ALL RIGHT.
WELL, THANKS, EVERYBODY, FOR
COMING OUT TODAY.
WELCOME TO THE PEOPLE ONLINE.
I HAVE THE DISTINCT PLSH YOU'RE
OF -- PLEASURE OF INTRODUCING
OUR SPEAKER TODAY FOR THE
SPECIAL SEMINAR TO THE SINGLE
CELL AND SPATIAL BIOLOGY USERS
GROUP.
DR. JAS MINIMUM PLUMMER IS
CURRENTLY THE DIRECTOR OF THE
CENTER FOR SPATIAL OMICS AT ST.
JUDE CHILDREN'S RESEARCH
HOSPITAL.
SHE'S ORIGINALLY FROM CANADA,
SHE TOLD ME THIS MORNING, WHICH
IN MOST YEARS WOULD MEAN WE'RE
REALLY ROOTING FOR HER BUT IN A
SUMMER OLYMPIC YEAR PERHAPS WE
SHOULD BE THINKING OF HER AS
COMPETITION THIS YEAR.
SHE COMPLETED HER UNDERGRADUATE
AND Ph.D. WORK AT RAILROAD
UNIVERSITY OF TORONTO, ANDS
DOING RESEARCH AT THE CHILDREN'S
HOSPITAL OF LOS ANGELES.
AFTER THAT, SHE MOVED TO THE
SRNLT FOR BIOINFORMATICS AT
FUNCTIONAL GENOMICS AT
CEDARS-SINAI MEDICAL CENTER.
OVER THE COURSE OF HER WORK AND
WHAT SHE'LL SHOW MANUFACTURE
TODAY SHE GAINED A DEEP
EXPERTISE IN FUNCTIONAL GENOMICS
AND SPECIFICALLY NEURAL
DEVELOPMENT HER OBSERVATIONS
INCLUDED MANY WORKS THAT
DEMONSTRATE HOW TUMORS ARISE DUE
TO ALTERATIONS BOTH GENETIC 1K3
EPIGENETIC AND CAN RUPT NORMAL
DEVELOPMENTAL PROGRAMS,
IMPORTANT TO THE PEDIATRIC
ONCOLOGISTS IN THE ROOM.
SHE NOW LEADS A GROUP AT SAINT
JUDZ USING CUTTING EDGE
SPATIAL -- ST. JUDE'S USING
CUTTING EAJ SPATIAL TECHNOLOGIES
AND MACHINE LEARNING AND
ARTIFICIAL INTELLIGENCE TO
PROFILE COMPLEX CELLULAR
INTERACTIONS THAT DRIVE
DEVELOPMENT AND IN SOME CASES
TUMOR GENESIS AND PATHOGENESIS.
HER APPROACH TO RESEARCH IS
DEEPLY ROOTED IN INNOVATION 1K3
THOROUGHNESS AND CURRENTLY HER
LAB IS FOCUSED ON UNRAVELING THE
MYSTERIES OF GENETIC INFLUENCE
IN CANCER SUSCEPTIBILITY IN
PATHOGENESIS.
THE TITLE OF HER LECTURE TODAY
IS SINGLE CELL AND SPATIAL
TECHNOLOGIES, APPLICATIONS TO
DISEASE.
DR. PLUMMER, THANK YOU FOR BEING
WITH US TODAY.
[APPLAUSE]
>> THANK YOU VERY MUCH
ESPECIALLY TO THE PEDIATRIC
ONCOLOGY BRANCH FOR COORDINATING
MY VISIT.
I LOOK FORWARD TO MEETING WITH
ALL OF YOU.
FIRST GLADGES ARE I TOOK THE
ASSIGNMENT, I PICKED UP THE
ASSIGNMENT OF KIND OF GIVING
BROAD STROKES BUT VERY SPECIFIC
TO HYPOTHESIS WE'RE INTERESTED
IN IN MY LAB.
THE IDEA THAT MAYBE YOU GUYS ALL
COME FROM DIFFERENT DOMAINS, BUT
MAYBE YOU CAN SEE HOW YOUR
PROJECTS WILL BE OF USE USING
SOME OF THESE THOLINGS.
-- USING SOME OF THESE
TECHNOLOGIES.
AGAIN FROM THE BEAUTIFUL
INTRODUCTION, THANK YOU FOR
THAT.
MY LAB IS INTERESTED IN
SOMETHING VERY PRINCIPAL.
I'M A GENETICIST AND REALLY
INTERESTED IN HOW WE CAN USE THE
CELLS OF ORIGIN, KIND OF IF YOU
WANT TO BE A
NEURODEVELOPMENTALLIST, YOU WANT
TO BE A CANCER BIOLOGIST, TO
REALLY UNDERSTAND WHERE CELLS
CAME FROM AND UNDER OUR CONTEXT,
REALLY UNDERSTANDING HOW GENETIC
PERTUBATIONS CAN DRIVE DISEASE
PATHOLOGY.
SO YOU'LL KIND OF 1R A BIG SCOPE
RIGHT -- SO OUR BIG SCOPE MOW TO
THINK ABOUT WHEN DO WE ACTUALLY
DECIDE TO USE SINGLE CELL AND
WHEN DO WE DECIDE TO USE SPATIAL
TECHNOLOGIES.
I'M NOT A TECHNOLOGIST, I'M
STILL A BIOLOGIST REALLY
INTERESTED IN CERTAIN QUESTIONS.
SO IN THIS CASE, ONE OF THE
QUESTIONS MY LAB IS INTERESTED
IN BACK TO THE IDEA OF CELLS OF
ORIGIN IS REALLY TAKING YOU
THRAW A CASE STUDY -- THROUGH A
CASE STUDY OF MULTIOMICS AND
NEURODEVELOPMENTAL DISORDERS,
THIS IS ACTUALLY AN UNDERLYING
PICTURE OF USING A TECHNOLOGY
CALLED GEOMIX TO LOOK -- ARE G
HE OMICS.
NEURAL DEVELOPMENT AFFECTS MORE
THAN 25% OF THE WORLD GLOBALLY.
IT'S UNDER A LARGER BRANCH OF
THE IDEA THAT WE HAVE NEURAL
DEVELOPMENTAL PATHOLOGIES IN
MANY DISEASES WHETHER THAT'S
DEPRESSION, ADHD, AUTISM,
SCHIZOPHRENIA, AND BIPOLAR.
SO THE TREE ON THE RIGHT IS
SHOWING YOU THAT IN A FAMILY,
YOU MAY HAVE AN AFFECTED
INDIVIDUAL WHO IS IN ORANGE AND
UNAFFECTED INDIVIDUALS, AND OVER
SEVERAL LINEAGES YOU'VE PROBABLY
HEARD OF LIKE AN UNCLE THAT MAY
HAVE HAD SCILTS FREN YA BUT --
SCITSZ FREN YA BUT THAT
SOMEONE'S NEPHEW OR NIECE MAY
HAVE AUTISM.
THIS WAS KIND OF THE STUDY THAT
SHOULD HAVE BEEN -- HAS A REALLY
PROFOUND FINDING FROM SOMETHING
VERY SIMPLISTIC, YOU'LL SEE I
USE A LOFT DIFFERENT TYPES OF
DATA TO REALLY GET TO THE IDEA
OF WHERE WE TEST THE HYPOTHESIS.
SO THE STUDY WAS REALLY SIMPLE
IN THAT THE PREFRONTAL CORTEX IS
THE PLACE BY WHICH A LOT OF
THESE ISSUES ARISE.
THIS IS YOUR HIGH LEVEL
COGNITIVE FUNCTION CENTER. SO
THEY JUST MUSHED UP DIFFERENT
PARTS OF THE BRAINS THAT ARE
AFFECTED BY AUTISM OR
NEUROPSYCHIATRIC DISEASE, SO ON
THE LEFT ARE KIND OF REGIONS OF
THE BRAIN THAT HAVE TYPICALLY UP
REGULATED GENES OR DOWN
REGULATED GENES.
PREFRONTAL CORTEX ARE BEING
DEFINED BY THESE GENES, THE RED
OR BLUE ONES.
WHAT WAS INTERESTING WHEN YOU
DID THAT IN AUTISM YOU JUST GOT
RID OF THAT PATTERNING, SO NOT
NECESSARILY THAT ALL GENES ARE
GOTTEN RID OF, THEY'VE GOTTEN
RID OF THAT KIND OF BEAUTIFUL
SPATIAL TEMPORAL PATTERN.
SO WHAT DOES THAT ACTUALLY LOOK
LIKE?
SO FROM THAT VERY BASIC
PRINCIPLE THAT OBVIOUSLY THERE'S
A DISREGULATING OF GENE
EXPRESSION.
SO IT'S NOT AS SIMPLISTIC AS
KIND OF ONCOLOGY WHERE YOU KIND
OF HAVE ONE OR TWO DRIVER GENES
OR FUSION PROTEINS IN THE CASE
OF PEDIATRIC CANCERS.
WHAT REALLY HAPPENS IN NEURO
DEVELOPMENT DISORDERS IS WE
DON'T HAVE A ONE HIT WONDER SO
FROM THIS CONTEXT YOU CAN SEE
THE YELLOW ARE THE DISORDERS.
IN AUTISMS ARE THE BLUE,
SYNDROMIC, THESE ARE REALLY BIG
HITS, IF YOU HAVE THESE, YOU
KIND OF HAVE VERY SEVERE NEURO
DEVELOPMENT DISORDERS, MOST OF
THEM ARE MENDELIAN DISORDERS.
WHAT YOU SHOULD SEE IN THE
MIDDLE ARE THINGS THAT ARE VERY
DIFFERENT BOTH PHENOTYPICALLY
HAVE A LOT OF GENES THAT ARE
INTERCONNECTED, ALMOST HALF OF
THESE GENES ARE ACTUALLY -- THAT
ARE ACTUALLY ASSOCIATED ACROSS
MORE THAN TWO PSYCHIATRIC
CATEGORIES.
SO WE TOOK THIS VERY BASIC
PRINCIPLE, RIGHT, SO IF ALL
THESE GENES ARE CONNECTED BUT
THEY'RE NOT NECESSARILY
CONNECTED BY THE EXACTED
MUTATIONS THEY HAVE, MAYBE
THEY'RE CONNECTED IN TERMS OF
THEIR GENE REGULATORY NETWORK,
RIGHT?
BACK TO THAT VERY IDEA OF
MUSHING UP A BRAIN AND IN
TYPICALLY-DEVELOPING CHILDREN
YOU HAVE THINGS THAT GO UP AND
THINGS THAT GO DOWN, MAYBE IT'S
THE UNDERLYING GENES, THAT
PATTERN OF THINGS BEING
CONNECTED ARE THE GENES THAT ARE
BEING REGULATED IN SIMILAR WAYS.
SO THIS IS NOT A VERY FANCY MATH
PROBLEM.
ESSENTIAL WE BUILD THESE
NETWORKS VERY SIMPLISTICALLY.
SO IF YOU IMAGINE THAT YOU HAVE
GENE NUMBER ONE BEING BLUE, GENE
NUMBER TWO BEING RED, GENE
NUMBER THREE BEING GREEN, IT'S
REALLY THE TRANSCRIPTION FACTORS
THAT BIND THEM, RIGHT, THAT GIVE
KIND OF THIS OVERLAPPING
PHENOTYPE.
IS ONE TRANSCRIPTION FACTOR IN
THE CASE OF TRANSCRIPTION FACTOR
SIX THAT BINDS THREE DIFFERENT
TYPES OF GENES AND MAYBE THAT'S
THE OVERLAPPINGNESS.
SO AS YOU BUILD THAT NETWORK IS
THE BOTTOM RIGHT-HAND SIDE.
SO YOU SEE NUMBER ONE AUTO
REGULATES ITSELF, NUMBER TWO
REGULATES ITSELF AND REGULATES
GENE NUMBER FIVE AND YOU CAN SEE
HOW THEN YOU GET TO THE MIDDLE
PATTERN.
SO OVER THE ENTIRE GENOME YOU
CAN SEE HOW TRANSCRIPTION
FACTORS START TO REGULATE BOTH
THEMSELVES AND COMMON GENES.
THAT LOOKS VERY MUCH, IT'S
REMINISCENT TO THAT FIRST SLIDE
I SHOWED YOU WHICH IS REALLY THE
PATTERN BY WHICH WE SEE IN TERMS
OF THESE NEUROPSYCHIATRIC
DISORDERS.
SO WE TOOK A LARGE GENOME
APPROACH TO THIS.
WE ESSENTIALLY WORKED AT A GROUP
AT UMASS MED WHICH HAVE TAKEN
ALMOST EVERY PUNITIVE GIENGD
PROTEIN WHICH IS -- BINDING
PROTEIN WHICH IS OVER 1200
TRANSCRIPTION FACTORS AND
ESSENTIALLY DID A YEAST 100
GREEN.
THOSE THAT ARE OLD ENOUGH MIGHT
REMEMBER YEAST 200, LIKE MYSELF.
PROTEIN-PROTEIN, ASSOCIATION,
TULL IT DOWN, TURNS BLUE, WE USE
FANCY MOLECULAR TRICKS FOR THIS.
YEAST ONE HYBRID DENOTES DNA ON
PROTEIN.
REMEMBER I SAID THERE ARE THESE
NEURODEVELOPMENTAL DISORDERS,
SAY YOU HAVE A DISORDER, MAJOR
MUTATION, YOU GET ONE PHENOTYPE.
BUT THE IDEA OF THIS IS THAT YOU
JUST NEED SOME TEMPORAL
REGULATION, RIGHT?
IT MIGHT NOT BE ALL OR NOTHING.
