Genomics data from The Cancer Genome Atlas (TCGA) project has led to the comprehensive molecular characterization of multiple cancer types. The large sample numbers in TCGA offer an excellent opportunity to address questions associated with tumo heterogeneity. Exploration of the data by cancer researchers and clinicians is imperative to unearth novel therapeutic/diagnostic biomarkers. Various computational tools have been developed to aid researchers in carrying out specific TCGA data analyses; however there is need for resources to facilitate the study of gene expression variations and survival associations across tumors. Here, we report UALCAN, an easy to use, interactive web-portal to perform to in-depth analyses of TCGA gene expression data. UALCAN uses TCGA level 3 RNA-seq and clinical data from 31 cancer types. The portal's user-friendly features allow to perform: 1) analyze relative expression of a query gene(s) across tumor and normal samples, as well as in various tumor sub-groups based on individual cancer stages, tumor grade, race, body weight or other clinicopathologic features, 2) estimate the effect of gene expression level and clinicopathologic features on patient survival; and 3) identify the top over- and under-expressed (up and down-regulated) genes in individual cancer types. This resource serves as a platform for in silico validation of target genes and for identifying tumor sub-group specific candidate biomarkers. Thus, UALCAN web-portal could be extremely helpful in accelerating cancer research. UALCAN is publicly available at http://ualcan.path.uab.edu.
CAR-T cell preclinical in vivo animal testing performed in xenograft murine models derived by well-defined cell lines or primary human tumor cells. Immunodeficient mice, lacking of effective innate immunity for the absence of B cells, T cells, or NK cells, are the optimal animal models for engraftment of tumor cells and evaluation of CAR-T cells. https://www.creative-biolabs.com/car-t/car-t-preclinical-in-vivo-assay.htm
The most complete map of oncogenes to date a summary of 568 oncogenes in 66 c...DoriaFang
By analyzing the genomes of 28,076 tumor samples from 66 types of cancer, 568 cancer driver genes were identified. This is the most complete map of cancer driver genes to date. The research data has been updated on the IntOGen platform.
In a narrow sense of cancer biomarker, it is limited to proteins the most used to challenge in the clinical applications, especially in the CAR-T therapy. Specifically, a cancer biomarker of the CAR-T provides the most prominent signal of cancer cells for distinguishing from normal cells and the most effective CAR T target for immune recognition and destruction. https://www.creative-biolabs.com/car-t/biomarker-identification-selection.htm
Genomics data from The Cancer Genome Atlas (TCGA) project has led to the comprehensive molecular characterization of multiple cancer types. The large sample numbers in TCGA offer an excellent opportunity to address questions associated with tumo heterogeneity. Exploration of the data by cancer researchers and clinicians is imperative to unearth novel therapeutic/diagnostic biomarkers. Various computational tools have been developed to aid researchers in carrying out specific TCGA data analyses; however there is need for resources to facilitate the study of gene expression variations and survival associations across tumors. Here, we report UALCAN, an easy to use, interactive web-portal to perform to in-depth analyses of TCGA gene expression data. UALCAN uses TCGA level 3 RNA-seq and clinical data from 31 cancer types. The portal's user-friendly features allow to perform: 1) analyze relative expression of a query gene(s) across tumor and normal samples, as well as in various tumor sub-groups based on individual cancer stages, tumor grade, race, body weight or other clinicopathologic features, 2) estimate the effect of gene expression level and clinicopathologic features on patient survival; and 3) identify the top over- and under-expressed (up and down-regulated) genes in individual cancer types. This resource serves as a platform for in silico validation of target genes and for identifying tumor sub-group specific candidate biomarkers. Thus, UALCAN web-portal could be extremely helpful in accelerating cancer research. UALCAN is publicly available at http://ualcan.path.uab.edu.
