This document discusses fibroblast growth factors (FGFs) and their receptors (FGFRs) in cancer. It notes that FGFRs are cell surface receptors involved in normal cellular processes but also cancer development and progression. FGFRs may promote cancer cell growth, invasion, and angiogenesis. The document provides details on FGF signaling pathways, mutations in FGFR genes linked to various cancers, and differential expression of FGFs/FGFRs across cancer types like breast, bladder, prostate, lung and multiple myeloma. It concludes that deregulation of FGFs/FGFRs supports cancer progression and discusses challenges in targeting them for cancer therapy.
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An oncogene is a gene that has the potential to cause cancer. In tumor cells, they are mutated or expressed at high levels. Most normal cells undergo a programmed form of rapid cell death (apoptosis) when critical functions are altered.
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An oncogene is a gene that has the potential to cause cancer. In tumor cells, they are mutated or expressed at high levels. Most normal cells undergo a programmed form of rapid cell death (apoptosis) when critical functions are altered.
The Wnt cascade has emerged as a critical regulator of stem cells. In many tissues, activation of Wnt signaling has also been found to be associated with cancer. Understanding the regulation by Wnt signaling may serve as a paradigm for understanding the dual nature of self-renewal signals.
ONCOGENE AND PROTOONCOGENE
P53 GENE AND ITS APPLICATION IN CANCER ETIOLOGY
TUMOUR SUPPRESSOR GENE AND BCA AND BAC GENE AND ITS APPLICATION ON THE APOPTOSIS AND DEATH RECEPTORS
p53 has been described as “GUARDIAN ANGEL OF THE GENOME”
because it performs following mechanism:
DNA Repair
Cell growth arrest
Apoptosis (programmed cell death)
P53 is also known as cellular tumour antigen Ag, phosphoprotein
P53 or tumour suppressor p53.
P53 protein is encoded by TP53.
g protein coupled receptors, ion channels, types of receptors, wnt signalling, cell signalling, tranduction pathway, disorders regarding the signalling
The Wnt cascade has emerged as a critical regulator of stem cells. In many tissues, activation of Wnt signaling has also been found to be associated with cancer. Understanding the regulation by Wnt signaling may serve as a paradigm for understanding the dual nature of self-renewal signals.
ONCOGENE AND PROTOONCOGENE
P53 GENE AND ITS APPLICATION IN CANCER ETIOLOGY
TUMOUR SUPPRESSOR GENE AND BCA AND BAC GENE AND ITS APPLICATION ON THE APOPTOSIS AND DEATH RECEPTORS
p53 has been described as “GUARDIAN ANGEL OF THE GENOME”
because it performs following mechanism:
DNA Repair
Cell growth arrest
Apoptosis (programmed cell death)
P53 is also known as cellular tumour antigen Ag, phosphoprotein
P53 or tumour suppressor p53.
P53 protein is encoded by TP53.
g protein coupled receptors, ion channels, types of receptors, wnt signalling, cell signalling, tranduction pathway, disorders regarding the signalling
Periodontitis is a chronic infectious inflammatory disease caused by microbes; however the presence of microbes is not enough for the cause of its complex nature of disease. Inflammation is the prime cause of periodontal disease. It commences with the aggregation of pathogenic microbes that induce the host to stimulate a cascade of inflammatory response reactions which in-turn leads to the destruction of the host tissues itself. There is a complex interplay of innate and adaptive immune responses which fights against the pathogens by direct interaction or by release of certain molecules including cytokines.
Cytokines are cell signalling molecules that aid cell to cell communication in immune responses and stimulate the movement of cells towards sites of inflammation, infection and trauma. Cytokine biology reveals that there are some subsets of cytokines which are pro-inflammatory cytokines which stimulate the inflammatory responses and cause tissue destruction.
A periodontist is expected to have a sound basis of the cytokine profile to understand the pathogenesis of periodontitis and also to discover the new treatment modality of anti-cytokine therapy.
Basic Mutagenic signal Transduction or the cancer signal transduction that control cell cycle are important pathways to understand cancer in molecular level and to invent targeted treatment.
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready - the key motivation behind the FAIR Guiding Principles. Concurrently, while recent efforts have explored the use of deep learning to fuse disparate data into predictive models for a wide range of biomedical applications, these models often fail even when the correct answer is already known, and fail to explain individual predictions in terms that data scientists can appreciate. These limitations suggest that new methods to produce practical artificial intelligence are still needed.
In this talk, I will discuss our work in (1) building an integrative knowledge infrastructure to prepare FAIR and "AI-ready" data and services along with (2) neurosymbolic AI methods to improve the quality of predictions and to generate plausible explanations. Attention is given to standards, platforms, and methods to wrangle knowledge into simple, but effective semantic and latent representations, and to make these available into standards-compliant and discoverable interfaces that can be used in model building, validation, and explanation. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine.
Bio
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
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Monitor common gases, weather parameters, particulates.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
3. RTKS IN CANCER
High-affinity cell surface receptors for many polypeptide
growth factors, cytokines, and hormones.
RTKs have been shown not only to be key regulators of
normal cellular processes but also to have a critical role
in the development and progression of many types of
cancer.
RTKs may thus participate in promoting several steps of
carcinogenesis, including clonal cancer cell expansion,
EMT, invasion and angiogenesis.
5. FIBROBLAST
&
GROWTH FACTOR
A type of cell that synthesizes the extracellular matrix and
collagen and plays a critical role in wound healing.
Growth factor is a naturally occurring substance capable
of stimulating cellular growth, proliferation and cellular
differentiation.
protein or a steroid hormone.
Growth factors typically act as signaling molecules
between cells.
6. FIBROBLAST GROWTH FACTORS
Family of growth factors involved in angiogenesis,
wound healing, and embryonic development.
FGFs are key players in the processes of proliferation and
differentiation of wide variety of cells and tissues.
The FGF family consists of 18 ligands that bind to four
homologous high-affinity FGFRs (FGFR1–FGFR4.
The FGFs are secreted polypeptidic growth factors that
bind to receptors expressed at the cell surface of target
cells.
7. IG-LIKE DOMAINS:
The extracellular part is composed of three Ig-like domains (I–
III). Ig domains are named after the immunoglobulin molecules.
One end of the Ig domain has a section that is important for the
specificity of antibodies for their ligands.
The first Ig-like domain is thought to play a role in receptor
autoinhibition
Domains II and III constitute the FGF ligand-binding site.
In FGFR1–3, alternative splicing in Ig-like domain III creates
isoforms with different ligand-binding specificities (FGFR1 IIIb–
FGFR3 IIIb and FGFR1 IIIc–FGFR3 IIIc).
8. FGF SIGNALING:
The dimerization event triggers the activation of the
FGFRs by bringing the intracellular kinases into close
proximity, enabling them to transphosphorylate each
other
9. ACTIVATION OF FGFR BY FRS2:
Fibroblast growth factor receptor substrate 2: Adapter protein
that links activated FGR to downstream signaling pathways.
FRS2 binds to the juxtamembrane region of the FGFR, and upon
activation of the receptor it becomes phosphorylated on several
tyrosine residues, creating docking sites for additional adaptor
proteins. By binding to phosphorylated FRS2, the adaptor GRB2
(growth-factor-receptor-bound protein 2) recruits the Ras/MAPK
pathway
10. R0LE 0F FGF IN BI0L0GICAL
RESP0NCE:
FGF signaling pathways are implicated in a
multitude of biological processes
Proliferation,
Anti-apoptotic signals and
Stimulate cell migration in many cell types
Organogenesis .
FGF signaling is implicated in the formation of
the heart, the lungs, the limbs and the nervous
system, and also plays an important role in
mammary and prostate gland development.
11. MUTATIONS:
FGF signalling is crucial during development,
and mutated FGFRs have been found to be
the cause of several developmental syndromes.
Mutated FGFR3 Achondroplasia
(disorder of bone growth ) & Bladder cancer
Mutated FGFR2 Endometrial cancers
Mutated FGFR4 Childhood sarcoma RMS
SNPS (SINGLE-NUCLEOTIDE POLYMORPHISMS)
Certain germ line SNPs have been identified in FGFRs
and are believed to modulate the malignant phenotype
in some cancer types.
FGFR4 G388R SNP Breast, Lung, Skin, Colon &
Prostate cancer
FGFR2 SNP Breast cancer
12. FUSION PROTEINS
Potent aberrant FGF signalling can be the result of
chromosomal translocations in which protein domains
causing dimerization are fused to the kinase domain of an
FGFR.
