The arithmetic of asking one question at a time
A diagnostic lung biopsy is often about the size of a grain of rice, and a portion of it is already spent on the diagnosis itself. Morphology, then a panel of immunohistochemistry stains to establish that it is adenocarcinoma and not something else. What remains is what the molecular lab has to work with.
In many Indian labs, that remainder is spent sequentially. Is it EGFR. Run the assay, consume a section. Is it ALK. Run the assay, consume more. ROS1 next, if there is anything left.
The problem is not that anyone has chosen a bad order. EGFR and ALK are the highest-yield questions and testing them first is rational. The problem is that current guidelines for advanced non-squamous NSCLC point to roughly a dozen biomarkers, and a sequential workflow on limited tissue gets through three or four before the block is exhausted. The remaining questions are not answered negatively. They are never asked.
What happens next is not dramatic. The patient starts platinum doublet chemotherapy, which is a reasonable decision given the information available. Some weeks later, on a repeat biopsy nobody wanted to perform, or sometimes never, a finding turns up that would have changed the first line.
This is not a knowledge problem
It is worth being precise about what the constraint actually is, because it is frequently described as awareness.
The genes are known. EGFR, ALK, ROS1, RET, BRAF, KRAS G12C, MET exon 14 skipping, ERBB2, NTRK. The drugs exist and many are approved in India. The guidelines are written and freely available. Oncologists at nodal centres know all of this perfectly well.
What is scarce is tissue, and what is inefficient is the workflow that spends it one question at a time. Awareness campaigns do not add tissue to a block.
Why MET exon 14 skipping is the useful example
MET exon 14 skipping occurs in roughly three percent of non-squamous NSCLC. Small enough to be low on a sequential testing order. Large enough that a busy thoracic unit sees it.
It is also instructive about assay design, for a reason that is easy to miss.
There is no single mutation that causes it. The underlying genomic events are heterogeneous: base substitutions, small insertions and deletions clustered around the splice sites at either end of exon 14, and some point mutations in the juxtamembrane domain. What they share is not their sequence. It is their consequence. Exon 14 drops out of the transcript, exons 13 and 15 fuse, and the resulting receptor loses a regulatory domain.
This matters practically. A DNA-only assay has to cover a scattered set of intronic and splice-region positions well enough to catch whichever variant a given patient happens to carry, and coverage at those positions varies between panel designs. RNA reads the skipped transcript directly. It detects the event without needing to know which of the many possible underlying variants produced it.
So when a solid tumour panel is described as DNA plus RNA, that is not a specification detail. For fusion drivers and for splice events like this one, RNA is the part that closes the gap.
What one assay changes
The case for a comprehensive panel is not that more genes is better in the abstract. It is that asking every question in a single pass removes the point at which the tissue runs out.
One draw. One extraction workflow, DNA and RNA together. EGFR including exon 20 insertions, KRAS G12C, BRAF, ERBB2, MET exon 14 skipping, and the ALK, ROS1 and RET fusions, resolved in the same run rather than across four weeks of sequential assays.
There is a second argument that matters more to a lab director than to an oncologist. A pan-solid-tumour panel is not a lung panel, and its content extends well beyond thoracic oncology into breast, ovarian, endometrial and other solid tumours. For a nodal centre that is currently running separate assays across different tumour streams, that breadth is the point. One validated workflow, one analysis pipeline, one set of competencies to maintain, applied across the whole solid tumour caseload rather than per indication.
What fifty-seven genes does not cover
A comprehensive panel is not a complete one, and it is better to state this plainly on a public page than to have a molecular pathologist discover it in a proposal.
PD-L1 remains a separate test. It is immunohistochemistry, not sequencing, and for first-line NSCLC it is arguably still the single most consequential biomarker. No DNA and RNA panel replaces it, and any lung workflow needs it running in parallel.
NTRK is not on the 57-gene content. NTRK fusions are rare in NSCLC, and larotrectinib and entrectinib are tumour-agnostic approvals, but the gap is real and a thoracic oncologist scanning a gene list will look for it.
Tumour mutational burden is not estimable at this panel size. At 83.6Kb of target territory, TMB cannot be derived to the standard that established assays operating over roughly a megabase and above provide. A panel this size answers driver questions, not mutational burden questions.
Structural and copy number scope is narrower than a large panel. Amplifications, complex rearrangements and resistance mechanisms outside the panel content are outside what this assay reports.
None of this argues against a focused panel. It argues for describing one accurately. A lab choosing this workflow is choosing the guideline-relevant driver core with fusion and splice detection, run once on limited tissue, at community-lab economics. That is a real and defensible proposition. It is not everything, and saying it is invites the only question that ends the conversation.
Turnaround is an operational decision, not a property of the assay
Sequencing itself takes a day or two. Almost nothing in a molecular report's turnaround time is sequencing.
The queue is accession, review and macrodissection, dual nucleic acid extraction, quality control, library preparation, waiting for enough samples to fill a run, sequencing, bioinformatics, variant interpretation and curation, sign-out, and then the wait for the next tumour board.
The run economics shape this directly. The published configuration supports 24 to 32 samples per run on one flow cell type and up to 96 on another. A lab that waits for a plate to fill has just built a queue whose length depends on referral volume. A lab that commits to a fixed weekly run accepts some unfilled capacity and gets a predictable turnaround in exchange.
This is why turnaround claims should always name their conditions. A centre running fixed batches with variant interpretation and sign-out performed in house will report faster than one batching opportunistically and sending interpretation out. The assay is the same in both cases. The difference is operational, and it belongs in the conversation before a number does.
A note on what a finding is worth
Finding a driver is not the same as accessing the therapy.
Capmatinib is approved in India by the DCGI for MET exon 14 skipping positive advanced NSCLC, with a conditional requirement for a Phase IV study in Indian patients. Tepotinib has been used in Indian patients and the published experience is documented. But the Indian case series reporting those outcomes names access to these agents as one of its principal practical obstacles, alongside loss to follow-up.
So the honest claim is narrower than it is usually made. Comprehensive testing does not guarantee a patient receives a targeted therapy. It establishes whether one is even worth pursuing, which is the precondition for everything downstream: access programmes, trial eligibility, and the conversation between an oncologist and a family about what is available. Without the finding, none of that begins. With it, some of it becomes possible.
Where this leaves the workflow question
If your lab currently runs sequential single-gene and small-panel testing on lung biopsies, the useful question is not which panel is largest. It is a narrower one: of the last fifty lung cases, how many went to first-line treatment with fewer than half the guideline biomarkers resolved, and how many of those had tissue left for a second attempt.
That number is usually available and rarely calculated. It is also the only argument that matters, because it is the lab's own data rather than a vendor's.
Genique Lifesciences works with clinical and research laboratories across India on solid tumour sequencing workflows, including panel selection, validation support, and bioinformatics and interpretation infrastructure. If you are reviewing your lung workflow, we can walk through the arithmetic against your own case mix.
Write to contact@genique.co with your current lung workflow and case volume, and we will come back with a comparison against it.