**Monday Immune Engager** — our weekly pick from the latest immune-engager digest.

**Paper:** [Combination therapy with a novel CD2-targeted costimulatory bispecific antibody overcomes limitations of CD3 T cell engager treatment for solid tumors](https://doi.org/10.1080/19420862.2026.2684378)

**Authors:** Welbeck Danquah, Mélanie Pichery, Thomas Eden, Aurelien Boyance, et al.

**Journal:** mAbs, 2026

**Why it matters:** CD3 T cell engagers have transformed blood cancer treatment but largely failed in solid tumors — this study proposes a modular two-drug strategy that separates T cell activation signals to rescue efficacy while dramatically reducing systemic toxicity.

---

**Summary**

CD3 T cell engagers (TCEs) work by bridging a T cell directly to a tumor cell, providing what immunologists call Signal 1. In blood cancers this is often sufficient, but solid tumors present an immunosuppressive microenvironment that demands a second costimulatory signal (Signal 2) for a sustained cytotoxic response. Pushing TCE doses higher to compensate triggers severe dose-limiting toxicities before the tumor is controlled — a bottleneck that has left tarlatamab as the only approved classical TCE for solid tumors. The Evotec team's solution is to keep the two signals as entirely separate drugs: a conventional EpCAM×CD3 TCE (solitomab) for Signal 1, and a novel HER2×CD2 bispecific for Signal 2.

The CD2 arm is built on a non-blocking antibody that acts as a positive allosteric modulator — rather than competing with CD58, the tumor's natural CD2 ligand, it increases CD2–CD58 binding by over twofold, amplifying the natural immune adhesion while simultaneously providing artificial costimulation. The Fc domain is silenced to prevent macrophage-mediated depletion of CD2-expressing T cells. In humanized xenograft mice bearing established HER2-positive breast tumors, the combination achieved complete tumor remission in 8 of 9 animals at a TCE dose that produced remission in only 1 of 9 when used alone.

Two additional findings underscore the approach's clinical relevance. First, when tumor cells were engineered via CRISPR-Cas9 to completely lack CD58 — mimicking a well-documented immune escape mechanism — the HER2×CD2 combination physically bridged the T cell to the tumor anyway, boosting TCE killing efficacy 25–35-fold over the TCE alone. Second, because CD28 expression is lost from a large proportion of CD8⁺ killer T cells with aging, CD28-targeted costimulatory strategies may be ineffective in the elderly patients who make up most solid tumor cases; CD2 expression remains robust on these cells. In a direct head-to-head comparison at matched killing efficacy, the CD2 bispecific induced only up to a 2-fold increase in IL-6, TNF, and IL-2, compared to up to a 200-fold increase from a comparable HER2×CD28 bispecific.

---

**Three takeaways**

1. Adding the HER2×CD2 bispecific to a sub-efficacious low dose of an EpCAM×CD3 TCE restored full anti-tumor cytotoxicity in vitro (~10-fold improvement) and drove complete tumor remission in 8 of 9 humanized mice versus 1 of 9 with the TCE alone.

2. The CD2 combination overcame CD58 loss — a common tumor immune escape route — by physically forcing T cell–tumor contact, boosting TCE efficacy 25–35-fold against CD58-knockout cancer cells.

3. CD2 costimulation effectively engaged CD28-negative CD8⁺ T cells (the dominant cytotoxic subset in elderly patients and solid tumors) while triggering up to 200-fold less pro-inflammatory cytokine release than a matched-efficacy HER2×CD28 bispecific.

---

**Read the source:** https://doi.org/10.1080/19420862.2026.2684378

**Top Trending Friday** — our weekly pick of the top-trending paper on r/science this week.

**Paper:** [A 5.3-million-year-old deep-sea whale necropolis in the Diamantina Zone](https://doi.org/10.1038/s41586-026-10546-z)

**Authors:** Xiaotong Peng, Peng Zhou, Xikun Song, Giovanni Bianucci, et al.

**Journal:** Nature, 2026

**Why it matters:** The discovery of a 1,200-kilometer accumulation of whale skeletons in the southeastern Indian Ocean rewrites the known depth limits of complex ecosystems and establishes the deep seafloor as a multi-million-year fossil archive for cetacean evolution.

