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Archive for the ‘Cancer-Immune Interactions’ Category

Yet another Success Story: Machine Learning to predict immunotherapy response

Curator and Reporter: Dr. Premalata Pati, Ph.D., Postdoc

Immune-checkpoint blockers (ICBs) immunotherapy appears promising for various cancer types, offering a durable therapeutic advantage. Only a number of cases with cancer respond to this therapy. Biomarkers are required to adequately predict the responses of patients. This article evaluates this issue utilizing a system method to characterize the immune response of the anti-tumor based on the entire tumor environment. Researchers build mechanical biomarkers and cancer-specific response models using interpretable machine learning that predict the response of patients to ICB.

The lymphatic and immunological systems help the body defend itself by combating. The immune system functions as the body’s own personal police force, hunting down and eliminating pathogenic baddies.

According to Federica Eduati, Department of Biomedical Engineering at TU/e, “The immune system of the body is quite adept at detecting abnormally behaving cells. Cells that potentially grow into tumors or cancer in the future are included in this category. Once identified, the immune system attacks and destroys the cells.”

Immunotherapy and machine learning are combining to assist the immune system solve one of its most vexing problems: detecting hidden tumorous cells in the human body.

It is the fundamental responsibility of our immune system to identify and remove alien invaders like bacteria or viruses, but also to identify risks within the body, such as cancer. However, cancer cells have sophisticated ways of escaping death by shutting off immune cells. Immunotherapy can reverse the process, but not for all patients and types of cancer. To unravel the mystery, Eindhoven University of Technology researchers used machine learning. They developed a model to predict whether immunotherapy will be effective for a patient using a simple trick. Even better, the model outperforms conventional clinical approaches.

The outcomes of this research are published on 30th June, 2021 in the journal Patterns in an article entitled “Interpretable systems biomarkers predict response to immune-checkpoint inhibitors”.

The Study

  • Characterization of the tumor microenvironment from RNAseq and prior knowledge
  • Multi-task machine-learning models for predicting antitumor immune responses
  • Identification of cancer-type-specific, interpretable biomarkers of immune responses
  • EaSIeR is a tool to predict biomarker-based immunotherapy response from RNA-seq

“Tumor also contains multiple types of immune and fibroblast cells which can play a role in favor of or anti-tumor, and communicates among themselves,” said Oscar Lapuente-Santana, a researcher doctoral student in the computational biology group. “We had to learn how complicated regulatory mechanisms in the micro-environment of the tumor affect the ICB response. We have used RNA sequencing datasets to depict numerous components of the Tumor Microenvironment (TME) in a high-level illustration.”

Using computational algorithms and datasets from previous clinical patient care, the researchers investigated the TME.

Eduati explained

While RNA-sequencing databases are publically available, information on which patients responded to ICB therapy is only available for a limited group of patients and cancer types. So, to tackle the data problem, we used a trick.

All 100 models learned in the randomized cross-validation were included in the EaSIeR tool. For each validation dataset, we used the corresponding cancer-type-specific model: SKCM for the melanoma Gide, Auslander, Riaz, and Liu cohorts; STAD for the gastric cancer Kim cohort; BLCA for the bladder cancer Mariathasan cohort; and GBM for the glioblastoma Cloughesy cohort. To make predictions for each job, the average of the 100 cancer-type-specific models was employed. The predictions of each dataset’s cancer-type-specific models were also compared to models generated for the remaining 17 cancer types.

From the same datasets, the researchers selected several surrogate immunological responses to be used as a measure of ICB effectiveness.

Lapuente-Santana stated

One of the most difficult aspects of our job was properly training the machine learning models. We were able to fix this by looking at alternative immune responses during the training process.

Some of the researchers employed the machine learning approach given in the paper to participate in the “Anti-PD1 Response Prediction DREAM Challenge.”

DREAM is an organization that carries out crowd-based tasks with biomedical algorithms. “We were the first to compete in one of the sub-challenges under the name cSysImmunoOnco team,” Eduati remarks.

The researchers noted,

We applied machine learning to seek for connections between the obtained system-based attributes and the immune response, estimated using 14 predictors (proxies) derived from previous publications. We treated these proxies as individual tasks to be predicted by our machine learning models, and we employed multi-task learning algorithms to jointly learn all tasks.

The researchers discovered that their machine learning model surpasses biomarkers that are already utilized in clinical settings to evaluate ICB therapies.

But why are Eduati, Lapuente-Santana, and their colleagues using mathematical models to tackle a medical treatment problem? Is this going to take the place of the doctor?

