From molecular design to immune remodeling: Advances in perylene diimide-based multimodal cancer therapies
Bibliographic record
Abstract
Perylene diimide (PDI) is a programmable theranostic platform that combines high photostability with facile medicinal-chemistry modification at the imide and bay positions. Recent advances in donor-acceptor tuning, π-conjugation extension/fusion, and aggregation control have pushed its absorption into the near-infrared II (NIR-II) window (1000-1700 nm), and enabled programmable partitioning between photothermal conversion and Type I/II photodynamic pathways under low irradiance. This review primarily surveys PDI derivatives reported from 2015 through 2025. We focus on mechanisms that move beyond conventional phototherapy: side-chain and topological designs enable precise localization to mitochondria, lysosomes, endoplasmic reticulum (ER), and nucleus, thereby coupling metabolic/oxidative-stress reprogramming, inducing ferroptosis, and potentially overcoming multidrug resistance; Nucleus-targeted PDI acts as a selective G-quadruplex (G4) stabilizer and dsDNA binder, stabilizing G4 structures in the c-MYC promoter and at telomeres/telomerase-associated sites to downregulate oncogenic transcription and provide light-independent chemotherapeutic potential. On the immunomodulation front, acute mitochondria-localized injury triggers immunogenic cell death (ICD) and releases mitochondrial DNA (mtDNA) to activate the cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway; inhibiting ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1) to prolong cyclic GMP-AMP (cGAMP) persistence sustains pathway activation and converts "cold" tumors into "hot" phenotypes responsive to immune checkpoint blockade. Altogether, guided by structure-aggregation-spectrum-function relationships, we map programmable links between NIR responses, excited-state energy dissipation, and immune remodeling, and we outline design principles for evolving this molecular scaffold into a streamlined single-molecule platform that integrates chemotherapy, metabolic intervention, and immune activation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".