Prognostic and clinical significance of Solute Carrier Family 7 Member 1 in ovarian cancer
Original Article

Prognostic and clinical significance of Solute Carrier Family 7 Member 1 in ovarian cancer

Wangang Gong1,2, Yongyi Chen1,2, Yingli Zhang1,2

1Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China; 2Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, China

Contributions: (I) Conception and design: Y Zhang; (II) Administrative support: Y Zhang; (III) Provision of study materials or patients: Y Chen; (IV) Collection and assembly of data: W Gong, Y Chen; (V) Data analysis and interpretation: W Gong; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

Correspondence to: Dr. Yingli Zhang. Zhejiang Cancer Hospital, 1 Banshan Road, Hangzhou, 310022, China. Email: zhangyl@zjcc.org.cn.

Background: Members of the solute carrier (SLC)7 family are known to play important roles in tumorigenesis and development. However, the prognostic significance of the SLC7 family in ovarian cancer (OC) remains unknown.

Methods: Expression patterns of SLC7 family members in OC were analyzed using gene expression profiling interactive analysis (GEPIA). The Kaplan-Meier plotter was applied to evaluate associations of the SLC7 gene family with prognosis of OC. SLC7A1 expression was additionally analyzed via immunohistochemical staining. χ2, Kaplan-Meier and Cox regression analysis were used to evaluate the relationship between SLC7A1 expression and clinicopathological features, platinum resistance and prognosis in patients with high-grade serous ovarian cancer (HGSOC).

Results: The GEPIA dataset revealed the abundant expression of SLC7A1, SLC7A4, and SLC7A7, and conversely, the low expression of SLC7A2 and SLC7A8 in OC relative to normal tissue samples. Kaplan-Meier survival analysis further indicated that high SLC7A1 and low SLC7A2 mRNA levels were significantly associated with overall survival (P<0.05). Positive SLC7A1 expression was detected in 65 (58.1%) HGSOC tissue samples, but not in all normal ovarian tissue samples (100%), indicating that the expression of SLC7A1 in HGSOC tissues was significantly higher than that in normal ovarian tissues (P<0.001). Additionally, expression of SLC7A1 was negatively associated with relapse-free survival (RFS; P<0.05).

Conclusions: SLC7A1 is a potential prognostic biomarker of OC.

Keywords: Ovarian cancer (OC); SLC7A1; relapse-free survival


Submitted Aug 16, 2020. Accepted for publication Dec 28, 2020.

doi: 10.21037/tcr-20-2744


Introduction

Ovarian cancer (OC) is one of the most common gynecological malignancies, accounting for the highest mortality rates among gynecological cancers. Moreover, it has a significant negative impact on the lives of women worldwide (1). Approximately 152,000 women die from OC every year, with a reported overall five-year survival rate of approximately 30% (2,3). Since OC is difficult to diagnose at the early stages, more than 75% cases are not detected until advanced disease and recurrence presents a common problem (4). Therefore, the identification of effective prognostic biomarkers remains an urgent requirement to improve management and prognosis of OC.

The solute carrier (SLC) transporter superfamily includes multiple membrane-binding proteins and participates in transmembrane transport of numerous substrates. Members of this protein family play critical physiological roles and therefore serve as potential therapeutic targets for many diseases (5). The SLC7 family consists of 13 genes and is divided into two subfamilies: (I) cationic amino acid transporters (CAT, SLC7A1-4) and (II) l-type amino acid transporters (LAT, SLC7 5-14) (6). Amino acids are essential for growth of living cells, in particular, abnormally proliferating tumor cells. Consequently, compared with normal cells, expression of amino acid transporters in cancer cells is usually upregulated (7). Multiple studies have confirmed that dysfunction of SLC family 7 genes is associated with the incidence of human diseases, in particular, the occurrence, development, metastasis, and drug resistance of different cancer types (8-10). For instance, SLC7A5 overexpression in invasive cancers is significantly correlated with expression of c-Myc, a key regulatory factor of tumor cell metabolism. SLC7A5 is upregulated with tumor progression and thus relatively increased in high-grade and metastatic tumors (11-13). Similarly, SLC7A11 is abundantly expressed in a variety of tumor types. For example, the overexpression of SLC7A11 in glioblastoma enhances the migration and invasion of tumor cells, and patients with high expression of SLC7A11 have poor prognosis (14,15).

