"AI, Please Find Me 10 Important Genomics Headlines from the Past Month"

Header:  What do you get if you ask AI for "Ten Important Genomics Headlines from the Past Month?"

While I was grocery shopping, it occurred to me to ask my AI (Chat GPT 5.2) to find ten interesting and important clinical genomics headlines from the past month.    I had no idea if it could do that or not.

In fact, it gave me two ten-item lists to choose from (its List #1 and its List #2).   When I asked, it also told me how List 1 differed from List 2 (different search instructions).

So below, you'll see LIST NUMBER ONE, then LIST NUMBER TWO, then AI explains how it came up with the two different styles.

Note: The original AI report sometimes had multiple links per citation.  When copied to my blog, only the first link is maintained.  The symbol +2 or +3 indicates that the original native report had had more links.  

See also original output here;

https://chatgpt.com/share/694ac73b-c4b4-8005-9eef-743dd34d2ad2

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Please look at headlines of discoveries in the genomics industry, meaning clinical genomics, in the last 30 days, and summarize. Describe up to 10 of the most important items. Use internet.

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Note; Both lists start with "popEVE" then vary.

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LIST NUMBER ONE

Below are 10 notable “clinical genomics” developments with headlines/new publications from roughly Nov 22–Dec 22, 2025 (last ~30 days from today).

1. AI for variant interpretation (rare disease): popEVE

• New Nature Genetics work + clinical-facing writeups describe popEVE, an evolutionary + population–calibrated model aimed at prioritizing likely causal variants (especially missense), including scenarios without parental sequencing. Nature+2Harvard Medical School+2

2. Same-day / ultra-rapid clinical WGS gets closer to routine

• NEJM correspondence highlights a workflow directionally supporting same-day genome sequencing in critical care (clinical urgency use-cases like NICU). PubMed+1

3. ctDNA-guided adjuvant therapy in stage III colon cancer (DYNAMIC-III)

• Nature Medicine randomized phase 2/3 DYNAMIC-III results: ctDNA is clinically powerful for risk stratification, but the study also illustrates how hard it is to prove practice-changing noninferiority/superiority in real-world adjuvant decisions. Nature+2The ASCO Post+2

4. Method innovation: cfDNA methylation + copy number from one assay

• npj Precision Oncology (Dec 15) shows MeD-seq–based cfDNA analysis extracting methylation + CN + tumor fraction signals together, positioned as a more “affordable” platform for tumor-agnostic plasma detection and MRD/response applications. Nature

5. Regulatory direction: FDA proposed reclassification for oncology therapeutic nucleic-acid test systems

• FDA posted a proposed order (Nov 25) aiming to place certain oncology therapeutic nucleic-acid-based test systems into Class II (with special controls / 510(k) expectations still central). This is “policy plumbing,” but it can materially affect CDx/therapy-linked test development economics. Federal Register+2Federal Register+2

6. CRISPR-era outcomes inch forward in pediatrics

• New data reported for Casgevy (exagamglogene autotemcel) in younger children (5–11) with SCD/TDT supports potential label expansion; clinically, genomics-enabled therapies are increasingly tied to earlier intervention windows. Reuters

7. NIH puts dollars behind in-vivo genome editor delivery

• NIH’s TARGETED Challenge (multi-million prize) spotlights delivery as the bottleneck for in-vivo editing—important because delivery constraints often determine whether genome editing can move beyond niche indications. National Institutes of Health (NIH)

8. MRD test market continues to expand evidence packages (industry)

• Example: Telo Genomics announced a retrospective blood-based MRD study in myeloma with University of Athens as part of a larger validation program—illustrative of the broader “evidence build” race across MRD platforms. BioSpace

9. New ctDNA/MRD readouts continuing to populate major oncology meetings

• Example: NeoGenomics announced new ctDNA (RaDaR) research being presented at SABCS 2025 focused on residual disease/recurrence risk—part of an accelerating stream of meeting-driven clinical genomics updates. NeoGenomics, Inc.

10. Multi-omics liquid biopsy messaging shifts toward “systems” (AI + multi-omics)

• Gene Solutions’ ESMO Asia 2025 updates emphasize AI-powered multi-omics liquid biopsy positioning (screening/precision oncology)—reflecting how vendors are bundling analytics + multi-modal signals rather than “single biomarker” claims. PR Newswire+1

If you want, I can re-slice these 10 into the buckets your blog audience usually likes (e.g., MRD/ctDNA, rare disease/WGS, regulatory, gene editing) and add 1–2 “so what?” lines per item in your tone.

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LIST NUMBER TWO

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Here are 10 headline-level “clinical genomics” developments from roughly Nov 22–Dec 22, 2025 (last ~30 days), focusing on items most likely to matter for testing, clinical adoption, or near-term patient impact.

