Functional Depth Biomarkers Distinguish Lung Squamous Cell Carcinoma from Lung Adenocarcinoma.

Sagnik Bhadury, Ashley P Tsang, Dipankar Ray, Kiran Lagisetty, Arvind Rao

Abstract readPreprint

In one paragraph

Article in Research square, 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

5 authors.

Sagnik BhaduryDepartment of Computational Medicine and Bioinformatics, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA.

Ashley P TsangDepartment of Computational Medicine and Bioinformatics, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA.

Dipankar RayDepartment of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.

Kiran LagisettyDepartment of Surgery, University of Michigan, Ann Arbor, MI, USA.

Arvind RaoDepartment of Computational Medicine and Bioinformatics, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA.

Funding

Synthesizing Image-derived Heterogeneity with Genomic measurements for Assessing Disease Aggressiveness in Lower Grade GliomasR37CA214955 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI KURTEK, SEBASTIAN, RAO, ARVIND · 2018 to 2024

$3.9M

NCI NIH HHS R37 CA214955

6 · The paper itself

Abstract

Lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) exhibit fundamentally distinct pathway coordination architectures. We developed a framework integrating pathway activity inference from spatial transcriptomics data, spatial proximity based network construction, and functional depth analysis across 996 TCGA patients. Applying Fraiman-Muniz depth statistics, we generated two representations: Population Referenced Depth quantifies typicality relative to population distributions, while Patient Referenced Depth assesses within-patient network organization. Random forest classification revealed that Patient Referenced Depth marginally outperforms population comparisons, achieving test AUC of 0.768. We focus on bidirectional interaction patterns obtained from spatial interaction networks of pathways. Multi-method feature integration identified three mechanistic frameworks distinguishing subtypes: myeloid orchestrated immune coordination (JAK-STAT ↔ TNF

Identifiers

PMID42523548

DOI10.21203/rs.3.rs-9347794/v1

PMCPMC13405495

What Socratic 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 Socratic graph.