---

**Summary**

In 2023, researchers piloting the human-occupied submersible *Fendouzhe* mapped the Diamantina Zone, a V-shaped trench in the southeastern Indian Ocean plunging between 4,600 and 7,000 meters depth. They documented 485 whale sites across roughly 1,200 kilometers of seafloor — 476 fossilized and five actively decomposing — shattering the previous global record of a few dozen known whale-fall sites, nearly all at shallower depths. The deepest active community was observed at 6,789 meters, far exceeding the previous depth record of ~4,200 meters for any whale-fall ecosystem.

The five active sites were all in the sulfur-philic stage, in which anaerobic bacteria metabolize lipids stored in whale bone marrow and produce hydrogen sulfide — a toxin to most life but the chemical foundation of a chemosynthesis-based food web (one that replaces sunlight with chemical energy). Organism densities reached 2,840 individuals per square meter, dominated by *Osedax* "zombie" worms (which bore into bone using secreted acid and digest lipids via symbiotic gut bacteria), chemosynthetic bivalves hosting sulfur-oxidizing bacteria in their gills, brittle stars, and — notably — *Xyloplax* sea daisies previously known only from sunken wood. The authors propose a "super corridor" hypothesis: with an estimated density of ~8 whale falls per square kilometer, the trench provides densely packed stepping stones allowing specialized larvae to disperse between falls, and onward to hydrothermal vents and cold seeps, across otherwise barren abyssal plains.

Strontium isotope dating (exploiting the fact that seawater's Sr-87/Sr-86 ratio shifts predictably over geologic time and becomes locked into bone mineral) of 33 fossil specimens yielded ages ranging from 120,000 years to 5.26 million years ago, with the oldest belonging to a newly described extinct beaked whale, *Pterocetus diamantinae*. Preservation over such timescales is attributed to an ultra-low sedimentation rate (<0.5 cm per 1,000 years), ferromanganese oxide coating that petrifies exposed surfaces, and the extraordinary bone density — pachyosteosclerosis — of beaked whale rostra, which resists both biological boring and chemical dissolution.

---

**Three takeaways**

1. Active whale-fall communities were documented at 6,789 meters depth, extending the known hadal depth limit for complex chemosynthesis-based ecosystems by more than 2,500 meters beyond the previous record.

2. Strontium isotope dating confirmed continuous whale-fall deposition in the Diamantina Zone since at least 5.26 million years ago, with the oldest specimen — a newly named extinct beaked whale — preserved on the open seafloor for over five million years.

3. Sea daisies (*Xyloplax* spp.), previously recorded only on sunken wood, were found colonizing whale bone at depths exceeding 5,600 meters, demonstrating that specialized deep-sea fauna can transition between chemically analogous organic-fall substrates.

---

**Read the source:** https://doi.org/10.1038/s41586-026-10546-z

**Monday Immune Engager** — our weekly pick from the latest immune-engager digest.

**Paper:** [Discovery of TCR-like antibodies to the KRAS G12D neoantigen via in silico-in vitro workflow](https://doi.org/10.1016/j.ymthe.2026.05.032)

**Authors:** SangPhil Ahn, Tae-Sung Oh, Seonghyuk Suh, Joon-Young Jeon, et al.

**Journal:** Molecular Therapy, 2026

**Why it matters:** A hybrid computational-experimental pipeline now offers a practical route to generate stable, high-affinity antibodies against intracellular oncoproteins — a class of targets that has long resisted conventional drug discovery.

---

**Summary**

KRAS G12D is one of the most prevalent oncogenic mutations in pancreatic, colorectal, and lung cancer, yet it sits inside the cell, beyond the reach of conventional antibody drugs. The cell's own antigen-presentation machinery offers a workaround: proteasomal degradation continuously loads short peptide fragments of intracellular proteins onto MHC class I complexes (here, HLA-C\*08:02) for display at the surface. TCR-like antibodies — synthetic immunoglobulins engineered to recognize these peptide–MHC complexes — could exploit this window, but traditional screening tends to produce binders that grip the large, invariant HLA scaffold rather than the tiny, single-amino-acid-variant peptide, creating a catastrophic off-target risk.

