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Sid Sijbrandij

Cancer Journey

Please email me if you want to look beyond the standard of care. I work with two full time people to follow up with everyone.

sytse.com/cancer

Feel free to share this presentation and above url with anyone

SID SIJBRANDIJ | CANCER JOURNEY

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Running Gitlab - ~$800M revenue publicly traded company with >2000 employees
Happily married to Karen, partner of over 25 years

Living the American dream after IPO'ing GitLab in 2021

SID SIJBRANDIJ | CANCER JOURNEY

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In 2022 I had pain while bench pressing, 6cm osteosarcoma

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END OF 2022

But then at the end of 2022 I felt pain and went to the emergency room…
They detected a 6 cm tumor that had grown from my spine!
We found out in 2023 it was high grade bone cancer.

Became the start of a journey

SID SIJBRANDIJ | CANCER JOURNEY

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Standard of care treatment for osteosarcoma (bone cancer)

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START OF 2023

Surgery including T5 vertebrae removal and spine fusion with a titanium frame
Radiation (SBRT and proton beam)
Chemo - 6 cycles (4 dox/cisplatin, 2 AIM) that were so intense that 4 blood transfusions were needed to keep me alive

SID SIJBRANDIJ | CANCER JOURNEY

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Also in 2022 Click chemistry won a nobel prize

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In 2017 I invested in click-chemistry for cancer in 2023 I took it

Single Patient IND

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Since 2017 I invested in a company called Shasqi that uses click-chemistry to target cancer treatments.

Because biotech didn't believe in them I become their biggest shareholder but now I was becoming a patient as well!

This way my first single patient IND treatment. Opening my mind to what is possible outside of the standard of care.

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It came back locally and there was no treatment or trial

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2024

No trails available: My rare disease and rare HLA-type didn't qualify for any trials: It was time to step up and take charge of my own care…

My oncologist: “I have no more drugs I would recommend. Maybe you can find a trial.”

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I'll talk to anyone, I'll go anywhere, and I can be there anytime.

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I went founder mode on my cancer

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Maximal Diagnostics

Making Treatments

Treatments in Parallel

Scaling for Others

Elliot Hershberg coined the 'founder mode' with https://centuryofbio.com/p/sid

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Maximal Diagnostics, test even if unsure how to action

35TB of data publicly available on https://osteosarc.com/

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SINGLE CELL SEQUENCING

DNA / RNA SEQUENCING

PATHOLOGY STAINING

FREQUENT BLOOD TESTING

DRUG RESPONSE

TARGETED PET SCANS

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Passersby at AACR made a world model based on my scRNA

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Developing 10+ personalized drugs and diagnostics

Personalized TCR-T cell therapy

Personalized cancer vaccines (mRNA, DNA, peptide)

Custom binder for target found in my tumor (PANX3)

Personalized CAR-T cell therapy

Personalized radiodiagnostics

Custom antibody-drug conjugates targeting my tumor

Note: I didn't develop most of the drugs I ended up taking.

SID SIJBRANDIJ | CANCER JOURNEY

And through this process, I’ve been able to initiate a number of personalized therapeutic programs. I don’t come from the world of biotech, but as I have learned from my fairly unique perspective as a patient, it has been interesting to see how the technological development curves I’m familiar with from software seem to be happening in biotech as well. We have been fortunate to work with a number of partners - both companies and academics - who are utilizing the huge amount of data we’ve collected about my cancer to build therapies that are well suited to attack it. In many cases, these programs are also helping to harden processes or create products that could be used for other people. I’m proud of this - as I said earlier, one of my goals is to increase the options available to other cancer patients so their journey is more straightforward than mine.

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I did many treatments in Parallel, not Serially

Treatments are usually tested one at a time

Most people run out of time as cancer spreads before finding a cure.

I'd rather die from side effects than from cancer

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"If it works, we won't know what cured you."

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The basics are not prohibitively expensive

Bulk RNA sequencing starting at $50

(and scale for deeper profiling)

Whole genome sequencing starting at $500

AI tools are very capable and $20+ per month

Many chemotherapies are available as low-cost generics

SID SIJBRANDIJ | CANCER JOURNEY

In terms of scaling for others - I’ll start by saying that the basics are not prohibitively expensive. What’s here on this slide is not “standard of care” by any means, and requires that you have control of tissue to generate data. But at this point in time, we are beneficiaries of scaling laws on both data generation and data analysis. On the data generation side, sequencing has gotten really good and really affordable. Whole genomes can be done for around $500, and companies like Plasmidsaurus do bulk RNA sequencing starting at $50. AI tools - like ChatGPT - are increasingly capable, as we’ve talked about, and the pro versions cost ~$20 per month, about as much as a Netflix subscription. I’ll emphasize here that these tools shouldn’t substitute for working with a doctor, but they can help with hypothesis generation. And then on the therapies side, off-patent drugs are much more affordable than on-patent ones.

