is too early?

Luc Marengere, TVM:  His company has early stage focus, on 1st in class molecules.  The sweet spot for their investment is a candidate selected compound, which should be 12-18 months from IND.  They will want to bring to phase II in less than 4 years for $15-17 million.  Their development model is bad for academic labs.  During this process free to talk to other partners.

Dr. Chaudhary, Biogen:  Never too early to initiate a conversation and sometimes that conversation has lasted 3+ years before a decision.  They like build to buy models, will do convertible note deals, candidate compound selection should be entering in GLP/Tox phase (sweet spot)

Merck: have MRL Venture Fund for pre series A funding.  Also reiterated it is never too early to have that initial discussion.  It will not put you in a throw away bin.  They will have suggestions and never like to throw out good ideas.

Michael Hostetler: Set expectations carefully ; data should be validated by a CRO.  If have a platform, they will look at the team first to see if strong then will look at the platform to see how robust it is.

All noted that you should be completely honest at this phase.  Do not overstate your results or data or overhype your compound(s).  Show them everything and don’t have a bias toward compounds you think are the best in your portfolio.  Sometimes the least developed are the ones they are interested in.  Also one firm may reject you however you may fit in others portfolios better so have a broad range of conversations with multiple players.

 

 

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Real Time Coverage @BIOConvention #BIO2019: International Cancer Clusters Showcase June 3, Philadelphia PA

Reporter: Stephen J. Williams PhD @StephenJWillia2

 

Larry Blandford PharmD from Precision Medicine Group gave introduction about development of precision oncology medicine.  Talked about value and value determination for partnerships.

Company Pitches:

Kernal Biologics: Preclinical immunotherapy company developing mRNA therapeutics.  Their therapy only have activity in p53 deficient cells (messenger 2.0).  They identified, by screening, multiple mRNAs that have oncoselectivity; ONC-333 is their lead mRNA active in AML and NSCLC.  Looking for 5.5M seed $

Vaccibody AS: Vaccine technology from Oslo University to target antigen to antigen presenting cells.  They are targeting the myocytes and dimerize the antigen to MHC.  Targeting melanoma, certain cervical cancers, and hemotologic cancers.  Technology based on identified neoantigens obtained from tumor biopsy.Three vaccines: VB10.neo  VB10.16 against HPV cervical

Chimeric Therapeutics: developing CART to solid malignancies against CLEC14 (tumor endothelial marker), may make tumor susceptible to hypoxia.  Targeting pancreatic cancer, prelim results in mice , efficacy of 15%, working on 3rd generation CART

Memo Therapeutics: Antibody therapeutics; based on Dropzylla single B cell sorting and subsequent screening for mAb.  Targeting checkpoint inhibitors on solid tumors;  have a new target other than PD1; target undisclosed on NK cells and T cells; Early stage have academic partners; seeking 20Million Swiss Francs

Takeda Oncology: Chris Hurff Senior Director Business Development; they depend on partnerships as they feel internal RD is less effective.  They are diversifying their portfolio from small molecules. They have over 200 partnerships (132 in Boston). They are focusing on heme, lung, and Immunooncology. Partnering model: CEI (center external innovation) deals with both academic and small biotechs.  They have numerous partners including Shatto and MD Anderson.

 

 

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