Abstract 3945: Serum detection of MUC1 and renin identifies circulating biomarkers for breast cancer prognosis.

Abstract Background: Cytogenetic abnormalities involving multiple loci on the long arm of chromosome 1 are among the most frequent alterations in human breast carcinoma. To define their biological and clinical significance, we conducted a large-scale integrative genomic analysis across diverse breast cancer datasets. Methods: Data from over 13,000 breast tumors (n = 13,146 samples; 12,229 patients across 30 studies) were analyzed using cBioPortal, including The Cancer Genome Atlas (TCGA). Copy number alterations, mRNA/protein expression, and clinical outcomes were evaluated. Comparative analyses with >100,000 samples across 35 other cancers (n = 105,424) determined specificity. Mutual exclusivity and co-occurrence analyses identified genetic interaction patterns relevant to tumor progression. Serum detectability of top candidates was evaluated. Results: Eight genes particularly TRIM67, DISC1, REN, DNM3, ATP1B1, VSIG8, SPTA1, and MUC1 from different loci of 1q chromosome showed recurrent amplifications (12-15%) in breast tumors, significantly exceeding frequencies in pan-cancer datasets (∼3%). These genes displayed low baseline expression in normal breast tissue but were highly expressed in tumors. Co-occurrence analyses revealed significant genetic interplay, including TP53 with MUC1/SPTA1/VSIG8 and PIK3CA with TRIM67/DISC1/REN, suggesting cooperative gain-of-function driving aggressive phenotypes. Among the eight amplified 1q genes, MUC1 and REN showed the strongest clinical relevance, as both encode secreted or shed proteins that were readily detectable in serum and have established associations with aggressive breast cancer biology. In contrast, DNM3 and ATP1B1 were detectable at lower abundance in serum-derived extracellular vesicles, supporting their potential as emerging but less established circulating markers. Conclusions: Multi-locus amplifications contribute collectively to breast cancer progression through distinct gene interaction networks. This study identifies a core set of functionally relevant, serum-detectable gene products that may serve as biomarkers for prognosis, recurrence monitoring, and therapeutic targeting in aggressive breast cancer. Citation Format: Alakesh Bera, Hai Hu, COL Craig D. Shriver, Meera Srivastava. Serum detection of MUC1 and renin identifies circulating biomarkers for breast cancer prognosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3945.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-3945
Primary Topic
Ferroptosis and cancer prognosis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 3945: Serum detection of MUC1 and renin identifies circulating biomarkers for breast cancer prognosis.

Meera Srivastava, CD Shriver, Alakesh Bera, H. Hu
Cancer Research
Ferroptosis and cancer prognosis
article

Abstract 3945: Serum detection of MUC1 and renin identifies circulating biomarkers for breast cancer prognosis.

Meera Srivastava, CD Shriver, Alakesh Bera, H. Hu
article en

Abstract

Abstract Background: Cytogenetic abnormalities involving multiple loci on the long arm of chromosome 1 are among the most frequent alterations in human breast carcinoma. To define their biological and clinical significance, we conducted a large-scale integrative genomic analysis across diverse breast cancer datasets. Methods: Data from over 13,000 breast tumors (n = 13,146 samples; 12,229 patients across 30 studies) were analyzed using cBioPortal, including The Cancer Genome Atlas (TCGA). Copy number alterations, mRNA/protein expression, and clinical outcomes were evaluated. Comparative analyses with >100,000 samples across 35 other cancers (n = 105,424) determined specificity. Mutual exclusivity and co-occurrence analyses identified genetic interaction patterns relevant to tumor progression. Serum detectability of top candidates was evaluated. Results: Eight genes particularly TRIM67, DISC1, REN, DNM3, ATP1B1, VSIG8, SPTA1, and MUC1 from different loci of 1q chromosome showed recurrent amplifications (12-15%) in breast tumors, significantly exceeding frequencies in pan-cancer datasets (∼3%). These genes displayed low baseline expression in normal breast tissue but were highly expressed in tumors. Co-occurrence analyses revealed significant genetic interplay, including TP53 with MUC1/SPTA1/VSIG8 and PIK3CA with TRIM67/DISC1/REN, suggesting cooperative gain-of-function driving aggressive phenotypes. Among the eight amplified 1q genes, MUC1 and REN showed the strongest clinical relevance, as both encode secreted or shed proteins that were readily detectable in serum and have established associations with aggressive breast cancer biology. In contrast, DNM3 and ATP1B1 were detectable at lower abundance in serum-derived extracellular vesicles, supporting their potential as emerging but less established circulating markers. Conclusions: Multi-locus amplifications contribute collectively to breast cancer progression through distinct gene interaction networks. This study identifies a core set of functionally relevant, serum-detectable gene products that may serve as biomarkers for prognosis, recurrence monitoring, and therapeutic targeting in aggressive breast cancer. Citation Format: Alakesh Bera, Hai Hu, COL Craig D. Shriver, Meera Srivastava. Serum detection of MUC1 and renin identifies circulating biomarkers for breast cancer prognosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3945.

Cancer ResearchVol. 86(7_Supplement)
Unifor (NO), Windber Research Institute (US), Uniformed Services University of the Health Sciences (US)
Good health and well-being
Openalex Percentile: Top 5%
Ferroptosis and cancer prognosis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.