CAR-T cell preclinical in vivo animal testing performed in xenograft murine models derived by well-defined cell lines or primary human tumor cells. Immunodeficient mice, lacking of effective innate immunity for the absence of B cells, T cells, or NK cells, are the optimal animal models for engraftment of tumor cells and evaluation of CAR-T cells. https://www.creative-biolabs.com/car-t/car-t-preclinical-in-vivo-assay.htm
The most complete map of oncogenes to date a summary of 568 oncogenes in 66 c...DoriaFang
By analyzing the genomes of 28,076 tumor samples from 66 types of cancer, 568 cancer driver genes were identified. This is the most complete map of cancer driver genes to date. The research data has been updated on the IntOGen platform.
In a narrow sense of cancer biomarker, it is limited to proteins the most used to challenge in the clinical applications, especially in the CAR-T therapy. Specifically, a cancer biomarker of the CAR-T provides the most prominent signal of cancer cells for distinguishing from normal cells and the most effective CAR T target for immune recognition and destruction. https://www.creative-biolabs.com/car-t/biomarker-identification-selection.htm
This slides briefly introduced why car t cell validation assay is essential for car t therapy development and which assays should be done to validate the safety, identity, purity and potency of car t cell products.
CAR T-cell Therapy_A New Era in Cancer ImmunotherapyTuhin Samanta
Illusory Antigen Receptor (CAR) T-cell treatment includes hereditary alteration of patient's autologous T-cells to express a CAR explicit for a tumor antigen, following by ex vivo cell extension and re-imbuement back to the patient. Vehicles are combination proteins of a chose single-chain section variable from a particular monoclonal immune response and at least one T-cell receptor intracellular flagging spaces. This T-cell hereditary change may happen either by means of viral-based quality exchange strategies or nonviral techniques, for example, DNA-based transposons, CRISPR/Cas9 innovation or direct exchange of in vitro deciphered mRNA by electroporation.
A brief overview of ROSALIND - a smart data platform designed to provide better personalized treatment options to cancer patients based on their genetic profile.
An Overview of Pancreatic Cancer - Creative BiolabsCreative-Biolabs
Pancreatic cancer is one of the malignant tumors with strong invasiveness, high degree of deterioration and low surgical resection rate in the digestive system. Optimizing early diagnosis and developing targeted therapy of pancreatic cancer are the key to improving the survival rate of patients. The slide named an overview of pancreatic cancer is created by Creative Biolabs who provides high-quality antibody production with advanced research tools, professional technical support, and rapid global delivery. In the slide, we will give you a comprehensive introduction to pancreatic cancer and its signaling pathways, diagnostics markers and targeted therapies, as well as Creative Biolabs’ antibody-related products and services. It is believed that you can fully understand how important it is to optimize early diagnosis and develop targeted drugs.
Learn more about how AARSOTA Bio-Immunotherapy integrates with Hope4Cancer's non-toxic cancer treatment strategies. Hope4Cancer's alternative cancer treatments reduces the toxic effects of prior chemo and radiation treatments while directly healing the cancer.
This PPT is about immune system and immune therapy, some basic knowledge about Chimeric Antigen Receptor or CAR technology and its application on tumor therapy.
Biomarkers and biomarker testing are changing the way some colorectal cancer is treated and knowing your biomarkers can help your doctors identify your best treatment options and help you in making well informed decisions about how your cancer will be treated allowing you to be your own best advocate.
Join in on this informative webinar with guest Dr. Christopher Lieu from the University of Colorado Cancer Center, as he discusses everything you need to know about biomarkers.
