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Multiomic characterization of small cell lung cancer: Real‐world insights into therapeutic opportunities

Overview of attention for article published in Cancer (0008543X), February 2026
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  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

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6 Mendeley
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Article details
Title
Multiomic characterization of small cell lung cancer: Real‐world insights into therapeutic opportunities
Published in
Cancer (0008543X), February 2026
DOI 10.1002/cncr.70284
Pubmed ID
Authors
Abstract

The dominant expression of lineage-related transcription factors (TFs)-ASCL1, NEUROD1, POU2F3, and, controversially, YAP1-has enabled the classification of small cell lung cancer (SCLC) into distinct subtypes (SCLC-A/N/P/Y, respectively). Emerging evidence suggests that a T cell-inflamed phenotype characterizes an SCLC subset. A large-scale multiomic analysis of samples from real-world patients with SCLC was conducted to examine the expression of clinically relevant biomarkers across SCLC subtypes. Comprehensive molecular profiling of patient samples (N = 944) was performed via next-generation DNA sequencing (592-gene panel or whole exome), RNA sequencing (whole transcriptome), and immunohistochemistry. Tumors were stratified on the basis of the dominant expression of an individual TF (SCLC-A/N/Y/P subtypes), coexpression of multiple TFs (mixed), or low expression of all four TFs (TF-) for characterization of immune-related gene signatures (T-cell inflamed, natural killer cell, and Stimulator of Interferon Genes pathway) and clinically relevant target genes. The cohort was composed of 25.6% SCLC-A, 10.2% SCLC-N, 12.5% SCLC-Y, 4.3% SCLC-P, 19.5% SCLC TF-, and 27.9% mixed subtypes. The SCLC-Y subtype exhibited the highest expression of immune-related gene signatures, with comparable expression observed in mixed samples expressing YAP1. Additionally, expression of clinically relevant target genes found in SCLC-A (DLL3, SEZ6, and BCL2) and SCLC-N (SSTR2) was increased in mixed samples expressing ASCL1 and NEUROD1. The TF- subtype was not associated with increased immune-related signatures or other target genes. This large-scale multiomic analysis revealed significant associations between SCLC subtypes and specific immune signatures and comutations. These findings provide insights into the molecular heterogeneity of SCLC, and highlight potential biomarkers for targeted therapies.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Librarian 1 17%
Other 1 17%
Student > Doctoral Student 1 17%
Unknown 3 50%
Readers by discipline
Readers by discipline Count As %
Immunology and Microbiology 1 17%
Social Sciences 1 17%
Materials Science 1 17%
Medicine and Dentistry 1 17%
Unknown 2 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 March 2026.
All research outputs
#11,917,409
of 34,640,154 outputs
Outputs from Cancer (0008543X)
#10,074
of 19,216 outputs
Outputs of similar age
#96,922
of 357,835 outputs
Outputs of similar age from Cancer (0008543X)
#48
of 118 outputs
Altmetric has tracked 34,640,154 research outputs across all sources so far. This one has received more attention than most of these and is in the 65th percentile.
So far Altmetric has tracked 19,216 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.3. This one is in the 47th percentile – i.e., 47% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 357,835 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 118 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.