Eduati explains

Mathematical models can provide an overview of the interconnection between individual molecules and cells and at the same time predicting a particular patient’s tumor behavior. This implies that immunotherapy with ICB can be personalized in a patient’s clinical setting. The models can aid physicians with their decisions about optimum therapy, it is vital to note that they will not replace them.

Furthermore, the model aids in determining which biological mechanisms are relevant for the biological response.

The researchers noted

Another advantage of our concept is that it does not need a dataset with known patient responses to immunotherapy for model training.

Further testing is required before these findings may be implemented in clinical settings.

Main Source:

Lapuente-Santana, Ó., van Genderen, M., Hilbers, P. A., Finotello, F., & Eduati, F. (2021). Interpretable systems biomarkers predict response to immune-checkpoint inhibitorsPatterns, 100293. https://www.cell.com/patterns/pdfExtended/S2666-3899(21)00126-4

Other Related Articles published in this Open Access Online Scientific Journal include the following:

Inhibitory CD161 receptor recognized as a potential immunotherapy target in glioma-infiltrating T cells by single-cell analysis

Reporter: Dr. Premalata Pati, Ph.D., Postdoc

https://pharmaceuticalintelligence.com/2021/02/20/inhibitory-cd161-receptor-identified-in-glioma-infiltrating-t-cells-by-single-cell-analysis-2/

Immunotherapy may help in glioblastoma survival

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

https://pharmaceuticalintelligence.com/2019/03/16/immunotherapy-may-help-in-glioblastoma-survival/

Deep Learning for In-silico Drug Discovery and Drug Repurposing: Artificial Intelligence to search for molecules boosting response rates in Cancer Immunotherapy: Insilico Medicine @John Hopkins University

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/07/17/deep-learning-for-in-silico-drug-discovery-and-drug-repurposing-artificial-intelligence-to-search-for-molecules-boosting-response-rates-in-cancer-immunotherapy-insilico-medicine-john-hopkins-univer/

Machine Learning (ML) in cancer prognosis prediction helps the researcher to identify multiple known as well as candidate cancer diver genes

Curator and Reporter: Dr. Premalata Pati, Ph.D., Postdoc

https://pharmaceuticalintelligence.com/2021/05/04/machine-learning-ml-in-cancer-prognosis-prediction-helps-the-researcher-to-identify-multiple-known-as-well-as-candidate-cancer-diver-genes/

AI System Used to Detect Lung Cancer

Reporter: Irina Robu, PhD

https://pharmaceuticalintelligence.com/2019/06/28/ai-system-used-to-detect-lung-cancer/

Cancer detection and therapeutics

Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2016/05/02/cancer-detection-and-therapeutics/

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Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Symposium: New Drugs on the Horizon Part 3 12:30-1:25 PM

Reporter: Stephen J. Williams, PhD

New Drugs on the Horizon: Part 3
Introduction

Andrew J. Phillips, C4 Therapeutics

  • symposium brought by AACR CICR and had about 30 proposals for talks and chose three talks
  • unfortunately the networking event is not possible but hope to see you soon in good health

ABBV-184: A novel survivin specific T cell receptor/CD3 bispecific therapeutic that targets both solid tumor and hematological malignancies

Edward B Reilly
AbbVie Inc. @abbvie

  • T-cell receptors (TCR) can recognize the intracellular targets whereas antibodies only recognize the 25% of potential extracellular targets
  • survivin is expressed in multiple cancers and correlates with poor survival and prognosis
  • CD3 bispecific TCR to survivn (Ab to CD3 on T- cells and TCR to survivin on cancer cells presented in MHC Class A3)
  • ABBV184  effective in vivo in lung cancer models as single agent;
  • in humanized mouse tumor models CD3/survivin bispecific can recruit T cells into solid tumors; multiple immune cells CD4 and CD8 positive T cells were found to infiltrate into tumor
  • therapeutic window as measured by cytokine release assays in tumor vs. normal cells very wide (>25 fold)
  • ABBV184 does not bind platelets and has good in vivo safety profile
  • First- in human dose determination trial: used in vitro cancer cell assays to determine 1st human dose
  • looking at AML and lung cancer indications
  • phase 1 trial is underway for safety and efficacy and determine phase 2 dose
  • survivin has very few mutations so they are not worried about a changing epitope of their target TCR peptide of choice