However, to our knowledge, no studies regarding the overall expression pattern and prognostic value of SLC7 genes have been documented in the literature. The associations among the clinicopathologic characteristics of OC and the SLC7 gene family remain unknown at present. In the current study, we focused on the expression patterns of individual SLC7 genes in OC and explored their prognostic significance. Our collective findings provide novel insights into the roles of the SLC7 gene family in OC that may be effectively applied for diagnostic treatment and prognostic purposes. In particular, our study aims to explore the relationship between the expression of SLC7A1 and platinum resistance and prognosis in patients with HGSOC, and to provide a possible theoretical basis for improving the treatment and prognosis of OC.

We present the following article in accordance with the REMARK reporting checklist (available at http://dx.doi.org/10.21037/tcr-20-2744).


Methods

cBioportal for Cancer Genomics

The relationship between SLC7 genes and OC and alterations in expression were analyzed using data from cBioportal (http://www.cbioportal.org/) for Cancer Genomics, an open-access resource for interactive exploration of multiple Cancer Genomics datasets (16). cBioPortal currently stores data on DNA copy number (assumptions for each gene, discrete values such as "deep deletion" or "amplification," and log2 levels), mRNA and microRNA expression, non-synonymous mutations, protein and phospholipid levels reverse-phase protein arrays (RPPA) and DNA methylation.

GEPIA validation of differential expression of SLC family 7 genes

GEPIA (http://gepia.cancerpku.cn/) is a multi-functional network database that collects RNA sequencing expression data from 9,736 tumor samples and 8,587 normal samples from TCGA and GTEx databases (17). GEPIA provides a variety of functions, including evaluation of tumor/normal differential expression profiles, analysis according to cancer type or pathological stage, patient survival analysis, similarity analysis, and so on. Then, the expression of SLC7 family in OC was analyzed in GEPIA database.

Kaplan-Meier plotter database analysis

As a tool for biomarker assessment, the Kaplan–Meier plotter (http://kmplot.com) was applied to analyze 54,675 genes and 10,188 tumor tissue samples (including breast, ovarian, lung, and gastric cancer types). The prognostic value of SLC7 mRNA transcript levels was additionally measured using the Kaplan–Meier plotter, which included gene expression profiles and survival information from 1,657 OC patients based on mRNA chip analysis (18). Patients were separated into two groups based on median gene expression of SLC7 family members (high vs. low). OS values of the two groups were compared using a Kaplan-Meier survival plot. Hazard ratio (HR) values with 95% CI, and log-rank P values were calculated. Data were considered significant at P values of <0.05.

Patient selection

This study was conducted in accordance with the Declaration of Helsinki (as revised in 2013) and it was conducted with approval from the Ethics Committee of Zhejiang Cancer Hospital (No. IRB-2015-175). Written informed consent was obtained from the participants. The 128 frozen tissue samples (collected between 2008 and 2014 and maintained at –80 °C) were provided by the Biobank of Zhejiang Cancer Hospital. All samples were fixed and paraffin-embedded. The samples for study included 112 HGSOC and 16 normal ovarian tissue samples. The tumor staging and histological grading were evaluated according to the staging criteria of the International Federation of Obstetrics and Gynecology (FIGO) (19).

All patients enrolled in the study received standard chemotherapy after operation. According to the recurrence of platinum treatment, the patients who relapsed or did not relapse after 6 months were platinum sensitive group, and those who relapsed less than 6 months were platinum resistant group. RFS was calculated from the date of diagnosis to the date of recurrence.