1. AI variant interpretation leap (popEVE) — A new model (“popEVE”) was reported to improve identification of pathogenic missense variants, including performance in large rare-disease family datasets and claims of better cross-population behavior vs prior tools. Why it matters: faster, more accurate rare disease diagnosis from existing sequencing. Financial Times

2. Genome “wiring diagram” at unprecedented resolution (Oxford MCC ultra) — Oxford researchers described a method (“MCC ultra”) mapping 3D genome structure down to single–base-pair resolution, linking physical genome organization to gene control. Why it matters: a plausible new path from “GWAS hit” → mechanism → drug target. University of Oxford

3. Long-read sequencing moves into routine care at scale (Radboudumc + Maastricht UMC+) — A major hospital system announced large-scale clinical deployment of long-read genome sequencing, starting at ~5,000 tests/year, with claims it can replace ~15 existing tests and increase diagnoses (including “>10% more” diagnoses for some rare diseases). Why it matters: this is the “implementation signal” that long-read is shifting from showcase to workflow standardization. Radboudumc

4. Personalized CRISPR “n=1” case gets fresh updates (Baby KJ) — Updates on the first hyper-personalized CRISPR treatment for a baby with CPS1 deficiency emphasized scalability questions and highlighted new efforts (e.g., ARPA-H programs) aimed at making individualized genetic medicines repeatable. Why it matters: the translational bottleneck is shifting from “can we edit?” to how to industrialize bespoke therapies. nucdf.org

5. CRISPR: Mainstream milestone coverage of the same CRISPR case — Broader reporting emphasized clinical milestones and continued monitoring, underscoring how quickly clinical genomics breakthroughs are becoming public-facing “proof stories.” Why it matters: raises expectations (patients, policymakers, investors) for personalized genetic medicines. People.com

6. CRISPR therapy expands toward younger children (Vertex/CRISPR’s Casgevy data) — New trial results were reported for ages 5–11 in sickle cell disease and transfusion-dependent beta thalassemia, supporting planned regulatory filings in 2026. Why it matters: expansion of genome-editing into broader pediatric use cases (and the related delivery/conditioning discussions). Reuters

7. ctDNA/MRD as an on-treatment “response barometer” across many tumors (Personalis NeXT Personal) — Reports around a new publication described ultrasensitive ctDNA dynamics correlating with immunotherapy response and survival across 24 solid tumor types (e.g., baseline detection and early-change/clearance concepts). Why it matters: strengthens the case for therapy-response monitoring as a routine genomic-adjacent biomarker, not just “recurrence after surgery.” GenomeWeb+1

8. Big-sequencing + “preventive WGS” collaboration (Illumina ↔ MyOme) — Illumina announced a collaboration and strategic investment with MyOme, oriented around clinical genomics + AI for earlier detection/prevention and a planned clinical trial. Why it matters: more capital/attention flowing into proactive WGS models (and, implicitly, the evidentiary/reimbursement fights that follow). Illumina+1

9. State-level gatekeeping signal for PGx (NYSDOH CLEP approval for SOLVD PreScript) — SOLVD reported New York State DOH CLEP approval for its pharmacogenomics test. Why it matters: NYS CLEP remains a meaningful “clinical legitimacy” checkpoint for certain genomic tests, even when federal pathways vary. Business Wire+1

10. Newborn screening policy expands for two rare genetic diseases (DMD, MLD) — Reuters reported HHS approval to add Duchenne muscular dystrophy and metachromatic leukodystrophy to the federal recommended newborn screening list. Why it matters: more infants identified early → rising demand for confirmatory genetic testing, specialty care pathways, and therapy access logistics. Reuters

If you want, I can also re-slice these into (A) sequencing/testing tech, (B) variant interpretation/AI, (C) gene therapy/editing, (D) policy/regulatory, and add 1–2 “so what for clinical labs” bullets under each.

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You just offered me two different approaches to finding 10 interesting genomics headlines from the last 30 days. Can you explain how the two methods differ.

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[BQ: Sounds like List 1 started from headlines and then ranked by value.  List 2 divided the space into multiple clinical zones, to be sure the results were stratified and varied.]

Sure. The two approaches differ in how you search, filter, and decide what counts as “important,” not just in how you present the results.

Here’s the clean distinction.

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Method 1: Headline-driven, news-first scan 

How it works

• Start with recent headlines (last ~30 days) from journals (NEJM, Nature Medicine, Nature Genetics), regulators (FDA/NIH), and industry press.

• Select items that are newly announced, published, or presented in that window.

• Importance is inferred from:

  • Where it appeared (top-tier journal, FDA notice, major meeting)

  • Whether it represents a new result, decision, or capability

What this method captures well

• “What just happened”

• Regulatory moves

• Trial readouts

• New assay classes or methods

• Things your readers might have missed last week

Strengths

• Time-accurate

• Defensible (“this really was new this month”)

• Good for newsletters, blogs, investor updates

Limitations

• Can feel heterogeneous or noisy

• Some items matter because of trajectory, not because the headline itself is dramatic

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Method 2: Theme- or bucket-driven curation 

How it works

• Start with pre-defined domains that matter to your audience:

  • MRD / ctDNA

  • Rare disease WGS

  • AI in variant interpretation

  • Regulatory / FDA

  • Gene editing / delivery

• Then ask: “What moved meaningfully in the last 30 days within each bucket?”

• Headlines are selected because they advance a storyline, not just because they are new.

What this method captures well

• Continuity across weeks or months

• Strategic inflection points

• Incremental but important progress

• Why multiple smaller headlines actually add up to something big

Strengths

• Much more analytical

• Ideal for policy blogs, strategy memos, client briefings

• Easier to add “so what?” commentary

Limitations

• Slightly less strict about “newsiness”

• Requires judgment calls about relevance and trend direction

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In short

Dimension	Headline-driven	Theme-driven
Starting point	What was published/announced	What domains matter
Time sensitivity	Very high	Moderate
Structure	Flat list	Organized buckets
Best for	News recap	Insight & strategy
Your typical use	“What happened this month?”	“What’s actually changing?”

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If you’d like, I can redo the same 10 items using the theme-driven method, with explicit trend lines and reimbursement/regulatory implications, which is usually where your genomics readers lean.