Identification of cancer drivers across tumor typesNuria Lopez-Bigas
Thousands of tumor genomes/exomes are being sequenced as part of the International Cancer Genome Consortium (ICGC), The Cancer Genome Atlas (TCGA) and other initiatives. This opens the possibility to have, for the first time, a comprehensive picture of mutations, genes and pathways involved in the cancer phenotype across tumor types. We have developed computational methods able to identify signals of positive selection in the pattern of tumor somatic mutations, which point to genes and pathways directly involved in the development of the tumors. We have applied these approaches to 3025 tumors from 12 different cancer types of the TCGA Pan-Cancer project, identifying 291 high-confidence cancer driver genes acting on those tumors (Tamborero et al 2013). We have also developed IntOGen-mutations (http://www.intogen.org/mutations), a novel web platform for cancer genomes interpretations, which analyses not only TCGA pan-cancer data but all mutation data from ICGC and other initiatives. The resource allows users to identify driver mutations, genes and pathways acting on more than 6000 tumors originated in 17 different cancer sites and to analyze newly sequence tumor genomes. Among the novel cancer drivers identified there are chromatin regulatory factors and splicing factors, which are emerging as important genes in cancer development and are regarded as interesting candidates for novel targets for cancer treatment. In my talk I will summarize all these recent findings.
More info: http://bg.upf.edu/blog/2013/10/my-slides-on-identification-of-cancer-drivers-across-tumor-types/
This slides briefly introduced why car t cell validation assay is essential for car t therapy development and which assays should be done to validate the safety, identity, purity and potency of car t cell products.
CAR T-cell Therapy_A New Era in Cancer ImmunotherapyTuhin Samanta
Illusory Antigen Receptor (CAR) T-cell treatment includes hereditary alteration of patient's autologous T-cells to express a CAR explicit for a tumor antigen, following by ex vivo cell extension and re-imbuement back to the patient. Vehicles are combination proteins of a chose single-chain section variable from a particular monoclonal immune response and at least one T-cell receptor intracellular flagging spaces. This T-cell hereditary change may happen either by means of viral-based quality exchange strategies or nonviral techniques, for example, DNA-based transposons, CRISPR/Cas9 innovation or direct exchange of in vitro deciphered mRNA by electroporation.
A brief overview of ROSALIND - a smart data platform designed to provide better personalized treatment options to cancer patients based on their genetic profile.
An Overview of Pancreatic Cancer - Creative BiolabsCreative-Biolabs
Pancreatic cancer is one of the malignant tumors with strong invasiveness, high degree of deterioration and low surgical resection rate in the digestive system. Optimizing early diagnosis and developing targeted therapy of pancreatic cancer are the key to improving the survival rate of patients. The slide named an overview of pancreatic cancer is created by Creative Biolabs who provides high-quality antibody production with advanced research tools, professional technical support, and rapid global delivery. In the slide, we will give you a comprehensive introduction to pancreatic cancer and its signaling pathways, diagnostics markers and targeted therapies, as well as Creative Biolabs’ antibody-related products and services. It is believed that you can fully understand how important it is to optimize early diagnosis and develop targeted drugs.
Learn more about how AARSOTA Bio-Immunotherapy integrates with Hope4Cancer's non-toxic cancer treatment strategies. Hope4Cancer's alternative cancer treatments reduces the toxic effects of prior chemo and radiation treatments while directly healing the cancer.
This PPT is about immune system and immune therapy, some basic knowledge about Chimeric Antigen Receptor or CAR technology and its application on tumor therapy.
Biomarkers and biomarker testing are changing the way some colorectal cancer is treated and knowing your biomarkers can help your doctors identify your best treatment options and help you in making well informed decisions about how your cancer will be treated allowing you to be your own best advocate.
Join in on this informative webinar with guest Dr. Christopher Lieu from the University of Colorado Cancer Center, as he discusses everything you need to know about biomarkers.
