️ Episode 109: Autocrine Interferon Poisoning: ADAR1–BRCA Synthetic Lethality

In this episode of PaperCast Base by Base, we explore how loss of the RNA editor ADAR1 becomes lethal to BRCA1/2‑mutant cancer cells through a tumor‑cell‑autonomous interferon response, outlining a biomarker‑guided path to ADAR1‑targeted therapy.

Study Highlights:
A focused PRR siRNA screen and multiple orthogonal validations revealed a robust synthetic lethality between BRCA1/2 mutations and ADAR1 loss across isogenic human and mouse models, non‑isogenic TNBC lines, and zebrafish, with the cytoplasmic ADAR1p150 isoform and its deaminase activity required for survival. ADAR1 depletion elevated R‑loops, replication stress, γ‑H2AX foci, micronuclei, and apoptosis in BRCA‑deficient cells, while RNase H1 overexpression partially rescued DNA‑damage phenotypes and viability, implicating R‑loop burden as a trigger. The knockout activated cytosolic nucleic‑acid sensing pathways—RIG‑I, MDA5, LGP2, PKR, and cGAS—driving type I interferon and integrated‑stress responses; co‑silencing these sensors or inhibiting JAK/STAT signaling abrogated lethality, whereas exogenous interferons enhanced it. Patient data showed higher cytoplasmic ADAR1p150 expression and increased A‑to‑I RNA editing activity in BRCA‑mutant tumors and PDX models, indicating an ADAR1 dependency that is detectable in clinical specimens.

Conclusion:
These results establish a clinically actionable blueprint in which BRCA1/2 status predicts vulnerability to ADAR1 inhibition by exploiting autocrine interferon poisoning rather than DNA breaks, suggesting combinations and sequencing distinct from PARP inhibitor strategies.

Reference:
Autocrine interferon poisoning mediates ADAR1‑dependent synthetic lethality in BRCA1/2‑mutant cancers. Nature Communications. 2025;16:6972. https://doi.org/10.1038/s41467-025-62309-5

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

Support:
If you'd like to support Base by Base, you can make a one-time or monthly donation here: https://basebybase.castos.com/

 ADAR1; BRCA1/2; synthetic lethality; interferon; R-loops

️ Episode 108: Epigenome Editing Reverses HBG Silencing

In this episode of PaperCast Base by Base, we explore how targeted removal of CpG methylation at the HBG promoters causally reactivates fetal hemoglobin (HbF) without cutting DNA, revealing a precise path to treat β‑hemoglobinopathies.

Study Highlights:
A forward CRISPR screen in adult‑type erythroid cells (HUDEP2) pinpointed UHRF1, a DNMT1 cofactor, as a mediator of HBG repression; its disruption globally reduced CpG methylation and increased HbF, and promoter re‑methylation with dCas9‑DNMT3A/3L restored silencing. Targeted demethylation using a dCas9‑TET1 editor at six guides produced localized promoter demethylation and strong γ‑globin activation—raising HBG/(HBG+HBB) up to ~86%—with expression sustained for months in culture. In primary CD34+ cell‑derived erythroblasts, the same promoter‑focused demethylation increased HBG mRNA and HbF without altering maturation markers, and chromatin profiling showed higher accessibility and activating histone marks while BCL11A occupancy persisted. Induction correlated with combined demethylation across multiple CpGs upstream of the TSS rather than any single site, and introducing a methyl‑CpG‑binding‑deficient MBD2 mutant mimicked activation, supporting a model in which CpG methylation recruits MBD2‑NuRD to enforce silencing.

Conclusion:
Targeted epigenome editing of CpG methylation at HBG offers a DNA‑break‑free avenue for durable HbF induction in β‑hemoglobinopathies.

Reference:
Bell HW, Feng R, Shah M, Yao Y, Douglas J, Doerfler PA, Mayuranathan T, O’Dea MF, Li Y, Wang Y‑D, Zhang J, Mackay JP, Cheng Y, Quinlan KGR, Weiss MJ, Crossley M. Removal of promoter CpG methylation by epigenome editing reverses HBG silencing. Nature Communications. 2025;16:6919. https://doi.org/10.1038/s41467-025-62177-z

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

Support:
If you'd like to support Base by Base, you can make a one-time or monthly donation here: https://basebybase.castos.com/

HBG promoter; CpG methylation; epigenome editing; fetal hemoglobin (HbF); MBD2–NuRD

Episode 107: Genome-wide Association Study Reveals Genetic Links to Pulpal and Apical Diseases

In this episode of PaperCast Base by Base, we explore a large-scale genome-wide association study investigating the genetic underpinnings of pulpal and apical diseases. Using Finnish health registry data from over 485,000 individuals in the FinnGen cohort, researchers identified genetic loci linked to susceptibility to endodontic infections, independent of caries status.