The discovery of TNO155: A first in class SHP2 inhibitor

Matthew J. LaMarche
Novartis @Novartis

  • SHP2 is an intracellular phosphatase that is upstream of MEK ERK pathway; has an SH2 domain and PTP domain
  • knockdown of SHP2 inhibits tumor growth and colony formation in soft agar
  • 55 TKIs there are very little phosphatase inhibitors; difficult to target the active catalytic site; inhibitors can be oxidized at the active site; so they tried to target the two domains and developed an allosteric inhibitor at binding site where three domains come together and stabilize it
  • they produced a number of chemical scaffolds that would bind and stabilize this allosteric site
  • block the redox reaction by blocking the cysteine in the binding site
  • lead compound had phototoxicity; used SAR analysis to improve affinity and reduce phototox effects
  • was very difficult to balance efficacy, binding properties, and tox by adjusting stuctures
  • TNO155 is their lead into trials
  • SHP2 expressed in T cells and they find good combo with I/O with uptick of CD8 cells
  • TNO155 is very selective no SHP1 inhibition; SHP2 can autoinhibit itself when three domains come together and stabilize; no cross reactivity with other phosphatases
  • they screened 1.5 million compounds and got low hit rate so that is why they needed to chemically engineer and improve on the classes they found as near hits

Closing Remarks

 

Xiaojing Wang
Genentech, Inc. @genentech

Follow on Twitter at:

@pharma_BI

@AACR

@CureCancerNow

@pharmanews

@BiotechWorld

@HopkinsMedicine

#AACR20

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Responses to the #COVID-19 outbreak from Oncologists, Cancer Societies and the NCI: Important information for cancer patients

Curator: Stephen J. Williams, Ph.D.

UPDATED 3/20/2020

Among the people who are identified at risk of coronovirus 2019 infection and complications of the virus include cancer patients undergoing chemotherapy, who in general, can be immunosuppressed, especially while patients are undergoing their treatment.  This has created anxiety among many cancer patients as well as their care givers and prompted many oncologist professional groups, cancer societies, and cancer centers to formulate some sort of guidelines for both the cancer patients and the oncology professional with respect to limiting the risk of infection to coronavirus (COVID19). 

 

This information will be periodically updated and we are working to get a Live Twitter Feed to bring oncologist and cancer patient advocacy groups together so up to date information can be communicated rapidly.  Please see this page regularly for updates as new information is curated.

IN ADDITION, I will curate a listing of drugs with adverse events of immunosuppression for people who might wonder if the medications they are taking are raising their risk of infections.

Please also see @pharma_BI for updates as well.

Please also see our Coronavirus Portal at https://pharmaceuticalintelligence.com/coronavirus-portal/

For ease of reading information for patients are BOLDED and in RED

ASCO’s Response to COVID-19

From the Cancer Letter: The following is a guest editorial by American Society of Clinical Oncology (ASCO) Executive Vice President and Chief Medical Officer Richard L. Schilsky MD, FACP, FSCT, FASCO. This story is part of The Cancer Letter’s ongoing coverage of COVID-19’s impact on oncology. A full list of our coverage, as well as the latest meeting cancellations, is available here.

 

The worldwide spread of the coronavirus (COVID-19) presents unprecedented challenges to the cancer care delivery system.

Our patients are already dealing with a life-threatening illness and are particularly vulnerable to this viral infection, which can be even more deadly for them. Further, as restrictions in daily movement and social distancing take hold, vulnerable patients may be disconnected from friends, family or other support they need as they manage their cancer.

As providers, we rely on evidence and experience when treating patients but now we face uncertainty. There are limited data to guide us in the specific management of cancer patients confronting COVID-19 and, at present, we have no population-level guidance regarding acceptable or appropriate adjustments of treatment and practice operations that both ensure the best outcome for our patients and protect the safety of our colleagues and staff.

As normal life is dramatically changed, we are all feeling anxious about the extreme economic challenges we face, but these issues are perhaps even more difficult for our patients, many of whom are now facing interruption

As we confront this extraordinary situation, the health and safety of members, staff, and individuals with cancer—in fact, the entire cancer community—is ASCO’s highest priority.

ASCO has been actively monitoring and responding to the pandemic to ensure that accurate information is readily available to clinicians and their patients. Recognizing that this is a rapidly evolving situation and that limited oncology-specific, evidence-based information is available, we are committed to sharing what is known and acknowledging what is unknown so that the most informed decisions can be made.

To help guide oncology professionals as they deal with the impact of coronavirus on both their patients and staff, ASCO has collated questions from its members, posted responses at asco.org and assembled a compendium of additional resources we hope will be helpful as the virus spreads and the disease unfolds. We continue to receive additional questions regarding clinical care and we are updating our FAQs on a regular basis.

We hope this information is helpful even when it merely confirms that there are no certain answers to many questions. Our answers are based on the best available information we identify in the literature, guidance from public health authorities, and input received from oncology and infectious disease experts.

For patients, we have posted a blog by Dr. Merry Jennifer Markham, chair of ASCO’s Cancer Communications Committee. This can be found on Cancer.Net, ASCO’s patient information website, and it provides practical guidance to help patients reduce their risk of exposure, better understand COVID-19 symptoms, and locate additional information.

