SNX protein family is broadly distributed in cytoplasm especially the endosomal network, and plays a great part in sorting and transportation of cargo protein in the endomembrane system of eukaryotes, keeping going cell biosynthesis and material secretion. Although researches on SNX family venture into diverse fields, including material sorting and transportation mediated by specific domains such as PX domain and PDZ domain, degradation and recycle of cell surface receptors, participation in the process of virus infection, taking part in signal transduction of neurotransmitter, regulating autophagy process and even affecting the growth of cancer cells. However, nearly half of the SNX family receives little attention. Therefore, our study was the first time that comprehensively discussed the correlation between SNX family and gastric cancer prognosis using bioinformatics technology, taking SNX family as a whole. Expression profiles of SNX family and relationship between transcriptional abundance and survival rates, association between SNX mRNA expression and tumor immunity, relevance between SNXs alteration and MSI status as well as tumor suppressing genes mutation were all included in this study, and finally one multivariable cox regression model for risk classification and six prognostic models based on ANN were employed to further disclose the prognostic role of SNX family in GC.
Based on TCGA gastric cancer transcriptome data STAD, we identified differentially expressed genes in gastric cancer comparing to adjacent normal tissue. SNX4/5/6/7/8/10/13/14/15/16/20/22/25/27/30 were overexpressed in gastric cancer, while SNX1/17/21/24/33 were higher expressed in normal tissue. In addition, Kaplan-Meier survival analysis based on TCGA showed that high expression of SNX3/18/19/29 indicated a shorter OS period, while those with SNX4/6/8/11/12/13/16 low expressed lived longer. KM curves presented with Kaplan-Meier Plotter revealed that much more SNX family members were closely related to OS, FP, and PPS. It was displayed that higher expression of SNX1/9/11/13/17/18/20/21/22/24/26/27/29/30/31/32/33 predicted a shorter OS, SNX2/3/4/5/6/7/8/10/12/14/15/16/19 just did the opposite. High translational level of SNX1/9/11/13/17/18/20/21/22/24/26/27/29/30/31/32/33 implied worse FP, while SNX2/3/4 /5/6/7/8/10/14/15/16/19 did the opposite. PPS analysisgave the same result as FP analysis did. Generally, analysis based on KM-Plotter offered a more satisfactory result than that based on TCGA did, because of a larger sample size, ranging from 631 to 875. Secondly, SNX25 was proved to be no statistically significant in the survival analysis based on neither TCGA and GEO database, and SNX12 did the same in FP or RFS analysis. What's more, we found an intriguingly phenomenon that SNX/4/5/6/7/8/10/13/14/15/16 is highly expressed in GC, but high expression suggested a better prognosis. SNX1 was lower expressed in gastric cancer, but its lower expression associated with longer survival time. Such results challenged we researchers’ conventional cognition, but it might also reflect the complexity of tumor prognostic study on the other hand. Actually, there have already been some, but not many members of the SNX family documented to be related to initiation, progression and prognosis of several cancer types. SNX1 has been deeply studied in gastrointestinal carcinoma. SNX1 mRNA and protein were first demonstrated to be low expressed in colon cancer, and gastric cancer cells with SNX1 deletion showed stronger proliferation ability and were more likely to activate the signal transduction of EGFR-ERK1/2 pathway induced by EGF, along with the sensitivity to anoikis decreased. [16] Then, miR-95 was found to bind to the 3'untranslated region of SNX1, and promoted proliferation of colon cancer cells caused by miR-95 overexpression could be reversed by SNX1 overexpression, suggesting that miR-95 alleviated anticancer effect of SNX1 in colon cancer. [17] Consistent with our study, SNX1 has also been shown to be lower expressed in gastric cancer by xiao-yong zhan et al, but patients with SNX1 high expression harbored longer OS, which is inconsistent with this study. [9] In gefitinib-resistant non-small cell lung cancer cells, SNX1 was found to inhibit the endocytosis and degradation of MET whose overexpression was believed to be responsible for gefitinib resistance in non-small cell lung cancer. [18] Similarly, regulating the degradation of c-MET in lysosomes, SNX2 was expected to be a novel drug target to elevate the sensitivity to EGFR-targeted drugs in non-small cell lung cancer. [19, 20] SNX2 might play a tumor suppressing role in liver cancer and colon cancer. SNX2 deletion has been found to promote hepatocyte growth factor receptor tyrosine phosphorylation and activation of ERK1/2 pathway. At the same time, SNX2 was lower expressed in colon cancer, and it suggested smaller cumulative survival rate. [21] Again, in high-grade gliomas, the overexpression of SNX3 disrupted EGFR and MET endosomes, inhibited the degradation of both through lysosome lysis, and thus promoted the proliferation of gliomas. [22] SNX5 is one of the components of the mammalian cargo-selective complex of retromer, so SNX5 exerted impact on tumor progression by directly affecting the transportation of diverse cell surface receptors or others. High