SO IF YOU HAD ONE GENE AND YOUR
GENE WAS A TRANSCRIPTION FACTOR
THEN YOU COULD DO CHIP SEQ WHICH
IS KIND OF THE GENE CENTRIC
APPROACH YOU SEE WHERE THERE'S
PURPLE AND YOU SAY YOU HAVE TCF4
AND THAT GETS BOUND BY MANY
DMINGZ IS THAT WOULD BE COOL
THEN YOU WOULD KNOW THAT
EVERYTHING THAT'S TCF4 BOUND BUT
IF YOU WANT TO KNOW MANY GENES
AND THAT THERE'S SHARES
TRANSCRIPTION FACTORS YOU HAVE
TO TAKE THIS APPROACH THE TWO
TAGS HERE, FANCY TAGS, ONE IS
FOR HISS SO WE CAN SELECT FOR
HISTONE MARKERS, SO WE CAN
SELECT FOR HISTIDINE AND SEE IF
THEY'RE GROWING, THAT'S FIRST
THING, THEN WE CHECK TO SEE IF
THEY'RE DONE.
THIS IS DONE IN TRIPLICATE, MANY
TRANSCRIPTION FACTOR IS PINNED
FOUR TIMES SO YOU CAN IMAGINE
THIS IS A REALLY AUTOMATED
SCREEN, WE DO IT BY ROBOT.
THE GENE REGULATORY NETWORK
LOOKS FOR 50 PUNITIVE
NEURODEVELOPMENTAL DISORDER
GENES.
IT EX-TRAP LATES QUICKLY.
THOSE 50 GENES ARE IN THE
YELLOW.
IN BLUE ARE ALL THE
TRANSCRIPTION FACTORS THAT
COMBINE IT.
I HOPE YOU APPRECIATE THAT IT'S
HIGHLY REGULATED, RIGHT, AND
INTERCONNECTED.
SO THAT IDEA THAT YOU HAVE A
SINGLE TRANSCRIPTION FACTOR AND
IT'S YOUR MASTER TRANSCRIPTION
FACTOR AND IT DOES EVERYTHING
AND ANYTHING IS ACTUALLY THE
NUANCE OF WHEN THOSE
TRANSCRIPTION FACTORS ARE BOUND
AND WHAT COMBINATIONS AND NOW WE
HAVE KIND OF CLOSER TO THE
GROUND TRUTH OF THAT COMPLEX
THAT CAN BIND A GIVEN
NEURODEVELOPMENTAL DISORDER
GENE.
HOW DO WE USE THAT?
THAT'S KIND OF THE FUNCTIONAL
GENOMIC SYSTEMS BIOLOGY APPROACH
TO KIND OF HAVE AN IDEA OF WHAT
THE TRANSCRIPTION FACTORS ARE.
AND ARE WE RIGHT ABOUT THIS?
SO WE GO BACK TO LIKE AND I ALSO
SAY THE DATA PARASITES, THERE'S
SO MUCH DATA OUT THERE TO ANY OF
THE TRAINEES, THIS ISN'T MY
DATA, IT'S COMPUTATIONALLY
ANALYZED, BUT THERE'S A
BEAUTIFUL ATLAS CALLED THE
YALLAN BRAIN ATLAS, THESE ARE
ALL THE REGIONS OF THE BRAIN
ACROSS DEVELOPMENTAL TIME.
THERE'S SOME EXPRESSION TO SOME
DEGREE OF EVERY SINGLE GENE IS
EXPRESSED IN THE BRAIN AT SOME
POINT IN DEVELOPMENT.
YOU CAN SEE WHEN WE USE OUR
NEURODEVELOPMENTAL GENE
PROMOTERS THAT YOU GET KIND OF A
HIGHER LEVEL OF WE CAN START TO
TEASE OUT DIFFERENT REGIONS OF
THE BRAIN.
SO REMEMBERING THIS IS BULK
DATA, SO USE THE
NEURODEVELOPMENTAL STORES
THEMSELVES WE CAN START TO TEASE
OUT DIFFERENT REGIONS OF THE
GENES, CEREBELLUM FALLS OFF THE
BACK OF YOUR HEAD, VERY DISTINCT
FROM THESE, WE GET MORE
DIFFERENTIATION THERE.
I HOPE YOU CAN APPRECIATE 158
TRANSCRIPTION FACTORS WE
IDENTIFIED ON THE SCREEN
ACTUALLY IN BULK DATA CAN GET
YOU INTO DEEPER LAYERS OF THE
BRAIN THAT WE WOULDN'T NORMALLY
BE ABLE TO UNCOVER.
IN THE BULK DATA WE'RE ACTUALLY
GETTING TO SOME SPATIAL
SPECIFICITY USING THESE KIND OF
LARGE REGULATORY APPROACHES.
SO THAT WAS A PRETTY STORY, IT'S
TYING OFF, WE HAVE LOTS OF DATA
FOR IT, WE EVEN HAVE SOME SICKLE
CELL, SO WHY -- WE ACTUALLY HAVE
SOME SINGLE CELL.
WHY DID WE ACTUALLY TURN TO
SPATIAL OMICS?
EVERYBODY HAS SEEN A VERSION OF
THIS, IT'S A PIE, I REALLY LIKE
THIS PICTURE.
I SHOWED YOU BULK WHY SEQ.
YOU'VE SEEN THIS WHERE YOU CAN
BREAK THAT OFF AND FIND THAT
BULK DATA ISN'T THAT IMPORTANT,
YOU REALLY WANT TO KNOW THE CELL
TYPES.
I WANT TO MAKE AN ARGUMENT THAT
YOU'RE JUST LOOKING AT CELL
PROPORTIONS.
SO YOU'VE MUSHED UP A BRAIN AND
HAVEN'T REALLY IDENTIFIED HOW
THEY'RE CONNECTED AND REALLY
IT'S THE SPATIAL TRANSCRIPT TOE
MECHANICS THAT WILL ALLOW YOU
HOW THOSE LEGO PIECES COME
TOGETHER TO FORM A FUNCTIONING
BRAIN BUT THIS IS REALLY
TRUTHFULLY MY LAND AND I SAY
THIS BECAUSE I'M VERY GUILTY OF
LIVING IN THE MIDDLE LAND, I
SPEND A LOT OF TIME AND MONEY AS
A PI AND IN THE LAB CONTRIBUTING
TO EVEN THE HUMAN CELL ATLAS.
SO WHAT BULK RNA SEQ DATA IS
TAKING THE ENTIRE BRAIN, MUSHING
IT UP AND HAVING A PELLET AND
WRITING IT ON A SEQUENCER.
I WOULD PROPOSE WE DIDN'T DO
THAT MUCH BETTER WITH SINGLE
CELL, SO YOU JUST DISASSOCIATE
AN ENTIRE BRAIN AND NOW HAVE A
CLOUD OF CELLS AND PUTTING THAT
ON A SEQUENCER.
FOR THOSE THAT KNOW NOTHING
ABOUT CANCER ESPECIALLY ADULT
CANCER IN THIS ROOM, I CAN HOPE
THAT YOU APPRECIATE THAT THESE
TWO THINGS ARE VERY APPRECIATE
BY EYE, THEY'RE VERY DIFFERENT,
SO WHAT I'VE DONE IN THE PAST IS
TAKING BREAST CANCER AND MUSHED
IT UP AND PUT IT INTO SINGLE
CLOUD, WHEN THAT LOOKS VERY
DIFFERENT THAN ADJACENT NORMAL.
SO WHAT DOES THIS LACK LIKE?
THIS IS REAL DATA.
THESE ARE ACTUALLY PLOTS THAT I
THINK I'VE CONTRIBUTED TO SO
GUILTY OF AND I'M SURE OTHER IN
THE ROOM THAT THOSE 44 CELLS
IDENTIFY THAT LOBULE IN BREAST
CANCER.
THOSE 44 CELLS IT DOESN'T MATTER
HOW MUCH COMPUTATION I PUT
BEHIND IT, I'M NEVER GOING TO
IDENTIFY AND MAKE THEM A UNIQUE
CELL ANNOTATION BECAUSE IT'S
ACTUALLY THEIR SPATIAL LOCATION
THAT MAKES THEM UNIQUE.
SO WHY SPATIAL?
I THINK I HELPED TO KIND OF SAY
LIKE WHERE YOU ARE IN CON -- AND
CONTEXT MATTERS AS BIOLOGIST I
THINK IT'S THE EASIEST THING WHO
EVEN MY HUSBAND WHO THINKS TUNA
AND CHICKEN IS PROTEIN, AND HE'S
NOT WRONG, HE CAN LOOK AT
PICTURES AND REALLY UNDERSTAND
THE DIFFERENCES WHICH I THINK IS
WHY WE ALL FUNDAMENTALLYALLY GOT
INTO OUR JOBS.
THE IDEA OF OUR TALK AND IN
GENERAL IS A BROADER VIEW
BECAUSE I KNOW A LOT OF THESE
TECHNOLOGIES ARE COMING IT YOUR
CAMPUS WHICH IS REALLY EXCITING
IS WE REALLY THINK ABOUT THESE
IN FOUR CATEGORIES.
GENOME, EPIGENOME, TRANSCRIPTOME
AND PROTEOME.
WE ALL KNOW THOSE WORLDS VERY
WELL.
IN THE GENOME PLACE AND SPACE WE
ARE NOT VERY WELL VADGESSED IN
THAT, THOSE ARE KIND OF
TECHNOLOGIES WE'LL NOT BE
TALKING ABOUT TODAY BUT THEY
EXIST.
EPIGENOME COMING FAST AND
FURIOUS, TEND TO BE D BIT SEQ,
MAJORITY OF THE TALK WE'LL BE
TALKING ABOUT TRANSCRIPTOME AND
PROTEOME, MAINLY BECAUSE I KNOW
THESE TECHNOLOGIES LIE HERE OR
THEY'RE BEING PURCHASED AND
AVAILABLE.
I'M NOT THE ONLY ONE.
I LOVE THIS REVIEW BECAUSE I'VE
BEEN IN SEQUENCING FOR A VERY
LONG TIME AND THIS IS SINCE LAST
YEAR AND YOU CAN SEE THE
EXPLOSION, I DON'T THINK MANY
FIELDS HAVE SEEN THIS LEVEL OF
EXPLOSION AND THAT'S BEING
REALLY I THINK ALL OF US HAVE
WANTED TO DO SPATIAL AT A HIGHER
LEVEL.
OMICS IS JUST PLEXING.
BY NO MEANS IMAGINE THAT THIS IS
A NEW THING, RIGHT?
WE DIDN'T INVENTED SPATIAL
BIOLOGY, IT'S BEEN AROUND FOR A
VERY LONG TIME.
BUT REALLY THE EXPLOSION.
COMMERCIALIZATION OF THESE
PRODUCTS HAVE ACTUALLY MADE IT
EASIER FOR US.
SO YOU CAN GO SEE A FEW OVER
HERE THAT WE'LL BE RUNNING
THROUGH TODAY, BUT ON CAMPUS YOU
HAVE XAN I UM -- WE HAVE XENIUM,
1K3 -- DID NOT COME OUT IN 2019,
IF CAME OUT THIS PAST YEAR.
THE ORIGINAL SLIDE I SHOWED
EARLIER ABOUT THE GENOME MOST OF
THE TARGET TYPES ARE REALLY ON
THE RNA, I'LL SHOW YOU SOME RNA
BUT WE'LL TRY TO VENTURE INTO A
LITTLE PROTEIN LAND.
I WOULD SAY MOST OF THE TYPES
FOR ANYBODY IN THIS ROOM THAT IS
NOT COMFORTABLE IN SPATIAL YET
TO REALLY BE THINKING ABOUT SOME
OF THE NEXT GENERATION
SEQUENCING, SO KIND OF THE
VIZEUM OR COREO FOR PEOPLE THAT
DON'T HAVE CAPITAL EQUIPMENT IS
A REALLY NICE ASSAY.
AGAIN, EVERYBODY ON THE SAME
MAP, THIS IS KIND OF AN IDEA OF
SEQUENCING BASED TECHNOLOGY.
I'M GOING TO WALK YOU THROUGH
VISIUM BUT IT'S NOT THAT
DIFFERENT, IT'S WHETHER OR NOT
YOU DNA BARCODED ON THE SPOT IN
A DIFFERENT WAY.
ESSENTIALLY YOU CAN TAKE ANY
SLIDES.
THE NICE THING ABOUT THE
VISIUM HD PLATFORM IS YOU CAN
TAKE FROZE TEN OR FFP, COME TALK
TO ME IF YOU WANT TO KNOW
SPECIFICITY.
FFP IS NICE IN TERMS OF
ARCHITECTURE.
THERE'S ONLY A CAPTURED AREA FOR
HD, WHICH IS 6.5, NOT LAUNCHED
YET IN 11 MILLIMETERS SO WHAT IT
IS FOR ALL THE TECHNOLOGIES
WHETHER THAT'S LIVE SEQ VERSION
TWO WHICH IS CURE YOA, STEREO OR
VISIUM IS WE PUT LITTLE DOTS
WHETHER THAT'S NANO BEAD IN THIS
CASE, IT'S NOT THAT DIFFERENT
THAN SINGLE CELL, WE IDENTIFY
THE SPATIAL LOCATION.
SO THE TISSUE IS PUT ON THIS, IT
FITS ON IT, WE MAKE LIBRARIES
OFF AND TOSS IT ON A SEQUENCER
AND NOW YOU HAVE THE CORD
NATALIE.
I HOPE YOU CAN APPRECIATE THAT
NOW THAT SINGLE CELL DATA THAT
WAS JUST A RED CLUSTER VERSUS
GREEN CLUSTER NOW IS A SPATIAL
LOCALIZATION THAT LOOKS VERY
SIMILAR TO THE CYTOARCHITECTURE
UNDERNEATH.
SO THIS IS REAL DATA FROM MY LAB
WHERE WE TOOK HUMAN DEVELOPING
BRAIN WITH THE QUESTION, RIGHT?
BACK TO THAT IDEA THAT IT REALLY
IS KIND OF WHERE AND WHEN YOU
ARE IN TIME AND PLACE OF WHEN
THESE TRANSCRIPTION FACTORS GET
TURNED ON THAT REALLY START TO
MAKE YOUR BRAIN CONNECT AND DO
DIFFERENT PROBLEM-SOLVING
METHODS.