Study Highlights:
The study analyzed three phenotypes—Pulpal and apical diseases, Pulpitis, and Necrosis of pulp or apical periodontitis—identifying 15 independent loci with genome-wide significance. Strong associations were found near the HORMAD2 gene on chromosome 22 and within the HLA class II region, particularly alleles DRB1*04:01 and DQB1*03:01. Functional analyses revealed that many of these loci regulate genes expressed in dental pulp tissue and are involved in immune pathways, especially antigen presentation via MHC class II. Replication in multiple cohorts confirmed associations for two HORMAD2-linked SNPs, and genetic correlations were observed between endodontic infections and pain, autoimmune, and cardiometabolic traits.

Conclusion:
These findings highlight immune dysregulation as a key mechanism in the pathogenesis of endodontic infections, opening new avenues for prevention, risk assessment, and targeted therapies.

Reference:
Salminen A, Hyvärinen K, Ritari J, Leppilahti JM, Palotie U, Vuollo V, et al. Genome-wide association study of pulpal and apical diseases. Nature Communications. 2025;16:6774. https://doi.org/10.1038/s41467-025-61721-1

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

Support:
If you'd like to support Base by Base, you can make a one-time or monthly donation here: https://basebybase.castos.com/

On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.

Keywords: GWAS, pulpitis, apical periodontitis, HLA, immune dysregulation

️ Episode 106: Decoding Brain Maps for Pharmacotranscriptomics

In this episode of PaperCast Base by Base, we explore a Nature Communications study, that introduces a fast, surface-based framework to decode imaging-derived brain phenotypes by aligning high-resolution cortical gene-expression maps with PET targets and structural MRI patterns. The work validates gene–protein correspondences in the serotonergic system and then dissects how GABAA_AA​ receptor subunit expression partitions the cortex into limbic-enriched and broadly cortical systems that relate to anxiety and depression traits.

Study Highlights:
The authors generate vertex-level cortical expression maps from the Allen Human Brain Atlas using geodesic kriging, reduce them to co-expression gradients with spatially autocorrelation-preserving nulls, and compare three decoding strategies—gradient-based vertex-level tests, linear mixed-effects, and generalized least squares—against serotonergic PET atlases. Applying the method to a benzodiazepine-binding PET atlas, they resolve two classes of GABAA_AA​ subunit genes: Cluster 1 (α2/α3/α5, β1/β3, ε, γ1) with limbic-biased expression and Cluster 2 (α1/α4, β2, γ2/γ3, δ) with widespread cortical expression. They align cortical thickness phenotypes from 279 participants to these signatures and stratify individuals into two neuroanatomical subgroups whose deviations from normative cortical thickness trajectories track with limbic versus widespread GABA signatures. In adults, higher anxiety co-varies with greater cortical-thickness deviations within regions showing high expression of the limbic Cluster 1 signature, supporting a mechanistic bridge between molecular targets and behavior.

Conclusion:
Imaging transcriptomics can function as in vivo pharmacotranscriptomics, suggesting subunit- and pathway-specific targets and stratification markers for precision interventions in neuropsychiatry.

Reference:
Ecker C, Pretzsch C M, Leyhausen J, Berg L M, Gurr C, Seelemeyer H, McAlonan G, Puts N A, Loth E, Dell’Aqua F, Mason L, Charman T, Oakley B, Bourgeron T, Beckmann C, Buitelaar J K, Arango C, Banaschewski T, Chiocchetti A G, Freitag C M, Hattingen E, Krueger-Burg D, Schmeisser M J, Repple J, Reif A & Murphy D G. Transcriptomic decoding of surface-based imaging phenotypes and its application to pharmacotranscriptomics. Nature Communications (2025). https://doi.org/10.1038/s41467-025-61927-3

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

Support:
If you'd like to support Base by Base, you can make a one-time or monthly donation here: https://basebybase.castos.com/

 On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.

