Back

mitoBKCa is functionally expressed in murine and human breast cancer cells and promotes metabolic reprogramming

Bischof, H.; Maier, S.; Koprowski, P.; Kulawiak, B.; Burgstaller, S.; Jasinska, J.; Serafimov, K.; Gross, D.; Schroth, W.; Matt, L.; Juarez Lopez, D. A.; Bonzheim, I.; Büttner, F. A.; Fend, F.; Schwab, M.; Birkenfeld, A. L.; Malli, R.; Lämmerhofer, M.; Bednarczyk, P.; Szewczyk, A.; Lukowski, R.

2023-10-04 cancer biology
10.1101/2023.10.02.560571 bioRxiv
Show abstract

Alterations in the function of K+ channels such as the voltage- and Ca2+ activated K+ channel of large conductance (BKCa) reportedly promote breast cancer (BC) development and progression. Underlying molecular mechanisms remain, however, elusive. Here, we provide electrophysiological evidence for a BKCa splice variant localized to the inner mitochondrial membrane of murine and human BC cells (mitoBKCa). Through a combination of genetic knockdown and knockout along with cell permeable BKCa channel blocker, we show that mitoBKCa modulates overall cellular and mitochondrial energy production and mediates the metabolic rewiring referred to as the "Warburg effect", thereby promoting BC cell proliferation in the presence and absence of oxygen. Additionally, we detect mitoBKCa and BKCa transcripts in low or high abundance, respectively, in clinical BC specimens. Together, our results emphasize, that targeting mitoBKCa could represent a treatment strategy for selected BC patients in future.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
EMBO Reports
○ 263 papers in training set
Top 0.1%
12.9%
Similar papers in this journal
2
eLife
● 5828 papers in training set
Top 7%
12.7%
Similar papers in this journal
3
Cell Death & Disease
147 papers in training set
Top 0.1%
10.6%
4
Nature Communications
○ 5641 papers in training set
Top 21%
7.9%
Similar papers in this journal
5
The Journal of Physiology
○ 150 papers in training set
Top 0.4%
5.5%
Similar papers in this journal
6
Cell Death & Differentiation
○ 48 papers in training set
Top 0.2%
4.0%
50% of probability mass above
7
Communications Biology
○ 993 papers in training set
Top 4%
4.0%
8
Journal of Cell Science
● 393 papers in training set
Top 2%
3.2%
9
iScience
○ 1154 papers in training set
Top 8%
3.2%
10
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 21%
2.4%
11
Life Science Alliance
● 285 papers in training set
Top 2%
2.1%
12
Oncogene
○ 85 papers in training set
Top 0.8%
2.1%
13
Cell Reports
○ 1498 papers in training set
Top 18%
1.9%
14
Science Advances
● 1243 papers in training set
Top 19%
1.7%
15
The EMBO Journal
○ 309 papers in training set
Top 3%
1.7%
16
Molecular Oncology
○ 55 papers in training set
Top 0.8%
1.5%
17
Journal of Cell Biology
● 392 papers in training set
Top 3%
1.3%
18
Biochimica et Biophysica Acta (BBA) - Molecular Cell Research
○ 29 papers in training set
Top 0.3%
1.3%
19
Cancers
○ 213 papers in training set
Top 4%
1.1%
20
Cell Death Discovery
○ 58 papers in training set
Top 1%
1.0%
21
Journal of Biological Chemistry
○ 690 papers in training set
Top 8%
1.0%
22
Advanced Science
○ 286 papers in training set
Top 8%
1.0%
23
Redox Biology
○ 70 papers in training set
Top 1%
0.8%
24
Molecular Biology of the Cell
● 311 papers in training set
Top 3%
0.8%
25
Cellular and Molecular Life Sciences
○ 96 papers in training set
Top 3%
0.6%
26
Cells
○ 249 papers in training set
Top 9%
0.6%
27
Scientific Reports
○ 3612 papers in training set
Top 77%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.