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Helping people look beyond standard of care

Book a free call online with one of our two team members who are available fulltime to help patients see what is available beyond the standard of care.

https://sijbrandijfoundation.org/fcct

Poornima Parameswaran, Ph.D.

Bayli DiVita Dean, Ph.D.

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Also see https://www.evenone.ventures/

I started 15 companies in 15 months to increase access

Custom protein and peptide therapies in oncology

Personalized mRNA cancer vaccines

Cancer

Biology-matched, non-hormonal treatment exploration for endometriosis

Women’s Health

Rescuing drugs

Rescuing shelved oncology assets

Biobanking

Maximum Optionality

Diagnostics

Maximum Profiling

Monitoring

Biomarker-driven radiodiagnostics

Deep immune profiling & combination therapeutics for unresolved immune disorders

Autoimmune

AI Agents

Personalized bioinformatics

Yuga

Rare disease

Relit

Personalized oncolytic viruses

Minuteman

Comprehensive functional drug testing

Personalized ASOs

Stitchpoint

Rarivive

Perita

Personalized gene editing

Ignitus

Measure and restore mitochondrial energy capacity

Cardiovascular/Longevity

Personalized TCR cancer therapies

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Make the industry more Patient First

Investigators can choose any federally compliant Institutional Review Board (IRB)
Phase 1 (safety) without FDA approval (at most notification), IRB approval is sufficient
Right to try (not market) after phase 1 is complete, reduce the invisible graveyards
Market some drugs after phase 1 is complete with conditional approval
Right to try data should overcome a very high bar to be held against an experimental drug
For low drug volumes allow GMP-light, replacing production process checks with check on the output (GQP)
Maximize survival instead of the current practice of minimizing liability to the practitioner
Doctors inform you about oncology trials
More extensive coverage of exploratory diagnostics like raw genomic sequencing data
From approved molecules to approved algorithms and process, for truly personalized medicines
Parallel treatments wherever reasonable, we don't need to know what cured you
The patient controls their tumor tissue (tissue rights) and most tumors are completely sequenced
Freedom to have an out of state doctor and nurse
HIPAA adjustment to more easily gather data
FTC involvement to make EMRs like Epic/Cerner interoperable with other systems
Allow patients to share their data with all healthcare professionals and/or everyone (MOSL)
Adopt a Context-Driven Evidence Approach For Reimbursing Rare Therapies
Make the real time clinical trials pilot permanent

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I currently have no evidence of disease

BUILDING "THERAPEUTIC LADDER" OF BACKUP TREATMENTS

MRNA NEOANTIGEN VACCINE

MULTIPLE MRD TESTS

ONGOING SURVEILLANCE

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My therapeutic ladder went from 0 to ~25 treatments

Consider while MRD low / negative

MRD increasing

(by ctDNA or positive margins)

Local progression

Metastatic progression

mRNA neoantigen vaccine
Checkpoint inhibition

TCR T cells (w/o lymphodepletion)
Vaccine induced T cells (w/o lymphodepletion)
Additional checkpoint inhibition
Options for manipulating immune microenvironment
VEGFR / TAA vaccine
DNA neoantigen vaccine

Radioligand therapy
ADCs selected from options for high-expressing targets (B7-H3, EphA2, ROR2, AXL)

Radioligand therapy
ADCs
Intratumoral therapies

Chemotherapy
Immunotherapy
Oncolytic virus
Cell therapy

Surgery + intraop radiation
Cryoablation / RFA / PEF
Carbon ion radiation

B7H3/FAP CAR-T cells
TCR-T cells
GD2 CAR-T cells
TILs
ADCs
Drugs with activity in functional models
Drugs with activity in AI models
Drugs with genomic rationale

MDM2 inhibitors
PARP inhibitors

Current / planned treatments

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How we found a target and picked radioligand therapy

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SINGLE CELL SEQUENCING

DNA / RNA SEQUENCING

PATHOLOGY STAINING

FREQUENT BLOOD TESTING

DRUG RESPONSE

TARGETED PET IMAGING

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Identifying cancer cells from single cell sequencing

Sequence the tumor at single cell resolution

Separate cancer cells from surrounding normal cells

Focus on tumor specific expression

Putative tumor cells

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Comparing tumor and normal tissue reveals signal

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Integrated my tumor with public normal tissue to identify tumor-speficic genes

Tumor cells formed a distinct cluster

Examined the genes most distinct between tumor and normal cells

These genes pointed to targetable biology

My cancer cells express a strong fibroblast-like program

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Fibroblast program points to FAP as a target

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YES

Decision at stake: To fly to Germany for experimental radiotherapy?