expression of SNX5 was demonstrated in well-differentiated papillary thyroid carcinoma, and co-expression of SNX5 and caspase-2 was also found in thyroid epithelial cells. [23] Meanwhile, high level of TSH was commonly considered to be a risk factor for recurrence of thyroid cancer after surgery, and SNX has been shown to suppress TSH expression. [24] However, there were also reports asserting that SNX5 was accused of inhibiting the degradation of EGFR, and this mechanism was later confirmed in hepatocellular carcinoma. [7, 8] Similarly, SNX5 bound to FBW7, thereby indirectly distract FBW7 from interacting with oncoproteins such as MYC, NOTCH and Cyclin E1 to mediate their degradation by ubiquitination, leading to an increase of oncoproteins and promoting the progression of head and neck squamous cell carcinoma. [25] As also institutional structure of retromer, SNX6 has been reported to enhance the core effect of breast cancer transcription in a dose-dependent manner, that is suppressing transcription in breast cancer. [26] In pancreatic cancer cells, SNX6 overexpression has been witnessed to maintain mesenchymal properties of tumor cells, contributing to metastasis, while SNX6 silencing inhibited the EMT process induced by TGF-β, suggesting engagement of SNX6 with metastasis of pancreatic cancer. [27] SNX9 has been shown to lower expressed in breast cancer and non-small cell lung cancer in highly advanced stage. Besides, SNX9 was co-localized with TKS5, a marker of invasive pseudopodia, and overexpression of SNX9 negatively regulated the number and function of invasive pseudopodia, thereby reducing its extracellular degradation. [28] In addition, overexpression of SNX9 has been found in vascular endothelial cells in colon cancer, which was proved to be associated with poor prognosis of colon cancer. At the same time, SNX9 was regarded as a new vascular regulator, because SNX9 knockout would decrease the recycling rate of β-integrin, resulting in a smaller amount of β-integrin on cell surface. [29] SNX10 manifested a tumor suppressing influence by regulating autophagy behavior of tumor cells to inhibit the progress of colorectal cancer. [30-32] SNX27 is a special member of the SNX family. In addition to the PX domain, it also contains a PDZ domain. G protein-coupled receptors are the largest membrane protein family and are broadly engaged with transduction of multiple intracellular downstream signaling pathways. Binding to the PDZ binding motif of G protein-coupled receptors through PDZ domain, SNX27 interferes with its recycling from the endosome to cell membrane, and thus SNX27 is expected to be the next promising tumor therapeutic target. [33] In general, SNX family members participating in construction of the retromer complex were directly involved in the degradation or cycling of numerous receptors, but other SNXs were also illustrated to regulate intracellular transportation through their distinct domains such as PDZ domain, giving an insight into the reason why aberrant expression of SNX family members affects tumor prognosis.
Analysis using Timer showed that cancer associated fibroblasts, endothelial cells, macrophages and Tregs were statistically significant in the survival analysis. SNX1/3/9/18/19/21/29/33, SNX1/17/18/20/21/29/31/33, SNX1/2/3/6/10/18/29/33, and SNX1/2/6/10/17/18/20/29 were strongly correlated with TIICs mentioned above, with Spearman coefficients all over 0.3. SNX29 seemed to be the next research hotspot of immune regulation in gastric cancer, for its positive correlation with all the four TIICs types. Although the latest study showed that SNX5 mediated autophagy and immunity induced by virus infection, there has been few reports of immune-related research on SNX family. [34] However, numerous studies have reported that autophagy had an indivisible relationship with tumor immunity, including MHC type II cytoplasmic and phagocytic antigen presentation, adaptive immunity and immune tolerance, and down-regulation of signal transduction during antigen presentation, T cell homeostasis, Th17 polarization, plasmacyte and humoral immunity, and immune mediator secretion regulation. [35] SNX4-SNX7 heterodimers has been verified to recruit autophagy regulators in the early stage of autophagosome assembly, and that SNX4 knockout will cause failure of rapidly ATG9A transportation from the perinuclear to the autophagosome-assembling site upon stimulation of autophagy to form the peripheral membrane pools necessary for autophagy assembly. [36] In addition, SNX18 has also been documented to interact with Dynamin-2 to induce membrane budding of recycling endosomes containing ATG9A and ATG16L1, which were then transported to the place where autophagosomes would be formed to participate in autophagosome assembly. [37] As mentioned above, in colon cancer, SNX10 has been proved to regulate expression of a core effector, P21, in tumor suppressing pathways and to affect metabolism of amino acids mediating activation of mTOR by regulating chaperone-mediated autophagy. Lacking for SNX10 would lead to reduced SRC endosomal lysosomal degradation, thereby activating SRC-mediated STAT3 and CTNNB1 signaling pathways. [30-32] These data indicated that the SNX protein family might be more likely to participate in tumor immunity in an indirect way through regulation of autophagy.
