Literature DB >> 35986082

Reply to: Target expression is a relevant factor in synthetic lethal screens.

Yosi Gilad1, Yossi Eliaz2, Yang Yu1, Adam M Dean1, San Jung Han1, Li Qin1, Bert W O'Malley3, David M Lonard4.   

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Year:  2022        PMID: 35986082      PMCID: PMC9391391          DOI: 10.1038/s42003-022-03747-5

Source DB:  PubMed          Journal:  Commun Biol        ISSN: 2399-3642


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I.J. Schultz & H.J.T. Coelingh Bennink Commun. Biol. 10.1038/s42003-022-03746-6 (2022) The major concern that the authors have risen is the enhanced sensitivity of BC cell lines to SI-12 treatment in our study as a result of the silencing of four genes—OR4D6, OR5I1, NDNF, and S1PR1—in spite of the lack of their expression in these cell lines, according to public databases and previously published studies. There are a few points that might explain this contradiction: It is important to mention that in the studies by Weber et al. [1] and Masjedi et al. [2], that the authors have mentioned, the transcriptome analysis was performed on untreated samples, while the importance of OR5I1 and OR4D6 in the context of our study manifested under SI-12 treatment. We have performed qPCR experiments to access the mRNA levels following siRNA treatment in MCF7 cells. We would like to mention that the apparent lack of concordance between our RT-qPCR data and DepMap RNA-Seq data could be due to false-negative discovery, which is a common issue of RNA-Seq[3,4], and that RT-qPCR is capable of greater sensitivity[5]. Moreover, it is well known that many key driver genes, including signaling receptors, are frequently expressed at very low levels in cancer cells[6,7] and therefore are even more prone for false-negative discovery by RNA-Seq. There are evidences that the expression of OR varies across individuals[8]; therefore it might be also the case across cell line subsets. It is an unfortunate, but inevitable nature of cancer cell lines that have the same parental origin, but which had been handled differently (in the case of MCF7 cells - for decades), to have a non-homogenous gene-expression profile. In the context of the discussed four genes, we found that it might be best exemplified by the fact that while the expression of S1PR1 is absent in MCF7 cells, as you have found by interrogation of publically available databases, this gene was found to be expressed in MCF7 cells elsewhere. Furthermore, it was found to have functional importance in this cell line[9-12]. Importantly, since the main goal our study was to find gene targets that can be pharmacologically inhibited, the focus of our study was made on screening candidates that could be validated not only by siRNA perturbation, but also by pharmacological inhibition. However, the authors of this MA focused on four genes, three of which could not be pharmacologically validated (OR4D6, OR5I1, and NDNF, since, to the best of our knowledge, there are no available pharmacological inhibitors for these three genes). Therefore, we made a clear statement in our paper that these genes are potential anti-cancer therapeutic targets in combination with SI-12 rather than validated ones. The only target out of the four genes that are in the focus of the discussion of this MA that has been validated both by an individual siRNA perturbation and pharmacological inhibition in combination with SI-12 is S1PR1. Indeed, our results show that the pharmacological inhibition of S1PR1 did not contribute to the cancer cell-killing effect in combination with SI-12 (which might support the author's concern regarding a robust and biologically significant expression of this gene). Therefore, this target was not included in our conclusive remarks as a valid target for combination treatment with SI-12. We would like to mention that the lack of complete agreement between initial screening candidates and later individual validations is almost a matter of fact in these types of experiments, and generally, this is why validation experiments are carried out following screening.
  12 in total

1.  Differentially expressed genes from RNA-Seq and functional enrichment results are affected by the choice of single-end versus paired-end reads and stranded versus non-stranded protocols.

Authors:  Susan M Corley; Karen L MacKenzie; Annemiek Beverdam; Louise F Roddam; Marc R Wilkins
Journal:  BMC Genomics       Date:  2017-05-23       Impact factor: 3.969

2.  Targeting the SphK1/S1P/S1PR1 Axis That Links Obesity, Chronic Inflammation, and Breast Cancer Metastasis.

Authors:  Masayuki Nagahashi; Akimitsu Yamada; Eriko Katsuta; Tomoyoshi Aoyagi; Wei-Ching Huang; Krista P Terracina; Nitai C Hait; Jeremy C Allegood; Junko Tsuchida; Kizuki Yuza; Masato Nakajima; Manabu Abe; Kenji Sakimura; Sheldon Milstien; Toshifumi Wakai; Sarah Spiegel; Kazuaki Takabe
Journal:  Cancer Res       Date:  2018-01-19       Impact factor: 12.701

3.  Estrogen receptor alpha gene ESR1 amplification may predict endocrine therapy responsiveness in breast cancer patients.

Authors:  Saori Tomita; Zhenhuan Zhang; Masahiro Nakano; Mutsuko Ibusuki; Teru Kawazoe; Yutaka Yamamoto; Hirotaka Iwase
Journal:  Cancer Sci       Date:  2009-02-25       Impact factor: 6.716

4.  Olfactory Receptors as Biomarkers in Human Breast Carcinoma Tissues.

Authors:  Lea Weber; Désirée Maßberg; Christian Becker; Janine Altmüller; Burkhard Ubrig; Gabriele Bonatz; Gerhard Wölk; Stathis Philippou; Andrea Tannapfel; Hanns Hatt; Günter Gisselmann
Journal:  Front Oncol       Date:  2018-02-15       Impact factor: 6.244

5.  Survival benefit of sphingosin-1-phosphate and receptors expressions in breast cancer patients.

Authors:  Fu-Ju Lei; Bi-Hua Cheng; Pei-Yin Liao; Hsiao-Ching Wang; Wei-Chun Chang; Hsueh-Chou Lai; Juan-Cheng Yang; Yang-Chang Wu; Li-Ching Chu; Wen-Lung Ma
Journal:  Cancer Med       Date:  2018-06-20       Impact factor: 4.452

6.  Olfactory receptor gene abundance in invasive breast carcinoma.

Authors:  Shirin Masjedi; Laurence J Zwiebel; Todd D Giorgio
Journal:  Sci Rep       Date:  2019-09-24       Impact factor: 4.379

7.  S1PR1 regulates the switch of two angiogenic modes by VE-cadherin phosphorylation in breast cancer.

Authors:  Shuang Liu; Chunsheng Ni; Danfang Zhang; Huizhi Sun; Xueyi Dong; Na Che; Xiaohui Liang; Chen Chen; Fang Liu; Jingru Bai; Xian Lin; Xiulan Zhao; Baocun Sun
Journal:  Cell Death Dis       Date:  2019-02-27       Impact factor: 8.469

8.  Identifying inaccuracies in gene expression estimates from unstranded RNA-seq data.

Authors:  Mikhail Pomaznoy; Ashu Sethi; Jason Greenbaum; Bjoern Peters
Journal:  Sci Rep       Date:  2019-11-08       Impact factor: 4.379

9.  Systematic comparison and assessment of RNA-seq procedures for gene expression quantitative analysis.

Authors:  Luis A Corchete; Elizabeta A Rojas; Diego Alonso-López; Javier De Las Rivas; Norma C Gutiérrez; Francisco J Burguillo
Journal:  Sci Rep       Date:  2020-11-12       Impact factor: 4.379

10.  Profiling of olfactory receptor gene expression in whole human olfactory mucosa.

Authors:  Christophe Verbeurgt; Françoise Wilkin; Maxime Tarabichi; Françoise Gregoire; Jacques E Dumont; Pierre Chatelain
Journal:  PLoS One       Date:  2014-05-06       Impact factor: 3.240

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