Immunohistochemical staining

Rabbit anti-SLC7A1 polyclonal antibody [14195-1-AP] was purchased from Proteintech. The second antibody (PV-9000) and Diaminobenzidine (DAB) kit were purchased from Beijing Zhongshan Golden Bridge Biotechnology Co., Ltd. The sample was embedded in paraffin, cut into a thickness of 4 µm, dewaxed with xylene and then hydrated. High pressure repair was performed with citrate buffer for 2.5 min. Wash three times with phosphate buffer saline (PBS) for two min each, soak in 3% hydrogen peroxide solution for 10 min, and wash with PBS three times for two min each time. The slices were incubated overnight with the primary antibody (1:100 dilution) at 4 °C. Rinse with running water for 15 min, then rinse with PBS for 3 times for 5 min each time. Add the second antibody, incubate at room temperature for 20 min, and rinse with PBS for 3 times for 5 min each time. Diaminobenzidine (DAB) was used to staining at room temperature, and observed under microscope, then re-stained with hematoxylin and sealed.

Evaluation of immunohistochemical data

The expression of SLC7A1 detected by immunohistochemistry was evaluated by staining index, staining index = staining intensity + positive staining ratio of tumor cells (20). The staining intensity was divided into four grades: 0 points (negative), 1 points (weakly positive), 2 points (moderately positive) or 3 points (strongly positive). The scores for the percentage of positive area are as follows: 0 points <5%, 1 point, 5–25%, 2 points, 26–50%, 3 points, 51–75%, and 4 points, >75%. Cases in which the sum of two scores was <5 points were classified as low expression, 0 points as no expression and ≥5 points as high expression.

Western blot analysis

RIPA reagent (Beyotime Institute of Biotechnology) containing protease inhibitor mixture (Beyotime) was used to lyse the tissue. After that, the total protein was quantified by BCA Kit (Beyotime Institute of Biotechnology). Twenty-five micrograms protein was separated in 10% polyacrylamide gel (Beyotime Institute of Biotechnology) and then transferred to nitrocellulose membrane (Thermo Fisher Scientific, Inc.). At room temperature, the membrane was blocked with 5% non-fat milk powder in PBST for 1 hour, and then incubated with the primary antibody against SLC7A1 (1:1,000; cat. no. ab14195-1-AP; Proteintech) at 4 °C overnight. After washing the membrane with PBST, the anti-rabbit secondary antibody (1:3,000; cat. no. 170-6515; Bio-Rad Laboratories, Inc.) was incubated for 1 hour. SuperSignal West Pico substrate and CL-XPosure film (Thermo Fisher Scientific, Inc.) were used to develop the film. Image Lab 3.0 (Bio-Rad Laboratories, Inc.) was used to analyze the results of Western blotting. β-actin is an internal reference protein.

Statistical analysis

The chi-square test (χ2) was used to analyze the correlation between SLC7A1 expression and clinicopathological features. The correlations between platinum resistance and SLC7A1 expression as well as clinical features were further analyzed with chi-square test (χ2). Kaplan-Meier and Cox proportional hazard regression tests were employed for univariate and multivariate survival analyses. All analyses were performed using SPSS PASW Statistics v18.0 (IBM, Chicago, IL, USA). Data were considered significant at P<0.05 and highly significant at P<0.01.


Results

Genetic differences in SLC7 family genes in OC

The database of cBioPortal OC (TCGA, Provisional) http://www.cbioportal.org was used to analyze the relationship between SLC7 genes and OC. Our results suggest that DNA amplification is one of the most important single factors displaying alterations in different histological types of OC (Figure 1A). We further analyzed the genetic alteration rates of single SLC7 genes; DNA amplification was the most common type of alteration, accounting for more than half of all genetic variation. Notably, genetic variation of SLC7A2 was predominantly attributed to DNA deep deletion (Figure 1B).

Figure 1 Different genetic alterations of SLC7 family members in OC. SLC7, solute carrier 7; OC, ovarian cancer.

mRNA expression of SLC7 family members in OC patients

We used the Gene Expression Profiling Interactive Analysis (GEPIA) dataset (http://gepia.cancer-pku.cn/) to evaluate expression of SLC7 mRNAs in OC. Our results showed that levels of SLC7A1, SLC7A4, SLC7A5, SLC7A7, SLC7A10, and SLC7A11 were higher in OC compared with normal tissues, among which SLC7A1, SLC7A4 and SLC7A7 levels were significantly elevated. Conversely, SLC7A2, SLC7A3, SLC7A6, SLC7A8, SLC7A9, and SLC7A14 levels were lower in OC compared with normal tissues, among which SLC7A2, and SLC7A8 levels were significantly decreased. SLC7A13 was the only gene for which expression data were lacking in OC patients (Figure 2).