This blog is available both in English and Spanish. Additional blog posts addressing patient questions will be posted as new questions are received and new information becomes available.

Find below a Tweet from Dr.Markham which includes links to her article on COVID-19 for cancer patients

https://twitter.com/DrMarkham/status/1237797251038220289?s=20

NCCN’s Response to COVID-19 and COVID-19 Resources

JNCCN: How to Manage Cancer Care during COVID-19 Pandemic

Experts from the Seattle Cancer Care Alliance (SCCA)—a Member Institution of the National Comprehensive Cancer Network® (NCCN®)—are sharing insights and advice on how to continue providing optimal cancer care during the novel coronavirus (COVID-19) pandemic. SCCA includes the Fred Hutchinson Cancer Research Center and the University of Washington, which are located in the epicenter of the COVID-19 outbreak in the United States. The peer-reviewed article sharing best practices is available for free online-ahead-of-print via open access at JNCCN.org.

Coronavirus disease 2019 (COVID-19) Resources for the Cancer Care Community

NCCN recognizes the rapidly changing medical information relating to COVID-19 in the oncology ecosystem, but understands that a forum for sharing best practices and specific institutional responses may be helpful to others.  Therefore, we are expeditiously providing documents and recommendations developed by NCCN Member Institutions or Guideline Panels as resources for oncology care providers. These resources have not been developed or reviewed by the standard NCCN processes, and are provided for information purposes only. We will post more resources as they become available so check back for additional updates.

Documents

Links

National Cancer Institute Response to COVID-19

More information at https://www.cancer.gov/contact/emergency-preparedness/coronavirus

What people with cancer should know: https://www.cancer.gov/coronavirus

Get the latest public health information from CDC: https://www.coronavirus.gov

Get the latest research information from NIH: https://www.nih.gov/coronavirus

 

Coronavirus: What People with Cancer Should Know

ON THIS PAGE

Both the resources at cancer.gov (NCI) as well as the resources from ASCO are updated as new information is evaluated and more guidelines are formulated by members of the oncologist and cancer care community and are excellent resources for those living with cancer, and also those who either care for cancer patients or their family and relatives.

Related Resources for Patients (please click on links)

 

 

 

Some resources and information for cancer patients from Twitter

Twitter feeds which may be useful sources of discussion and for cancer patients include:

 

@OncLive OncLive.com includes healthcare information for patients and includes videos and newsletters

 

 

@DrMarkham Dr. Markham is Chief of Heme-Onc & gyn med onc @UF | AD Med Affairs @UFHealthCancer and has collected very good information for patients concerning #Covid19 

 

 

@DrMaurieMarkman Dr. Maurie Markman is President of Medicine and Science (Cancer Centers of America, Philadelphia) @CancerCenter #TreatThePerson #Oncology #Genomics #PrecisionMedicine and hosts a great online live Tweet feed discussing current topics in cancer treatment and care for patients called #TreatThePerson Chat

UPDATED 3/20/2020 INFORMATION FROM NCI DESIGNATED CANCER CENTERS FOR PATIENTS/PROVIDERS

The following is a listing with links of NCI Designated Comprehensive Cancer Centers and some select designated Cancer Centers* which have information on infectious risk guidance for cancer patients as well as their physicians and caregivers.   There are 51 NCI Comprehensive Cancer Centers and as more cancer centers formulate guidance this list will be updated. 

 

Cancer Center State Link to COVID19 guidance
City of Hope CA Advice for cancer patients, survivors and caregivers
Jonsson Cancer Center at UCLA CA Cancer and COVID19
UCSF Hellen Diller Family Comprehensive Cancer CA COVID-19 Links for Patients and Providers
Lee Moffit FL Protecting against Coronavirus 19
University of Kansas Cancer Center* KS COVID19 Info for patients
Barbara & Karmanos Cancer Institute (Wayne State) MI COVID19 Resources
Rogel Cancer Center (Univ of Michigan) MI COVID19 Patient Specific Guidelines
Alvin J. Siteman Cancer Center (MO) Coronavirus
Fred & Pamela Buffet CC* NE Resources for Patients and Providers
Rutgers Cancer Institute of NJ NJ What patients should know about COVID19
Memorial Sloan Kettering NY What COVID19 means for cancer patients
Herbert Irving CC (Columbia University) NY Coronavirus Resource Center
MD Anderson Cancer  TX Planning for Patients, Providers
Hunstman Cancer Center UT COVID19 What you need to know
Fred Hutchinson WA COVID19 What patients need to know

 

 

