Evidence map›Paper›PMID 38216952›Full record

ArticleBMC cancer2024

SARIFA as a new histopathological biomarker is associated with adverse clinicopathological characteristics, tumor-promoting fatty-acid metabolism, and might predict a metastatic pattern in pT3a prostate cancer.

Johanna S Enke, Matthias Groß, Bianca Grosser, Eva Sipos, Julie Steinestel, Phillip Löhr, Johanna Waidhauser, Constantin Lapa, Bruno Märkl, Nic G Reitsam

Abstract read
In one paragraph

Article in BMC cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  11. [SARIFA-a new multi-entity biomarker].Pathologie (Heidelberg, Germany) · 2024
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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

10 authors.

Johanna S EnkeNuclear Medicine, Faculty of Medicine, University of Augsburg, Augsburg, Germany.
Matthias GroßPathology, Faculty of Medicine, University of Augsburg, Augsburg, Germany.
Bianca GrosserPathology, Faculty of Medicine, University of Augsburg, Augsburg, Germany.
Eva SiposPathology, Faculty of Medicine, University of Augsburg, Augsburg, Germany.
Julie SteinestelUrology, Faculty of Medicine, University of Augsburg, Augsburg, Germany.
Phillip LöhrHematology and Oncology, Faculty of Medicine, University of Augsburg, Augsburg, Germany.
Johanna WaidhauserHematology and Oncology, Faculty of Medicine, University of Augsburg, Augsburg, Germany.
Constantin LapaNuclear Medicine, Faculty of Medicine, University of Augsburg, Augsburg, Germany.
Bruno MärklPathology, Faculty of Medicine, University of Augsburg, Augsburg, Germany.
Nic G ReitsamPathology, Faculty of Medicine, University of Augsburg, Augsburg, Germany. nic.reitsam@uka-science.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecently, we introduced Stroma-AReactive-Invasion-Front-Areas (SARIFA) as a novel hematoxylin-eosin (H&E)-based histopathologic prognostic biomarker for various gastrointestinal cancers, closely related to lipid metabolism. To date, no studies on SARIFA, which is defined as direct tumor-adipocyte-interaction, beyond the alimentary tract exist. Hence, the objective of our current investigation was to study the significance of SARIFA in pT3a prostate cancer (PCa) and explore its association with lipid metabolism in PCa as lipid metabolism plays a key role in PCa development and progression.

methodsTo this end, we evaluated SARIFA-status in 301 radical prostatectomy specimens and examined the relationship between SARIFA-status, clinicopathological characteristics, overall survival, and immunohistochemical expression of FABP4 and CD36 (proteins closely involved in fatty-acid metabolism). Additionally, we investigated the correlation between SARIFA and biochemical recurrence-free survival (BRFS) and PSMA-positive recurrences in PET/CT imaging in a patient subgroup. Moreover, a quantitative SARIFA cut-off was established to further understand the underlying tumor biology.

resultsSARIFA positivity occurred in 59.1% (n = 178) of pT3a PCas. Our analysis demonstrated that SARIFA positivity is strongly associated with established high-risk features, such as R1 status, extraprostatic extension, and higher initial PSA values. Additionally, we observed an upregulation of immunohistochemical CD36 expression specifically at SARIFAs (p = 0.00014). Kaplan-Meier analyses revealed a trend toward poorer outcomes, particularly in terms of BRFS (p = 0.1). More extensive tumor-adipocyte interaction, assessed as quantity-dependent SARIFA-status on H&E slides, is also significantly associated with high-risk features, such as lymph node metastasis, and seems to be associated with worse survival outcomes (p = 0.16). Moreover, SARIFA positivity appeared to be linked to more distant lymph node and bone metastasis, although statistical significance was slightly not achieved (both p > 0.05).

conclusionsThis is the first study to introduce SARIFA as easy-and-fast-to-assess H&E-based biomarker in locally advanced PCa. SARIFA as the histopathologic correlate of a distinct tumor biology, closely related to lipid metabolism, could pave the way to a more detailed patient stratification and to the development of novel drugs targeting lipid metabolism in pT3a PCa. On the basis of this biomarker discovery study, further research efforts on the prognostic and predictive role of SARIFA in PCa can be designed.

Indexed as

Prostate-Specific AntigenProstatic NeoplasmsBiomarkersDisease-Free SurvivalHumansMalePositron Emission Tomography Computed TomographyProstatectomyBiomarkersProstate-Specific AntigenBiomarker studyLipid metabolismPrognostic biomarkerProstate cancerpT3a prostate cancer

Identifiers

PMID38216952
PMCPMC10785487

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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.