Identification of cancer drivers across tumor typesNuria Lopez-Bigas
Thousands of tumor genomes/exomes are being sequenced as part of the International Cancer Genome Consortium (ICGC), The Cancer Genome Atlas (TCGA) and other initiatives. This opens the possibility to have, for the first time, a comprehensive picture of mutations, genes and pathways involved in the cancer phenotype across tumor types. We have developed computational methods able to identify signals of positive selection in the pattern of tumor somatic mutations, which point to genes and pathways directly involved in the development of the tumors. We have applied these approaches to 3025 tumors from 12 different cancer types of the TCGA Pan-Cancer project, identifying 291 high-confidence cancer driver genes acting on those tumors (Tamborero et al 2013). We have also developed IntOGen-mutations (http://www.intogen.org/mutations), a novel web platform for cancer genomes interpretations, which analyses not only TCGA pan-cancer data but all mutation data from ICGC and other initiatives. The resource allows users to identify driver mutations, genes and pathways acting on more than 6000 tumors originated in 17 different cancer sites and to analyze newly sequence tumor genomes. Among the novel cancer drivers identified there are chromatin regulatory factors and splicing factors, which are emerging as important genes in cancer development and are regarded as interesting candidates for novel targets for cancer treatment. In my talk I will summarize all these recent findings.
More info: http://bg.upf.edu/blog/2013/10/my-slides-on-identification-of-cancer-drivers-across-tumor-types/
Cancer is a leading cause of death in developed countries. In this webcast Dr. Andreas Scherer will explain how personalized medicine can transform our approach to fighting this disease. He will also discuss current roadblocks and diagnostic challenges, and the pivotal role of Next Gen Sequencing to overcome these challenges.
The webcast will inform about best practices to design and implement a cancer testing pipeline: from sample preparation, to sequencing, to secondary and tertiary analysis of sequencing data. The goal is to rapidly identify clinically actionable data that allows an oncologist to quickly determine the best available treatment options.
The webcast will include demonstrations of the Golden Helix VarSeq software in the context of analyzing cancer gene panels and somatic mutations.
Cancer is a leading cause of death in developed countries. In this webcast Dr. Andreas Scherer will explain how personalized medicine can transform our approach to fighting this disease. He will also discuss current roadblocks and diagnostic challenges, and the pivotal role of Next Gen Sequencing to overcome these challenges.
The webcast will inform about best practices to design and implement a cancer testing pipeline: from sample preparation, to sequencing, to secondary and tertiary analysis of sequencing data. The goal is to rapidly identify clinically actionable data that allows an oncologist to quickly determine the best available treatment options.
The webcast will include demonstrations of the Golden Helix VarSeq software in the context of analyzing cancer gene panels and somatic mutations.
4th International Conference on Biomarkers & Clinical Research, will be organized around the theme "Impact of Biomarker Developments in Health Diagnostics and Clinical Research."
Information about from where subjects will be recruited based on the.pdffeelingsboutiques
Information about from where subjects will be recruited based on the blood sampling to test mir-
22 in cancer pateints?
Solution
I have understood your question as \" what are the places conducting clincial trials on patients ,
where screening for miR-22 is done on cancer patients\"
I have retrieved the following clinical trials from clinicaltrials .gov registry, which shows the
various hosptials/research centres conducting clinical trials on micro-RNA and cancer in US.
miR-22 as such has only one study in egypt on COPD ( alung disease ) not on cancer. the list is
exhaustive ,around 66 studies, hopefully it is useful for you.