Figure 2 Levels of SLC7 family members in OC evaluated using GEPIA. *, P<0.05. SLC7, solute carrier 7; OC, ovarian cancer; GEPIA, Gene Expression Profiling Interactive Analysis.

Prognostic value of the SLC7 expression in OC

Kaplan–Meier plotter analysis showed that high expression of SLC7A1 (OS HR =1.14, 95% CI, 1.0 to 1.3, P=0.045), SLC7A3 (OS HR =1.38, 95% CI, 1.12 to 1.69, P=0.00018), and SLC7A14 (OS HR =1.31, 95% CI, 1.06 to 1.63, P=0.0014) was associated with poor prognosis in patients with OC. Conversely, low expression of SLC7A2 (OS HR =0.79, 95% CI, 0.69 to 0.9, P=0.00048), SLC7A4 (OS HR =0.82, 95% CI, 0.71 to 0.94, P=0.0052), SLC7A5 (OS HR =0.80, 95% CI, 0.69 to 0.93, P=0.0036) and SLC7A11 (OS HR =0.70, 95% CI, 0.61 to 0.79, P=3.9e-08) was correlated with poor prognosis (Figure 3). We further used the Kaplan–Meier plotter to determine the correlations among overall survival (OS), first progression (FP), post-progression survival (PPS) and SLC7 gene expression in OC patients, determined via Forest plot (Figure 4). SLC7A1 had significant prognostic value in OS, FP, and PPS and was therefore selected for further in-depth analysis.

Figure 3 Analysis of OS in relation to SLC7 family members in OC patients using the Kaplan-Meier plotter. P values were calculated using the log-rank test. OS, overall survival; SLC7, solute carrier 7.
Figure 4 Correlation of OS, FP and PPS with SLC7 gene family expression in OC patients. *, P<0.05. OS, overall survival; FP, first progression; PPS, post-progression survival; SLC7, solute carrier 7; OC, ovarian cancer.

SLC7A1 expression in relation to clinicopathological characteristics of patients with HGSOC

Immunohistochemistry was used to detect the expression of SLC7A1 protein in 112 HGSOC and 16 normal ovarian tissues (Figure 5). The results disclosed expression of SLC7A1 in 65 of the HGSOC samples (58.1%) but not the remaining 47 HGSOC samples (41.9%). Notably, SLC7A1 was not detected in all 16 normal ovarian tissue samples (100%). The results showed that the expression level of SLC7A1 in HGSOC tissues was significantly higher than that in normal ovarian tissues (P<0.001; Table 1). Among the 112 HGSOC samples, we observed no distinct correlation between SLC7A1 expression and age of patients, FIGO stage, histologic grade, CA-125, lymph node metastasis or postoperative residual tumor size (P>0.05), while platinum resistance was strongly correlated with SLC7A1 expression (P=0.043; Table 2). At the same time, Western blotting was used to detect the expression of SLC7A1 in 4 cases of HGSOC and 4 cases of normal ovarian tissues. The results showed that the expression of SLC7A1 in HGSOC tissues was significantly up-regulated compared with normal tissues (Figure S1).

Figure 5 Immunohistochemical detection of SLC7A1. Negative expression of SLC7A1 in (A) normal ovarian and (B) HGSOC tissues. (C) Low expression of SLC7A1 in HGSOC tissues. (D) High expression of SLC7A1 in HGSOC tissues. HGSOC, high-grade serous ovarian cancer.

Table 1

Expression of SLC7A1 in HGSOC and normal ovarian tissue samples

Variables SLC7A1 expression P value
Low High
HGSOC 47 65 <0.001
Normal 16 0

Statistical analysis was performed with a Fisher’s exact test. HGSOC, high-grade serous ovarian cancer.