️ Episode 105: Genome-level Selection as a Universal Marker of Cancer Therapy Resistance

In this episode of PaperCast Base by Base, we explore groundbreaking research revealing how the evolutionary dynamics of tumor genomes can serve as a universal marker of resistance to cancer therapy. By analyzing whole-exome sequencing data from multiple cancer types—both treated and untreated—the study uncovers a consistent evolutionary signal that correlates with treatment failure and poor prognosis.

Study Highlights:
The authors examined the strength of protein-level selection (dN/dS) and mutational burden (N) across diverse patient cohorts, including colorectal, esophageal, lung, breast, bladder, glioblastoma, leukemia, and multiple myeloma. In untreated cancers, dN/dS values remained stable during primary tumor progression, with some cancer-specific changes in metastases. In stark contrast, resistant tumors from treated patients showed a near-universal shift toward neutral evolution (dN/dS ≈ 1), a state linked to higher tumor fitness and worse outcomes. This shift was validated in both published datasets and a large original multiple myeloma cohort, and was consistent across solid tumors and hematologic malignancies. Analyses of sequential biopsies and phylogenetic trees revealed a bi-phasic evolutionary pattern: early positive selection of driver mutations followed by late purifying selection against deleterious passengers, with the neutral regime marking maximal tumor adaptability.

Conclusion:
Monitoring the selection regime of tumor genomes during treatment could provide a valuable biomarker to guide clinical decisions, enabling timely adjustments in therapy when resistance emerges.

Reference:
Persi E, Sudalagunta PR, Wolf YI, Canevarolo RR, Damaghi M, Shain KH, Silva AS, Koonin EV. Genome-level selection in tumors as a universal marker of resistance to therapy. Nature Communications. 2025;16:6535. doi:https://doi.org/10.1038/s41467-025-61709-x

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

Support:
If you'd like to support Base by Base, you can make a one-time or monthly donation here: https://basebybase.castos.com/

Episode 104: Cross-population GWAS and proteomics improve risk prediction and reveal mechanisms in atrial fibrillation

In this episode of PaperCast Base by Base, we explore a large cross-ancestry study that integrates genome-wide association results with plasma proteomics to map genetic architecture, nominate causal pathways and proteins, and boost risk prediction for atrial fibrillation (AF).

Study Highlights:
The authors meta-analyzed AF across ancestries—more than two million participants overall—and reported 525 genome-wide significant loci among 168,007 AF cases, with PITX2 and ZFHX3 emerging as shared signals across populations. Gene prioritization and pathway enrichment reinforced core roles in muscle contraction and cardiogenesis and highlighted additional mechanisms such as TGF-β signaling and electrical coupling. Mendelian randomization linked multiple modifiable traits—adiposity measures, LDL cholesterol, type 2 diabetes, blood pressure, smoking, alcohol use, sedentary behavior, and insomnia—to AF risk. Protein-wide Mendelian randomization nominated 28 circulating proteins with potential causal effects on AF, several of which already have drugs in other indications. Finally, combining a polygenic risk score with a protein score substantially improved incident AF prediction, achieving an AUC of 0.823 and outperforming either component alone.

Conclusion:
Together, cross-ancestry genetics plus proteomics sharpen AF biology, spotlight prevention targets, and move multi-omic risk stratification closer to clinical application.

Reference:
Yuan S, Chen J, Ruan X, Li Y, Abramowitz SA, Wang L, Jiang F, Xiong Y, Levin MG, Voight BF, Gill D, Burgess S, Åkesson A, Michaëlsson K, Li X, Damrauer SM, Larsson SC. Cross-population GWAS and proteomics improve risk prediction and reveal mechanisms in atrial fibrillation. Nature Communications. 2025;16:6426. doi:10.1038/s41467-025-61720-2

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

Support:
If you'd like to support Base by Base, you can make a one-time or monthly donation here: https://basebybase.castos.com/

On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.

️ Episode 103: Genome Sequencing Forecasts Outcomes After Congenital Cardiac Surgery

In this episode of PaperCast Base by Base, we explore how large-scale exome sequencing combined with explainable AI can predict adverse outcomes after surgery for congenital heart defects. Using a prospective cohort from the Pediatric Cardiac Genomics Consortium, the study links specific genetic pathways to real-world postoperative risks and shows how genomics sharpens clinical risk stratification.