YES

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Radiotherapy with FAP in Germany

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Radiotherapy with FAP in Germany

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Cancer responded, enabling surgery

Its gone!

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f

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T-cell infiltration increased dramatically!

June 2024

Jan 2025

Apr 2025

Single Cell RNA Seq

tumor

T cells

June 2024: Aggressive Multimodal “Pre-Treatment”

Systemic and localized chemo-SBRT phase → Massive tissue damage and inflammation

Neoantigen vaccines → Early immune priming

Short course of PD-1 inhibitor

Jan 2025: 5 immunotherapies in parallel!

CTLA-4 checkpoint blockade
PD-1 checkpoint blockade
NK cellular therapy
IL-15 superagonist for NK/T-cell activation
Oncolytic virus for Immune activation, tumor lysis

Apr 2025: Precision Targeted + Immunotherapy. Stromal targeting.

¹⁷⁷Lu and ²²⁵Ac-FAPi → Targeted radiotherapy against fibroblasts

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Personalized mRNA Vaccine

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DNA / RNA SEQUENCING

PATHOLOGY STAINING

FREQUENT BLOOD TESTING

DRUG RESPONSE

TARGETED PET IMAGING

SINGLE CELL SEQUENCING

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Neoantigens ranked based on available data and algorithms

Neoantigens prioritized based on data from multiple samples, use of multiple algorithms, HLA binding predictions, and inclusion in prior vaccines
Availability of deep bulk RNA sequencing allowed use of variant allele expression for prioritization

SID SIJBRANDIJ | CANCER JOURNEY

My tumor has been sequenced at multiple time points - the resection from my initial diagnosis, along with biopsies that were taken after it recurred with the express goal of understanding it further. In addition, I’ve had a series of personalized peptide vaccines made, utilizing the sequencing data that had been done. Earlier this year, my team put substantial effort into going through all of these different inputs to select neoantigens that could go into an mRNA vaccine.

You can see here a few plots that represent the work. My tumor has a modest mutational burden, so we could go through the mutations one by one to pick the best ones. We looked to see which ones persisted across all time points and which ones had already been vaccinated against. We also ran a bunch of algorithms to predict which neoantigens would actually present on my HLA and be immunogenic.

We were extremely fortunate to have been able to move very quickly with a medical center to go from first introduction to optimization, manufacturing, and administration of the vaccine in under 6 months. And now that they’ve run that process for me, they should be able to go much faster for subsequent patients.

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From project start

to injection in 6 months!

https://www.houstonmethodist.org/newsroom/houston-methodist-develops-first-personalized-mrna-cancer-vaccine-for-osteosarcoma/

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Flow cytometry shows active T cells

osteosarc.com/timeline

T-cells are more active than healthy controls

A regulatory T-cell population is elevated

T-cell behaviour tracks with checkpoint inhibitor dosing

SID SIJBRANDIJ | CANCER JOURNEY

Here you can see some early data from the flow panel,. Will’s group at Baylor has compared the results from my blood to those from healthy donor controls. On the tip left, you can see that my T cells are consistently more active than healthy controls, which makes sense since they’ve been exposed to antigen through vaccine. On the bottom left, you can see that the percentage of CD4+ T cells that look like regulatory T cells is relatively high - something we will be watching out for. On the right, you can see our antibody in the panel that detects checkpoint inhibitor drug occupancy on T cells picks up the expected kinetics of the drug. The longer it’s been since my last dose, the lower the effective dose, and the timing matches up with the reported halflife of the drug.

As single cell data comes back, we’ll learn a lot more about my T cell response to vaccination across the different varieties of vaccines.

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Blood monitoring for tumor and immune signals

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Vaccine

Neoantigen

Discovery

Monthly Blood Review

Flow cytometry panel

TCR Sequencing

MRD Testing

“Complete blood count” through high parameter flow cytometry. Distribution of immune cell types in PBMCs and sorting of T cells for further analysis

Single cell sequencing of T cells to measure abundance of specific clones (TCR-T or neo- antigen related, and other) and T cell phenotype. Bulk TCRseq to get full distribution of TCRs

Signatera, Personalis & Billion-to-one to measure ctDNA in blood. Exploring circulating tumor cell, RNA-based, and protein-based strategies as well.