To solve this, the authors built a two-stage pipeline. In the computational stage, the inverse-folding model ProteinMPNN was used to redesign only the complementarity-determining region (CDR) loop tips of human antibody variable fragments docked against the KRAS G12D–HLA-C\*08:02 complex, leaving the backbone fixed to prevent misfolding. The nine top-scoring designs seeded a yeast surface-display library for iterative selection, including negative selection against cells pulsed with a SARS-CoV-2 peptide to eliminate cross-reactive binders. X-ray crystallography at 4.5 Å confirmed the final antibody contacts the mutant aspartate at position 3 and lysine at position 7 directly — notably, AlphaFold2 failed to predict this interface accurately, underscoring that physical validation remains essential.

Final affinity maturation and solubility engineering yielded variants with KD values as low as 2.38 nM and no detectable human off-target reactivity by phage display profiling. When the targeting head was reformatted as a CAR-T construct or a bispecific T-cell engager (SCDB), both formats selectively killed KRAS G12D-positive cells while sparing wild-type KRAS cells in vitro. The study's main limitation is that all cytotoxicity data are from cell-based assays; in vivo efficacy and safety remain to be demonstrated.

---

**Three takeaways**

1. A combined in silico–in vitro workflow — structural docking plus constrained CDR redesign by ProteinMPNN, followed by yeast display selection with rigorous negative sorting — produced antibodies with ~70-fold affinity improvement over the initial hit (KD 1.36 µM → 17.4 nM), ultimately reaching 2.38 nM after solubility engineering.

2. Solubility-focused amino acid substitutions (variants DQE and DE) eliminated hydrophobic aggregation patches, dramatically improving manufacturing yield while simultaneously boosting affinity — a result not typically expected from solubility optimization.

3. The same targeting head retained its exquisite peptide selectivity in both CAR-T and SCDB formats, driving dose-dependent, selective cytotoxicity against KRAS G12D-positive target cells with no detectable killing of wild-type KRAS cells.

---

**Read the source:** https://doi.org/10.1016/j.ymthe.2026.05.032

**Top Trending Friday** — our weekly pick of the top-trending paper on r/science this week.

**Paper:** [Work from Home and Disability Employment](https://doi.org/10.1257/aeri.20240538)

**Authors:** Nicholas Bloom, Gordon B. Dahl, Dan-Olof Rooth

**Journal:** American Economic Review: Insights, 2025

**Why it matters:** The post-pandemic rise in remote work appears to have accomplished more for disability employment than three decades of targeted legal mandates ever did.

**Summary**

Between 2019 and 2024, full-time employment for working-age adults with physical disabilities surged roughly 14% — an unprecedented divergence from employment trends for non-disabled workers, which remained essentially flat over the same period. Bloom, Dahl, and Rooth ask whether the concurrent fourfold increase in work-from-home (WFH) rates caused this surge, or whether a tight post-pandemic labor market and shifting demographics are responsible.

To isolate the causal effect of WFH, the authors clear three methodological hurdles. First, they restrict their sample to the five physical disability categories in the Current Population Survey (hearing, vision, ambulatory, self-care, and independent living), dropping the cognitive category entirely — its population grew by over a million during the pandemic, likely due to long COVID and anxiety, which would artificially inflate apparent employment gains. Second, they measure WFH rates using only non-disabled workers within each occupation, preventing reverse causality: individuals with disabilities make up roughly 3% of the workforce and cannot plausibly have driven a society-wide 400% shift in remote work adoption. Third, they exploit variation across 86 occupational codes — comparing high-WFH occupations like computer science against low-WFH ones like secondary teaching — while flexibly controlling for general employment growth within each occupation to strip out the effect of labor market tightness.

The resulting causal estimate is a 1.0% increase in full-time disability employment for every 1 percentage point rise in WFH, strengthening to 1.3% when the authors use a pre-pandemic instrumental variable (the Dingel–Neiman remote-work feasibility index) that is entirely free of pandemic-era demand shocks. To determine *why*, the team examined wage data using a triple-difference model comparing disabled and non-disabled workers in the same remote-heavy occupations. Relative wages for disabled workers fell 4.2% — a textbook signature of an outward labor supply shift, not a demand shock. Workers previously locked out by commuting barriers and inaccessible office environments entered the market once those frictions disappeared, and their influx outpaced employer demand, pushing relative wages down even as employment climbed.