Study Highlights:
A prospective observational cohort of 2,253 patients underwent whole-exome sequencing; variants were prioritized with an AI genome-interpretation tool, cardiac phenotypes were auto-classified, and Bayesian networks quantified risk. Damaging de novo variants in chromatin-modifying genes and recessive/biallelic genotypes in cilia-related genes were associated with higher probabilities of mortality, cardiac arrest, and prolonged ventilation, whereas their absence lowered risk. Effects were strongest in high-complexity surgeries and specific phenotypes—such as left-ventricular outflow tract obstruction/hypoplastic left heart for chromatin genes and heterotaxy for cilia genes—and were amplified by extra-cardiac anomalies. The framework delivers personalized, clinically relevant risk estimates that can inform pre-operative planning, including proactive respiratory strategies for patients with ciliary dysfunction.

Conclusion: Genomic profiling at or before surgery can meaningfully refine outcome forecasts for children with complex CHD, supporting earlier, targeted interventions and more precise peri-operative care.

Reference:
Watkins WS, Hernandez EJ, Miller TA, et al. Genome sequencing is critical for forecasting outcomes following congenital cardiac surgery. Nature Communications. 2025;16:6365. https://doi.org/10.1038/s41467-025-61625-0  

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

Support:
If you'd like to support Base by Base, you can make a one-time or monthly donation here: https://donate.stripe.com/bJe6oI2GD0co7oE9iWcMM00

On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.

Episode 102: Clinical Impact of Pharmacogenetic Risk Variants in a Large Chinese Cohort

In this episode of PaperCast Base by Base, we explore how large-scale pharmacogenomics translates to real-world care using data from the Taiwan Precision Medicine Initiative. We follow a Nature Communications study that analyzes gene–drug interactions across 486,956 Han Chinese participants, quantifying how pharmacogenetic risk variants shape adverse drug events and effectiveness in routine practice while situating the findings within broader themes such as gene–disease association, variant interpretation, functional and structural genomics, and clinical deployment of precision medicine.

Study Highlights:
Using custom SNP arrays with imputation and targeted validation, the authors profiled actionable variants across 19 pharmacogenes and linked them to prescriptions and outcomes captured in longitudinal electronic medical records. They focused on four well-powered gene–drug pairs—NUDT15/TPMT with azathioprine, CYP2C19 with clopidogrel, ABCG2/SLCO1B1/CYP2C9 with statins, and CYP2C9 with NSAIDs—to estimate risks of myelosuppression, major adverse cardiovascular events, statin-associated muscle events, and gastrointestinal/renal toxicity. Across analyses, pharmacogenetic risk variants showed statistically significant associations with adverse events, yet the absolute excess risks were modest and most carriers tolerated therapy without predicted side effects. The work underscores implementation complexity: benefits depend on clinical context and competing risks, with high-frequency actionable loci in East Asian populations and non-genetic factors (like comorbidities and drug–drug interactions) often driving outcomes. Notably, limitations in resolving CYP2D6 structural variation from array data precluded analysis of several key pairs, motivating future whole-genome sequencing and standardized phenotyping.

Conclusion:
Large-scale PGx can inform risk-aware prescribing in diverse populations, but integrating genotype with comorbidities, concomitant medications, and improved genotyping (e.g., WGS) is essential to unlock clinical utility at population scale.

Reference:
Wei, C.-Y., Wen, M.-S., Cheng, C.-K., Sheen, Y.-J., Yao, T.-C., Lee, S.-L., et al. Clinical impact of pharmacogenetic risk variants in a large Chinese cohort. Nature Communications. 2025;16:6344. https://doi.org/10.1038/s41467-025-61644-x

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.

️Episode 101: JAK2 Inhibition Selects RAS-Mutant Clones in Myelofibrosis

In this episode of PaperCast Base by Base, we explore how JAK2 inhibition with ruxolitinib can reshape clonal architecture in myeloproliferative neoplasms (MPN), favoring outgrowth of RAS‑pathway mutant subclones and altering patient outcomes. We situate these findings within the broader landscape of genomics, functional and structural genomics, and proteomics—touching on themes like gene–disease association, variant interpretation, and resistance mechanisms in targeted therapies.