Rank
NCT Number
Title
Recruitment
Conditions
Sponsor/Collaborators
Gender
URL
1
NCT02366494
Micro RNAs to Predict Response to Androgen Deprivation Therapy
Recruiting
Prostate Cancer
Medical College of Wisconsin
Male
https://ClinicalTrials.gov/show/NCT02366494
2
NCT02253251
Clinical Validation of the Role of microRNA Binding Site Mutations in Cancer Risk, Prevention
and Treatment
Recruiting
Cancer
MiraKind
Both
https://ClinicalTrials.gov/show/NCT02253251
3
NCT01231386
MIRNA Profiling of Breast Cancer in Patients Undergoing Neoadjuvant or Adjuvant Treatment
for Locally Advanced & Inflammatory Breast Cancer
Recruiting
Breast Cancer
City of Hope Medical Center
Female
https://ClinicalTrials.gov/show/NCT01231386
4
NCT01541800
Circulating microRNAs as Disease Markers in Pediatric Cancers
Recruiting
Leukemia|Lymphoma|Central Nervous System
Ann & Robert H Lurie Children\'s Hospital of Chicago
Both
https://ClinicalTrials.gov/show/NCT01541800
5
NCT02464930
Evaluation of MicroRNA Expression in Blood and Cytology for Detecting Barrett\'s Esophagus
and Associated Neoplasia
Recruiting
Barrett\'s Esophagus|Gastroesophageal Reflux|Esophageal Adenocarcinoma
Midwest Biomedical Research Foundation|Kansas City Veteran Affairs Medical
Center|University of Kansas
Both
https://ClinicalTrials.gov/show/NCT02464930
6
NCT00806650
Anti-IMP3 Autoantibody and MicroRNA Signature Blood Tests in Finding Metastasis in
Patients With Localized or Metastatic Kidney Cancer
Active, not recruiting
Kidney Cancer
City of Hope Medical Center|National Cancer Institute (NCI)
Both
https://ClinicalTrials.gov/show/NCT00806650
7
NCT02127073
Pilot Study of Oxytocin and microRNA Identification in NAF, Serum, and Tissue in Women
With Breast Cancer
Recruiting
Breast Cancer|Ductal Carcinoma in Situ
Sheldon Feldman|Columbia University
Female
https://ClinicalTrials.gov/show/NCT02127073
8
NCT02531607
Lipidomics, Proteomics, Micro RNAs and Volatile Organic Compounds
Recruiting
Pancreatic Neoplasms
Florida Hospital
Both
https://ClinicalTrials.gov/show/NCT02531607
9
NCT01595126
Longitudinal Study of Biomarkers
Recruiting
Central Nervous System Tumor
Ann & Robert H Lurie Children\'s Hospital of Chicago
Both
https://ClinicalTrials.gov/show/NCT01595126
10
NCT00581750
Molecular Genetic Basis of Invasive Breast Cancer Risk Associated With Lobular Carcinoma in
Situ
Active, not recruitin.
Join Fight CRC in a webinar about biomarkers. In this session, Dr. Chris Lieu will focus the discussion on the NTRK biomarker, in addition to ctDNA, and Next-Generation Sequencing.
Background : During the conference of ASCO 2015, there was no consensus about TIL role in beast cancer and no recommendations concerning the microscopic assessment of TIL. In fact, the patients could be put on anti-PD1 drugs without the necessity of highlighting PD1 positive cells by using immunohistochemistry. Nevertheless, many questions about the prognostic impact of TIL, the methods of assessment, the type of TIL to count remain unresolved. Material and Methods : We performed a review of the literature on the sites : Pubmed and Cochrane. We used the key-words : �TIL in cancer�; �TIL in breast cancer� and �prognostic impact of TIL in breast cancer�. Results : According to our inclusion and exclusion criteria, thirty eight articles were retained. Our review of the literature showed that assessing TIL in high grade tumors seem unnecessary. They seem available in intermediate graded tumors. In neo-adjuvant and adjuvant conditions, CD3+ lymphocytes seem to be correlated to a good response to chemotherapy. After a chemotherapy, quantification T reg lymphocytes CD4 + FOXP3+ seems helpful because the decrease of their number is correlated to a good prognosis. Conclusion : The role of TIL in breast cancer is clearly established. The mechanisms of immune escape induced to discovery of immune therapy. The role of the microscopic examination and the subtyping of TIL using immunohistochemistry hasn�t been clearly established. Through this review of the literature, we tried to establish a diagram highlighting the different subtypes of TIL to evaluate and their prognostic impact.
1. THE STANFORD-CANCER GENOME ATLAS PORTAL:
A WEB/MOBILE NAVIGATION INTERFACE FOR EXPLORING THE
CLINICAL ASSOCIATIONS OF CANCER DRIVERS
Tutorial: How to navigate the web portal
2. Three ways of looking TCGA data
What are the clinically relevant genes/miRs/proteins?
