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Back to Journal »Journal of Inflammation Research» Volume 14
Gasdermin D in different subcellular locations predicts different progression, immune microenvironment and prognosis of colorectal cancer
Authors: Wang Jie, Kang Y, Li Y, Sun Li, Zhang Jie, Qian Sheng, Luo Ke, Jiang Yu, Sun Li, Xu Fei
Published on November 25, 2021, the 2021 volume: 14 pages 6223-6235
DOI https://doi.org/10.2147/JIR.S338584
Single anonymous peer review
Reviewing editor: Professor Quan Ning
Wang Jiahui,1,2,* Yixin Kang,1,2,* Yuxuan Li,1,2,*Liang Sun,1,2 Zhang Jun,1,2 Qian Senmi,1,2 Locke,1 Jiang Yi, 3Sun Lichao,4 Xu Fangying1,2 1Department of Pathophysiology and General Surgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang; 2Zhejiang Key Laboratory of Disease Proteomics, Zhejiang University School of Medicine, Hangzhou, Zhejiang; 3Anhui Department of Statistics, School of Mathematical Sciences, Hefei, Anhui; State Key Laboratory of Molecular Oncology, National Cancer Center/Tumor Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, No. 866 Yuhangtang Road, Hangzhou, Zhejiang Surgery, Zhejiang Provincial Key Laboratory of Disease Proteomics, No. 866 Yuhangtang Road, Hangzhou, Zhejiang, 310058 Tel +86— 571-88208198 Fax +86- 571-88208197 Email [Email Protection] Beijing Pan, People’s Republic of China Homeland South Lane 17 National Cancer Center/Tumor Hospital, Chinese Academy of Medical Sciences, Sun Li, State Key Laboratory of Supramolecular Oncology, Peking Union Medical College 100021 Email [protected by email] Background: Pyrolysis is a type of cell death that causes an immune response . Gasdermin D (GSDMD), as the executor of pyrolysis, has become an attractive target for cancer research. However, the clinical significance of GSDMD expression in different subcellular locations remains unclear. Methods: Immunohistochemical method was used to detect 178 cases of colorectal cancer and follow-up data to detect GSDMD. Collect general data and information of systemic inflammation indicators from case records, and examine clinicopathological parameters through a microscope. Immunohistochemical detection of CD3+, CD4+, CD8+ T lymphocytes, CD20+ B lymphocytes, CD68+ macrophages. Univariate survival analysis (Kaplan-Meier method, log-rank test) and multivariate Cox proportional hazards model were used to analyze the effect of GSDMD on overall survival. Results: Survival analysis showed that the high expression of cytoplasmic GSDMD was an independent favorable indicator of prognosis (P=0.027) and improved the efficacy of chemotherapy (P=0.012). Positive cytoplasmic GSDMD expression indicates a lower possibility of distant metastasis (P=0.024), but nuclear GSDMD expression predicts deeper infiltration depth (P=0.007). The expression of membranous GSDMD was positively correlated with CD68+ macrophages in the tumor center (P=0.002) and CD8+ lymphocytes in the front of tumor invasion (P=0.007). However, nuclear GSDMD was negatively correlated with CD68+ macrophages in the front of tumor invasion (P<0.001) and CD8+ lymphocytes in the center of the tumor (P=0.069). Cytoplasmic GSDMD is associated with more CD3+ lymphocytes in the tumor center (P=0.066) and tumor invasion front (P=0.008). In addition, a positive membrane GSDMD indicated a low ratio of neutrophils to lymphocytes (P = 0.013). Conclusion: The subcellular localization pattern of GSDMD is related to the progression of CRC and immune response and should be studied in future studies. Keywords: gasdermin D, pyrolysis, prognosis, immune microenvironment, colorectal cancer
Colorectal cancer (CRC) is the leading cause of cancer deaths worldwide. It is estimated that among all cancers diagnosed, CRC ranks third in incidence (10.6%) and second in mortality (9.3%)1. Advances in screening and treatment have significantly improved the prognosis of CRC. However, the 5-year survival rate ranges from 90% in early-stage patients to 14% in patients diagnosed with distant metastases. 2 Immunotherapy has opened up a new way to improve the prognosis of patients with distant metastases of CRC. 3
