Mendelspod Podcast

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For two decades, tests like Oncotype DX have helped oncologists decide which early-stage breast cancer patients should receive chemotherapy. But those tools were designed mainly to predict early recurrence, leaving physicians with far less clarity about the risk that cancer might return years later.
For today’s program, George Sledge, Chief Medical Officer at Caris Life Sciences, discusses new findings from the TAILORx trial showing how multimodal AI—combining molecular sequencing, digital pathology, and clinical data—can improve long-term prediction of breast cancer recurrence.
Sledge explains that breast cancer recurrence may actually reflect two different biological processes unfolding over time. Molecular signals captured through RNA analysis appear most informative for predicting recurrence in the first five years, while computational analysis of digital pathology images becomes especially powerful for predicting recurrence later in the disease course.
“The best results come from looking at multiple omic levels,” Sledge says, describing a shift away from single biomarker tests toward integrated biological analysis.

We began this podcast back around the time the ENCODE project announced that much of the genome was biochemically active. The big science project was undoing the tidy idea of “junk DNA,” and not without controversy. But activity is not the same as purpose. On today’s show, we move past the question of whether the non-coding genome does something and ask a more ambitious one: why has evolution retained so much genomic material unless it carries adaptive potential?
Theral speaks with Sudhakaran Prabakaran, computational biologist at Northeastern University and founder of NonExomics, about his provocative new book, “Eclipsed Horizons: Unveiling the Dark Genome.” Drawing on his lab’s work cataloging more than 250,000 non-canonical proteins, Prabakaran argues that regions outside traditional gene definitions are constantly generating novel open reading frames—previously unrecognized proteins that may shape adaptation, speciation, and disease.
Chapters:
(00:00) Identical Genomes, Wildly Different Fish
(04:00) The Dark Proteome Wakes Up
(10:00) Protein Pop-Up Shops
(20:00) Homo Minimus and the Space Thought Experiment
(30:00) Precision Medicine Beyond the Exome
From rapidly diversifying cichlid fishes to human accelerated regions (HARs) of the human genome linked to schizophrenia, he makes the case that protein birth and death is continuous, cheap, and exploratory. In his framing, the “dark genome” functions less like debris and more like a flexible evolutionary sandbox—capable of producing latent biological parts that can be deployed under stress or even extreme environments like spaceflight.
The book goes beyond ENCODE’s demonstration of activity and asks what that activity is for, crossing into that taboo in biology, teleonomic analysis. Weaving together proteomics, evolutionary biology, information theory, and even speculative extensions into space biology, Prabakaran suggests that genomes may be structured not just to preserve past adaptations, but to enable future ones.
For those of you staying put on the ground, the implications are very tangible for precision medicine. His company NonExomics is using non-canonical protein signatures to stratify cancer patients and refine difficult diagnoses, arguing that the next wave of biomarkers may lie outside the exome.
Provocative? Certainly. Grounded in emerging proteomics tools and real clinical cases? Also yes. This conversation probes directly into that mysterious future of biology.


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“We have been talking now for 15, 20 years about the diagnostic odyssey. That shouldn’t exist anymore. The new odyssey is the therapeutic odyssey.”
That’s Stephen Kingsmore, president and CEO of Rady Children’s Hospital (he just announced his retirement), explaining the impact of a new genome mapping technology from Illumina.
Whole-genome sequencing has transformed diagnosis, but some of the hardest pediatric cases persist because the structure of the genome has remained difficult to resolve. Today on Mendelspod, we cover Illumina’s newly launched proximity mapped reads, showing how long-range genomic context can be captured directly on existing Illumina sequencers and integrated into the lab workflow. The conversation traces how this added structural clarity is already improving diagnostic confidence and, critically, enabling highly precise n-of-1 therapies such as antisense oligonucleotides (ASOs).
Olivia Kim-MacManus, a pediatric neurologist and ASO trial leader, shows how the new diagnostic precision directly feeds therapeutic design.
“All of these genetic therapy approaches hinge on precise diagnostics,” she notes, emphasizing that allele-specific and haplotype-aware targeting is essential for ASOs and other emerging gene-based interventions.
From the product and workflow side, Ali Crawford joins us as Senior Director of Science Research at Illumina, detailing how the technology works without requiring new instruments or complex workflows, eliminating the need for separate library preparation steps.
“You just order the kit and go,” she says, highlighting how preserving spatial information on the flow cell unlocks variant calls and structural insight that were previously inaccessible with their standard short-read sequencing.
When genome structure comes into better focus, treatments are no longer theoretical.