SO WHICH WE ARE, THIS IS GUILTY,
SO HERE IS OUR SINGLE NUCLEI
DATA, WE'VE DONE ATAC ON THIS,
MUSHED UP THAT BRAIN, TAKEN FOUR
PIECES, ALL OF THEM DIERCHT
FUNCTIONS, PREFRONTAL --
DIFFERENT FUNCTIONS, PREFRONTAL
CORTEX, THALAMUS, OCCIPITAL, WE
TAKE THESE AND WE MAP THEM.
SO YOU CAN SEE LIKE I
FUNDAMENTALLY CALL THESE GLUE
N4, IT'S SO ARBITRARY, WE'RE ALL
DOING T I'M SUPER-GUILTY OF IT,
BUT LOOK AT GLUE N4 RIGHT HERE,
IT IS JUST THESE CELLS.
SO IF YOU KNOW ANYTHING ABOUT
THE BRAIN, THIS IS THE NEURAL
PROGENITOR POPULATION.
FROM THE YELLOW TO THIS KIND OF
DARK GREEN IT'S CALLED THE SUB
VENTRICULAR ZONE, WHERE ALL
NEURONS ARE BORN, THEY BEGIN TO
DIFFERENTIATED IN THIS ORANGE
ZONE.
IF I WERE TO GO HERE AND LOOK AT
IT IT'S JUST A ORANGE BLOB BUT
OBVIOUSLY CONTEXT MATTERS.
SO IN THIS PINK DOT THOSE ARE
PARASITES, THIS IS WHERE
VASCULATURE IS STARTING TO FORM.
SO EVEN THOUGH WE HAVE THINGS
HERE, IT'S ACTUALLY CONTEXT OF
KIND OF WHERE THEY'RE
INTERLAYING.
DOES IT MATTER?
YES, IT DOES.
IN THAT SUB VENTRICULAR ZONE I
TOLD YOU ABOUT, IT'S THIS ZONE
RIGHT HERE, THAT ZONE IS
ACTUALLY DEFINED FROM HERE TO
HERE BUT YOU CAN SEE IN CERTAIN
NEURONAL SUBTYPES THAT WE
ACTUALLY HAVE SPATIAL RESOLUTION
THAT WE WERE NEVER ABLE TO SEE
BEFORE.
SO IT'S ONLY IN THIS LAYER.
THAT GLUE -- THIS IS NOT YET A
NEURON.
OKAY.
I CARE ABOUT JEBLGHTS, RIGHT?
I SHOWED YOU -- I CARE ABOUT
GENETIC, RIGHT?
I SHOWED YOU THIS WHOLE PROBLEM
ABOUT HAVING SHARED GENETIC, I
KNOW ALL OF US ARE REALLY BORED
ABOUT CELL ATLASSING.
HOW DO WE MOVE THAT BACK INTO
OUR HYPOTHESIS IN TERMS OF WHAT
WE THINK ABOUT IN TERM OF THIS
FIELD?
BACK TO THAT DIAGRAM.
RIGHT?
THAT DIAGRAM, GENES ASSOCIATED
WITH NEURODEVELOPMENTAL
DISORDERS.
SO WE JUST TAKE ONE BRANCH OF
THEM.
FOR SAKE OF TIME I'LL JUST WALK
YOU THROUGH ONE BRANCH.
THIS IS AUTISM.
WE TOOK THE TOP AUTISM GENES,
THEY'RE ALL SHOWN HERE, THEY'RE
ALL MAPPED HERE, AND THEN WE
LOOKED AT OUR SPATIAL DATA.
IN OUR SPATIAL DATA WE ACTUALLY
SEE, SO REMEMBER BACK TO THIS
PICTURE, RIGHT?
THIS PICTURE, THIS IS ALL SINGLE
CELL ANALYSIS.
EACH LAYER DIFFERENT PROPORTIONS
OF CELLS.
SO IN THIS LAYER, WE HAVE HIGH
LEVEL NEURAL PROGENITOR CELLS.
WHEN YOU LOOK AT THOSE
NEURODEVELOPMENTAL DISORDERS,
NOTHING IS REALLY GOING ON IN
EARLY DEVELOPMENTAL TIME.
WHAT REALLY STARTS TO HAPPEN IS
WE START TO GET ENRICH MENTD AND
INTERPLAY OF -- ENRICHMENT AND
INTERPLAY OF THESE CELL TYPES AS
THESE NEURONS HERE ARE STARTING
TO DIVIDE.
NOW WE HAVE ACTUAL CONTEXT TO
THE CELL TYPES THAT WE
DISCOVERED IN SINGLE CELL DATA
OF WHERE THEY COULD ACTUALLY
START TO CAUSE DISEASE.
SO I WILL WALK YOU THROUGH REAL
LIFE.
THIS IS A REAL LIFE EXAMPLE OF
HOW I'VE DONE DATA VERY
INCORRECTLY.
PLEASE LEARN FROM A LOT OF
WASTED MONEY, NOT WASTED, IT
WILL STILL GO IN THE PAPER.
SORMING BACK TO THAT DIAGRAM
WHERE I SHOWED -- SO REMEMBERING
BACK TO THAT DIAGRAM WHERE I
SHOWED YOU HERE SYNDROMIC GENES,
ONE OF THOSE IF YOU HIT IT VERY
HARD AND YOU HAVE A MUTATION IN
AN AXON YOU CAN ACTUALLY CAUSE
THIS PHENOTYPE CALLED TCF4 HAS A
VERY IF PHENOTYPICAL PHENOTYPE
WHERE THEY'RE DEVELOPMENTALLY
DELAYED, IT'S ALSO IN GWAS AND
ALSO COME UP IN AUTISM.
EARLIER IT WAS THOUGHT TO BE
JUST A SYNDROMIC GENE, NOW THAT
WE HAVE MORE CASES AND CONTROLS
WE CAN START TO AUGMENT IT.
THERE'S EVEN MICE MODELS NOW,
WHERE YOU MAKE A MUTANT AND HAVE
PHENOTYPES HA CORRELATE REALLY
WELL.
INCLUDING HYPERVENTILATION.
THIS IS COOL.
GOES BACK TO THE IDEA THAT
SPATIAL MATTERS.
RIGHT?
WE CAN FIND A BRAIN PATTERN BUT
WHAT IS THE SAME GENE DOING IN
SOMETHING RESPIRATORY.
STAY TUNED.
THAT'S ANOTHER TALK.
BACK TO BULK DATA, PARASITE,
THINGS WE'VE DONE RIGHT AND
THINGS WE'VE DONE WRONG.
WE'VE ALWAYS KNOWN IN THE FIELD
TCF4 IN THE FIELD IT'S A
TRANSCRIPTION FACTOR.
YOU TAKE IT OUT, CAUSE A SEVERE
PHENOTYPE.
S A LITTLE BIT OVER TIME MAYBE
YOU GET AUTISM.
IN BULK DATA WE CAN SEE SOX9
OVER DEVELOPMENT OF TIME HAS
THIS BUSM ANTI-REGULATION TO
EACH OTHER -- BEAUTIFUL
ANTI-REGULATION TO EACH OTHER.
WHAT DOES THAT LOOK LIKE IN
SINGLE CELL 1234R BACK TO THAT
PLOT I SHOWED YOU BEFORE, LOTS
OF MONEY, MASTER TRANSCRIPTION
FACTOR.
SOX9 MIGHT BE IN THIS, BUT IT
WASN'T ENOUGH TO DEFINE THE CELL
TYPE WE CAN'T SAY ANYTHING ABOUT
IT.
BETTER YET WE WOULDN'T HAVE
FOUND IT, RIGHT?
HERE WE FOUND IT IN BULK DATA
WHERE THERE'S A STRIATION
PATTERN.
HERE THERE'S NO RECIPROCITY.
BUT WHEN WE LOOK SPATIALLY AND I
DIDN'T PUT THE STATISTICS IN BUT
THERE IS STATISTICS TO SHOW THAT
EVERY PLACE TCF4 MASTER
TRANSCRIPTION FACTOR IT'S ON
EVERYWHERE, EVERYWHERE TCF4 IS,
SOX9 IS OFF AND VICE VERSA.
SO WHEN IT HITS THE OUTER
CORTEX, TCF4 GOES OFF BUT GOES
SUPER HIGH IN NEURONS THAT SOX9
IS NOT PRESENT IN.
FOR THE SAKE OF TIME I WOULD
WALK YOU THROUGH KIND OF OUR
CASE STUDY ALZHEIMER'S, THIS IS
BACK TO KIND OF THE IDEA THAT IT
GOES ALONG ALL DISEASE.
IC EVERYBODY WANTS TO BE IN THE
NEWEST TECHNOLOGY AND I WILL SAY
EVEN OLDER TECHNOLOGIES WORK SO
THIS IS THE IDEA BACK TO VISIUM
THAT YOU CAN TAKE EXISTING
DATASETS OF SINGLE CELL, WE DID
ESSENTIALLY THE SAME IDEA, SO
TAKING TEMPORAL LOBE WHERE WE
KNOW ALZHEIMER'S IS MOST
AFFECTED, HAVE SINGLE CELL DATA,
SO EVEN IN OLDER CLASSIC VISIUM
WE CAN SEE DIFFERENCES BETWEEN
CONTROL AND AUTISM, AND REALLY
LOOKING AT THOSE WE SEE ACTUALLY
LAYER SPECIFIC DIFFERENCE.
SO THE DIFFERENCES ARE NOT
COMING BACK FROM MUSHING UP A
BRAIN AND FINDING A SINGLE CELL
PHENOTYPE.
WE ACTUALLY SEE DIFFERENCES IN
THESE GENES BASED ON WHETHER
THEY'RE IN WHITE MATTER SO THOSE
ARE MAINLY GLIAL CELLS AND IF
THEY'RE IN NEURONS WE ACTUALLY
HAVE THESE KIND OF SPATIAL
PATTERNS TO ETCH AFTER THESE
GEERNZ TO DEFINE THESE LAYERS.
-- GENES TO DEFINE THESE LAYERS.
LAYERS MATTER.
SO BACK TO THE IDEA THAT IT
DOESN'T ALWAYS HAVE TO BE BIG
MULTIOMIC DATA, HOW DO YOU
REFINE IT AND GET INTO A SPACE
AND PLACE WHERE LABORATORIES CAN
USE THIS MOVING FORWARD?
SO NOW THAT WE'VE USED KIND OF
HIGH LEVEL VISIUM DATA WE CAN
TAKE THOSE INTO LARGER DATASETS,
DO MOUSE MODELS AND DO THOSE
KIND OF DHINGZ AND REALLY
ESTABLISH -- THINGS AND REALLY
ESTABLISH IT WAS AN ASTROCYTE
PHENOTYPE WE SAW IN THE
DIFFERENCE BETWEEN CONTROL IN
ALZHEIMER'S NOW WE HAVE A
MARKER.
SO FROM USING VISIUM WE NOW HAVE
A MARKER TO SHOW THOSE ASTRO
SIETSZ, SEE THOSE WHITE ONES ARE
ACTUALLY INFORMULA ITED IN
ALZHEIMER'S COMPARED TO CONTROL
AND WE HAVE A LOCALIZATION FOR
THEM.
WE WOULDN'T HAVE BEEN ABLE TO
DISCOVER THAT AND KNOW THIS GENE
HAD WE NOT DONE KIND OF WHOLE
TRANSMIT TOMORROW.
SO -- TRANSCRIPTOME.
THAT'S FIRST HERE, KNOWING THERE
ARE SOME CANCER PEOPLE, I'M NOT
GOING TO TALK PEDIATRIC CANCER
THIS TALK BUT MAYBE WHEN I COME
BACK.
BUT I'M SHOWING THIS VERY
PARTICULAR EXAMPLE BECAUSE THE
NUANCES DID NOT COME OUT IN ANY
OF THE APROCHES THAT WE EXISTED
TODAY -- APPROACHES THAT WE
EXISTED TODAY.
ONE OF THE IDEAS IN OUR GROUP IS
BACK TO CELLS OF ORIGIN, SOME OF
THE CELLS OF ORIGIN THAT WE'RE
INTERESTED IN ACTUALLY ARE TO
ADDRESS HEALTH DISPARITIES.
SO THE CASE STUDY FOR THIS IS
THAT THIS IS ONE GRAPH THAT
KEEPS ME UP LATE AT NIGHT, AND
I'M GUILTY OF IT.
I THINK DR. ELLIS KNOWS THAT I
PARTICIPATE IN A LOT OF GWAS
CHARACTERIZATIONS, SO GENOMICS
HAS HAD THIS 81% EXPLOSION, THIS
IS PUBLISHED IN THE END OF '22,
I'M HAPPY TO HAVE PARTICIPATED
IN THAT.
BUT 86% OF THIS EXPLOSION HAS
BEEN IN CAUCASIAN OR EUROPEAN
ANCESTRY.
SO YOU CAN SEE THAT WE'VE HAD
THIS HUGE EXPLOSION SINCE 2016,
BUT THE RED IS REALLY DEMARKED
BY EUROPEAN AND WE'RE MISSING
ALL OF THESE.
SO BEING A GENETICIST, YOU KNOW,
WE HAVE THIS DISPARITY AND WE
ARE AT NIH AND NCI AND I KNOW
THIS HAS BEEN A BIG MISSION FOR
THE NEXT KIND OF STRATEGIC PLANS
IS TO REALLY INCORPORATE THE
IDEA OF HOW ARE THESE -- HOW ARE
THESE ANCESTRIES ACTUALLY
AFFECTED HOW PATHOGENICITY COMES
IN CANCER AND HOW THESE DISEASES
ARE AFFECTED IN TERMS OF
PREVALENCE, IMMUNOTHERAPIES, ET
CETERA.
I'VE BEEN LUCKY ENOUGH TO ACTUAL
GET FUNDING IN THIS, SO WE
CONTRIBUTE IN THE SINGLE CELL
AFRICAN CARIBBEAN NETWORK.