**Three takeaways**

1. A 1 percentage point increase in WFH within an occupation causally increases full-time employment for physically disabled workers by 1.0–1.3%, depending on the estimation strategy.

2. The post-pandemic expansion of remote work accounts for 68–85% of the total rise in full-time employment for this demographic — ruling out labor market tightness as the primary driver.

3. A 4.2% relative wage decline for disabled workers in high-WFH occupations, alongside rising employment, is consistent with a labor supply expansion: WFH removed commuting and workplace accessibility barriers, drawing a large latent workforce into the market.

**Read the source:** https://doi.org/10.1257/aeri.20240538

**Paper:** [From free speech advocates to critics: The Trump administration's new rhetoric promotes support for censorship among Trump voters](https://doi.org/10.1073/pnas.2532084123)

**Authors:** Matthew E. K. Hall, B. Tyler Leigh, Brittany C. Solomon

**Journal:** Proceedings of the National Academy of Sciences, 2026

**Why it matters:** The study offers rare experimental evidence — using real, not hypothetical, elite rhetoric — that partisan cues can meaningfully erode public commitment to one of the most widely endorsed democratic norms in the United States.

---

**Summary**

Following the assassination of conservative activist Charlie Kirk, the Trump administration's messaging shifted from championing free speech to explicitly endorsing restrictions on it — an unusual move for a sitting president. Researchers at the University of Notre Dame seized on this as a natural experimental stimulus and conducted a pre-registered survey experiment (meaning hypotheses, sample sizes, and statistical models were publicly locked in before any data were collected) with 13,305 quota-matched U.S. adults in October 2025. Participants were randomly assigned to read real anti-speech quotes from Trump and his allies, researcher-generated pro-speech quotes in a similar style, or no quotes at all, and their support for government censorship of out-party media and individuals was then measured.

Among Trump voters exposed to the anti-speech rhetoric, support for censoring the opposing party increased significantly — a shift of roughly 0.35 on a standard scale, translating to approximately one in three respondents moving from opposition or neutrality toward acceptance of censorship. The researchers describe this migration toward indifference as "democratic neutrality," arguing that a norm does not require passionate authoritarians to collapse; it only requires enough people to stop actively defending it. The pro-speech control quotes, by contrast, produced no measurable effect in either direction, suggesting that confirming an existing baseline belief does not trigger the same cognitive reprocessing that a norm violation does.

One particularly striking finding — and a key methodological strength — was that stripping Trump's name from the quotes and attributing them to a generic "prominent politician" produced identical results. The rhetoric moved attitudes at the same rate regardless of explicit attribution, indicating that the grievance framing and linguistic style had been sufficiently internalized to function as a partisan signal on their own. A notable caveat is that the study captures a short-term attitudinal snapshot; whether repeated exposure consolidates these shifts into durable opinion change remains an open question.

---

**Three takeaways**

1. Exposure to explicit anti-speech rhetoric from Trump and his allies produced a statistically significant increase in support for government censorship of the out-party among Trump voters (β = 0.35), shifting roughly one in three toward a position of democratic neutrality.

2. The identical rhetoric had the opposite effect on non-Trump voters — Harris voters, third-party voters, and non-voters — who responded with a significant backlash, becoming meaningfully *more* protective of out-party speech.

3. The attitudinal shifts occurred at equivalent rates whether or not the quotes were attributed to Trump by name, demonstrating that the rhetorical style and grievance framing alone were sufficient to trigger partisan realignment without an explicit source label.

---

**Read the source:** https://doi.org/10.1073/pnas.2532084123

**Monday Immune Engager** — our weekly pick from the latest immune-engager digest.

**Paper:** [MAGE-A4/MAGE-A8-targeted TCR-based bispecific T cell engager in recurrent and/or refractory solid tumors: a phase 1 trial](https://doi.org/10.1038/s41591-026-04455-x)

**Authors:** Martin Wermke, Sebastian Ochsenreither, Dirk Jaeger, Heiko Becker, et al.

**Journal:** Nature Medicine, 2025

**Why it matters:** By using an engineered T cell receptor domain instead of an antibody to target intracellular cancer-testis antigens presented on the cell surface via HLA, IMA401 opens a route to solid tumor immunotherapy that sidesteps the target-scarcity problem that has long limited bispecific T cell engagers in this setting.

