Precision therapies for #cancer are underutilized for a variety of reasons: lack of sensitive diagnostic tools, lack of clinician awareness, et cetera.
This is changing one step at a time.
(A Thread)
Conceptually, precision drugs exploit genetic defects in a patient's tumor. Using comprehensive next-gen #sequencing (NGS), clinicians can surface mutations that indicate the use of a precision drug.
If we don't catch mutations, we underutilize therapies.
One notoriously difficult variant class is an #NTRK Fusion, which is common in certain pediatric cancers and sometimes present in common adult cancers.
While precision therapies targeting NTRK-fusions exist, only recently have we improved our ability to detect them in tumors.
NTRK is an umbrella term for three genes (NTRK1, 2, and 3) responsible for the growth of nerve tissue. NTRK genes encode for transmembrane proteins (TRK, as shown below). TRK proteins 'catch' growth signals and relay that signal to the cell nucleus triggering cell growth!
An NTRK-fusion happens when part of the NTRK gene collides with another gene. This makes a 'Frankenstein' (chimeric) protein. Functionally, this is like kicking in a light switch such that the light is always on.
In a cancer cell, this means the 'grow!' signal is always on.
Why are these hard to detect? Firstly, sequencing DNA isn't the right choice because the non-coding (intronic) regions of NTRK genes are highly repetitive, which biases #sequencing results.
A better choice is to sequence RNA, but this still leaves us with a big problem...
Before sequencing, we need to attach molecules (primers) to the edges of an mRNA. It's easy to bind one to the NTRK-side of the mRNA, but unless we know the other side of the fusion a priori, it's hard to bind a primer.
This means the mRNA can't be read very well.
Anchored Multiplex PCR is a method that uses universal primers that always bind to the unknown (?) half of the NTRK fusion product, vastly improving analytical sensitivity by eliminating false negatives.
In summary, this is an example of a novel technique to more reliably call novel NTRK-fusion events in cancerous tissue, thereby increasing the utilization of TRK-inhibitors in those patients, ostensibly improving their outcomes.
>90% of Americans over 45 have seen a Cologuard ad this week.
Fewer know of the test's parent company, Exact Sciences (EXAS), whose tests also guide care for the majority of early-stage breast cancer patients in the US.
Today, we released a 5-year model + article on Exact.
Our (base case) 2027 price target is $140 ($49 today). To get there, here's what we believe has to happen:
1. Exact's core business (Cologuard + Oncotype DX) grows on avg. >15% per year thru 2027, reaching $4B.
2. Exact achieves EBITDA positivity in the '23/'24 timeframe.
What we believe must happen (Cont.):
3. Exact uses its earnings to reinvest in its burgeoning pipeline, service its outstanding debt, and maintain its capital equipment.
4. Exact's pipeline, in aggregate, hits >$1B revenue by the end of 2027.
Now that @Quantum_Si has given us a peek under the hood of its protein #sequencing platform (Platinum), we can begin comparing actual results to theory.
A few months ago, I shared this paper that gave a theoretical framework for protein sequencing: pubs.acs.org/doi/10.1021/ac…
The author simulated how different factors, such as the # of readable amino acids (AAs) and the read length, would affect a protein sequencer's ability to unambiguously detect the 20,000 canonical human proteins in our bodies.
That chart is attached below.
I've marked in green where QSI currently stacks up. Based on its recent pre-print (linked below), Platinum can directly read seven (7) amino acids (F, Y, W, L, I, V, and R) with peptide reads that seem to max out around 20 AAs.
A recent publication by Dennis Lo et al applied long-read sequencing (LRS) in the prenatal screening (#NIPT) setting. It's a rather unorthodox technology/application pairing, and it's got me scratching my head a bit.
For context, earlier this year, Lo et al published a convolutional neural network ("the HK model") that enabled PacBio LRS devices to read methylation (5mC) across the entire genome with very high fidelity. This is important later.
@MJLBio@Sanctuary_Bio@Biohazard3737 Sure! I realize I was being a little vague with those statements. Generally, I think you're correct in your interpretation of the importance of P2 (great $/GB, but at a smaller scale) as well as duplex sequencing.
Something that is important to recognize, though ...
@MJLBio@Sanctuary_Bio@Biohazard3737 ... is how product deployment works differently between PacBio and Nanopore, which is partly an artefact of culture and of time in the public markets, in the public markets. I'm not advocating for one over the other with my next statements.
@MJLBio@Sanctuary_Bio@Biohazard3737 PacBio has been a public company for a long time. While the management has changed much since the failed Illumina merger, the familiarity with how to operate as a public company has not.
PacBio is more secretive and only unveils fully built-out commercial products.
I'd like to share my initial reaction to today's Berkeley Lights report. But first, I need to do some housekeeping. I can't comment on stock movements, share financial projections, or debate fair value.
Generally, I respect anyone who's put this much work into a topic. I won't pretend to have a clean rebuttal to every point. In my experience, beyond the hyperbole and hasty generalizations, there is some truth in these types of reports.
I want to soberly appraise those truths.
Also, I'd invite the subject-matter experts waiting in the wings to build off of this thread, add detail, or share their experiences. Ultimately, we're all after the same thing.
I will start with a few concessions and end with a few counterpoints to today's report: