Stromal Cell-expressed Malignant Gene Patterns Contribute to the Progression of Squamous Cell Carcinomas Across Different Sites

Overview

Journal Front Genet

Date 2024 Jul 29

PMID 39071777

Authors

Kaiyan Qi

Guangqi Li

Yuanjun Jiang

Xuexin Tan

Qiao Qiao

Affiliations

Soon will be listed here.

Abstract

Background: Squamous cell carcinomas (SCCs) across different anatomical locations possess common molecular features. Recent studies showed that stromal cells may contribute to tumor progression and metastasis of SCCs. Limited by current sequencing technology and analysis methods, it has been difficult to combine stroma expression profiles with a large number of clinical information.

Methods: With the help of transfer learning on the cell line, single-cell, and bulk tumor sequencing data, we identified and validated 2 malignant gene patterns (V1 and V5) expressed by stromal cells of SCCs from head and neck (HNSCC), lung (LUSC), cervix (CESC), esophagus, and breast.

Results: Pattern V5 reflected a novel malignant feature that explained the mixed signals of HNSCC molecular subtypes. Higher expression of pattern V5 was related to shorter PFI with gender and cancer-type specificity. The other stromal gene pattern V1 was associated with poor PFI in patients after surgery in all the three squamous cancer types (HNSCC = 0.0055, LUSC = 0.0292, CESC = 0.0451). Cancer-associated fibroblasts could induce HNSCC cancer cells to express pattern V1. Adjuvant radiotherapy may weaken the effect of high V1 on recurrence and metastasis, depending on the tumor radiosensitivity.

Conclusion: Considering the prognostic value of stromal gene patterns and its universality, we suggest that the genetic subtype classification of SCCs may be improved to a new system that integrates both malignant and non-malignant components.

References

Chai A, Lim K, Cheong S . Translational genomics and recent advances in oral squamous cell carcinoma. Semin Cancer Biol. 2019; 61:71-83. DOI: 10.1016/j.semcancer.2019.09.011. View

Wang L, Saci A, Szabo P, Chasalow S, Castillo-Martin M, Domingo-Domenech J . EMT- and stroma-related gene expression and resistance to PD-1 blockade in urothelial cancer. Nat Commun. 2018; 9(1):3503. PMC: 6115401. DOI: 10.1038/s41467-018-05992-x. View

Xu M, Zhang T, Xia R, Wei Y, Wei X . Targeting the tumor stroma for cancer therapy. Mol Cancer. 2022; 21(1):208. PMC: 9628074. DOI: 10.1186/s12943-022-01670-1. View

Sharma G, Colantuoni C, Goff L, Fertig E, Stein-OBrien G . projectR: an R/Bioconductor package for transfer learning via PCA, NMF, correlation and clustering. Bioinformatics. 2020; 36(11):3592-3593. PMC: 7267840. DOI: 10.1093/bioinformatics/btaa183. View

Rahal Z, Sinjab A, Wistuba I, Kadara H . Game of clones: Battles in the field of carcinogenesis. Pharmacol Ther. 2022; 237:108251. PMC: 10249058. DOI: 10.1016/j.pharmthera.2022.108251. View

Gieniec K, Butler L, Worthley D, Woods S . Cancer-associated fibroblasts-heroes or villains?. Br J Cancer. 2019; 121(4):293-302. PMC: 6738083. DOI: 10.1038/s41416-019-0509-3. View

Puram S, Tirosh I, Parikh A, Patel A, Yizhak K, Gillespie S . Single-Cell Transcriptomic Analysis of Primary and Metastatic Tumor Ecosystems in Head and Neck Cancer. Cell. 2017; 171(7):1611-1624.e24. PMC: 5878932. DOI: 10.1016/j.cell.2017.10.044. View

Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi A, Tanaseichuk O . Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun. 2019; 10(1):1523. PMC: 6447622. DOI: 10.1038/s41467-019-09234-6. View

Eschrich S, Pramana J, Zhang H, Zhao H, Boulware D, Lee J . A gene expression model of intrinsic tumor radiosensitivity: prediction of response and prognosis after chemoradiation. Int J Radiat Oncol Biol Phys. 2009; 75(2):489-96. PMC: 3038688. DOI: 10.1016/j.ijrobp.2009.06.014. View

10.

Cox T . The matrix in cancer. Nat Rev Cancer. 2021; 21(4):217-238. DOI: 10.1038/s41568-020-00329-7. View

11.

Plava J, Cihova M, Burikova M, Matuskova M, Kucerova L, Miklikova S . Recent advances in understanding tumor stroma-mediated chemoresistance in breast cancer. Mol Cancer. 2019; 18(1):67. PMC: 6441200. DOI: 10.1186/s12943-019-0960-z. View

12.

. Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature. 2015; 517(7536):576-82. PMC: 4311405. DOI: 10.1038/nature14129. View

13.

Hanahan D, Weinberg R . Hallmarks of cancer: the next generation. Cell. 2011; 144(5):646-74. DOI: 10.1016/j.cell.2011.02.013. View

14.

Brunet J, Tamayo P, Golub T, Mesirov J . Metagenes and molecular pattern discovery using matrix factorization. Proc Natl Acad Sci U S A. 2004; 101(12):4164-9. PMC: 384712. DOI: 10.1073/pnas.0308531101. View

15.

Carter S, Cibulskis K, Helman E, McKenna A, Shen H, Zack T . Absolute quantification of somatic DNA alterations in human cancer. Nat Biotechnol. 2012; 30(5):413-21. PMC: 4383288. DOI: 10.1038/nbt.2203. View

16.

Chen X, Song E . Turning foes to friends: targeting cancer-associated fibroblasts. Nat Rev Drug Discov. 2018; 18(2):99-115. DOI: 10.1038/s41573-018-0004-1. View

17.

Dotto G . Multifocal epithelial tumors and field cancerization: stroma as a primary determinant. J Clin Invest. 2014; 124(4):1446-53. PMC: 3973113. DOI: 10.1172/JCI72589. View

18.

Bhowmick N, Neilson E, Moses H . Stromal fibroblasts in cancer initiation and progression. Nature. 2004; 432(7015):332-7. PMC: 3050735. DOI: 10.1038/nature03096. View

19.

Gaujoux R, Seoighe C . A flexible R package for nonnegative matrix factorization. BMC Bioinformatics. 2010; 11:367. PMC: 2912887. DOI: 10.1186/1471-2105-11-367. View

20.

Kim H, Park H . Sparse non-negative matrix factorizations via alternating non-negativity-constrained least squares for microarray data analysis. Bioinformatics. 2007; 23(12):1495-502. DOI: 10.1093/bioinformatics/btm134. View