---

**Summary**

Conventional bispecific T cell engagers (TCEs) are constrained to surface antigens, which are rarely tumor-specific enough in solid tumors to avoid on-target, off-tumor toxicity. IMA401 addresses this by replacing the antibody-based targeting arm with a high-affinity TCR domain that recognizes a peptide derived from the cancer-testis antigens MAGE-A4 and MAGE-A8 presented on the HLA-A\*02:01 allele — proteins that are epigenetically silenced in normal adult tissue but re-expressed across a broad range of solid tumors. The molecule also incorporates a deliberately low-affinity CD3-recruiting domain, which reduces peripheral T cell "sink" sequestration and limits hyperactivation-driven exhaustion, and a silenced Fc region that extends serum half-life to roughly 15–17 days, enabling biweekly dosing.

This prespecified interim analysis of a phase 1 basket trial enrolled 61 heavily pretreated patients (median 3–4 prior lines) across more than 15 solid tumor indications, using a Bayesian logistic regression model to guide dose escalation from 0.0066 mg to 2.5 mg. The maximum tolerated dose was not reached per protocol, and the recommended phase 2 dose (RP2D) was set at 1–2 mg biweekly. At 2.5 mg, three of seven patients experienced dose-limiting grade 4 neutropenia; introducing 8 mg dexamethasone premedication with step dosing eliminated further dose-limiting toxicities within the RP2D range. Cytokine release syndrome occurred in 38% of patients but was exclusively grades 1–2, and no cases of immune effector cell-associated neurotoxicity syndrome (ICANS) were observed. One possibly treatment-related death from pneumonia occurred at 2.5 mg without dexamethasone premedication, in a patient with rapidly progressing lung metastases.

In the RP2D-treated population (n = 41), the confirmed objective response rate (ORR) was 20%, rising to 29% in the largest histology subgroup — head and neck squamous cell carcinoma (4/14 patients) — with a 64% disease control rate and a median duration of response of 8.8 months. Objective responses were also observed in patients who had previously progressed on immune checkpoint inhibitors, including in a combination cohort with pembrolizumab that showed no additive toxicity. One melanoma patient maintained ongoing progression-free survival exceeding 33.9 months.

---

**Three takeaways**

1. IMA401 demonstrated a 20% confirmed ORR at the RP2D across 15 tumor types, reaching 29% in head and neck squamous cell carcinoma — in patients with a median of 3–4 prior lines of therapy.

2. The safety profile at the RP2D was characterized by exclusively low-grade (grades 1–2) cytokine release syndrome, zero cases of ICANS, and a dose-dependent neutropenia that was clinically mitigated with dexamethasone premedication and step dosing.

3. Objective responses were observed in patients with prior immune checkpoint inhibitor resistance, and combining IMA401 with pembrolizumab produced no additive toxicity while maintaining antitumor activity.

---

**Read the source:** https://doi.org/10.1038/s41591-026-04455-x

**Paper:** [Language Modeling Materializes a World Model of Protein Biology](https://biohub.ai/papers/esm_protein.pdf)

**Authors:** Salvatore Candido, Alexander Rives, et al.

**Journal:** White paper — Biohub / Evolutionary Scale

**Why it matters:** Training a protein language model on billions of diverse metagenomic sequences appears to produce not just pattern matching but an internally organized, causally predictive representation of biophysical and functional principles — with direct implications for structure prediction and therapeutic design.

---

**Summary**

The paper asks whether scaling masked language modeling on protein sequences — where the model learns to predict missing amino acids from surrounding context — genuinely forces the emergence of a world model of protein biology, or merely produces sophisticated statistical memorization. The training corpus for the ESM Cambrian (ESMC) model family expands from the ~50 million sequences used in ESM2 to roughly 2.8 billion sequences, drawn heavily from metagenomic datasets including samples from hydrothermal vents, permafrost, and hypersaline lakes. Scaling compute up to a 6-billion-parameter model reveals a log-linear relationship between compute and precision in predicting long-range tertiary contacts — the physical touches between amino acids that are distant in the 1D sequence — with no observed plateau.