Study Highlights:
Using a longitudinal myelofibrosis cohort with paired molecular evaluations, the authors show that patients exposed to ruxolitinib preferentially acquire or expand RAS pathway mutations, with variant allele frequencies increasing over time and a higher prevalence of multiple RAS‑mutant clones; in contrast, such enrichment is uncommon in untreated patients and RAS status predicts poorer overall and transformation‑free survival only under ruxolitinib exposure. Single‑cell DNA sequencing and ex vivo treatment of primary CD34+ cells demonstrate that RAS‑mutant clones gain a fitness advantage under JAK/STAT inhibition in both wild‑type and hyper‑activated JAK/STAT contexts, while canonical MPN driver allele burdens often decline. In vitro and in vivo competition assays, alongside shRNA‑mediated JAK2 knockdown, show increased proliferation and clonogenicity of RAS‑mutant cells during JAK2 inhibition, and co‑treatment with a MEK inhibitor partially reverses this advantage. Mechanistically, MAPK pathway activation and JAK2 downregulation correlate with release from oncogene‑induced senescence and increased cell‑cycle progression in RAS‑mutant cells, and external datasets further associate RAS alterations with resistance to multiple JAK2 inhibitors.

Conclusion:
Screening for pre‑existing RAS pathway mutations and monitoring clonal evolution during JAK2‑inhibitor therapy may inform risk, guide combination strategies, and ultimately improve MPN patient management.

Reference:
Maslah N, Kaci N, Roux B, Alexe G, Marie R, Pasquer H, Verger E, Daltro De Oliveira R, Culeux C, Mlayah B, Gauthier N, Gonzales F, Zhao L‑P, Ganesan S, Gou P, Ling F, Soret‑Dulphy J, Parquet N, Vainchenker W, Raffoux E, Padua RA, Giraudier S, Marty C, Plo I, Lobry C, Stegmaier K, Puissant A, Kiladjian J‑J, Cassinat B, Benajiba L. JAK2 inhibition mediates clonal selection of RAS pathway mutations in myeloproliferative neoplasms. Nature Communications. 2025;16:6270. doi:10.1038/s41467-025-60884-1

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.

️ Episode 100: Epigenomic Diagnosis and Prognosis of Acute Myeloid Leukemia

In this episode of PaperCast Base by Base, we explore a groundbreaking study that maps the epigenomic landscape of Acute Myeloid Leukemia (AML) and develops powerful diagnostic and prognostic tools for clinical use. The research introduces the Acute Leukemia Methylome Atlas (ALMA), integrating large-scale DNA methylation data, machine learning, and long-read sequencing to refine subtype classification and predict patient outcomes.

Study Highlights:

The authors harmonized DNA methylation profiles from 3,314 patient samples across 11 cohorts to build ALMA, an interactive atlas that visualizes hematopoietic heterogeneity and enables precise AML subtype classification. Using this resource, they developed two prognostic models: AML Epigenomic Risk, based on genome-wide methylation patterns, and a concise 38-CpG signature, both predicting five-year overall survival across pediatric and adult cohorts. They implemented a specimen-to-result protocol using nanopore sequencing, achieving high concordance between epigenomic predictions and genomic lesions, and demonstrated robustness across diverse clinical scenarios. While rare subtypes remain challenging due to limited training data, both models significantly outperformed current risk stratification systems.

Conclusion:

This work paves the way for faster, more affordable, and more accurate diagnosis and prognosis in AML, with potential to transform personalized treatment strategies.

Reference:

Marchi, F., Shastri, V. M., Marrero, R. J., Nguyen, N. H. K., Öttl, A., Schade, A-K., Landwehr, M., Krali, O., Nordlund, J., Ghavami, M., Sckaff, F., Mansinghka, V. K., Cao, X., Slayton, W., Starostik, P., Cogle, C. R., Ribeiro, R. C., Rubnitz, J. E., Klco, J., Elsayed, A., Gamis, A. S., Triche, T. J., Ries, R., Kolb, E. A., Aplenc, R., Alonzo, T., Pounds, S., Meshinchi, S., & Lamba, J. K. (2025). Epigenomic diagnosis and prognosis of Acute Myeloid Leukemia. Nature Communications, 16, 6961. https://doi.org/10.1038/s41467-025-62005-4

License:

This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.