Table 2

Associations between the expression level of SLC7A1 and clinicopathological characteristics

SLC7A1 expression P value
Low High
Age, years
   ≤54 25 35 0.945a
   >54 22 30
FIGO stage
   I–II 5 6 0.999b
   III–IV 42 59
Histological grade
   G2 26 34 0.404a
   G3 17 31
CA-125, U/mL
   ≤500 10 16 0.680a
   >500 37 49
Lymph node metastasis
   No 22 28 0.695a
   Yes 25 37
Residual tumor size, cm
   ≤1 34 44 0.598a
   >1 13 21
Platinum resistance
   Present 6 18 0.043a
   Absent 40 43

Statistical analysis was performed with aχ2 test or bFisher’s exact test.

Prognostic value of SLC7A1 in OC

As shown in Table 3, Kaplan-Meier univariate analysis showed that there was a significant correlation between SLC7A1 expression and RFS in patients with HGSOC (P<0.05). FIGO stage, CA-125, lymph node metastasis and residual tumor size were also correlated with RFS (P<0.05). As shown in Table 4, multivariate Cox regression analysis further confirmed FIGO stage (HR =5.141; 95% CI, 1.531 to 17.260; P=0.008), CA-125 (HR =1.831; 95% CI, 1.062 to 3.155; P=0.029), lymph node metastasis (HR =1.673; 95% CI, 1.057 to 2.648; P=0.028) and SLC7A1 expression (HR =1.617; 95% CI, 1.045 to 2.504; P=0.031) were significantly associated with RFS. Accordingly, late-stage FIGO, CA-125 >500, lymph node metastasis and high expression of SLC7A1 were identified as risk factors for recurrence of HGSOC.

Table 3

Univariate survival analysis of relapse-free survival of patients with ovarian cancer

Variable n Mean ± SE 95% CI P value
Age, years
   ≤54 60 21.617±3.157 15.429–27.806 0.725
   >54 47 23.402±3.543 16.457–30.346
FIGO stage
   I–II 11 66.455±9.978 46.898–86.011 <0.001
   III–IV 96 17.801±1.893 14.092–21.510
Histological grade
   G2 57 25.591±3.775 18.567–33.364 0.177
   G3 46 19.364±2.927 13.628–25.101
CA-125, U/mL
   ≤500 25 30.568±5.744 19.310–41.826 0.041
   >500 82 19.536±2.363 14.904–24.169
Lymph node metastasis
   No 47 32.120±4.516 23.269–40.971 0.001
   Yes 60 14.994±1.918 11.234–18.755
Residual tumor size, cm
   ≤1 76 26.643±3.206 20.359–32.926 0.004
   >1 31 13.645±2.664 8.823–18.867
SLC7A1 expression
   Low 46 29.177±4.327 20.696–37.658 0.031
   High 61 16.917±2.183 12.638–21.196

Analysis was performed with a log-rank test.

Table 4

Multivariate survival analysis of relapse-free survival of patients with ovarian cancer

Variable β SE HR 95% CI P value
FIGO stage (III–IV) 1.637 0.618 5.141 1.531–17.260 0.008
CA-125 (>500) 0.605 0.278 1.831 1.062–3.155 0.029
Lymph node metastasis (Yes) 0.515 0.234 1.673 1.057–2.648 0.028
Residual tumor size (>1 cm) 0.439 0.238 1.551 0.973–2.472 0.065
SLC7A1 expression (High) 0.481 0.223 1.617 1.045–2.504 0.031

According to Cox regression analysis.


Discussion

In the present study, we focused on the expression profiles of SLC7 family members and their associations with survival outcomes in patients with OC. Our results showed that SLC7A1, SLC7A4, and SLC7A7 levels were significantly higher whereas those of SLC7A2 and SLC7A8 were significantly lower in OC relative to normal tissues. Kaplan–Meier Plotter survival analysis further indicated that increased SLC7A1 and decreased SLC7A2 mRNA levels were highly associated with OS (P<0.05).