Layer-level analysis of ESMC shows the network decouples enzymatic function (peaking around layers 50–60) from fine-grained 3D structural information (peaking in the final layers), and can recognize identical catalytic function across entirely different protein fold topologies. The companion structure prediction system, ESMFold 2, projects atomic coordinates directly from single-sequence representations using a stabilized recurrent architecture — looping pairwise state through the same weights up to 48 times with a contractive map to prevent exploding activations — achieving state-of-the-art results on FoldBench, particularly on antibody–antigen docking (scored by DockQ). Generative design experiments produced single-chain variable fragments binding clinically relevant targets like PD-L1 at nanomolar affinity.

To interrogate the latent space, the researchers applied sparse autoencoders (SAEs) to layer 60 of ESMC, decomposing polysemantic dense embeddings into interpretable, higher-dimensional sparse features corresponding to secondary structures, taxonomic groups, and complex pathway memberships such as MitoCarta assignments. Using max-pooled SAE features as protein barcodes, remote homology retrieval outperformed both FoldSeek (structure-based) and MMseqs2 (sequence-based) at under 30% sequence identity. Two validation experiments — unsupervised clustering of over 2 million unannotated proteins and NMF-based pathway assignment to uncharacterized sequences — support the claim that these features reflect causal biological organization rather than label projection.

---

**Three takeaways**

1. Scaling a masked protein language model on 2.8 billion metagenomic sequences produces a log-linear improvement in long-range contact prediction that shows no sign of plateauing at 6 billion parameters.

2. ESMFold 2's stabilized recurrent folding module achieves state-of-the-art DockQ performance on antibody–antigen complexes from single sequences, largely without relying on multiple sequence alignments.

3. Sparse autoencoder features extracted from ESMC layer 60 enable remote homology retrieval at below 30% sequence identity that outperforms both structural and sequence-alignment baselines, and successfully clusters over 2 million functionally unannotated proteins.

---

**Read the source:** https://biohub.ai/papers/esm_protein.pdf

**Monday Immune Engager** — our weekly pick from the latest immune-engager digest.

**Paper:** [Novel bispecific T-cell engagers overcoming acquired EGFR resistance](https://doi.org/10.1080/19420862.2026.2674236)

**Authors:** Lennart Kühl, Ann-Kathrin Löffler, Oliver Seifert, Dennis Michler, et al.

**Journal:** mAbs, 2026

**Why it matters:** Acquired resistance to EGFR-targeted antibody therapies remains a major barrier in colorectal and head-and-neck cancers, and this study presents an engineered antibody-based approach that circumvents both extracellular receptor mutations and downstream signaling bypass.

---

**Summary**

EGFR (epidermal growth factor receptor) is a well-validated oncology target, but monoclonal antibodies like cetuximab frequently lose efficacy as tumors acquire missense mutations — single amino acid substitutions such as S492R and G465R — in the extracellular domain where cetuximab binds. To find antibodies that could sidestep these escape variants, the researchers screened a human antibody phage display library against mutant EGFR protein, identifying an initial hit (A7) and then improving its binding roughly eightfold through VL shuffling (systematically swapping the antibody light chain while retaining the productive heavy chain), yielding the lead antibody H10 with a dissociation constant of ~4 nM. Epitope mapping confirmed that H10 binds a region overlapping but spatially shifted from the cetuximab site, explaining why it retains high affinity for the clinically prevalent escape variants that abolish cetuximab binding. Functional assays showed H10 suppresses EGFR phosphorylation, blocks downstream ERK signaling, and inhibits tumor cell proliferation comparably to cetuximab on wild-type-expressing cells.

