Evidence map›Paper›PMID 42614645›Full record

ReviewOncology reviews2026

Beyond the hallmarks of cancer: enabling technologies reshaping cancer diagnosis, prevention, and treatment.

Sarfaraz K Niazi

Abstract readReview
In one paragraph

Review in Oncology reviews, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Sarfaraz K NiaziCollege of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, WA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer biology has been organized for 2 decades by the hallmarks framework, articulated in 2000 and most recently revised in 2026. The pace of technological change in oncology now requires reframing how cancer is detected, prevented, and treated. This review argues that the hallmarks framework, while historically essential, is no longer sufficient on its own to capture contemporary cancer care, and repositions the discussion around enabling technologies that operate across and beyond individual hallmarks. For diagnosis, multi-omic liquid biopsy, AI-assisted radiomics and digital pathology, spatial transcriptomics, single-cell sequencing, and machine-learning analysis of plasma proteomics now support earlier detection, prediction of cancer risk years before diagnosis, monitoring of clonal evolution, and prediction of treatment response. For prevention, the validated population-level success of Human papillomavirus and HBV vaccination is contrasted with investigational directions including mRNA platforms, CRISPR-enabled antigen optimization, personalized neoantigen prophylaxis, and biomarker-stratified molecular interception, none of which has yet been validated in prospective human cancer-prevention trials. For treatment, the discussion is organized by modality class: immune checkpoint inhibitors and resistance strategies, antibody-drug conjugates, bispecific antibodies and T-cell engagers, radioligand therapies, tumor-infiltrating lymphocyte therapy, CRISPR-edited CAR-T and TCR therapies, photonic and photoimmunologic therapies, RNA therapeutics, and adaptive combination regimens. Comparative tables summarize diagnostic platforms, immunotherapeutic modalities, photonic therapies, CRISPR-edited immunotherapy trials, neoantigen vaccine pipelines, and convergent strategies. The trajectory of oncology will be defined less by incremental refinement of hallmarks and more by convergent technologies that integrate diagnostics, prevention, and treatment into continuous, data-driven systems.

Indexed as

AI-enabled cancer diagnosticsantibody and radioligand-targeted therapeuticsconvergent cancer technologiesimmune checkpoint and cellular therapiesmRNA neoantigen vaccinesmulti-omic liquid biopsyphotonic and photoimmunologic cancer therapies

Identifiers

PMID42614645
PMCPMC13481877

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.