This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.mendelspod.com/subscribe

This is a free preview of a paid episode. To hear more, visit www.mendelspod.com

CareDx is a company on the move. For years, they have been a bellwether in molecular diagnostics. Their early bet on gene expression testing in transplant medicine, their bruising fight over Medicare coverage, and their pivot into cell-free DNA monitoring have all reflected the growing pains of precision medicine itself.
Now, under CEO John Hanna, the company looks less like a single-test diagnostics firm and more like a clinical ecosystem.
Hanna brings an unusual vantage point. He began his career in health insurance before moving into molecular diagnostics—giving him insight into both innovation and reimbursement. That dual perspective shaped CareDx’s recent evolution: focus tightly on a defined clinical niche—transplantation—while expanding horizontally into the tools, software, and services that surround it.
Today, CareDx operates across three segments: lab products (including high-resolution HLA typing kits using PCR, NGS, and nanopore), a growing software and patient solutions business, and its flagship genomics portfolio led by AlloSure, its donor-derived cell-free DNA assay. What distinguishes the company now is its “solution selling” approach—engaging transplant centers not just with a test, but with workflow software, quality reporting tools, specialty pharmacy, and EMR integration.
“Our solution selling strategy is working,” he says today.
At the scientific core remains the effort to replace invasive biopsies with molecular monitoring. AlloSure’s innovation—detecting donor-derived cell-free DNA without requiring donor genotyping—made routine blood-based rejection monitoring scalable. Yet adoption is not purely technical.
“The biggest challenge with our space is building belief that molecular testing can replace tissue biopsy.”
Clinician education, clinical trials, and guideline inclusion remain central to shifting standards of care. CareDx has leaned heavily into this, hiring medical leadership specifically to translate data into practice. The company is also layering AI on top of its molecular assays. AlloSure Plus integrates genomic results with EMR-derived clinical variables to generate a rejection risk score. CareDx’s operational mantra has been to put the burden of complexity on the company, not the clinician.

Large-scale genomics is back — and this time, it’s global by design.
In this episode of Mendelspod, we return to the kind of ambitious, shared genomics project that helped define the field a decade ago. The Global Parkinson’s Genetics Program (GP2) has now genotyped more than 100,000 participants worldwide, with roughly one third of samples coming from historically underrepresented populations. That scale and diversity are already reshaping how Parkinson’s disease is studied — and how it may eventually be treated.
My guests are Andrew Singleton, co-lead of GP2, and Ignacio (Nacho) Mata, a geneticist at Cleveland Clinic and founder of the Latin American Research Consortium on the Genetics of Parkinson’s Disease (LARGE-PD). Together, they describe how globally representative datasets are not a political aspiration, but a scientific necessity — especially in an era of precision medicine.
Singleton explains that studying Parkinson’s across populations doesn’t just broaden participation; it increases scientific power.
“The more we learn about individual populations, the more we understand about disease as a whole — and the more chances we have to come up with treatments for disease as a whole,” he says.
Mata brings a complementary perspective from years of building Parkinson’s genetics infrastructure in Latin America. He emphasizes that without inclusion in genetic and biomarker research, entire populations risk being excluded from the next generation of molecularly targeted therapies.
“If we don’t have our patients studied for genetics or biomarkers, then those patients will not have access to the new treatments,” he notes, adding that GP2 is designed to narrow rather than widen existing health disparities.
We explores how GP2’s open-science structure has been key to its success and could serve as a model for other global research projects. GP2 has invested heavily in training and infrastructure so that researchers around the world can lead analyses locally, rather than simply contributing samples.
As both guests make clear, this is only the beginning. With hundreds of thousands of samples committed and a new generation of globally distributed investigators, GP2 is laying the groundwork for biologically defined subtypes of Parkinson’s and for more precise diagnostics and disease-modifying therapies.
When genomics gets big enough — and inclusive enough — scale itself becomes a discovery.


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