• By name of genes, miRs or proteins
• By cancer type
• By clinical parameters
Profiling by clinical parameters:
What is the difference in genetic/proteomic changes
between classes in a clinical parameter in a certain
cancer?
Two hit hypothesis test:
Do the two genetic/proteomic changes occur together
or not?
I
II
III
3. I. Checking what clinical parameters are associated with
genes/miRs/proteins of your interest
Type the name of gene/miR/protein here:
Ex) TP53
Click Submit
4. I. Checking what clinical parameters are associated with
genes/miRs/proteins of your interest
Type the name of gene/miR/protein here:
Ex) TP53
Click Submit
Get to the summary page of TP53
5. I. Check what clinical parameters are associated with
genes/miRs/proteins of your interest
TP53 is associated with:
i) Race in breast cancer
ii) Triple marker in breast cancer
iii) N-Status in thyroid cancer
iv) Histo grade in uterine cancer
6. The mutation frequency of genes/miRs/proteins of your interest
across all cancer types
Sort function
7. The copy number variation frequency of genes/miRs/proteins of
your interest across all cancer types
8. I. What are the clinically relevant genes/miRs/proteins?
When you are interested in a certain cancer type, click here and select a cancer type
9. I. What are the clinically relevant genes/miRs/proteins?
If you select COADREAD, webpage shows the summary list with clinical parameters that are
available in COADREAD
10. I. What are the clinically relevant genes/miRs/proteins?
If you select genes in ClinicalStage, webpage shows the list of genes associated with a clinical stage in
COADREAD
11. I. What are the clinically relevant genes/miRs/proteins?
Clinical parameters with categorical values; click each class in a clinical parameter
12. I. What are the clinically relevant genes/miRs/proteins?
When you are interested in a clinical parameter, click here and select a clinical parameter
13. I. What are the clinically relevant genes/miRs/proteins?
If you select clinical stage, the web page shows the summary list from all the cancer types
currently in our data set where clinical stage is available. This is a pan-TCGA summary type
page.
14. I. What are the clinically relevant genes/miRs/proteins?
If you select genes in STAD, the web page shows the list of genes associated with a clinical stage in
stomach cancers
15. I. In summary, you can get to the summary page of WRN which is
associated with clinical stage in colorectal cancer three different ways
16. I. In summary, you can get to the summary page of WRN which is
associated with clinical stage in colorectal cancer by three different ways
17. II. Profiling by Clinical Parameter
When you want to know the differences of a gene between samples with different
clinical parameter types - in terms of genetic/proteomic profiling - use the middle
panel
How does PIK3CA behave differently between EBV infected and non-infected
samples in stomach cancer?
1. Type PIK3CA
2. Select STAD
3. Select EBV present
4. Click Submit
18. II. Profiling by Clinical Parameter
Summary of PIK3CA CNV between EBV infected and
non-infected samples in stomach cancer
19. II. Profiling by Clinical Parameter
Difference in PIK3CA mutations between EBV infected and non-infected samples in stomach cancer
20. II. Profiling by Clinical Parameter
Difference in expression level of PIK3CA between EBV infected and non-infected samples in stomach cancer
21. III. Two hit hypothesis test
What is the difference in copy number changes of TP53 between samples with and
without TP53 mutation in colorectal cancers?
Second level sample group:
With this example, it will then split colorectal cancers
into two groups –
i) samples with TP53 mutation
ii) samples without TP53 mutations
First level sample group:
With this example, what is the distribution of copy
number changes of TP53 in each group?
22. III. Testing two hit hypothesis
Summarize the copy number changes of TP53 by samples with/without TP53
mutations in colorectal cancers
23. III. Testing two hit hypothesis
Summarize the copy number changes of TP53 by samples with/without TP53
mutations in colorectal cancers
Hemizygous deletion occurred significantly more in samples with TP53 mutations than samples without
TP53 mutations