SLC7A1, also known as CAT-1, is a cationic amino acid transporter (CAT) whose main function is to mediate arginine uptake (21). The growth of several cancer cell lines, including acute myeloid leukemia, breast cancer, and colorectal cancer, is highly dependent on arginine (22-24). Compared with normal breast cells, the human breast cancer cell lines, T47D and MDA-MB-231, are reported to overexpress SLC7A1. Knockout of the SLC7A1 gene resulted in a significant increase in apoptosis of MCF-7 and T47D cells in vitro (23). Other studies have demonstrated the abundant expression of CAT-1 mRNA and protein in colorectal cancer tissue relative to normal tissue. Apoptosis of colorectal cancer cells could be induced by knockout of SLC7A1, supporting its utility as a unique molecular biomarker and therapeutic target for colorectal cancer (25). Another recent investigation showed that SLC7A1 is highly expressed in tumors and involved in the central mechanism of tumor evasion against the T-cell-mediated anti-tumor immune response, leading to poor prognosis (25). Our finding that overexpression of SLC7A1 in OC patients is correlated with poor OS is consistent with previous results. In Kaplan-Meier Plotter Database, the OS, FP and PPS time of high expression of SLC7A1 in patients with OC was short, and P<0.05, showing a good prognostic value. In the follow-up verification experiment, we collected 112 patients with OC and found that patients with high expression of SLC7A1 were more likely to develop drug resistance and more likely to relapse than patients with low expression.

In our study, 22.4% patients developed platinum resistance, in keeping with previous reports (26). Some studies have shown that MIR-122 is the highest expression of miRNA, in normal liver, but significantly decreased in hepatoma cells resistant to sorafenib. On the other hand, SLC7A1 has been found to be the direct target of miR-122. MIR-122 promotes the sensitivity of hepatocellular carcinoma cells to sorafenib by targeting and inhibiting SLC7A1 (27). The results of this study suggest that the up-regulation of SLC7A1 is related to the platinum resistance in HGSOC, but further research is needed to clarify this mechanism.

Another important finding of this study is that recurrence of HGSOC is associated with several factors, such as late FIGO stage, lymph node metastasis, and high SLC7A1 expression. Several researchers have confirmed that postoperative recurrence of HGSOC increases with more advanced clinical stage. Late clinical stage is an independent risk factor for postoperative recurrence of OC, in accordance with our results (28). Advanced clinical stage is associated with promotion of intraperitoneal tumor implantation and metastasis and potential invasion of blood or lymphatic vessels, resulting in distant metastasis (29). The rate of lymph node metastasis in advanced OC is considerably higher. Intraoperative pelvic and para-aortic lymphadenectomy have been shown to significantly reduce tumor metastasis and recurrence (30,31). Data from the present study consistently demonstrated that lymph node metastasis is a risk factor for recurrence of HGSOC (32). Lymphadenectomy is one of the known factors affecting recurrence of OC. Therefore, extensive dissection of pelvic and celiac lymph nodes could reduce the possibility of postoperative recurrence of OC (33,34). CA-125 is the most commonly used tumor marker for diagnosis of OC recurrence. More than 90% of patients presenting with advanced OC, especially HGSOC, experience remission or deterioration of the disease. In our experiments, postoperative CA-125 >500 U/L was determined as a high risk factor for HGSOC recurrence. Additionally, SLC7A1 was identified as an independent prognostic factor for RFS in HGSOC.

To our knowledge, this is the first report to demonstrate that platinum resistance and prognosis are associated with SLC7A1 expression in patients with HGSOC. However, our study has a number of limitations that should be considered, such as its small sample size and single-center nature. In conclusion, the high expression of SLC7A1 is associated with poor prognosis and platinum resistance in patients with HGSOC. SLC7A1 may therefore serve as an effective potential biomarker for HGSOC.


Acknowledgments

Funding: None.


Footnote

Reporting Checklist: The authors have completed the REMARK reporting checklist. Available at http://dx.doi.org/10.21037/tcr-20-2744

Data Sharing Statement: Available at http://dx.doi.org/10.21037/tcr-20-2744

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/tcr-20-2744). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki (as revised in 2013) with approval from the Ethics Committee of Zhejiang Cancer Hospital (No. IRB-2015-175). Written informed consent was obtained from all participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.