Because tumors can also acquire activating KRAS mutations that short-circuit EGFR signaling downstream — rendering surface blockade irrelevant — the team re-engineered H10 into bispecific T-cell engagers (TCEs) that physically recruit CD3-positive killer T cells to the tumor cell, bypassing intracellular resistance entirely. Two formats were tested: a 1+1 (one EGFR arm, one CD3 arm) and a 2+1 (two EGFR arms, one CD3 arm). The 2+1 format exploited avidity — a stronger, geometrically stable two-handed grip — and proved markedly superior on tumor cells expressing low levels of EGFR (~1,000 receptors/cell). In vitro co-culture assays demonstrated potent T cell–mediated killing of cells bearing S492R, G465R, and KRAS-mutant backgrounds where cetuximab-based TCEs completely failed, and a syngeneic mouse model showed significant tumor growth inhibition. A key limitation acknowledged by the authors is on-target/off-tumor toxicity: EGFR is expressed on healthy epithelial tissues, and broad T-cell activation risks cytokine release syndrome — a challenge the researchers note will likely require protease-activatable masking strategies in future clinical development.

---

**Three takeaways**

1. H10 binds an epitope that overlaps with but is spatially shifted from the cetuximab binding site, enabling it to maintain high affinity for the major clinical escape variants S492R and G465R that completely abrogate cetuximab binding.

2. A 2+1 bispecific format — two EGFR-binding arms and one CD3-binding arm — leverages avidity to achieve potent T cell–mediated cytotoxicity even on tumor cells expressing as few as ~1,000 EGFR molecules per cell, where the 1+1 format was substantially less effective.

3. H10-based TCEs successfully killed tumor cells harboring both extracellular EGFR escape mutations and downstream KRAS activating mutations in vitro, and suppressed tumor growth in a syngeneic mouse model — resistance mechanisms that rendered cetuximab-based TCEs ineffective.

---

**Read the paper:** [https://doi.org/10.1080/19420862.2026.2674236](https://doi.org/10.1080/19420862.2026.2674236)

**Paper:** [The lived experience of rejection sensitivity in ADHD — A qualitative exploration](https://doi.org/10.1371/journal.pone.0314669)

**Authors:** Annabel Rowney-Smith, Beth Sutton, Lisa Quadt, Jessica A. Eccles

**Journal:** PLOS One, 2024

**Why it matters:** Emotional dysregulation — and rejection sensitivity in particular — affects the majority of adults with ADHD yet remains largely absent from standard diagnostic criteria, leaving a significant dimension of patient suffering unrecognized and untreated.

---

**Summary**

Rejection sensitivity is a facet of emotional dysregulation in which perceived criticism or social rejection triggers intense dysphoria (profound psychological unease, from the Greek "hard to bear"). Despite emotional dysregulation being estimated to affect up to 70% of adults with ADHD, it is systematically excluded from mainstream diagnostic criteria, which have historically prioritized observable, externalizing behaviors like inattention and hyperactivity. To capture this hidden internal experience, the authors conducted semi-structured focus group interviews with five undergraduate students holding formal ADHD diagnoses, then applied thematic analysis to the transcripts. The open-ended prompt — "If you do, how do you identify with rejection-sensitive dysphoria?" — allowed participants to drive the narrative.

Analysis revealed three core themes. First, **withdrawal**: participants described preemptive social and academic avoidance, including deliberately submitting university work late or below standard to create a psychological buffer against a professor's criticism — even when a 10% grade penalty was automatic. Second, **masking** (also called camouflaging): to avoid being labeled "needy," participants constructed a performed exterior of toughness so sustained that it produced dissociation — a state in which they felt like outside observers of their own conversations, disconnected from their authentic emotional states. Third, **bodily sensations**: perceived rejection triggered vivid physical responses — chest tightness, throat constriction, gastrointestinal nausea, and a spreading internal heat one participant compared to a chemical hand warmer — consistent with acute sympathetic nervous system (fight-or-flight) activation.

The key limitation is sample size: only five participants, two of whom also carried an autism spectrum diagnosis and one a dyslexia diagnosis, making it impossible to isolate ADHD-specific mechanisms from co-occurring neurodivergent traits. The findings are a valuable starting point for a larger research agenda rather than generalizable conclusions.

---

**Three takeaways**

1. Anticipatory fear of rejection — not confirmed rejection itself — was the primary driver of preemptive withdrawal, including deliberate academic self-sabotage that narrowed participants' long-term social and career trajectories.

