Fig 2: High frequency of SDHA amplification and upregulation in ovarian cancer. (A) A heatmap representing the expression of 367 proteins in 9 HGSOC PDX models. Two PDX subsets were identified, one with increased, and the other with decreased expression of proteins associated with mitochondrial function (unpaired t-test). (B) The analysis of multiple metabolic pathways in PDX with high vs. low mitochondrial metabolism revealed 7 differentially expressed proteins represented by gene ID. Data are represented as mean ± SD; * = p < 0.05, ** = p < 0.01, and *** = p < 0.001 (multiple t-test). (C) In silico TGCA data analysis revealed that amongst 7 differentially expressed proteins between PDX with high vs. low mitochondrial metabolism, SDHA amplification and upregulation was the predominant genetic alteration reaching 19% of HGSOC cases. (D) The SDHA amplification occurs with the highest frequency in ovarian carcinoma when compared with 25 other malignancies. For additional information see Supplementary Table S1 and Figure S1.

Fig 3: SDHA increases mitochondrial respiration in ovarian cancer cell lines. (A–C) OCR was measured in ovarian cancer cell lines overexpressing SDHA or SDHA KD cells vs. controls by the Seahorse XF Cell Mito Stress Test. Cells were challenged by oligomycin “oligo”, FCCP, and antimycin A “AA”. Basal OCR represents the mitochondrial respiration at resting state, the maximum respiration indicates the cellular response to an increased ATP demand, and respiratory reserve indicates the cell capacity to utilize mitochondria during periods of high-energy expenditure. (D–F) Glycolytic Rate Assay was performed to calculate Proton Efflux Rate (PER) derived from glycolysis (glycoPER) in ovarian cancer cell lines overexpressing SDHA or SDHA KD cells vs. controls. Cells were challenged with AA to inhibit mitochondrial oxygen consumption followed by addition of 2-DG. The obtained PER values allowed to calculate basal glycolysis and maximal glycolysis, and glycolytic reserve. Data are represented as mean ± SEM, illustrating differences in OCR between cell lines (unpaired t-test, **** = p < 0.0001, ** = p < 0.01 * = p < 0.05, NS = not significant).

Fig 4: The SDHA overexpressing cell lines are highly sensitive to shikonin. (A) Ovarian cancer cell lines (OVCAR3, OVCAR4, TYKnu, and OVSAHO) were exposed to anti-metabolic compound library. The most potent agents are denoted in red. (B) The anti-cancer efficacy of the most potent compounds was evaluated in SDHA-high vs. SDHA-low cell lines. Shikonin was the most effective agent in specifically killing SDHA overexpressing cells. (C–E) Ovarian cancer cell lines endogenously overexpressing SDHA (OVSAHO) or conditionally overexpressing SDHA (Caov3-SDHA and OVCAR3-SDHA) were treated with shikonin or chemotherapy (paclitaxel, carboplatin) to assess % of viable cells. (C) Shikonin is significantly more effective in killing OVSAHO cells than chemotherapy. (D,E) Cells overexpressing SDHA are significantly more sensitive to shikonin than respective controls. In cell lines overexpressing SDHA shikonin reduced cell viability more profoundly than carboplatin in both cell lines, and than paclitaxel in Caov3 cell line. (A–E) Data are represented as mean ± SEM; * = p < 0.05, *** = p < 0.001, **** = p < 0.0001, and NS = not significant (one-way ANOVA followed by post hoc Tukey’s test). For additional information see Supplementary Table S2 and Figure S4.

Fig 5: SDHA increases ATP production rate in ovarian cancer cell lines. (A–F) Seahorse XF Real- Time ATP Rate Assay was performed using ovarian cancer cell lines overexpressing SDHA or SDHA KD cells vs. controls. Both OCR and ECAR were simultaneously measured in live cells revealing OCR-linked (mitoATP) and ECAR-linked (glycoATP) in basal conditions, and after addition of oligomycin “oligo”, and antimycin A “AA”. (G) Quantitative measurement of ATP production rate from mitochondrial and glycolytic pathways. (H) Graph represents a distribution of mitochondrial and glycolytic ATP production rates shown as % of mitoATP and % of glycoATP.