As we all know, the characteristics of tumor cells and their microenvironment will affect the prognosis of cancer. Lymphocytes and tumor-associated macrophages (TAM) are the most common immune cells in the immune microenvironment (IME). Abundant cytotoxic T lymphocytes may indicate a good prognosis. M1 macrophages are beneficial to the prognosis of patients, but M2 macrophages are not good for the prognosis of patients. IME can be simply classified as "hot" or "cold". "Hot" tumors are characterized by active infiltration of T lymphocytes, and "cold" tumors are characterized by lack or rejection of T lymphocytes. 4 Pyrolysis, as the perpetrator of cytokine release and inflammation, may be regarded as a converter between "hot" and "cold". 5
Pyroptosis is defined as gasdermin (GSDM)-mediated programmed cell death, which is accompanied by the destruction of cell membranes and the release of cell contents, which then triggers immune response and inflammation. 6 The GSDMs family includes six members: GSDMA, GSDMB, GSDMC, GSDMD, GSDME and pejvakin (PJVK). GSDMD is a mediator of pyrolysis induced by inflammasomes, and is the first pyrolysis executor to be identified and studied the most. Human GSDMD is cleaved by Caspase-1/4/5 at position 272FLTD275, and then forms the N-terminal domain of GSDMD and the C-terminal domain of GSDMD. The N-terminal domain of GSDMD binds to and penetrates the cell membrane to induce pyrolysis. 7 GSDMD is widely expressed in different tissues and cell types, including intestinal epithelium. 8
GSDMD is associated with poor prognosis of lung adenocarcinoma and osteosarcoma. 9,10 Wu et al. analyzed the expression of GSDMD in 244 cases of CRC and found that GSDMD was an unfavorable predictor. 11 However, they did not distinguish the clinical significance of GSDMD expression in the cell membrane, cytoplasm, and nucleus. In addition, the correlation between GSDMD expression and IME in cancer tissue samples has not been determined. IME includes different types of lymphocytes, macrophages, granulocytes and other cells. The distribution of immune cells in the front of tumor invasion and tumor center is diverse. Microenvironment heterogeneity can also cause heterogeneity among cancer cells and affect treatment response. 12
The cytokines released in the process of pyrolysis trigger a systemic immune response. The number and percentage of inflammatory cells in peripheral blood are potential prognostic markers before treatment. For example, when the lymphocyte/monocyte ratio (LMR) is ≤ 2.83, patients with stage III colon cancer cannot find the benefit of adjuvant chemotherapy based on 5-FU. 13 Neutrophil/lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR) and prognostic nutritional index (PNI) are all important markers for treatment or prognostic evaluation. 14,15
In this study, we collected 178 CRC samples with follow-up and clinicopathological data, and assessed the expression and localization of GSDMD through immunohistochemistry to explore the effects of GSDMD on cancer progression, immune microenvironment, systemic inflammation and prognosis Influence.
The 178 patients with colorectal cancer were all residents of Xiaoshan District, Zhejiang Province. The patient did not receive chemotherapy or radiotherapy before surgery. The follow-up information was provided by the Xiaoshan Center for Disease Control and Prevention. The median follow-up time was 26.5 months (2-75 months). By the end of the follow-up, 149 patients were alive and 29 patients had died. Among the 178 cases, 98 were males and 80 were females; 100 tumors were located in the colon and 78 were located in the rectum. The age at diagnosis was 24 to 91 years old, with an average of 62.53 years old. Among them, 43 cases were in TNM stage I, 53 cases were in TNM stage II, 66 cases were in TNM stage III, and 16 cases were in TNM stage IV. 84 patients received 5-Fu-based postoperative chemotherapy. This retrospective study was approved by the Ethics Committee of Zhejiang University School of Medicine. The retrospective characteristics of this study and the anonymization of patient data do not require informed consent. The study complies with the Declaration of Helsinki.
All parts of the archives are reviewed and diagnosed by two pathologists. Clinical pathological predictors include histological type, histological grade, tertiary lymphatic structure, vascular infiltration, perineural infiltration, depth of infiltration, lymph node metastasis, distant metastasis, and TNM staging.