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Creating a Personalized TCR-T

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SINGLE CELL SEQUENCING

DNA / RNA SEQUENCING

PATHOLOGY STAINING

FREQUENT BLOOD TESTING

DRUG RESPONSE

TARGETED PET IMAGING

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TCR-T process

Discovery & Verification Workflow

Collection �of tumor biopsy & blood or other T-cell containing samples

Prediction & Prioritization�of targets from tumor mutation sequencing and vaccine design

neoTCR Identification�using binding or functional screens on T cells from patient sample

Functional Verification �of neoTCR hits to prioritize for product selection

Product Selection�of 1 or more neoTCRs considering:

Functionality
Target diversity/abundance
HLA diversity
Tumor escape

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SID SIJBRANDIJ | CANCER JOURNEY

We are working with a group called Pathfinder Oncology to create an engineered TCR T cell therapy that utilizes T cell receptors fished out of by blood with bits of tumor that are then engineered into healthy, expanded T cells. As a quick primer, T cells are part of the immune system that very specifically kill invaders. Because cancers are mutated, they can show up as ‘invaders’ to the immune system, and a lot of modern cancer therapy tries to use this dynamic to fight cancer. Each T cell has a unique receptor, which we can shorten to TCR (standing for “T cell receptor”). The TCR is what the T cell uses to identify its target; when the TCR meets its target, or “antigen,” the T cell activates and does its job - some kill cells, some recruit other members of the immune system, some support the fighters. Pathfinder is utilizing an approach developed by PACT Pharma, a company that advanced pioneering work from Jim Heath and other researchers. PACT unfortunately went bankrupt when the funding environment for biotech companies turned a few years ago, but the approach makes sense and Pathfinder has found a way to try to use the infrastructure PACT had built to help individual patients like me. You can see a brief description of the approach here.

One of the advantages of doing this for one patient - in this case, me - is that we can do what makes sense. We have a ton of data about my tumor and my immune system that we can and should utilize to better select TCRs for this therapy. And the team has been creative in identifying new approaches and technologies that have come up since the PACT team built their process. By taking a multi-pronged approach, we can both expand the set of TCRs we add to the top of the selection funnel, and cross validate the ones we think are best suited to move forward.

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See expansion of relevant clones in single cell data

DYNC1H1 TCR expanded to 53 clones in April 2025 resection when tumor was essentially cleared

scRNAseq Clustering by Cell Phenotype (T2 Biopsy)

CD8 T cells

Proliferating

CD8 T cells

Colored dots show DYNC1H1-specific CD8+ T cells identified by discovery workflow in T2 biopsy including 2 clones for TCR-T.

scRNAseq Clustering by Cell Phenotype (T3 Resection)

Proliferating

CD8 T cells

SID SIJBRANDIJ | CANCER JOURNEY

Here, we can return again to the single cell data we collected from my tumor over time. One of the things we’re looking at carefully is the actual identity of the T cells that are in the tumor microenvironment. The single cell technology we used enables us to sequence the identity of the T cell receptor genes in each T cell, which is important because we want to see if the clones that appear to recognize tumor targets are sticking around, if new clones are making their way into and expanding in the tumor, etc. Here you can see a few clones of particular note - because they also came up through other methods in the TCR-T process! You can see that clones against the mutated gene DYNC1H1 have expanded from time point to time point alongside treatment, which is a good sign, and we’re likely to move forward with one of these in our final TCR-T.

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Selecting TCRs for therapy

Item	Criteria	Rationale	P01-F02 DYNC1H1	P01-G10 DYNC1H1	P02-A07 DYNC1H1	D3 or F3 TECPR1
1	TCR comes from antigen experienced T cell	Memory T cell has been selected in vivo and supports safety profile of TCR-T product	Memory phenotype	+	+	TBD
2	TCR comes from T cell showing tumor trafficking	T cell present (and expanded) in TIL population or recently trafficked through tumor supports tumor relevant targeting	Present and expanded in TILs	-	-	-
3	TCR targets truncal or high prevalence neoepitope expressed in most recent tumor biopsy	Increases likelihood that TCR-T product will be functional in patient	DYNC1H1 (high prevalence)	+	+	TECPR1 (truncal)
4	TCR targets HLA with no evidence of LOH	TCR requires HLA expression on tumor for function	C*07:01	+	B*27:05 (phased)	TBD
5	Evidence of multiple clonotypes generated by immune response	More clonotypes suggest a more robust immune response	At least 8 clonotypes identified	+	- (only one)	TBD
6	TCR shows strong EC₅₀ for neoepitope and little response to wild-type peptide	TCR will be potently activated by presented peptide with little to no off-tumor safety issues	0.12 nM EC50	+ (0.05 nM EC₅₀)	- (43 nM EC₅₀)	TBD
7	TCR is CD8-independent	TCR will recognize tumor cells when edited into both CD4 and CD8 T cells	YES	+	-	TBD
8	TCR kills multiple target cells pulsed with both minimal and long peptide when target cells in excess to T cells	Serial killing of target cells indicates potency while killing of long peptide-pulsed target cells suggests physiological antigen processing and presentation	~80% killing at 1:4 E:T ratio	+ (~80% killing)	- (~45% killing)	TBD