THE IDEA IS THAT THERE'S A
DIFFERENT RATE OF CANCER IN ALL
OF THESE BUT THAT REALLY
PROFILING KIND OF THE CELLS OF
ORIGIN TO THESE DISEASES SO IN
THE CASE OF OVARIAN CANCER IT'S
ACTUALLY NOT THE OVARY, IT'S THE
FALLOPIAN TUBE THAT IS THE CELL
OF ORIGIN.
PROSTATE CANCER AND BREAST
REALLY GETTING AN UNDERSTANDING
OF KIND OF HOW THESE DIFFERENT
POPULATIONS, HOW THEIR CELLS OF
ORIGIN LOOK LIKE IN ORDER TO
REALLY APPLY THEM TO HOW THOSE
DISEASES ARISE.
SO THIS IS A SLIDE THAT I
PURPOSELY PUT HERE BECAUSE I
KNOW A LOT OF PEOPLE HERE ARE
INTERESTED IN DOING SINGLE CELL
AND IT'S NOT JUST A SPATIAL
TALK.
SO THIS CAME FROM REAL LIFE.
I'M NOT A METHOD ON GIST, BUT
BECAUSE YOU CAN IMAGINE, WE HAVE
FUNDING TO DO THIS IN AFRICA,
WE'VE BOUGHT -- WE CAN DO IT
WELL, WE ARE LEADERS IN THE
FIELD OF NUCLEI PREP BUT I'LL BE
REALLY HONEST, YOU STILL HAVE TO
GO THROUGH CUSTOMS AND THE
MINUTE THERE'S A STICKER THAT
HAS BIOHAZARD ON IT, THERE'S AN
INCREASED PRICE IN AFRICA.
SO I APPROACHED ONE OF MY
COLLEAGUES AND SAID LIKE WE CAN
DO THE FIX AND CUT, THAT'S A 10X
PROTOCOL THEY'VE BORROWED FROM
US, AND COULD WE DO IT IN FFP?
THE IDEA OF THIS WAS REALLY TO
TAKE FFP BLOCKS AND MAKE SINGLE
CELL AVAILABLE ACROSS OUR
REPOSITORIES.
SO I'LL WALK YOU THROUGH, WE'VE
DONE A LOT OF DIFFERENT BREAST
TYPE, A LOT OF DIFFERENT TISSUE
TYPES, WE'VE DONE BOTH NUCLEI
PREP BOTH SNAP FROZEN AND FFP,
THIS IS UNDER REVIEW BUT 10X HAS
OUR PROTOCOL SO THAT'S OUR MAIN
CREDITCISM IS THAT IT'S ALREADY
PUBLISHED.
THIS IS WORK WITH DOCTORS IN
AUSTRALIA.
WE TOOK THE SAME BREAST CANCER
AND TOOK A METASTASIS AND TOOK
BREAST CANCER AND MUSHED IT UP
LIKE EVERYBODY DOES AND THE DATA
LOOKS BEAUTIFUL SO WE CAN FIND
ALL THE SAME CELL TYPES THAT YOU
CAN FIND IN FRESH FROZEN IN OUR
FFP METHOD.
SO THAT MAP EVERYBODY KIND OF
KNOWS MAPS LIKE THIS WHERE WE
CAN SEE EVERY CELL TYPE.
WE CAN ACTUALLY -- WE ACTUALLY
HAVE HIGHER FIBROBLAST CONTENT
ACTUALLY IN THE FFP THAN IN THE
FRESH FROZEN.
BUT I GO BACK TO THIS MAP.
SO THIS IS WHAT WE'RE ABLE TO DO
IN FRESH FROZEN OR FFP, WE CAN
DO IT IN NUCLEI, BUT LOOK AT
WHAT THAT MAP ACTUALLY LOOKS
LIKE IN THE TISSUE.
THIS IS AN -- THIS ISN'T EVEN
VISIUM HD.
THIS IS JUST US TAKING SINGLE
CELL MUCH LIKE I SHOWED YOU IN
THE BRAIN BUT NOW DIRECTLY INTO
TUMORS.
I HOPE YOU CAN APPRECIATE THAT
THIS LOOKS VERY DIFFERENT THAN
THIS.
WHILE THIS TUMOR IS METASTATIC
AND THIS IS NOT, THIS IS
PRIMARY, YOU CAN SEE THAT THE
INFILTRATION OF THE SINGLE CELL
DATA IS VERY DIFFERENT ONCE IT'S
BECOME METASTATIC TUMOR.
WE ARE NOT RESOLVING THAT.
IN THE SINGLE CELL DATA ALL
WE'RE RESOLVING IS CELL
PROPORTIONS THAT ARE CELL PRO
POURINGS OF THESE CELL TYPES
HAVE CHANGED BETWEEN PRIMARY AND
METASTASIS BUT WE HAVEN'T
ACTUALLY LOOKED AT HOW THOSE
NEIGHBORHOODS ACTUALLY LOOK
DIFFERENT.
AND THE INFLUENCES OF THE
MICROENVIRONMENT FROM PRIMARY TO
METASTATIC.
SO I'M WALKING YOU THROUGH HOW
WE KIND OF GOT THE METHODOLOGIES
UP AND RUNNING, HOW THAT WOULD
BE AVAILABLE TO YOU TO THINK
ABOUT KIND OF THE REPOSITORIES
THAT YOU'RE ABLE TO HAVE AT NIH
TO REALLY START TO PLOW THROUGH
THAT DATA NOW THAT YOU DON'T
HAVE TO COLLECT IT FRESH.
BUT HOW DID WE GO BACK TO THAT
ORIGINAL QUESTION OF WHY WE
DEVELOPED THAT ME ODDOLOGY?
SO THE METHODOLOGY REALLY ARISE
FROM THIS QUESTION, BACK TO THAT
THING THAT LEAVES ME AWAKE AT
NIGHT IS THIS IS DATA FROM KIND
OF OUR GROUP WHERE WE LOOKED
ACROSS KIND OF THOSE THREE
POPULATIONS, RIGHT?
SO AFRICAN ANCESTRY BEING IN THE
U.S., AFRICAN ANCESTRY BEING IN
CARIBBEAN AND AFRICAN ANCESTRY
BEING IN AFRICA.
SO IT WAS REALLY HARD ESPECIALLY
FROM NIH TO GET FUNDING BECAUSE
WHENEVER WE COMPARED THE U.S.
POPULATION TO THE AFRICAN
POPULATION, IT REALLY BECAME
ABOUT -- AND TRUE TO THEIR POINT
IS THAT IT'S A MORE AGGRESSIVE
DISEASE.
SO WHILE WE HAVE A HIGH
INCIDENCE HERE, WE'RE VEG AT
CURING IT IN THE U.S., THAT'S
THE BLUE, BUT IN AFRICA, THEY
DON'T REALLY HAVE A HIGH
INCIDENCE BUT YOU DIE.
IT'S VERY VERY AGGRESSIVEMENT
THAT COULD BE KIND OF THEY COME
AT LATE STAGE, AGE MATCH, STAGE
MATCH THE BEST WE COULD.
WE COULDN'T ALWAYS TREATMENT
MATCH.
BUT IT WAS WHEN WE ADDED, WHAT
CHANGED THE GAME FOR US AND
PROBABLY CHANGED THE GAME FOR
FUNDING IS WHEN WE ADDED AFRICAN
CARIBBEAN.
REMEMBER AFRICAN CARIBBEAN CAN
BE MAN TORD IN TERMS OF ANCESTRY
BASED ON WHEN SLAVE SHIPS CAME.
THEY HAVE ASIAN, THEY HAVE
HISPANIC AND WHAT'S SURPRISING
TO US IS IN THE AFRICAN
CARIBBEAN NOT ONLY DO THEY HAVE
HIGH INCIDENCE, THEY HAVE A
HIGH MORTALITY.
THAT GETS AT THE IDEA THAT
CRAPPY HOSPITALS, CRAPPY ACCESS
TO CARE, IT'S KIND OF EQUIVOCAL
ACROSS AFRICA AND CARIBBEAN BUT
IT'S LITERALLY THEIR ANCESTRY
THAT IS MOVING THE NEEDLE
FORWARD.
WE SEE THAT IN OVARY AND
PROSTATE BUT IN DIFFERENT
DIRECTIONS.
ACTUALLY INTERESTING, WE GET
DIFFERENT SUBTYPES.
SO OVARIAN WE GET WEIRD SUBTYPES
THAT WE DON'T SEE IN THE U.S.
SO BACK TO THE IDEA OF
INFRASTRUCTURE AND CAPACITY
BUILDING.
WE DIDN'T START AS TUMOR PEOPLE
BUT BECAUSE WE BUILT THE
INFRASTRUCTURE THERE TO DO
SINGLE CELL, WE HAVE KIND OF THE
INFRASTRUCTURE TO MOVE IT
FORWARD INTO TUMORS, SO THIS IS
LED BY THE SAME GROUP,
DR. GEORGE OUT OF MIAMI AND WE
TAKE THOSE 32 SITES, DO THE
SURGICAL RESECTIONS THERE, WE
TRY AND MATCH SO WE'RE TRYING TO
BRING THEM UP INTO KIND OF U.S.
STANDARDS OF COLLECTING CLINICAL
INFORMATION AND ACTUALLY THE
HARDEST PART IS MERGING THE
METADATA BECAUSE THEY ARE STILL
IN PAPER SOMETIMES, THEY DON'T
EVEN HAVE RECORDED NOTES.
SO WE KIND OF DO THAT BOTH HERE
AND THERE AND TRY AND MERGE IT
AS BEST AS POSSIBLE.
WE COLLECT AND TRY TO DO TISSUE
PROCESSING AS MUCH AS POSSIBLE
THERE BECAUSE WE'RE TRYING TO
MAKE SURE THAT THEY KIND OF CAN
KEEP THE BALL ROLLING AND GIVE
THEM NEW INFRASTRUCTURE, BUT
UNFORTUNATELY THIS IS WHERE THE
BIFURCATION HAPPENS, SO THAT
MOST OF THE DATA ACQUISITION IS
BEING -- AND PROCESSING IS BEING
DONE IN THE U.S.
I THINK WE ALL KNOW THAT FOR
KIND OF CAVEATS OF THE PRICING
AND HOW MANY TOOLS ARE REQUIRED.
BUT WE'RE ALSO TRYING TO USE
PATHOLOGY ACROSS SITES BECAUSE
CANYON -- BECAUSE A CANADIAN
PATHOLOGIST CALLS CANCER
DIFFERENT THAN U.S. AND WE'VE
MERGED THAT AND MADE 966
ANTIBODY TRIPLE NEGATIVE BREAST
CANCER WITH ACOYA, I WAS LUCKY
NUF TO HELP DESIGN T PART OF
THEIR DISCOVERY PANEL, THAT
WOULD BE AVAILABLE TO YOU GUYS
HERE WHO HAVE CODEX AND
OBVIOUSLY A LOT OF THEM ARE
BREAST SPECIFIC, CAWNTD HAVE A
TRIPLE NEGATIVE BREAST CANCER
PANEL UNLESS YOU INCLUDE THINGS
LIKE ER HER 2 AND PR AND THEN
TRYING TO GIVE ADDITIONAL
STRUCTURE MARKERS AND METABOLIC
MARKERS WE THINK MIGHT BE
IMPORTANT TO CELL TYPING.
OH AND JUST TO RUN THROUGH VERY
BASICALLY WHAT THAT IS, SO
REMEMBERING THAT TRANSCRIPTOMICS
TENDS TO BE USING HIJACKING THE
SINGLE CELL WHERE HE WITH PUT A
UMI ON IT AND WE CAN KIND OF
PLEX LOTS OF THINGS.
IN THE CASE OF ANTIBODIES WE'RE
TAKING THE SAME APPROACH.
IN PROTEIN WE'RE TAKING THE SAME
APPROACH, TAKING EMI'S INSTEAD
OF RNA PROBE SET, HIJACKING IT
AND PUTTING IT ONTO ANTIBODY,
YOU CAN DO IN-HOUSE CONJUGATION
WHICH IS WHAT 80% OF MY PANEL S
WE TAKE THOSE AND IT'S NOT SUPER
FANCY ALTHOUGH THE MACHINE
PROBABLY COSTS A LOT SU JUST
CYCLE IT.
YOU PUT ON FOUR OR FIVE AT A
TIME AND IT CAN ALLOW YOU,
THERE'S OVER REPORTS OF OVER 100
NOW OF PLEXING.
YOU CAN IMAGINE WITH 100
ANTIBODIES OR 66, YOU CAN GET TO
A SIMILAR LEVEL, NOT QUIF CAL
LEVEL OF -- NOT EQUIVOCAL LEVEL
OF BEING ABLE TO CELL ANNOTATE
YOUR DATA.
I LOVE TO SHOW, I MUSHED THESE
UP FOR A VERY LONG TIME.
THOSE DHEENT KNOW CANCER
ASSOCIATED FIBROBLAST ARE
THOUGHT TO HELP TO CONTRIBUTE TO
AGGRESSION OF DISEASE.
IT'S LITERALLY ONE TO FIVE
PERCENT OF ALL SINGLE CELL
DATASETS BECAUSE FIBROBLAST
DON'T LIKE TO GO MANY A DROPLET
SYSTEM.
THE THINGS IN YELLOW ARE VERY,
VERY, VERY DIFFERENT.
THEY'RE LITERALLY LOOK AT THESE
GUYS OVER HERE THAT ARE
LITERALLY INFILTRATED BY
VASCULATURE.
RIGHT?
THEY'RE ALMOST FULLY SURROUNDED
AND THEY HAVE DIFFERENT IMMUNE
CELL COMPONENTS COMPARED TO THE
ONES OVER HERE.
SO EVEN IN CALF DATA, THEY HAVE
DIFFERENT COMPONENTS WITHIN THE
TUMOR.