Please also see related information on Coronavirus 2019 and Cancer and Immunotherapy at the following links on the Open Access Online Journal:

Volume Two: Cancer Therapies: Metabolic, Genomics, Interventional, Immunotherapy and Nanotechnology in Therapy Delivery 

at

https://pharmaceuticalintelligence.com/biomed-e-books/series-c-e-books-on-cancer-oncology/volume-two-immunotherapy-in-cancer-radiation-oncology/

AND

Coronavirus Portal

 

 

 

 

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19th Annual Koch Institute Summer Symposium on Cancer Immunotherapy, June 12, 2020 at MIT’s Kresge Auditorium

Reporter: Aviva Lev-Ari, PhD, RN

 

 

Summer Symposium 2020

Engineering the Next Wave of Immunotherapy

The 19th Annual Koch Institute Summer Symposium on June 12, 2020 at MIT’s Kresge Auditorium will focus on cancer immunotherapy.

Cancer immunotherapy has revolutionized the landscape of cancer treatment, our thinking of tumor biology and clinical practice. Following the groundbreaking successes of checkpoint blockade therapy and CAR T cell therapy, culminating in multiple FDA-approved treatments and the awarding of the 2018  Nobel Prize in Medicine to Jim Allison and Tasuku Honjo, the field is currently at a critical juncture.

While checkpoint blockade therapy has demonstrated that the immune system can be harnessed to fight cancer,  the next generation of treatments will require us to understand what causes resistance in non-responders, how this can be overcome, and how these issues are best addressed clinically. Discussing these questions will be at the core of this symposium as we move towards our ultimate goal to increase the number of patients benefiting from immunotherapy

Session Speakers


Targeting T Cells
Rafi Ahmed, Michael Dougan, Chris Love

Thinking Beyond T Cells
Angelika Amon, Yasemine Belkaid, Stefani Spranger

Engineering Clinical Translation  
Nina Bhardwaj, Chris Garcia

Panel Discussion: Clinical Translation: A Real Life Perspective


Daniel Chen, Howard Kaufman, Kimberly Schaefer-Weaver
Moderator: Steven Silverstein

SOURCE

https://ki.mit.edu/news/events/symposium/2020

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An Intelligent DNA Nanorobot to Fight Cancer by Targeting HER2 Expression

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

3.2.9

3.2.9   An Intelligent DNA Nanorobot to Fight Cancer by Targeting HER2 Expression, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair

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.

4.3.6

4.3.6  Single-cell RNA-seq helps in finding intra-tumoral heterogeneity in pancreatic cancer, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 4: Single Cell Genomics

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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Newly Found Functions of B Cell

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

4.1.8

4.1.8   Newly Found Functions of B Cell, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 4: Single Cell Genomics

The importance of B cells to human health is more than what is already known. Vaccines capable of eradicating disease activate B cells, cancer checkpoint blockade therapies are produced using B cells, and B cell deficiencies have devastating impacts. B cells have been a subject of fascination since at least the 1800s. The notion of a humoral branch to immunity emerged from the work of and contemporaries studying B cells in the early 1900s.

Efforts to understand how we could make antibodies from B cells against almost any foreign surface while usually avoiding making them against self, led to Burnet’s clonal selection theory. This was followed by the molecular definition of how a diversity of immunoglobulins can arise by gene rearrangement in developing B cells. Recombination activating gene (RAG)-dependent processes of V-(D)-J rearrangement of immunoglobulin (Ig) gene segments in developing B cells are now known to be able to generate an enormous amount of antibody diversity (theoretically at least 1016 possible variants).

With so much already known, B cell biology might be considered ‘‘done’’ with only incremental advances still to be made, but instead, there is great activity in the field today with numerous major challenges that remain. For example, efforts are underway to develop vaccines that induce broadly neutralizing antibody responses, to understand how autoantigen- and allergen-reactive antibodies arise, and to harness B cell-depletion therapies to correct non-autoantibody-mediated diseases, making it evident that there is still an enormous amount we do not know about B cells and much work to be done.

Multiple self-tolerance checkpoints exist to remove autoreactive specificities from the B cell repertoire or to limit the ability of such cells to secrete autoantigen-binding antibody. These include receptor editing and deletion in immature B cells, competitive elimination of chronically autoantigen binding B cells in the periphery, and a state of anergy that disfavors PC (plasma cell) differentiation. Autoantibody production can occur due to failures in these checkpoints or in T cell self-tolerance mechanisms. Variants in multiple genes are implicated in increasing the likelihood of checkpoint failure and of autoantibody production occurring.

