Evidence map›Paper›PMID 35927264›Full record

ArticleNature communications2022

Minimally invasive detection of cancer using metabolic changes in tumor-associated natural killer cells with Oncoimmune probes.

Deeptha Ishwar, Rupa Haldavnekar, Krishnan Venkatakrishnan, Bo Tan

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.8field-weighted citation impact, top 15% of its field
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

4 citing papers in PubMed, 23 citations in OpenAlex.

  1. Review
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  4. Review
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

4 authors at 1 institution in 1 country.

Deeptha Ishwar *Institute for Biomedical Engineering, Science and Technology (I BEST), Partnership between Ryerson University and St. Michael's Hospital, Toronto, ON, M5B 1W8, Canada.
Rupa Haldavnekar *Institute for Biomedical Engineering, Science and Technology (I BEST), Partnership between Ryerson University and St. Michael's Hospital, Toronto, ON, M5B 1W8, Canada.ORCID http://orcid.org/0000-0001-8188-081X
Krishnan VenkatakrishnanInstitute for Biomedical Engineering, Science and Technology (I BEST), Partnership between Ryerson University and St. Michael's Hospital, Toronto, ON, M5B 1W8, Canada. venkat@ryerson.ca.ORCID http://orcid.org/0000-0002-6491-3971
Bo TanInstitute for Biomedical Engineering, Science and Technology (I BEST), Partnership between Ryerson University and St. Michael's Hospital, Toronto, ON, M5B 1W8, Canada.ORCID http://orcid.org/0000-0001-8141-4819
St. Michael's Hospital · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Natural Killer (NK) cells, a subset of innate immune cells, undergo cancer-specific changes during tumor progression. Therefore, tracking NK cell activity in circulation has potential for cancer diagnosis. Identification of tumor associated NK cells remains a challenge as most of the cancer antigens are unknown. Here, we introduce tumor-associated circulating NK cell profiling (CNKP) as a stand-alone cancer diagnostic modality with a liquid biopsy. Metabolic profiles of NK cell activation as a result of tumor interaction are detected with a SERS functionalized OncoImmune probe platform. We show that the cancer stem cell-associated NK cell is of value in cancer diagnosis. Through machine learning, the features of NK cell activity in patient blood could identify cancer from non-cancer using 5uL of peripheral blood with 100% accuracy and localization of cancer with 93% accuracy. These results show the feasibility of minimally invasive cancer diagnostics using circulating NK cells.

Indexed as

Killer Cells, NaturalNeoplasmsHumansLymphocyte ActivationNeoplastic Stem Cells

Identifiers

PMID35927264
PMCPMC9352900
OpenAlexW4289766693

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.