A Sampling of Highlights from the Literature
Bibliographic record
Abstract
Senescence-induced vascularization (by Manu5 via Wikimedia Commons)Mutated, activated KRAS is a common feature of pancreatic ductal adenocarcinoma (PDAC). Inhibitors of the downstream MEK and CDK4/6 pathways suppress PDAC growth by inducing cellular senescence and production of chemokines, cytokines, and matrix metalloproteinases. This triggers vasculature remodeling of the PDAC tumors and subsequent NF-κB– and VEGFR-driven tumor infiltration by CD8+ T cells. MEK and CDK4/6 inhibitors lead to exhaustion of the recruited T cells, which are rescued by PD-1 blockade. Inducing senescence with immune checkpoint blockade may improve outcomes.Ruscetti M, …, Lowe SW. Cell 2020 Apr 16;181:424–41.e21.Radiation therapy (by Jakembradford via Wikimedia Commons)Radiation induces genomic DNA (gDNA) fragmentation but little cytosolic DNA sensing with IFN-I production. Radiation also induces mitochondrial permeabilization, and the mitochondrial DNA (mtDNA) activates caspase-9, leading to intrinsic apoptosis. By disrupting caspase-9, apoptosis is inhibited and the cytosolic mtDNA activates the STING pathway and increases IFN-I, promoting cross-priming by DCs and activating T cells. However, the T cells become exhausted, and combining PD-L1 blockade with radiation therapy and caspase inhibition increases antitumor activity and abscopal effects.Han C, …, Fu Y-X. Nat Immunol 2020 May 1;21:546–54.Centuries-old Egyptian knock-in technique (in Wirth Gallery, Royal Ontario Museum)Adoptive cell therapies (ACT) have had limited success in solid tumors. The authors develop pooled knock-in sequencing (PoKI-seq), a high-throughput barcoding method in which pooled, targeted, knock-in constructs in T cells are assessed via combined single-cell transcriptome analysis and pooled knock-in screening, as a strategy to identify constructs that can improve T-cell abundance and function for treating solid tumors. Among a large panel of natural and synthetic genes, knock-in of a synthetic TGFβR2-41BB chimeric receptor was found to best improve in vitro activity and efficacy of ACT in melanoma.Roth TL, …, Marson A. Cell 2020 Apr 30;181:728-44.e21.Autophagy recycles class I MHC (from Fig. 1 of White et al., Clin Cancer Res 2015)Pancreatic ductal adenocarcinoma (PDAC) rarely responds to immune checkpoint blockade (ICB). Although MHC-I is downregulated in PDAC, it is not due to mutations in, or loss of heterozygosity of, antigen presentation or structural genes. Instead, surface MHC-I is selectively targeted by lysosomes via NBR1-mediated autophagy. Autophagy inhibition restores MHC-I expression and improves antitumor immunity, effects dependent on CD8+ T cells and enhanced by concurrent dual ICB. This autophagy-mediated immune evasion mechanism in PDAC cells suggests that its targeting could boost antitumor responses.Yamamoto K, …, Kimmelman AC. Nature 2020 May 1;581:100–5.Myeloid subsets sensitive to external cues (from Fig. 1 of Clappaert et al., Front Immunol 2018)Factors that regulate function of the heterogeneous myeloid cells in cancer are not fully known. Zhang et al. find that in patients and mice with colorectal tumors, myeloid cell–targeting immunotherapies have distinct macrophage and DC subset–specific effects, revealing myeloid cells as central players in cell interaction networks in the tumor. Mohamed et al. demonstrate that myeloid-derived suppressor cell (MDSC) function relies on PERK, the unfolded protein response–related kinase, via activation of transcription factor NRF2. PERK deletion disrupts mitochondrial homeostasis and induces IFN by activating the STING pathway, reprogramming the MDSC to promote CD8+ T-cell responses. Thus, intelligent targeting of defined myeloid cells can manipulate regulation and improve antitumor responses.Zhang L, …, Yu X. Cell 2020 Apr 16;181:442–59.e29.Mohamed E, …, Rodriguez PC. Immunity 2020 Apr 14;52:668–82.e7.CRISPR/Cas9–edited T cells for therapy (by Guido4 via Wikimedia Commons)CRISPR-Cas9 is being investigated to improve immunotherapy responses. A phase I clinical trial shows that T cells with a disrupted PD-1 gene infused into patients with treatment-refractory non–small cell lung cancer had only grade 1/2 treatment-related adverse events. The edited T cells persist post-infusion and are trackable. Off-target mutation frequency was 0.05%. These data support the safety and feasibility of clinical use in T cell–based immunotherapies.Lu Y, …, Mok T. Nat Med 2020 Apr 27. DOI: 10.1038/s41591-020-0840-5.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.046 | 0.019 |
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".