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Functional screening

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SINGLE CELL SEQUENCING

DNA / RNA SEQUENCING

PATHOLOGY STAINING

FREQUENT MRD TESTING

DRUG RESPONSE

TARGETED RADIO DIAGNOSTICS

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Drug Response Testing with organoids (functional testing)

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Testing response of live cancer cells to a large number of FDA approved drugs, including immunotherapies, via mass changes

Testing response of mircoenvironment preserving cancer organoids to a large number of approved treatments, experimental treatments, and ADC payloads, via growth assays

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Organoid testing for additional options

Used to test potential ADC payloads, therapeutic hypotheses we could action with systemic drugs
Organoids from June 2024 biopsy highly sensitive to Trabectedin - holding in reserve in case needed

January 2025 biopsy testing

SID SIJBRANDIJ | CANCER JOURNEY

I’ll come back to this in more detail later, but we’ve also worked with a lab at UCLA led by Alice Soragni to do ex vivo drug testing on organoids derived from my tumor. Given they are MEZZ-EN-KY-MAHL and have complex microenvironments, there are not many protocols out there for making organoids from sarcomas. The Soragni lab has figured out how to work with sarcomas, and they have made organoids from biopsies from my cancer. Here you can see dose response curves from testing of a number of different compounds directly against the organoids grown from my tumor from the sample taken this January. We are using the results of this testing to prioritize chemotherapy options in case we need them. For example, the testing from last summer showed a very strong response to Trabectedin, marketed as Yondelis, which disrupts DNA structure and interferes with transcription and DNA repair.

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T cell functional response to checkpoint inhibitors

Significant mass response seen for ipilimumab and dostartlimab
No significant mass response seen for any other checkpoint inhibitor drugs tested

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MDM2 as targeted therapy

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SINGLE CELL SEQUENCING

PATHOLOGY STAINING

FREQUENT MRD TESTING

TARGETED RADIO DIAGNOSTICS

DRUG RESPONSE

DNA / RNA SEQUENCING

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Very high regional expression around MDM2

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Tumor MDM2 expression is in top 0.3% of all cancers (comparing 2600 tumors)

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MDM2 expression much higher than predicted by copy-number.

I recently prevented a drug targeting it from being destroyed by the manufacturer!

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CAR-T Program

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SINGLE CELL SEQUENCING

DNA / RNA SEQUENCING

PATHOLOGY STAINING

FREQUENT MRD TESTING

DRUG RESPONSE

TARGETED RADIO DIAGNOSTICS

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B7-H3 as a seemingly good target…

Put together a CAR-T product featuring the latest scientific advances!

Synthetic, tuned receptor
Modifications for durability
Safety switches as a fail-safe

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… but Beijing scan spooked us about liver tox

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BUT. One of the things we are doing now that my cancer is not detectable is hunting for it with biomarker-specific PET tracers. We managed to find a radioligand imaging agent against B7-H3 that was available through a trial in China. The idea was, let’s use this to hunt for my cancer, and also get a sense for where B7-H3 is expressed elsewhere in my body. The idea of see-and-then-treat has been super helpful with the FAP radioligand therapy, and we’ve used the approach to personalize my dosing. Why not use it to guide other modalities too?

Here you can see my liver lighting up. The coloring is a bit deceiving, but we do see that the uptake in my liver was higher than they had observed for any of the other patients they’d used this imager with to date.

Melting my liver with a hyper-potent CAR-T seemed like a bad idea, so we decided to pivot.

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Now we are building a SNIPR system

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Investing in PANX3 as a potentially very clean target

By RNA, PANX3 is:

Highly expressed in my tumor (X axis)
Not highly expressed in any normal tissue in the GTEX database (Y axis)

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Sid Sijbrandij

Cancer Journey

cancer@sytse.com

Please email me if you want to look beyond the standard of care. I work with two full time people to follow up with everyone.

sytse.com/cancer

Feel free to share this presentation and above url with anyone

Thank you!

SID SIJBRANDIJ | CANCER JOURNEY