Autoantibodies are pathogenic in a number of human diseases including SLE (Systemic lupus erythematosus), pemphigus vulgaris, Grave’s disease, and myasthenia gravis. B cell depletion therapy using anti-CD20 antibody has been protective in some of these diseases such as pemphigus vulgaris, but not others such as SLE and this appears to reflect the contribution of SLPC (Short lived plasma cells) versus LLPC (Long lived plasma cells) to autoantibody production and the inability of even prolonged anti-CD20 treatment to eliminate the later. These clinical findings have added to the importance of understanding what factors drive SLPC versus LLPC development and what the requirements are to support LLPCs.

B cell depletion therapy has also been efficacious in several other autoimmune diseases, including multiple sclerosis (MS), type 1 diabetes, and rheumatoid arthritis (RA). While the potential contributions of autoantibodies to the pathology of these diseases are still being explored, autoantigen presentation has been posited as another mechanism for B cell disease-promoting activity.

In addition to autoimmunity, B cells play an important role in allergic diseases. IgE antibodies specific for allergen components sensitize mast cells and basophils for rapid degranulation in response to allergen exposures at various sites, such as in the intestine (food allergy), nose (allergic rhinitis), and lung (allergic asthma). IgE production may thus be favored under conditions that induce weak B cell responses and minimal GC (Germinal center) activity, thereby enabling IgE+ B cells and/or PCs to avoid being outcompeted by IgG+ cells. Aside from IgE antibodies, B cells may also contribute to allergic inflammation through their interactions with T cells.

B cells have also emerged as an important source of the immunosuppressive cytokine IL-10. Mouse studies revealed that B cell-derived IL-10 can promote recovery from EAE (Experimental autoimmune encephalomyelitis) and can be protective in models of RA and type 1 diabetes. Moreover, IL-10 production from B cells restrains T cell responses during some viral and bacterial infections. These findings indicate that the influence of B cells on the cytokine milieu will be context dependent.

The presence of B cells in a variety of solid tumor types, including breast cancer, ovarian cancer, and melanoma, has been associated in some studies with a positive prognosis. The mechanism involved is unclear but could include antigen presentation to CD4 and CD8 T cells, antibody production and subsequent enhancement of presentation, or by promoting tertiary lymphoid tissue formation and local T cell accumulation. It is also noteworthy that B cells frequently make antibody responses to cancer antigens and this has led to efforts to use antibodies from cancer patients as biomarkers of disease and to identify immunotherapy targets.

Malignancies of B cells themselves are a common form of hematopoietic cancer. This predilection arises because the gene modifications that B cells undergo during development and in immune responses are not perfect in their fidelity, and antibody responses require extensive B cell proliferation. The study of B cell lymphomas and their associated genetic derangements continues to be illuminating about requirements for normal B cell differentiation and signaling while also leading to the development of targeted therapies.

Overall this study attempted to capture some of the advances in the understanding of B cell biology that have occurred since the turn of the century. These include important steps forward in understanding how B cells encounter antigens, the co-stimulatory and cytokine requirements for their proliferation and differentiation, and how properties of the B cell receptor, the antigen, and helper T cells influence B cell responses. Many advances continue to transform the field including the impact of deep sequencing technologies on understanding B cell repertoires, the IgA-inducing microbiome, and the genetic defects in humans that compromise or exaggerate B cell responses or give rise to B cell malignancies.

Other advances that are providing insight include:

  • single-cell approaches to define B cell heterogeneity,
  • glycomic approaches to study effector sugars on antibodies,
  • new methods to study human B cell responses including CRISPR-based manipulation, and
  • the use of systems biology to study changes at the whole organism level.

With the recognition that B cells and antibodies are involved in most types of immune response and the realization that inflammatory processes contribute to a wider range of diseases than previously believed, including, for example, metabolic syndrome and neurodegeneration, it is expected that further

  • basic research-driven discovery about B cell biology will lead to more and improved approaches to maintain health and fight disease in the future.

References:

https://www.cell.com/cell/fulltext/S0092-8674(19)30278-8

https://onlinelibrary.wiley.com/doi/full/10.1002/hon.2405

https://www.pnas.org/content/115/18/4743

https://onlinelibrary.wiley.com/doi/full/10.1111/all.12911

https://cshperspectives.cshlp.org/content/10/5/a028795

https://www.sciencedirect.com/science/article/abs/pii/S0049017218304955

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Gender affects the prevalence of the cancer type, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

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

 

Gender of a person can affect the kinds of cancer-causing mutations they develop, according to a genomic analysis spanning nearly 2,000 tumours and 28 types of cancer. The results show striking differences in the cancer-causing mutations found in people who are biologically male versus those who are biologically female — not only in the number of mutations lurking in their tumours, but also in the kinds of mutations found there.