SO MUSHING IT UP AND JUST
CALLING -- YOU'RE NOT EVEN ABLE
TO REALLY CALL EVEN THE YELLOW
BECAUSE THEY'RE SO LOW
EXPRESSING, BUT EVEN CALLING IT
THAT HAS NO CONTEXT TO WHAT
THEIR ACTIVITY COULD BE.
SO HOW DO YOU DO THIS?
IT'S GOING TO BE THE LAST PART
OF THE TALK TO THINK ABOUT HOW
YOU COMPUTATIONALLY DO THIS.
SO SING -- SO SINGLE CELL --
SINGLE CELL MIGHT BE ONE HURDLE
TO OVERCOME.
I WOULD SAY PROTEIN AND IMAGING
BASE IS ANOTHER HURDLE.
WE TAKE A VERY SINGLE CELL
APPROACH TO THIS.
YOU IMAGINE WE KIND OF CODE ALL
THE CELLS AND THEN EVERY CELL
BECOMES KIND OF A CIRCLE AND IN
THAT CIRCLE SO THIS IS MIR SCOPE
DATA, IMAGINING THIS CAN CROTION
OVER AND I WANTED TO SHOW YOU
THAT, THAT THESE ARE REALLY
ROBUST SYSTEMS IN THE SENSE THAT
THESE ARE NOT -- THESE ARE
PROCESSED IN UNDERDEVELOPED
COUNTRIES AND YOU CAN IMAGINE AT
THAT OUR TUMORS DON'T LOOK
AMAZING.
SO YOU CAN STILL KIND OF GET RNA
DATA OUT OF IT.
BUT WHAT WE DO IS WE ASSIGN
EVERY GENE, SO IF YOU'RE A GENE
HERE THAT LIVES IN THIS CELL,
EVERY TIME WE SEE THAT GENE IN
THAT CELL YOU BECOME KIND OF A
COUNT, VERY SIMILAR TO SINGLE
CELL DATA.
AND WHAT DOES THIS LOOK LIKE?
THIS IS ACTUALLY OUT OF DATE NOW
BUT WE'RE AT 8 MILLION CELLS.
SO IN MY ONE LITTLE STUDY WE
HAVE 8 MILLION CELLS AND
COUNTING.
IN THE HUMAN CELL ATLAS WAS
PUBLISHED IN MAY 2022 AND IT HAD
1 MILLION CELLS.
THIS BEAUTIFUL ATLAS WHICH WAS
THE SECOND BIGGEST AT LAS TO
PUBLISH WAS LAST YEAR IN 2023
WITH 2.4 AND YOU CAN IMAGINE
JUST IN THAT DATASET FROM MY
SMALL DATASET IS 8 MILLION AND
YOU CAN SEE KIND OF YOU DON'T
GET EVERY CELL TYPE BUT IF YOU
CHOOSE THE RIGHT MARKERS YOU CAN
KIND OF GET ALL THE SIMILAR CELL
TYPES, YOU USE YOUR SINGLE CELL
DATA TO KIND OF INFORM WHAT
MARKERS YOU WANT TO DO.
AND THIS IS REALLY WHAT I'M
PROUD ABOUT.
SO WE'RE ACTIVELY DOING THIS
THROUGH CLINICAL TRIALS.
I SPENT PRETTY MUCH EIGHT MONTHS
TRYING TO MAKE SURE THAT WE
COULD DO BIOPSIES AND MAKE
BIOPSIES DON'T ALWAYS LIKE TO
SIT ON A -- THEY DON'T HAVE A
LOT OF SURFACE AREA AND TENSION
ON THESE SLIDES, SO WE SPEND A
LOT OF TIME TRYING TO MAKE SURE
WE COULD DO BIOPSIES SO WE COULD
DO ACTIVE CLAIN CAL TRIALS.
-- CLINICAL TRIALS.
IN THE U.S., BLACK WOMEN, MORE
AGGRESSIVE DISEASE THAN WHITE
WOMEN.
EPITHELIAL CELLS RELATIVE TO
STROMA, YOU CAN SEE THAT
COMPOSITION IS COMPLETELY
DIFFERENT.
SO REMEMBERING WHEN I MUSHED
THIS UP, I WOULD BE ABLE TO SAY
WELL THERE'S PROBABLY MORE E CAD
HERE ENS CELL -- E-CADHERENCE,
BUT THEY HAVE DIFFERENT TUMORS,
THIS IS MORE AGGRESSIVEMENT
THESE HAVE MORE TUMOR CELLS BUT
THIS IS MORE AGGRESSIVE.
BUT YOU CAN STILL DO THE SAME
THINGS YOU DID WITH SINGLE CELL,
FIND ENDOTHELIAL CELL MARKERS,
MILE NOID MARKERS AND EVEN IN
EPITHELIAL CELLS I CAN ADD
ANOTHER MARKER AND FIND WHICH
CELLS ARE TUMOR VERSUS NORMAL.
WHAT I THINK IS MOST CONVINCING
IS THE IDEA OF THIS
NEIGHBORHOOD.
SO THESE ARE KIND OF THE
NEIGHBORHOODS.
I HATE THIS LITERALLY, SO IN
THIS NEIGHBORHOOD MAYBE IT'S A
BLUE NEIGHBORHOOD WHERE THERE'S
EPITHELIAL CELLS SURROUNDED BY
MACROPHAGES.
THIS IS KIND OF THE SWITCH IN
YOUR BRAIN THAT YOU HAVE TO
THINK ABOUT IN TERMS OF KIND OF
WHAT SINGLE CELL DATA TELLS US
AND WHAT SPATIAL DATA TELLS US,
BECAUSE GOING BACK TO THIS,
RIGHT, GOING BACK TO THIS -- OH,
I WENT THE WRONG WAY.
WE KNOW WHAT THEIR CELL
COMPOSITION IS.
WE KNOW.
THEY COULD BE ECADHERENT CELLS
BUT WHO DO THEY TALK TO AND WHY
DO THEY LOOK DIFFERENT?
REMEMBERING THE IDEA THAT U.S.
BLACK WOMEN LOOK VERY DIFFERENT
THAN CARIBBEAN BLACK IT'S
ACTUALLY THE CELL NEIGHBORHOOD
COMPOSITION THAT WHO THOSE CELLS
ARE AROUND, ARE THEIR
MACROPHAGES AROUND THEM, ARE
THERE DON'T EAT ME MACROPHAGES
THAT ARE PROTECTING THE TUMOR
CELLS?
THAT'S REALLY WHERE THE OUTCOMES
ARE CHANGE.
SO YOU CAN SEE HERE THEY HAVE
DIFFERENT COMPOSITIONS OF WHAT
THOSE NEIGHBORHOODS ARE.
NOO ACTUALITY, THERE ARE
NEIGHBORHOODS THAT EXIST IN ONE
AND NOT THE OTHER.
SO HOW CAN WE DO BETTER?
AGAIN, BACK TO THE IDEA THAT I
SAID THE LAST PART OF THE TALK
IS GOING TO BE HOW DIFFICULT
COMPUTATIONAL ANALYSIS IS ON
THIS.
BUT I SAID DON'T FEAR, WE'LL GET
THERE.
THE IDEA AND EVEN FOR ME MY LAB
DOES MACHINE LEARNING AND AI AND
I NEVER WOULD HAVE THOUGHT THAT
TO BE THE CASE.
BUT CAN WE DO BETTER?
I THINK WE CAN AGO NOS CLI LEARN
FROM -- AGO NOSSICLY LEARN FROM
THIS.
I'M VERY SIMPLISTIC IN HOW I
THINK ABOUT MACHINE LEARNING AND
A I.
I SAID TO ONE OF MY COMPUTER
SCIENTISTS ABOUT IMPROVING
BACKGROUND AND SIGNAL TO NOISE
IN ONE OF OUR PICTURES AND SAID
LISTEN I CAN OPEN UP MY PHONE
WITH MY FACE, IT JUST NEEDED
MORE AND MORE IMAGES TO LEARN
THAT.
WE WEREN'T THERE YET.
BUT IMAGINE WHAT WE COULD DO
WITH SPATIAL DATA THAT WE
COULDN'T DO WITH SINGLE CELL OR
BULK DATA BECAUSE WHAT WE'RE
VERY GOOD WITH AI AND ML IS
LANGUAGE MODELS AND SPATIAL
RECOGNITION.
WE TIED A SMALL APPROACH WITH
THIS.
WE TOOK MACHINE LEARNING MODEL
BUILT IN BULK RNA SEQ DATD FROM
TCGA, FOR ANYONE THAT'S IN
TUMORS YOU'LL KNOW WHY WE HAD TO
DO THAT BECAUSE MACHINE LEARNING
NEEDS LOTS AND LOTS OF DATA'S
INPUT AND WE TOOK ONE FEATURE TO
KIND OF LEARN THIS MODEL WHICH
IS A VERY BASIC CANCER BIOLOGY
PHENOTYPE WHICH IS THAT THE IDEA
OF CANCER STEMNESS, SO YOU HAVE
CANCER, YOU GO THROUGH THERAPY,
AND THAT TUMORS THAT RECUR
REVERT AND DEDIFFERENTIATE TO
MORE STEMNESS PHENOTYPE.
SO MY COLLABORATOR DR. MALTA IN
BRAZIL, IT'S A CELL PAPER, SHE
LEARNED THIS AGAINST CLINICAL
OUTCOME DATA AND IT PERFORMED
MUCH BETTER THAN METHYLATION RNA
SEQ AXOMS ALONE.
ME BEING NAIVE TO MACHINE
LEARNING I SAID WELL COULDN'T WE
USE SINGLE CELL DATA?
BECAUSE SINGLE CELL DATA HAS --
YOU COULD USE EVERY CELL LIKE
YOU USED EVERY PATIENT AND COULD
WE LEARN THE MODEL AT THAT WAY?
YOU CAN SEE WE DOWNLOAD THE
ENTIRE EVERY SINGLE CELL BREAST
CANCER DATASET AVAILABLE TO US
AND WE CALCULATED 9 MODEL.
IN THIS MODEL THE IDEA IS STILL
THE SAME WHERE YOUR HIGH STEM
YOU'RE RED, WHERE YOU'RE BLUE
YOU'RE LOW STEM SO YOU SHOULD BE
MORE QUOTE UNQUOTE NORMAL LIKE
CELLS.
YOU CAN SEE THAT OVERLAPS VERY
HIGHLY WITH THE CLINICAL SUBTYPE
SO AGNOSTIC TO WHAT YOUR CELL
TYPE IS, RIGHT?
DON'T LOOK AT THIS PICTURE, LOOK
AT THIS PICTURE.
THERE'S STEMNESS IN CERTAIN
TYPES OF CELLS AND NOT OTHER
TYPES OF CELLS, RIGHT?
SOLT CELLS WE DON'T EXPECT
STEMNESS IN THEY'RE BLUE.
THE CELLS WE EXPECT STEMNESS IN
LIKE CANCER EPITHELIAL CELLS
THEY'RE SUPER SUPER RED AND THAT
ACTUALLY OVERLAPS, REMEMBER WE
DOWNLOADED THESE DATASETS,
THEY'RE DIFFERENT CLINICAL SUB
TYPES.
WHEN WE LOOK INTO THIS STUDY SET
WHICH IS MERGED EVEN IN THE
CLINICAL SUBTYPES FOR NO ONE
THAT KNOWS BREAST CANCER TRIPLE
NEGATIVE BREAST CANCER WHICH IS
IN THE GREEN IS THE MOST
AGGRESSIVE FORM AND YOU CAN SEE
THAT THE GREEN OVERLAPS VERY
HIGHLY WITH STEMNESS.
SO ARE WE GOOD AT THIS?
I WOULD SAY YES, WE'RE PRETTY
GOOD AT IT IN SINGLE CELL, WE
CAN WE CAN GET DOWN TO WHICH
CELL TYPES, THIS CAN BE ANY
MODEL, WE'RE JUST USING STEM
RIGHT NOW, AND A VERY CLEVER
COMPUTATIONAL BIOLOGIST IN MY
LAB WHO WAS LIKE WELL SPATIAL
HAS MORE DATA, CAN WE APPLY IT
TO SPATIAL?
SO WE USE VISIUM, XE MIUM,
COSMICS, CODEX, WHATEVER, YOU
NAME T WE CAN USE, AND WE CALL
THESE CLUSTERS.
IMAGINE THAT IS SINGLE CELL
PROJECTION, THIS IS PATHOLOGY
CLASSIFICATION.
PATHOLOGIST IS MISSING ALL THE
STEMNESS.
YOU'RE CAPTURING SOME OF THE
STEPHNESS WITH EPITHELIAL CELLS
BUT NOT ALL AND SAME IN XENIUM
AND MERSCOPE, YOU HAVE A TUMOR,
THEY'RE OVERLAPPING, I SEE A CD4
SO I'LL CALL IT IMMUNE CELL.
IT'S TELLING YOU WHAT PART OF
THE TUMOR IS THE MOST AGGRESSIVE
PART.
THIS IS A BEAUTIFUL
REPRESENTATION, THIS IS JUST
CODEX DATA.
SO IF YOU DON'T THINK YOU CAN DO
MULTI-OMIC APPROACHES OR DEEP
LEARNING WITH PROTEIN DATA
YOU'RE WRONG IF YOU HAVE ENOUGH
MARKERS YOU CAN.
SO THIS IS ACTUALLY NORMAL
TISSUE ALL UP IN HERE.
IF YOU LOOK, THERE'S NO
STEMNESS, IT'S ALL BLUE.
BUT WHAT YOU SEE HERE IS THAT IN
THE TUMOR, AT THE TUMOR
INTERFACE, WE GET REALLY HIGH
STEM, AND THEN IN CERTAIN
POCKETS THAT ARE KIND OF
DRIPPING OUT WE GET CERTAIN STEM
TOO.
BUT THESE ARE ALL INTERMIXED
CELL ANNOTATIONS, RIGHT?
THEY'RE NOT THAT AN EPITHELIAL
CELL IS AN EPITHELIAL CELL BY
IT'S.