References

  1. Global Burden of Disease Cancer Collaboration. The Global Burden of Cancer 2013. JAMA Oncol 2015;1:505-27. Erratum in: JAMA Oncol 2015;1:690. [Crossref] [PubMed]
  2. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018. CA Cancer J Clin 2018;68:7-30. [Crossref] [PubMed]
  3. Colombo PE, Fabbro M, Theillet C, et al. Sensitivity and resistance to treatment in the primary management of epithelial ovarian cancer. Crit Rev Oncol Hematol 2014;89:207-16. [Crossref] [PubMed]
  4. Matulonis UA, Sood AK, Fallowfield L, et al. Ovarian cancer. Nature Reviews Disease Primers 2016;2:16061. [Crossref] [PubMed]
  5. Lin L, Yee SW, Kim RB, et al. SLC transporters as therapeutic targets: emerging opportunities. Nat Rev Drug Discov 2015;14:543-60. [Crossref] [PubMed]
  6. Scalise M, Galluccio M, Console L, et al. The Human SLC7A5 (LAT1): The Intriguing Histidine/Large Neutral Amino Acid Transporter and Its Relevance to Human Health. Front Chem 2018;6:243. [Crossref] [PubMed]
  7. Fotiadis D, Kanai Y, Palacin M. The SLC3 and SLC7 families of amino acid transporters. Mol Aspects Med 2013;34:139-58. [Crossref] [PubMed]
  8. Shen L, Qian C, Cao H, et al. Upregulation of the solute carrier family 7 genes is indicative of poor prognosis in papillary thyroid carcinoma. World J Surg Oncol 2018;16:235. [Crossref] [PubMed]
  9. Januchowski R, Zawierucha P, Andrzejewska M, et al. Microarray-based detection and expression analysis of ABC and SLC transporters in drug-resistant ovarian cancer cell lines. Biomed Pharmacother 2013;67:240-5. [Crossref] [PubMed]
  10. Ji X, Qian J, Rahman SMJ, et al. xCT (SLC7A11)-mediated metabolic reprogramming promotes non-small cell lung cancer progression. Oncogene 2018;37:5007-19. [Crossref] [PubMed]
  11. Lu X. The Role of Large Neutral Amino Acid Transporter (LAT1) in Cancer. Curr Cancer Drug Targets 2019;19:863-76. [Crossref] [PubMed]
  12. Gao P, Tchernyshyov I, Chang TC, et al. c-Myc suppression of miR-23a/b enhances mitochondrial glutaminase expression and glutamine metabolism. Nature 2009;458:762-5. [Crossref] [PubMed]
  13. Cormerais Y, Massard PA, Vucetic M, et al. The glutamine transporter ASCT2 (SLC1A5) promotes tumor growth independently of the amino acid transporter LAT1 (SLC7A5). J Biol Chem 2018;293:2877-87. [Crossref] [PubMed]
  14. Polewski MD, Reveron-Thornton RF, Cherryholmes GA, et al. SLC7A11 Overexpression in Glioblastoma Is Associated with Increased Cancer Stem Cell-Like Properties. Stem Cells Dev 2017;26:1236-46. [Crossref] [PubMed]
  15. Robert SM, Buckingham SC, Campbell SL, et al. SLC7A11 expression is associated with seizures and predicts poor survival in patients with malignant glioma. Sci Transl Med 2015;7:289ra86. [Crossref] [PubMed]
  16. Cerami E, Gao J, Dogrusoz U, et al. The cBio cancer genomics portal: an open platform for exploring multidi-mensional cancer genomics data. Cancer Discov 2012;2:401-4. [Crossref] [PubMed]
  17. Tang Z, Li C, Kang B, et al. GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res 2017;45:W98-102. [Crossref] [PubMed]
  18. Gyorffy B, Lanczky A, Szallasi Z. Implementing an online tool for genome-wide validation of survival-associated biomarkers in ovarian-cancer using microarray data from 1287 patients. Endocr Relat Cancer 2012;19:197-208. [Crossref] [PubMed]