 

Liver tumours from women were more likely to carry mutations caused by a faulty system of DNA mending called mismatch repair, for instance. And men with any type of cancer were more likely to exhibit DNA changes thought to be linked to a process that the body uses to repair DNA with two broken strands. These biases could point researchers to key biological differences in how tumours develop and evolve across sexes.

 

The data add to a growing realization that sex is important in cancer, and not only because of lifestyle differences. Lung and liver cancer, for example, are more common in men than in women — even after researchers control for disparities in smoking or alcohol consumption. The source of that bias, however, has remained unclear.

In 2014, the US National Institutes of Health began encouraging researchers to consider sex differences in preclinical research by, for example, including female animals and cell lines from women in their studies. And some studies have since found sex-linked biases in the frequency of mutations in protein-coding genes in certain cancer types, including some brain cancers and advanced melanoma.

 

But the present study is the most comprehensive study of sex differences in tumour genomes so far. It looks at mutations not only in genes that code for proteins, but also in the vast expanses of DNA that have other functions, such as controlling when genes are turned on or off. The study also compares male and female genomes across many different cancers, which can allow researchers to pick up on additional patterns of DNA mutations, in part by increasing the sample sizes.

 

Researchers analysed full genome sequences gathered by the International Cancer Genome Consortium. They looked at differences in the frequency of 174 mutations known to drive cancer, and found that some of these mutations occurred more frequently in men than in women, and vice versa. When they looked more broadly at the loss or duplication of DNA segments in the genome, they found 4,285 sex-biased genes spread across 15 chromosomes.

 

There were also differences found when some mutations seemed to arise during tumour development, suggesting that some cancers follow different evolutionary paths in men and women. Researchers also looked at particular patterns of DNA changes. Such patterns can, in some cases, reflect the source of the mutation. Tobacco smoke, for example, leaves behind a particular signature in the DNA.

 

Taken together, the results highlight the importance of accounting for sex, not only in clinical trials but also in preclinical studies. This could eventually allow researchers to pin down the sources of many of the differences found in this study. Liver cancer is roughly three times as common in men as in women in some populations, and its incidence is increasing in some countries. A better understanding of its aetiology may turn out to be really important for prevention strategies and treatments.

 

References:

 

https://www.nature.com/articles/d41586-019-00562-7?utm_source=Nature+Briefing

 

https://www.nature.com/news/policy-nih-to-balance-sex-in-cell-and-animal-studies-1.15195

 

https://www.ncbi.nlm.nih.gov/pubmed/26296643

 

https://www.biorxiv.org/content/10.1101/507939v1

 

https://www.ncbi.nlm.nih.gov/pubmed/25985759

 

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Immunoediting can be a constant defense in the cancer landscape

Immuno-editing can be a constant defense in the cancer landscape, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

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

 

There are many considerations in the cancer immunoediting landscape of defense and regulation in the cancer hallmark biology. The cancer hallmark biology in concert with key controls of the HLA compatibility affinity mechanisms are pivotal in architecting a unique patient-centric therapeutic application. Selection of random immune products including neoantigens, antigens, antibodies and other vital immune elements creates a high level of uncertainty and risk of undesirable immune reactions. Immunoediting is a constant process. The human innate and adaptive forces can either trigger favorable or unfavorable immunoediting features. Cancer is a multi-disease entity. There are multi-factorial initiators in a certain disease process. Namely, environmental exposures, viral and / or microbiome exposure disequilibrium, direct harm to DNA, poor immune adaptability, inherent risk and an individual’s own vibration rhythm in life.

 

When a human single cell is crippled (Deranged DNA) with mixed up molecular behavior that is the initiator of the problem. A once normal cell now transitioned into full threatening molecular time bomb. In the modeling and creation of a tumor it all begins with the singular molecular crisis and crippling of a normal human cell. At this point it is either chop suey (mixed bit responses) or a productive defensive and regulation response and posture of the immune system. Mixed bits of normal DNA, cancer-laden DNA, circulating tumor DNA, circulating normal cells, circulating tumor cells, circulating immune defense cells, circulating immune inflammatory cells forming a moiety of normal and a moiety of mess. The challenge is to scavenge the mess and amplify the normal.

 

Immunoediting is a primary push-button feature that is definitely required to be hit when it comes to initiating immune defenses against cancer and an adaptation in favor of regression. As mentioned before that the tumor microenvironment is a “mixed bit” moiety, which includes elements of the immune system that can defend against circulating cancer cells and tumor growth. Personalized (Precision-Based) cancer vaccines must become the primary form of treatment in this case. Current treatment regimens in conventional therapy destroy immune defenses and regulation and create more serious complications observed in tumor progression, metastasis and survival. Commonly resistance to chemotherapeutic agents is observed. These personalized treatments will be developed in concert with cancer hallmark analytics and immunocentrics affinity and selection mapping. This mapping will demonstrate molecular pathway interface and HLA compatibility and adaptation with patientcentricity.