DOES IT WORK BACK TO THOSE
BEAUTIFUL BIOPSY SNS SO
REMEMBERING I HAD ALL THESE CELL
ANNOTATIONS, I SHOWED YOU COOL
NEIGHBORHOODS, THERE'S DIFFERENT
PARTS OF IT, WHICH YOU CAN KIND
OF SEE HERE.
BUT REMEMBER CARIBBEAN BLACK
WOMEN ARE VERY DIFFERENT THAN
U.S. BLACK IN THEIR OUTCOME, AND
REMEMBERING THEY HAD KIND OF
MORE EPITHELIAL CELLS ON THIS
SIDE VERSUS THIS SIDE.
BUT LOOK AT THE STEMNESS.
THERE'S NOT AS MANY POCKETS OF
RED.
WHILE THERE'S NOT A LOT OF RED,
THERE IS SOME RED HERE AND HERE,
THERE'S LOTS OF RED HOT SPOTS IN
THE BIOPSY.
THOSE ALL OVERLAP WITH CANCER
EPITHELIAL CELLS BUT AGAIN THERE
MUST BE SOME OTHER DRIVER THAT'S
BEYOND OUR CELL ANNOTATION.
AND HOW DO WE SEE TREATMENTS
REALLY BEING ALTERED?
I DIDN'T SEE THIS IN THE SINGLE
CELL DATA, AND YOU'RE GOING TO
LEAVE AND WANT TO BE A SPATIAL
OMICS PERSON LIKE ME AND I
DIDN'T WANT TO BE, IT'S VERY
EXPENSIVE, BUT LOOK AT THIS
DATA.
THIS DATA IS PART OF THE
8 MILLION CELL TYPE, IT'S TRIPLE
NEGATIVE BREAST CANCER.
THEY DON'T USUALLY EXHIBIT
PARP1, WE KIND OF IGNORE THEM.
BUT THE PARP1 CELLS ARE
LITERALLY BEING PROTECTED BY THE
MACROPHAGES, THE DON'T EAT ME
MACROPHAGES, FOR US THAT'S
ACTUALLY IMMUNOTHERAPY THINGS WE
CAN SEE IN THE DATA IFLTS THAT
ACTUALLY WILL -- ITSELF THAT
ACTUALLY WILL LINK TO
TREATMENTS.
THOSE AREN'T NEW TREATMENTS, WE
DON'T NEED TO DEVELOP NEW DRUGS,
WE JUST MIGHT BE GIVING THEM THE
WRONG DRUGS.
SO I WON'T SPEND A LOT OF TIME
ON THIS, BUT I THINK THIS IS ONE
WAY AND YOU CAN LOOK UP A PAPER
WHERE IT'S KIND OF OUR CALL TO
ARMS TO KIND OF INCREASE
ACCESSIBILITY BECAUSE WE KNOW
THAT HNE CAN BE DONE EVERYWHERE.
LIKELY WE WON'T BE ABLE TO DO
THESE CRAZY SPATIAL OMICS STUFF
THERE BUT HOPEFULLY COST OF
ASSAYS, TRAINING AND COMPUTATION
CAN BE GIVEN BACK TO THEM.
AND WHERE ARE WE?
SO WHERE ARE WE AND WHERE DO WE
THINK WE'RE HEADED?
I'M REALLY HAPPY TO BE HERE
BECAUSE I THINK YOU GUYS ARE
ALREADY ON THE PLATFORM TO
THINKING ABOUT THIS.
SO I MOVED TO ST. JUDE FOR THIS
REASON.
WE ALREADY HAVE AWFUL THESE
SPATIAL OMICS TECHNOLOGIES UP
AND RUNNING, I'M HAPPY TO HELP
COLLABORATE OR GET YOU GUYS OFF
THE GROUND BECAUSE IT'S GOING TO
NEED A LOT OF PEOPLE TO DO THIS
ALL AT ONCE.
WE'RE ALREADY DOING IT.
SO WE'RE DOING IT LIVE THROUGH
CLINICAL TRIALS, DOING TMA'S
ACROSS 43 MARKERS.
WE REALLY THINK IT'S APPLICABLE
TO OTHER ORGANISMS AND MORE
TISSUE TYPES ESPECIALLY HE
GENOMICS SO I'M REALLY -- EPI
GENOMICS SO I'M REALLY WATCHING
THE FIELD CLOSELY.
THIS IS A CALL OUT TO THE FIELD,
HOPEFULLY TO HELP YOU OUT AS WE
MOVE LOONG.
THERE'S BEEN A BIG CALL THE IN
FIELD FOR ESTABLISHING METRICS
SO LOOK OUT FOR THIS.
WE'RE TRYING TO FINISH THIS OFF
BUT WE ESSENTIALLY DID CALLED
SPATIAL TOUCHSTONE WHERE WE
DOWNLOADED EVERY PUBLIC DATASET
THAT'S BEEN IMAGED SPATIAL
TRANSCRIPTOMICS, WE OURSELVES
HAVE PROFILED MORE CELLS THAN
THEY HAVE, SO WE'VE CONDUCTED,
WE HAVE OVER 8 MILLION CELLS IN
OUR REPOSITORY AND THE ENTIRE
REPOSITORY ONLINE SO FAR
6.4 MILLION.
WE'VE DONE THE SAME TISSUE
SECTION ACROSS THREE DIFFERENT
SITES, ACROSS TWO DIFFERENT
PLATFORMS, AND WE HAVE
2.5 BILLION TRANSCRIPTS.
THIS IS FRESH OFF THE PRESS.
THIS IS THE SAME PROSTATE TUMOR
DONE ACROSS THREE SITES ACROSS
TWO PLATFORMS ACROSS DIFFERENT
CELL SEGMENTATION MARKS.
WE'RE VERY GOOD AT IT.
OBVIOUSLY THIS GETS TO THE IDEA
WHEN PEOPLE SAY WHEN YOU CUT
THROUGH THINGS WITH THE TUMOR
HETEROGENEITY, I THINK WE'LL GET
THERE, I THINK THE MORE PEOPLE
DEPOSIT DATA AND EVEN WITH THAT
QUESTION WE STILL SEE
REPRODUCIBILITY.
SO WHAT YOU CAN SEE ON THE
LEFT-HAND SIDE IS OUR DATA.
SO OUR DATA IS MORE CONSISTENT
IN TERMS OF HOW MANY TRANSCRIPTS
PER CELL WE GET ACROSS ALL OF
THEM BUT MOST IMPORTANTLY I
THINK IS THIS METRIC, IS THIS IS
THE PUBLIC DATASET WHICH IS THE
PINK WHICH IS KIND OF ALL OVER
THE MAP FOR SIGNAL TO NOISE AND
IF I'M HONEST WE HAD CRAPPY DATA
TOO, LIKE IF YOU LOOK AT THIS,
I'M NOT GOING TO TELL WHAT THE
INSTITUTE IS BUT THEY GUESSED
WHEN THEY SAW THEIRS BUT EVEN
ACROSS YOU ARE ADATD SET WE DO
VERY WELL WITH SIGNAL TO NOISE
RATIOS.
WHY AM I TELLING YOU THIS?
BECAUSE THIS ENTIRE REPOSITORY
WILL BE AVAILABLE WHERE WE'VE
DONE THREE THINGS FOR THE FIELD.
ONE IS TO DO SPATIAL TOUCHSTONE
PROTOCOLS, IT'S PROTOCOLS.IO,
IT'S RIT RESIDUALLY EVEN MY
SINGLE NEW PATHO SEQ, FFPE IS ON
IT, HOW TO STAIN EVERYTHING TO
MAKE REPRODUCIBLE DATA, WE KNOW
OUR DATASET WAS MUCH MORE
REPRODUCIBLE.
WE'VE DEPOSITED ALL OUR CURATION
AND MINING OF IT SO YOU CAN TAKE
ANYTHING THAT GOT DERIVED OFF A
MACHINE HERE AND EITHER RUN IT
LOCALLY, WE'VE PACKAGED THIS OUT
AS OUR OWN SOFTWARE.
THE NICE PARTED ABOUT OUR
SOFTWARE IS YOU CAN CALCULATE
ALL OUR METRICS AND ALSO TAKE
ALL YOUR SINGLE CELL DATA WITH
ALL YOUR ANNOTATIONS AND PUT IT
DIRECTLY ON YOUR IMAGING BASE
DATA THROUGH THE PORTAL WHICH I
THINK MOST PEOPLE IN THIS ROOM
WILL WANT TO USE TAKE EVERYTHING
THAT COMES OFF THE MACHINE, PUT
IT IN OUR PORTAL, I JUST TO WANT
SEE WHERE MY EXAMPLE IS, SO THIS
IS YOUR RED LINE.
ARE YOU ON THE RED LINE?
IS IT A GOOD RED?
IF YOU'RE BREAST, WHAT DOES
BREAST LIKE?
IF WE PROFILE PROSTATE AND YOU
DID PROSTATE, HOW MANY
TRANSCRIPTS OR CELLS SHOULD I
THINK ABOUT?
SO YOU'RE ABLE TO KIND OF DO
THAT.
SO THAT'S COMING OUT SOON.
LET BY GESTALT, SO IF YOU HAVE
ANY QUESTIONS ABOUT SPATIAL,
THIS IS KIND OF A HOME-GROWN
VERY FRUSTRATED CENTER FOR
SPATIAL PEOPLE REALLY STARTING.
THIS IS WHAT I LOOKED LIKE
BEFORE SPATIAL.
I HAD NO NECK.
I GREW A NECK LATER.
BUT YEAH, I GREW A NECK BECAUSE
THERE'S BOTTLENECKS, SEE?
BUT REALLY, I ENCOURAGE ALL OF
YOU TO COME, LTS A MONTHLY -- I
THINK -- PLEASE COME BECAUSE WE
NEED MORE PEOPLE TO ORGANIZE
BECAUSE ACTUALLY THIS ISN'T EVEN
OUR DAY JOB, BUT THE IDEA IS
REALLY TO THINK ABOUT HOW TO
HAVE MORE COLLECTIVE EFFORTS
BECAUSE THE AMOUNT OF DATA, IF
YOU'RE OVERWHELMED WITH THE IDEA
OF DOING SPATIAL, THESE ARE THE
PLACES YOU WANT TO GO TO.
YOU CAN ASK QUESTIONS.
THINK ABOUT BROADENING YOUR
TEAMS.
I HAVEN'T SPENT AS MUCH TIME IN
A ROOM WITH A PATHOLOGIST AS I
HAVE FOR THE LAST THREE YEARS.
AND REALLY TO ANY TRAINEES, IF
YOU'RE DOING ANY KIND OF Ph.D.
OR POST-DOCKING, I WOULD THINK
ABOUT COMPUTATIONAL TRAINING
ESPECIALLY IF YOU'RE BRINGING
THIS IN-HOUSE.
SO I'M JUST GOING TO END WITH
ACKNOWLEDGMENTS, TO MY TEAM THAT
WAS AT CEDARS, TO HARRY FU WHO
IS IN OHIO FOR THE ALZHEIMER'S,
FOR THE BEAUTIFUL EAST ONE
HYBRID STUFF IS WITH DR. MARION
HOT[READING NAIMEDZ]
, AND ACROSS MANY INSTITUTES AND
FUNDING FROM AWS TISM SPEAKS --
FROM AUTISM SPEAKS.
THIS IS THE LARGE CONSORTIUM,
ALL 32 SITES, LED BY DR. GEORGE,
THIS IS ACTUALLY US IN AFRICA
BECAUSE YOU HAVE TO GO THERE AND
COLLECT SAMPLES, THIS IS THE
TEAM THERE THAT PROCESSED 1K3
DR. MARLETTA 1K3 DR. MALTIFF FOR
THE MACHINE LEARNING MODELS AND
THEN SPATIAL TOUCHSTONE, THIS IS
THE LARGE TEAM, IT'S BEEN A
GLOBAL EFFORT, IT'S BEEN
GOLIATH, THIS IS THE FUNDING
SOURCE, SEEING THAT I'M ALTHOUGH
NIH.
NOBODY FUNDS THIS WORK.
IT WAS REALLY MY DEEP SEEDED
ANNOYANCE WITH THE FIELD AND
MARKETING, WHEN COMPANIES TELL
YOU THINGS WORK AND THEY DON'T.
SO HOPEFULLY YOU'LL USE T
HOPEFULLY YOU'LL HELP US IN THE
CAUSE, BECAUSE MY PIGGY BANK IS
BROKEN NOW.
SO THANK YOU AND I'M HAPPY TO
TAKE QUESTIONS.
[APPLAUSE]
>> THANK YOU SO MUCH FOR THE
WONDERFUL TALK.
I WONDER IF YOU COULD COMMENTED
A LITTLE BIT ON SORT OF YOUR
EXPERIENCE WITH THE BIOPSY
SAMPLES, AND I EVEN SAW THE
TMA'S NOW THAT YOU'RE USING.
YOU KNOW, WE TALKED THIS MORNING
ABOUT TUMOR HETEROGENEITY AND
HERE YOU'RE ALWAYS GOING TO BE
LIMITED WHERE THE NEEDLE GETS
STUCK.
SO HOW DO YOU SORTED OF ENVISIOF
ENVISION GETTING A BIG ENOUGH
SAMPLE FROM A BIOPSY SAMPLE TO
ANSWER SOME OF THE BIG DISCOVERY
QUESTIONS YOU'RE ASKING.
>> SO I WOULD SAY, I DIDN'T
SPEND A LOT OF TIME ON T BUT I
THINK FIELDS OF VIEW MATTERS.
SO I KNOW EVERYBODY WANTS TO GO
SUB MOLECULAR, RIGHT?
WE WANT TO DO THINGS LIKE MAR
FISH AND XENIUM AND COSMICS, BUT
I THINK YOU'RE RIGHT, YOU HAVE
TO START WITH THE IDEA OF LARGE
PROFILINGS ESPECIALLY IF YOU
THINK ABOUT TUMOR HETEROGENEITY.