These intracellularly localized fusion proteins are
permanently dimerized in the absence of ligand, resulting
in continuous signalling.
They are therefore particularly potent oncogenes that can
drive proliferation of cancer cells.
DIFFERENTIAL EXPRESSION
Ligand-independent signalling can also occur from over
expressed FGFRs.
Over expression of FGFR1 Human breast cancer
13. IMPAIRED DOWN-REGULATION OF FGF
SIGNALLING
Increased levels of FGFRs on the cell surface can also be
the result of impaired down-regulation. After binding, the
ligand– receptor complex is normally endocytosed and
transported to lysosomes for degradation
Defective internalization will result in higher levels of
receptor on the cell surface and prolonged signalling.
Mutations in any protein involved in the internalization of
FGFRs could thus potentially increase FGF signalling.
EXAMPLE:
Cbl, the ubiquitin ligase responsible for the proper down
regulation of many RTKs, has been found mutated in AML
(acute myeloid leukaemia)
14. BREAST CANCER
FGFR2 IIIb and FGF10 are required for embryonic mammary gland
development
Amplification of FGFR
Activation of FGFR1 in mouse or human mammary cell lines
resulted in increased cell proliferation, survival and invasion
confirming the potential oncogenic nature of FGFR1 signalling
Amplification of FGFR2 Triple-negative breast tumors
Ectopic expression of FGFR4, FGF8,FGF10
Amplification of FGF3 occurs in 15–20% of human breast cancers
ENDOMETRIAL CANCER
Mutations in FGFR2 have been identified in approximately 10%of
human endometrial carcinomas
15. BLADDER CANCER
Frequent mutations in FGFR3 (approximately 70%) UCC(
cancer that typically occurs in the urinary system: the kidney,
urinary bladder, and accessory organs)
Decreased levels of FGFR2
Over expression of FGFR1
PROSTATE CANCER
Normal prostate stromal cells produce several FGFs, including
FGF2, FGF7 and FGF9
Up-regulation of FGF1, FGF2, FGF6,FGF7, FGF8 and FGF9
High expression of FGF8 in malignant prostate epithelium has
been associated with decreased patient survival
Over expressed FGFR1
16. LUNG CANCER
SCLC & NSCLC
Frequent amplification of FGFR1 human squamous cell lung cancer
High copy number gain of the FGFR1 gene has also been identified in
SCLC
High levels of serum FGF2 are associated with a poor prognosis
Somatic mutations in FGFR1, FGFR2 and FGFR4 have been identified
in lung carcinomas
RMS
RMS is a cancer originating from skeletal muscle and is the most
frequent soft tissue sarcoma in children
FGFR4 identified in 7–8% of RMS tumors
High expression of FGFR4 has also been associated with advanced
stage and poor survival in RMS
FGFR1 and FGFR2 have been reported to be over expressed in RMS
17. MM (MULTIPLE MYELOMA)
MM is a plasma cell malignancy that is characterized by
accumulation of clonal plasma cells in bones and bone marrow
where they cause bone lesions and interfere with the production
of normal blood cells.
Over expressed FGFR3 15–20%
EMS
EMS/SCLL is a rare but aggressive neoplasm with a high rate of
progression into acute leukaemia
At the molecular level, the disorder is associated with
chromosomal translocations involving the FGFR1 gene on
chromosome 8p11-12
18. OTHER TYPES OF CANCER
Brain cancer
Head and neck cancer
Gastric cancer and ovarian cancer
Stomach cancer and colon cancer
CONCLUDING REMARKS
Deregulation of FGFs and FGFRs is detected in a
number of solid human tumors and may sustain
several of the cancer hallmarks.
In particular, FGFs and FGFRs seem to act
oncogenically to stimulate several steps of cancer
progression, including cancer cell proliferation and
survival, as well as angiogenesis
19. FUTURE CHALLENGES
Future challenges in targeting FGFs/FGFRs in
cancer therapy include increasing the
knowledge about the effect of FGFRs in
progression of specific cancer types, the
development of FGFR therapeutics with few
side effects, and the development of diagnostic
and prognostic biomarkers to enable
appropriate patient selection for cancer
treatment.