References:

 

https://www.linkedin.com/pulse/immunoediting-cancer-landscape-john-catanzaro/

 

https://www.cell.com/cell/fulltext/S0092-8674(16)31609-9

 

https://www.researchgate.net/publication/309432057_Circulating_tumor_cell_clusters_What_we_know_and_what_we_expect_Review

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4190561/

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5840207/

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5593672/

 

https://www.frontiersin.org/articles/10.3389/fimmu.2018.00414/full

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5593672/

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4190561/

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4388310/

 

https://www.linkedin.com/pulse/cancer-hallmark-analytics-omics-data-pathway-studio-review-catanzaro/

 

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Immunotherapy may help in glioblastoma survival

Immunotherapy may help in glioblastoma survival, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

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

 

Glioblastoma is the most common primary malignant brain tumor in adults and is associated with poor survival. But, in a glimmer of hope, a recent study found that a drug designed to unleash the immune system helped some patients live longer. Glioblastoma powerfully suppresses the immune system, both at the site of the cancer and throughout the body, which has made it difficult to find effective treatments. Such tumors are complex and differ widely in their behavior and characteristics.

 

A small randomized, multi-institution clinical trial was conducted and led by researchers at the University of California at Los Angeles involved patients who had a recurrence of glioblastoma, the most common central nervous system cancer. The aim was to evaluate immune responses and survival following neoadjuvant and/or adjuvant therapy with pembrolizumab (checkpoint inhibitor) in 35 patients with recurrent, surgically resectable glioblastoma. Patients who were randomized to receive neoadjuvant pembrolizumab, with continued adjuvant therapy following surgery, had significantly extended overall survival compared to patients that were randomized to receive adjuvant, post-surgical programmed cell death protein 1 (PD-1) blockade alone.

 

Neoadjuvant PD-1 blockade was associated with upregulation of T cell– and interferon-γ-related gene expression, but downregulation of cell-cycle-related gene expression within the tumor, which was not seen in patients that received adjuvant therapy alone. Focal induction of programmed death-ligand 1 in the tumor microenvironment, enhanced clonal expansion of T cells, decreased PD-1 expression on peripheral blood T cells and a decreasing monocytic population was observed more frequently in the neoadjuvant group than in patients treated only in the adjuvant setting. These findings suggest that the neoadjuvant administration of PD-1 blockade enhanced both the local and systemic antitumor immune response and may represent a more efficacious approach to the treatment of this uniformly lethal brain tumor.

 

Immunotherapy has not proved to be effective against glioblastoma. This small clinical trial explored the effect of PD-1 blockade on recurrent glioblastoma in relation to the timing of administration. A total of 35 patients undergoing resection of recurrent disease were randomized to either neoadjuvant or adjuvant pembrolizumab, and surgical specimens were compared between the two groups. Interestingly, the tumoral gene expression signature varied between the two groups, such that those who received neoadjuvant pembrolizumab displayed an INF-γ gene signature suggestive of T-cell activation as well as suppression of cell-cycle signaling, possibly consistent with growth arrest. Although the study was not powered for efficacy, the group found an increase in overall survival in patients receiving neoadjuvant pembrolizumab compared with adjuvant pembrolizumab of 13.7 months versus 7.5 months, respectively.

 

In this small pilot study, neoadjuvant PD-1 blockade followed by surgical resection was associated with intratumoral T-cell activation and inhibition of tumor growth as well as longer survival. How the drug works in glioblastoma has not been totally established. The researchers speculated that giving the drug before surgery prompted T-cells within the tumor, which had been impaired, to attack the cancer and extend lives. The drug didn’t spur such anti-cancer activity after the surgery because those T-cells were removed along with the tumor. The results are very important and very promising but would need to be validated in much larger trials.

 

References:

 

https://www.washingtonpost.com/health/2019/02/11/immunotherapy-may-help-patients-with-kind-cancer-that-killed-john-mccain/?noredirect=on&utm_term=.e1b2e6fffccc

 

https://www.ncbi.nlm.nih.gov/pubmed/30742122

 

https://www.practiceupdate.com/content/neoadjuvant-anti-pd-1-immunotherapy-promotes-immune-responses-in-recurrent-gbm/79742/37/12/1

 

https://www.esmo.org/Oncology-News/Neoadjuvant-PD-1-Blockade-in-Glioblastoma

 

https://neurosciencenews.com/immunotherapy-glioblastoma-cancer-10722/

 

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