  19. Zeppernick F, Meinhold-Heerlein I. The new FIGO staging system for ovarian, fallopian tube, and primary peri-toneal cancer. Arch Gynecol Obstet 2014;290:839-42. [Crossref] [PubMed]
  20. Zhang M, Liu T, Xia B, et al. Platelet-Derived Growth Factor D Is a Prognostic Biomarker and Is Associated With Platinum Resistance in Epithelial Ovarian Cancer. Int J Gynecol Cancer 2018;28:323-31. [Crossref] [PubMed]
  21. Morris SM Jr. Arginine: master and commander in innate immune responses. Sci Signal 2010;3:pe27. [Crossref] [PubMed]
  22. Mussai F, Egan S, Higginbotham-Jones J, et al. Arginine dependence of acute myeloid leukemia blast proliferation: a novel therapeutic target. Blood 2015;125:2386-96. [Crossref] [PubMed]
  23. Abdelmagid SA, Rickard JA, McDonald WJ, et al. CAT-1-mediated arginine uptake and regulation of nitric oxide synthases for the survival of human breast cancer cell lines. J Cell Biochem 2011;112:1084-92. [Crossref] [PubMed]
  24. Lu Y, Wang W, Wang J, et al. Overexpression of arginine transporter CAT-1 is associated with accumulation of L-arginine and cell growth in human colorectal cancer tissue. PLoS One 2013;8:e73866. [Crossref] [PubMed]
  25. Werner A, Amann E, Schnitzius V, et al. Induced arginine transport via cationic amino acid transporter-1 is nec-essary for human T-cell proliferation. Eur J Immunol 2016;46:92-103. [Crossref] [PubMed]
  26. Berns EM, Bowtell DD. The changing view of high-grade serous ovarian cancer. Cancer Res 2012;72:2701-4. [Crossref] [PubMed]
  27. Wei L, Wang X, Lv L, et al. The emerging role of microRNAs and long noncoding RNAs in drug resistance of hepatocellular carcinoma. Mol Cancer 2019;18:147. [Crossref] [PubMed]
  28. Kehoe S, Hook J, Nankivell M, et al. Primary chemotherapy versus primary surgery for newly diagnosed advanced ovarian cancer (CHORUS): an open-label, randomised, controlled, non-inferiority trial. Lancet 2015;386:249-57. [Crossref] [PubMed]
  29. Tsuyoshi H, Orisaka M, Fujita Y, et al. Prognostic impact of Dynamin related protein 1 (Drp1) in epithelial ovarian cancer. BMC Cancer 2020;20:467. [Crossref] [PubMed]
  30. Mirza MR, Monk BJ, Herrstedt J, et al. Niraparib Maintenance Therapy in Platinum-Sensitive, Recurrent Ovarian Cancer. N Engl J Med 2016;375:2154-64. [Crossref] [PubMed]
  31. Ducie J, Dao F, Considine M, et al. Molecular analysis of high-grade serous ovarian carcinoma with and without associated serous tubal intra-epithelial carcinoma. Nat Commun 2017;8:990. [Crossref] [PubMed]
  32. Joueidi Y, Dion L, Bendifallah S, et al. Management and Survival of Elderly and Very Elderly Patients with Ovarian Cancer: An Age-Stratified Study of 1123 Women from the FRANCOGYN Group. J Clin Med 2020;9:1451. [Crossref] [PubMed]
  33. Scott LJ. Niraparib: First Global Approval. Drugs 2017;77:1029-34. [Crossref] [PubMed]
  34. Lorusso D, Scambia G, Pignata S, et al. Prospective phase II trial of trabectedin in BRCA-mutated and/or BRCAness phenotype recurrent ovarian cancer patients: the MITO 15 trial. Ann Oncol 2016;27:487-93. [Crossref] [PubMed]
Cite this article as: Gong W, Chen Y, Zhang Y. Prognostic and clinical significance of Solute Carrier Family 7 Member 1 in ovarian cancer. Transl Cancer Res 2021;10(2):602-612. doi: 10.21037/tcr-20-2744

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