The concept of microsatellite instability was put forward by Z LODIN in the central nervous system in 1958, but it was since 1991 that people started disclosing its specific role in tumor initiation, progression and even prognosis. [38] TCGA has divided GC into four categories according to their molecular subtypes: GC with Epstein Barr Virus positive (EBV), microsatellite instability (MSI), genomically stable (GS) and chromosomal instability (CIN). MSI is defined as a hyper-mutated phenotype of satellites, short tandem repeats running through the entire genome, and it occurs when the mismatch repair mechanism is impaired. The mismatch repair mechanism is mediated by a series of mismatch repair enzymes, including MLH1 whose promoter methylation directly leads to MSI occurrence. [39] Classifications of MSI status are not completely unified, but there are mainly two of them. The first type encompasses MSS (microsatellite stable), MSI-H (microsatellite instability-high), and MSI-L (microsatellite instability-low); the second type refers to MSI-H, MSS/MSI-L, and data of MSI status in this study from cBioportal database applied both of them. [40, 41] The mutation frequency of the SNX family reached 47%, and the altered population was more likely to suffer from MSI and MSI-H or hyper-mutated MSI. Consistent with the result mentioned above, the altered samples were detected with higher frequency of MLH1 silencing, or MLH1 promoter methylation in other words. AT-Rich Interaction Domain 1A (ARID1A), characterized as chromatin remodeling gene, and TP53, are broadly considered as tumor suppressors, both more commonly seen mutated in SNXs altered group. Corresponding to prior reports that after the application of next-generation sequencing, deficiency of mismatch repair mechanism arising from MLH1 promoter methylation has been proved stimulus to MSI, and ARID1A mutation were more commonly seen in those with MSI, suggesting ARID1A Mutation might also be a contributor to MSI. [42] In addition, the altered group had a higher probability of 8q gain, and studies have confirmed that SNX8q gain functioned as a negative predictor of prognosis in prostate cancer, renal clear cell carcinoma, resectable pancreatic adenocarcinoma, and hematological malignant tumors. [43-45] Tt has been documented that C-MYC was located at 8q and 8q gain might up-regulate the expression of C-MYC, resulting in activation of downstream MAPK/ERK pathway. [46] Therefore, we here conclude that SNX family alteration may contribute to various malignant mutational events such as that of ARID1A, TP53 and MLH1, thus leading to MSI in GC, but there needs further research for winnowing out SNXs that playing the biggest role.
Through multivariate and univariate cox regression analysis, we found that characteristics of age, SNX3/4/8/11/13/14/25/30 were independent risk factors for OS in GC. From the nomogram, we found that SNX4/8/13 had greater impact on risk classification for patients even than T/N-stage did. The C index of the training set and the validation set divided by a ratio of 6:4 was 0.75 and 0.72, respectively, and AUC were 0.778, 0.749, and 0.752. The model manifested promising potential for risk classification, for those defined as with high risk underwent apparent shorter survival period and higher mortality. Finally, high risk acted as herald of higher immune cells score and higher immune cells function score, which again proved the positive relevance between SNX family expression and tumor immune infiltration. This part of the study suggested that the SNX family had promising potential of risk classification for those with GC and helping access postoperative OS comprehensively.
In recent years, ANN has been proved doing well in model construction for predicting postoperative survival of patients with cancers, lymph nodes metastasis, and drug resistance during chemotherapy or targeted therapies and so on, and they even performed better than traditional prediction models. With SNX3/4/6/8/11/12/13/16/19/29 and age, T-stage, n-stage and sex as feature values for OS estimation, or SNX3/6/8/11/12/13/19 and pathological stage inputted as feature values for RFS evaluation, and AUC of training sets and validation sets was 0.87/0.72, 0.84/0.72, 0.90/0.71, 0.94/0.66, 0.83/0.71, 0.88/0.72, corresponding to one-, three-, and five-year OS and RFS prediction. The one-year RFS prediction model seemed not valuable enough, and it might be caused by the unbalanced problem of 428 samples within which recurrence accounted for only 11.7%, leading to weak generalization ability of the model. Given a lager sample, the ANN models would manifest a more promising predictive potential, and the value of SNX family in GC prognosis estimation would be further reflected.