I WOULD SAY THE GOOD NEWS ABOUT
SINGLE CELLS, MAYBE YOU PUSHED
UP 3 MILLION CELLS SO YOU WOULD
FEEL LIKE YOU GOT A BETTER
REPRESENTATION OF THE TUMOR.
I WOULD ARGUE THAT'S PROBABLY
NOT THE CASE GIVEN THAT YOU ONLY
TOOK LIKE ONE PERCENT OF THE
TUMOR, RIGHT?
SO YOU'RE NOT GOING TO GET THERE
WITH SINGLE CELL EITHER, EVEN IF
YOU HAVE A 5-POUND TUMOR, YOU'RE
TAKING 10,000 CELLS TO REPRESENT
IT.
I WOULD SAY APPROACHES LIKE G HE
OMICS.
WE WERE ASKING QUESTIONS LIKE
DOES INNER MASS OF A STROMAL
VERSUS EPITHELIAL LOOK DIFFERENT
ON THE NORMAL, WHAT'S THE
CONTRIBUTION OF NORMAL --
SOMETHING LIKE G HE OMIC SRKSZ
WOULD GIVE YOU BULK RNA SEQ DATA
BUT YOU COULD DO COOL STUFF
WHERE YOU TAKE ALL THE SINGLE
CELL DATA FROM EVERYBODY ELSE'S
DATA SET AND YOU DECOMPOSE THE
CELLS, RIGHT?
SO EVEN IN THAT BULK DATA YOU
COULD FIND OUT ALL THE IMMUNE
CELLS THAT ARE EXPRESSING CD4 SO
IT'S A BULK SIGNAL THAT GIVES
YOU KIND OF SINGLY LEVEL DATA.
SO I WOULD START THERE.
I WOULD SAY THAT EVEN IF YOU
TOOK KIND OF THE PATHOLOGY
APPROACHES YOU'RE STILL IN A
BETTER PLACE, RIGHT?
SO OUR THING WITH THE BIOPSIES
IS THAT WE'RE GETTING 8 MILLION
CELLS, RIGHT?
SO THE ASMALLEST TMA I'M GETTING
70,000 CELLS.
THAT'S LIKE THE BIGGEST, THAT'S
SEVEN 10X EXPERIMENTS, RIGHT?
SEVEN 10X EXPERIMENTS.
SO EVEN WHEN THE PRICING IS
SHOCKING TO YOU, THE AMOUNT OF
DATA YOU'RE GETTING OFF THE
SLIDE IS JUST THAT YOU -- LOOK
AT THAT 8 MILLION CELL, I WOULD
NEVER HAVE GOTTEN THERE IF I WAS
TAKING A HUMAN CELL ATLAS
APPROACH OF JUST SINGLE CELLING
IT OUT.
SO GRANTED YOU'RE MUSHING UP A
TUMOR BUT YOU'VE GOT 10 PERCENT,
ONE PERCENT, TWO PERCENT OF THE
TUMOR, YOU'RE NOT GETTING A FULL
VIEWPOINT AND THE RARE CELL
TYPES, YOU TALK ABOUT TUMOR
MICROENVIRONMENT, I WOULD RATHER
HAVE ONE-THIRD OF THE TUMOR
PROFILED AND KNOW THAT A
MACROPHAGE -- WE SEE PRY BRO
BLASTS LITERALLY PROTECTING THE
TUMOR.
THAT'S WHEN T CELLS CAN GET IN,
RIGHT?
THAT'S WHEN KWR50UR CAR T, YOU
WANT TO TALK ABOUT RESPONDERS,
NONRESPONDERS, THAT TOTAL QULAIJ
HAS EVERYTHING TO DO WITH WHAT
THERAPY GOT IN.
-- THAT TOTAL LINEAGE HAS
EVERYTHING TO DO WITH WHAT
THERAPY GOT IN.
>> VERY NICE TALK.
SO IN THIS SORT OF BALANCE
BETWEEN SORT OF BROAD SURVEY TO
THE MORE TARGETED AND MAYBE
BEING ABLE TO RUN MORE SAMPLES
FOR THE SAKE OF COST, WHERE DO
YOU MAKE THAT CHOICE?
IN YOUR EXPERIENCE, WHEN DO YOU
FEEL LIKE YOU FIGURED IT OUT AND
YOU CAN NOW DESIGN THAT LOWER
PANEL?
>> SO NO ONE IS IN THIS -- NO
ONE IN THIS ROOM IS GOING TO
WANT TO HEAR THIS BUT I THINK
IT'S MY JOB ESPECIALLY RUNNING
THE LARGE EQUIPMENT DIENLD OF
FIRMT EVERYBODY THAT WANTS TO DO
A PANEL.
I THINK YOU NEED TO HAVE BEEN IN
THE FIELD A WHILE.
EVEN IF IT'S GEOMICS, LOW
HANGING FRUIT OF WHERE YOU SEE
THE SPATIAL CONTEXT.
SO I HAVE THIS VERY CLEAR
EXAMPLE WHERE SOMEBODY WAS
TRYING TO LOOK AT DOWN'S
SYNDROME THIGH MUSES TUMORS --
THYMUS TUMORS.
DOWN'S SYNDROME, IT'S A WHOLE
CHROMOSOME CHANGE, THEY SAW ALL
THIS COOL STUFF IN THEIR SINGLE
CELL DATA SO THEY WANTED TO
COMPARE ONE REGION BACK TO THIS
OTHER REGION BARKS TO THIS
QUESTION OF TUMOR
MICROENVIRONMENT.
IT HAD EVERYTHING TO DO WITH WAS
IT PROXIMAL TO THE THYMUS, DID
THEY GET NORMAL CELLS OUT CIALG
RIGHT?
IT WASN'T -- RIGHT?
IT WASN'T THAT WE CLEANED UP THE
NORMAL, BECAUSE WE SHUNTED HAVE
DONE THAT 2349 1234E8, IT WAS
THE INFILTRATION AT THE BORDER
OF THOSE CELLS.
IT WAS FUNNY THEY WANTED US TO
GROUP IT OUT BUT IT WASN'T THAT
DOWN'S SYNDROME WAS LEADING IT,
IT WAS THAT THE TUMOR BORDER
THAT WAS LEADING ALL OF THE
ANALYSIS.
SO I WOULD SAY, PLAY WITH SOME
LEVEL OF VIZIUM OFFER GEOMICS.
RIGHT NOW TO GET A PAPER YOU
DON'T NEED AN NF30 BUT I WOULD
USE IT WHERE YOU HAVE THE WHOLE
TRANSCRIPTOME.
I WOULDN'T GO AT XENIUM UNLESS
YOU HAVE A LOT OF DATA TO MAKE A
CUSTOM PANEL.
YOU COULD PROBE.
YOU DON'T EVEN HAVE TO SPEND
MONEY.
WE HAVE SO MUCH SINGLE CELL DATD
THAT NOBODY HAS INTERPOLATED TO
THE LEVEL THEY NEED.
LOCK AT THAT SINGLE CELL BREAST
CANCER DATASET I SHOWED YOU.
I WOULD TAKE MARKERS NOW FROM
THAT.
I GENERATED ZERO DATA FOR THAT
PAPER.
BUT REALLY HAVING A BASELINE,
THAT DOESN'T MEAN ALWAYS RELYING
ON COMPUTATIONAL PEOPLE.
I WOULD SAY EVEN MORE MY LAB I
RELY -- EVEN FOR MY LAB I RELY
HEAVILY ON THE BIOLOGISTS, I
DON'T WANT TO KEEP GOING INTO
THE WEEDS.
I WOULD SAY SOME LEVEL OF A
WHOLE TRANSCRIPTOME AND WHEN YOU
HAVE THAT CONFIDENTLY I WOULD DO
COSMICS OR XENIUM AND NOW I'M
DOING A LOT OF ACOOYA.
I DIDN'T HAVE TIME FOR THAT, I'M
HAPPY TO COME BACK, AND REALLY
INTRODUCING HOW MUCH DO YOU NEED
AND HOW MUCH CORRELATION IS
THERE.
>> YES, MY NAME IS AMY, I'M
LEADING THE SPATIAL IMAGING
TECHNOLOGY RESOURCE AND WE HAVE
COS MECHANICS GEOMICS THAT WE
RUN AND HAVE CODEX IN THE NEW
SYSTEM AND THESE ARE JUST
BEAUTIFUL DATA AND YOU ARE
SHOWING AN EXAMPLE OF THE
DIFFERENCE BETWEEN U.S. BLACK
AND CARIBBEAN BLACK IN ONE
EXAMPLE HIGHLIGHTING THE
NEIGHBORHOODS.
BUT WHAT DO YOU THINK, HOW MANY
SAMPLES DO YOU NEED JUST TO
REALLY GET TO WHAT IS DRIVING
THE DIFFERENCES OR WHAT CAN BE
ONE MECHANISM DRIVING THE
DIFFERENCES BECAUSE IF YOU RUN
TEN BIOPSIES FROM OTHER SAMPLES,
WE SEE DIFFERENCES, RIGHT,
DEPENDING ON WHERE WE HIT AND
OBVIOUSLY WHERE THE SAMPLES COME
FROM, THE PATIENTS THEY COME
FROM.
>> YEAH, THAT'S KIND OF WHY I
STARTED TO SHOW IT, BUT WE'RE
PRETTY MUCH DOING HIGH LEVEL
KIND OF TISSUE ANNOTATION, SO
BACK TO YOUR QUESTION.
AND THEN WE GO AFTER TMA'S.
SO OUR LAST WAS 600 IT WAS A
CLINICAL TRIAL FROM MSK WE DID
600 PATIENTS.
PATIENTS MUST LOOK LIKE
THEMSELVES EVEN WHEN A
RECURRENCE HAPPENS BUT WHEN WE
HAVE THAT MUCH DATA THERE'S NO
LEVEL OF -- LIKE THE ONLY THING
CLOSE TO THAT WOULD BE TCGA
LEVEL DATA AND THAT TOOK THEM 20
YEARS TO DO.
I WOULD SAY YOU WOULD HAVE THAT,
IT'S A COLLECTION MAKING THE
TMA'S BUT EVEN IN THESE SMALL
CORES WE GET 70,000 OR 100,000
CELLS, SO IN TERMS OF NUMBERS, I
MEAN, DON'T QUOTE ME ON THIS,
BECAUSE LIKE PEOPLE ASK ME ALL
THE TIME FOR LETTERS OF SUPPORT
ARE DATA.
WE'RE NOT THERE COMPUTATIONALLY
YET.
I WOULD SAY WE'VE DONE IT WITH
LIKE ENDS OF 4 FOR VISIUM OR
GENOMICS, THEN WE'VE PROFILED
AND GOTTEN OUR PROBE SET N OF 4
OR '6EVERYTHING HAS TO HAPPEN IN
END OF TWO ON A 10X SYSTEM AND
GONE TO PROBE SETS AT THAT
POINT.
PROBE SETS WITH SPATIAL
TOUCHSTONE IS NOT A SMALL FEAT,
BUT EVEN I THINK ONCE YOU HAVE
KIND OF A SET TISSUE TYPE,
YOU'LL BE BETTER AT IT.
SO LIKE ONCE YOU'VE KIND OF
INVESTED IN PROSTATE CANCER AND
YOU KNOW THATLY WITH, PROSTATE
CANCER IS REALLY LOW TRANSCRIPT,
SO WHEN WE FIRST STARTED DOING,
WE'RE LIKE THIS IS AWFUL.
BUT HUMAN BRAIN IS LIKE, THERE'S
A REASON WHY EVERY SINGLE
COMPANY SHOWS A MOUSE BRAIN,
RIGHT?
BECAUSE A GENE, YOU SAW THAT,
EVERY GENE IS LITERALLY
EXPRESSED IN THE BRAIRCH AT SOME
POINT IN TIME.
-- BRAIN AT SOME POINT IN TIME.
SO I WOULD SAY THAT IS A FEW IN
THE SEQUENCING REALM AND THEN
MAYBE IN THE TENS TO 20s IN
THE PROBE LAND.
BUT DON'T QUOTE ME ON THAT.
THAT'S A LOT OF MONEY TOO WHEN I
SAY THAT, LIKE EACH SLIDE IN THE
PROBE LAND IS $4,000.
YEAH.
THAT'S WHY I SAY THAT.
I WOULD LIKE HUNDREDS BUT I'M
BEING PRACTICAL TO THE EEM IN
THE ROOM.
>> AND -- TO THE PEOPLE IN THE
ROOM.
>> CAN YOU COMMENT ON THE TME'S?
FOR EXAMPLE YOU SHOWED THE VERY
LOCALIZED INTERACTION BETWEEN
THE MACROPHAGE PS AND THE
FIBROBLASTS.
WHAT IF YOU ARE MISSING THAT?
AND I DON'T KNOW HOW MANY
CORES -- INTLO WELL, THAT'S WHY
YOU DO 600, RIGHT?
THAT WAS FOUR SLIDES WHEN WE DID
600.
SO IT'S AFFORDABLE.
SO IF I'M MISSING TBHUN A
PATIENT, I'LL LEARN ACTUALLY
WHEN YOU TALK ABOUT TUMOR
HETEROGENEITY THAT'S HOW YOU
WOULD DO IT BECAUSE YOU HAVE
DIFFERENT PUNCHES.
THAT'S WHEN YOU PULL THE
PATHOLOGISTS IN THE ROOM, I'M
LUCKY AT ST. JUDE THAT WE HAVE
FOUR IN HOUSE PATHOLOGISTS,
THEY'RE REALLY GOOD AT
GETTING -- VET PATHOLOGISTS,
THEY'RE REALLY GOOD AT LOOKING
AT HUMAN STUFF BECAUSE THEY'RE
LOOKING AT MOUSE AND
INTERPRETATION AND PDX MODEL SO
IN THAT SENSE I SPEND A LOFT
TIME IN THE ROOM WITH THE
PATHOLOGISTS.
THEY SPENT YEARS AND YEARS OF
THEIR FELLOWSHIP BEING MINI
COMPUTERS.