2. Sustained masking backfired: projecting indifference caused peers to deliver harsher criticism, intensifying the very rejection sensitivity it was meant to conceal and producing a dissociative disconnection from participants' own emotional states.

3. Rejection sensitivity produced acute, individualized physical symptoms — spreading heat, cardiac awareness, nausea, and paralysis — that participants and the authors characterized as functionally identical to a fight-or-flight stress response.

---

**Read the paper:** [https://doi.org/10.1371/journal.pone.0314669](https://doi.org/10.1371/journal.pone.0314669)

**Monday Immune Engager** — our weekly pick from the latest immune-engager digest.

**Paper:** [Deep peptide recognition profiling decodes TCR specificity and enables disease-associated antigen discovery](https://doi.org/10.1038/s41587-026-03128-x)

**Authors:** Nan Wang, Hugh Yeh, Ben Lai, Jason Perera, Kevin M. Jude, et al.

**Journal:** Nature Biotechnology, 2026

**Why it matters:** Mapping how T cell receptors actually recognize peptides — rather than inferring it from sequence alone — opens a scalable path to identifying the self-antigens driving autoimmune diseases like ankylosing spondylitis.

**Summary**

Predicting what a T cell receptor (TCR) will recognize based on its amino acid sequence is notoriously unreliable: nearly identical TCRs can bind completely different antigens, while structurally dissimilar TCRs can converge on the same target. To attack this problem directly, the authors focused on a clinically defined set of HLA-B\*27:05-restricted TCRs from patients with ankylosing spondylitis (a disease causing spinal fusion) and acute anterior uveitis (severe inflammatory eye disease). They used high-throughput yeast display — engineering yeast to present roughly one billion peptides on their surfaces — to screen 21 patient-derived TCRs and generate what they call deep peptide recognition profiles (PRPs): empirical maps of which peptides each TCR actually binds. Because the HLA-B\*27:05 binding groove strongly favors arginine at position 2 and proline at position 8 as anchor residues, the team fixed those positions to stabilize the library and concentrate diversity in the central contact residues where the CDR3β loop — the dominant recognition element in this system — makes its contacts.

The resulting PRPs were used to fine-tune protein language models (pLMs) built on a transformer encoder paired with a convolutional neural network. These models substantially outperformed AlphaFold3 and tFold-TCR at predicting T cell activation. Critically, functional clustering of TCRs by Jensen-Shannon divergence of their PRPs was largely independent of sequence similarity metrics like CDR3β edit distance and TCRdist — confirming that sequence proximity is a poor proxy for recognition overlap. Turning the trained models on the human proteome, the team identified novel candidate autoantigens, including a peptide derived from the gene *PSG5*, and validated it by showing that CD8⁺ T cells from HLA-B27-positive patients upregulated the activation marker CD69 in response to this peptide. An important caveat: fixing anchor residues creates a reductionist model of the natural peptide repertoire, and while CDR3β dominates in this system, the authors acknowledge that the alpha chain modulates response magnitude and could limit generalization to other HLA contexts.

To address uncertainty when predicting novel TCRs, the authors introduced a Mahalanobis distance metric that quantifies how far a new TCR sits from the training distribution in the model's learned embedding space — effectively a built-in confidence score that flags when predictions should not be trusted and directs experimental resources toward functionally uncharted receptors.

**Three takeaways**

1. TCR functional clustering based on PRP divergence (Jensen-Shannon distance) is largely independent of sequence similarity, demonstrating that CDR3β edit distance and TCRdist fail to capture convergent recognition in this system.

2. pLMs fine-tuned on PRPs outperform AlphaFold3 and tFold-TCR in predicting T cell activation, and this capability enabled the discovery and in vitro validation of *PSG5* as a novel candidate autoantigen recognized by patient-derived HLA-B27-positive CD8⁺ T cells.

3. Model generalization to held-out TCRs correlates with functional distance (PRP divergence) rather than sequence similarity, and Mahalanobis distance in the model's embedding space serves as a reliable intrinsic confidence metric to prioritize future experimental mapping.

**Read the paper:** [https://doi.org/10.1038/s41587-026-03128-x](https://doi.org/10.1038/s41587-026-03128-x)