SO WHEN YOU LOOK AT THE TUMORS
AND BACK TO YOUR QUESTION WHAT
PART OF THE TUMOR DO YOU TAKE?
WE DON'T REALLY KNOW.
WE'RE BIOLOGISTS.
PATHOLOGISTS CAN TELL YOU, THEY
HAVE AT LEAST A GEOGRAPHICAL
LOCATION THAT MIGHT BE THE SAME,
RIGHT?
DOESN'T HAVE MOLECULAR PROFILING
SO WHEN YOU MAKE THAT TMA IT'S
NOT JUST DON'T GO PUNCH THE
TUMOR, LIKE THAT WAS SIX
PATHOLOGISTS, BUT THAT'S FOUR
YEARS OLD THAT ACOYA DATA,
RIGHT?
YOU HAVE TO SIT WITH THE
PATHOLOGISTS AND GET THEM TO SAY
THIS IS WHAT I THINK IT IS AND
MAKE THE TMA AND MAYBE IT WILL
TAKE LONGER BUT THEN LOOK AT HOW
MUCH DATA YOU GET, RIGHT?
SO IF THERE'S A VARIANCE, LIKELY
IT'S THAT PATIENT AND MAYBE IT'S
THEY'RE GOING TO BE A
NONRESPONDER BECAUSE THEY DON'T
HAVE THE RIGHT IMMUNE
BACKGROUND.
BUT AT LEAST THAT LAYER HELPS
YOU WITH THE CYTOARCHITECTURE
THAT THEY'RE SEEING THE SAME
THING.
THEN YOU HAVE TO START WITH A
HYPOTHESIS, RIGHT?
SO IF YOU THINK THERE'S A
REGIONALIZATION OF CALFS, THEN
MARK CALFS, DO A SERIAL SECTION,
GET THEM TO STAIN AND PUNCH FROM
THERE, RIGHT 1234 SO I WOULD SAY
THERE ARE WAYS AND APPROACHES
THAT, BUT THERE HAS TO BE
LEARNED EXPERIENCE, THIS IS TO
THE SCIENTISTS IN THE ROOM.
DON'T THINK YOU CAN JUST GO INTO
THE BIO BANK AND PULL.
YOU CAN.
BUT I GUARANTEE YOU'LL HAVE MUCH
BETTER QUALITY OF DATA AND NOT
MAKE A MISTAKE AND HAVE LIKE SIX
YEARS OF DATA YOU CAN LOOK AT,
RIGHT?
I WOULD SAY THAT IT'S WORTH THE
ADDED TIME IN THE BEGINNING.
YES?
>> WONDERFUL TALK.
I MEAN, THIS IS KIND OF LIKE MY
LOVE LANGUAGE THAT YOU'RE
TALKING ABOUT.
>> DON'T TELL MY HUSBAND.
>> SO WHAT ARE YOUR THOUGHTS
ABOUT UTILIZING YOUR APPROACHES,
WHETHER IT BE SPATIAL
PROTEOMICS, TRANSCRIPTOMICS OR
IDEALLY THE COMBINATION OF BOTH
TO REALLY LOOK AT THINGS SUCH AS
GRAFT VERSUS HOST, TRANSPLANT
REJECTION, I THINK THAT WOULD BE
ACTUALLY KIND OF INTERESTING.
HAVE YOU EVER THOUGHT ABOUT
DOING ANYTHING?
>> OH, WE'RE HACKING THAT NOW,
SO DON'T TELL ANY OF THE
COMPANIES.
OH, YEAH, WE DO IT ALL THE TIME
NOW.
>> OKAY.
>> SO THE BEAUTY OF OLD CLASSIC
VEZIUM IS FOR THIS, SO YOU DON'T
REALLY HAVE TO HACK IT, YOU CAN
PUT IN, LIKE WE DID IT IN COVID,
WE PUT COVID PROBES IN 1K3 THEN
JUST ALIGN CDNA TO WHATEVER AND
WITH VEZM YOU JUST PUT PROBES IF
THE INSTALL IS LOW, YOU HAVE ANY
SPECIES AND YOU ALIGN IT WHETHER
THAT'S VIRUS OR WHATEVER.
SO WE CAN DO THAT.
I FIGURED OUT HOW TO DO IT IN
XENIUM I THINK.
BUT LIKE YOU CAN GET THEM TO
MAKE CUSTOM PANELS AND YOU CAN
DO WHATEVER SPECIES YOU WANT
INTO IT, RIGHT?
SO I THINK IT'S IN ONE BEAUTIFUL
THING EVEN WITH BACTERIAS YOU
CAN SEE IT IN THE HNE SO IT
DOESN'T EVEN HAVE TO COST YOU.
MAYBE YOU DON'T EVEN CARE B YOU
JUST WANT TO IDENTIFY AN IMAGE
REGISTER WHERE THE HOST IS, AND
WE SEE BEAUTIFUL THINGS I KNOW
NOTHING ABOUT INFECTION,
PLEURIFIC BEAUTIFUL THINGS.
THE IDEA THAT THERE'S AN INITIAL
T CELL RESPONSE, IT'S ACTUALLY
NOT THERE, IT'S NOT LOCALIZED TO
THE BACTERIA RKTS IT'S KIND OF
LOCALIZED HERE, YOU HAVE
EVERYTHING HERE AND SOMETHING
HAPPENS IN RESPONSE IN THAT PART
OF THE TISSUE.
SO WE ARE SEEING THAT AND I
THINK THIS IS THE WAY FORWARD
FOR SURE.
>> THANKS.
>> HI.
THANK YOU.
GREAT TALK.
I HAVE JUST TWO QUESTIONS FOR
THE FUTURE.
THE FIRST ONE SOMETHING THAT WE
ARE STRUGGLING RIGHT NOW, AND IN
THIS WHOLE SPATIAL STUDIES,
YOU'RE SHOWING ALL THESE NICE
CORRELATION THAT IT SEEMED TO
MAKE SENSE WHEN YOU SHOW ONE
TISSUE VERSUS THIS TISSUE AND WE
CAN SEE OH YEAH THESE CELLS ARE
HERE, THESE OTHER CELLS ARE
HERE.
BUT WHEN YOU START TO LOOK AT
600 PATIENTS OR 600 DATA, THEN
YOU HAVE THESE NICHES MEASURE AT
DIFFERENT LEVELS HERE AND
DIFFERENT LEVELS HERE, AND I AM
CURRENTLY MISSING, BECAUSE I AM
NOT A COMPUTATIONAL BIOLOGY OR A
STATISTICIAN, THE TOOLS THAT
WILL ALLOW YOU TO ACTUALLY
QUANTIFY THOSE THINGS AND
ESTABLISH THESE NICHES ARE TRULY
DIFFERENT IN THESE SET OF
PATIENTS VERSUS THESE OTHER SET
OF PATIENTS.
I DON'T KNOW IF THAT'S CLEAR FOR
YOU.
>> SO I WOULD SAY, AGAIN, LEARN
FROM MY MISTAKE.
THEY'RE NOT MISTAKES ACTUALLY
BECAUSE I USE BIOSTAT --
BIOSTATISTICIAN BUT THE LAB
BIOLOGIST IS GOING TO LOOK AT IT
THE SAME WAY AS AN IMAGING BASED
TRAINED PERSON 6789 SMFTD MOST
BEAUTIFUL AL G ALGORITHMS ARE CG
FROM SATELLITE PEOPLE BECAUSE
THE TOOLS I USE NOW, THERE'S A
WHOLE ARGUMENT ABOUT CELL
AUGMENTATION BLAH BLAH BLAH I
DON'T EVEN DO THAT ANYMORE
BECAUSE I JUST HIRE PEOPLE THAT
LITERALLY THEY DON'T EVEN KNOW
WHAT A CELL IS, THEY DON'T EVEN
KNOW WHAT A MOLECULAR BARCODE
IS, BUT THEY WILL DRAINTD SETS
TO TELL UH-OH, WELL, THINK ABOUT
T THEY'RE JUST PIXELS, THEY'RE
LIKE OH YEAH YEAH THEY'RE JUST
PIXELS, THEY HAVE DIFFERENT
COLORS, YOU CAN PUT WHATEVER
CHANNEL YOU WANT BUT OVER TIME
THEY CAN NORMALIZE THAT DATA
BECAUSE THEY'VE NORMALIZED IT
ACROSS THE ENTIRE SLIDE.
THEY'RE AGNOSTIC TO THE IDEA OF
PATIENT ONE VERSUS PATIENT TWO
VERSUS PATIENT THREE.
SO THINK ABOUT IT IN TERMS OF
YOUR PHONE.
SO YOUR PHONE CAN AUTO FOCUS AND
AUTO REGULATE HIGH LIGHT, LOW
LIGHT.
THAT'S THE LEVEL OF COMPUTATION
THEY'RE DOING.
THEY'RE NOT DOING IT DID CD4
KIND OF COME UP?
RIGHT?
I THINK THAT'S THE PROBLEM WITH
SOME OF THE SOFTWARES COMING OFF
THE MACHINES IS THEY'RE BEING
LEARNED BY GENOMISISTS, HOW MANY
TRANSCRIPTS WERE IN THAT CELL.
EVERY COMPANY HATES TALKING TO
ME BECAUSE I KEEP ASKING WHAT
ABOUT THE NEBULA?
I DON'T SHOW YOU THAT DATA BUT
WHEN YOU TAKE THE TISSUE WHEN
YOU RUN THESE MACHINES THERE ARE
PROBES IN THE BLACK PART THAT
HAS NO TISSUE SO FOR ME IF
THERE'S 64 PROBES THERE THEN HOW
CAN I RELY ON THE COUNT IN MY
CELL?
THEY'RE LIKE OH JUST DON'T LOOK
AT THAT.
LITERALLY WHAT I'VE BEEN TOLD.
RIGHT?
SO I WOULD SAY THE APPROACHES
ARE COMING, WE HOPE EVEN WITH
GESTALT PEOPLE DEPOSIT DATA
BECAUSE THOSE APPROACHES NEED US
TO LEARN ON EVERY KIND OF TISSUE
TYPE, RIGHT?
SO I WOULD SAY START LOOKING
INTO THOSE KIND OF THINGS WHERE
YOU START TO SEE IMAGING BASE
#-D APPROACHES TOO -- BASED
APPROACHES TOO, IGNORING THE
BARCODES AND I THINK WHEN WE
START FOCUSING ON THAT AND NOT
GENOMIC TOOLS INTO SPATIAL, THE
FIELD WILL EVOLVE VERY QUICKLY
AND IT IS.
A LOT OF THOSE PEOPLE ARE LIKE
OH, I CAN DO THAT.
I JUST CAME FROM AN AI MEETING
ABOUT THAT WHERE ONCE YOU PLANT
IT IN THEIR HEAD THAT TISSUE IS
SPATIAL, THEY'RE LIKE OH, I
COULD DO THAT.
SO IT'S COMING.
>> OKAY.
AND VERY SHORT, BECAUSE I DON'T
WANT TO DISTRACT, BUT WHAT IS
YOUR THOUGHT ABOUT REUSING
MATERIAL?
BECAUSE I WORK IN A PLACE WHERE
BIOPSIES ARE ONE MILLIMETER, TWO
MILLIMETER, VERY TINY, SMALL,
AND WE'VE BEEN SPER
CONVENIENTING AND DOING THINGS
THAT -- WE'VE BEEN INTERVENING
AND DOING THINGS THE COMPANY
DOESN'T USUALLY TELL YOU TO DO.
>> I WOULD SAY LOOK OUT FOR THIS
ONE RIGHT HERE.
SPATIAL TOUCHTONE PROTOCOLS.
>> OKAY.
>> WE'VE TRIED TO INCLUDE
EVERYTHING BUT OBVIOUSLY WE'RE
TRYING TO GET IT PUBLISHED RIGHT
NOW BUT ON THE PROTOCOLS I
IMAGINE WE'LL INCLUDE MORE BUT
WE'VE DONE EVERYTHING.
WE'VE DONE DMAISH SWRO SO YOU
USE --
>> VEZIUM, WE'VE DONE THE
COOLEST ONE, OH, MAYBE I EVEN
HAVE IT THERE, THE ACTUAL
CRAPPY, THAT GUY RIGHT THERE.
SEE THE CRAPPY ONE IN THE
MIDDLE?
THAT ACTUALLY GOT RUN ON FULL
XENIUM RNA PANEL INTO COSMIC'S
PROTEIN.
SO LIKE WE'RE THERE.
LIKE WE CAN DO IT.
I WOULD SAY THE AMAZING PART
ABOUT THE ACOYA SYSTEM AND I
BRAG ABOUT THIS A LOT, IT'S HARD
TO GET A FUNCTIONING PANEL.
IF YOU HAVE A FUNCTIONING PANEL,
THAT THING CAN SIT THERE FOR SIX
MONTHS.
YOU CAN TAKE ALL YOUR TIME TO
ANALYZE YOUR DATA AND YOU WANT
TO ADD ANOTHER ANTIBODY YOU JUST
GO BACK, TAKE THE FLOW CELL OFF,
IT HAS TO HAVE A NEW BARCODE BUT
THEN YOU CAN STAIN.
WE'RE DOING A LOT OF THAT NOW.
SO LIKE, YOU KNOW, THE HNE LIKE
AFTER XENIUM, THE H -- THE HNE
AFTER COSMIC SS.
I WOULD SAY IT'S VERY DIFFICULT
FOR CORE TO DO, IF CORE SAYS NO
TO YOU DON'T BE UPSET, THEY
DON'T WANT TO RUIN YOUR $3,000
CELL, BUT FLOW SET I'VE TAUGHT
THEM ON ZOOM OF THE YO YOU CAN T
TOWF TAKE RAZOR BLADES AND YOU
HAVE TO DO THINGS CORES DON'T
WANT TO DO, BUT I WOULD SAY THE
FIELD IS THERE.
ALL THE PROTEIN ONES CAN BE
HELD.
>> ALL RIGHT.
THANK YOU.