Collect preoperative peripheral blood indicators from patient records, including plasma albumin concentration, platelet count, neutrophil count, lymphocyte count, monocyte count, total white blood cell count, neutrophil percentage, lymphocyte percentage, single The percentage of nuclear cells and the percentage of eosinophils. In addition, NLR, PLR, LMR, and PNI are also calculated. NLR is determined as the ratio of peripheral neutrophil count to lymphocyte count. PLR is equal to the ratio of peripheral platelet count to lymphocyte count. LMR is defined as the ratio of lymphocytes to monocytes. The calculation formula of PNI is (serum albumin (g/L)+5×total number of lymphocytes×109/L).
We constructed a tissue microarray of 178 CRC tissue samples. Each case had 3 tissue perforations, which were taken from the normal mucosa of the formalin-fixed paraffin-embedded block, the tumor center (TC), and the tumor invasion front (TIF). The TIF area was determined to be the 20-fold field of view within the most distal tumor cell. Transfer the punch with a diameter of 1 cm to a receiver paraffin block (6×7 punch). Finally, the acceptor paraffin block was cut into 4μm thick sections and mounted on a glass slide coated with APES (3-aminopropyltriethoxysilane).
This study investigated five types of immune cells (CD3+, CD4+, and CD8+ T lymphocytes, CD20+ B lymphocytes, and CD68+ macrophages) and GSDMD. The GSDMD antibody was a gift from Professor Feng Shao (National Institute of Biological Sciences, Beijing, China). Information about primary antibodies and staining patterns is summarized in Supplementary Table 1. CD3, CD4, CD8 and CD20 were detected in the tissue microarray. CD68 and GSDMD were stained throughout the tissue section. The sections were deparaffinized and dehydrated before immunohistochemical staining. Microwave antigen retrieval was performed in citrate buffer (0.01M, pH 6.0), and a two-step method (PV-9000 polymer detection system, Zhongshan Jinqiao, Beijing, China) was performed. Then it was developed with 3,3-diaminobenzidine (DAB) solution and counterstained with hematoxylin. For the blank control, the primary antibody was replaced with PBS solution (100mM, pH7.4). Obvious brown particle staining is defined as positive. Loss of data is caused by the tissue falling off the slide. NanoZoomer 2.0HT (Hamamatsu, Japan) was used to digitally scan all immunohistochemically stained glass slides.
Regarding the expression of GSDMD in cancer cells, we used the following scale to score the percentage of positive cells: 0 = no staining; 1 = less than 5%; 2 = 5–25%; 3 = 26–50%; 4 = 51 –75%; 5 = more than 75%. Using computer automated methods (Image-pro plus 6.0, Media Cybernetics Inc.) count the number of immune cells in the four hot spots (20×, 545×577 μm2), and define the density of immune cells as each high Average count-power field (HPF, 20×).
Use IBM SPSS Statistics 26.0 (IBM SPSS, Armonk, NY, USA) for statistical analysis. We use chi-square test or Fisher's exact test to compare GSDMD expressions with other categorical variables. The t test is used to check the difference in the overall distribution between two groups. Use the "Survfit" function in R for univariate survival analysis, and use the Kaplan-Meier method and Log rank test to draw the survival curve. The cumulative survival rate is calculated using the life table method. Use the Cox proportional hazards model for multivariate survival analysis, and use the forward stepwise method to introduce variables into the model. If the P value is <0.05, it is determined that there is a significant difference. If 0.05≤P value<0.1, it is determined that there is a trend of significant difference.
GSDMD is expressed in the cell membrane, cytoplasm and nucleus (Figure 1). The number of cases with each score in different locations is listed in Supplementary Table 2. In the following analysis, GSDMD positive is defined as a score>0, when the score=0, GSDMD is negative. The positive rates of GSDMD in cell membrane, cytoplasm and nucleus were 3.93% (7/178), 63.48% (113/178) and 61.24% (109/178), respectively. The expression of cytoplasmic GSDMD and nuclear GSDMD was consistent (P=0.001). Figure 1 The immunohistochemical staining images of GSDMD in membrane (A), cytoplasm (B) and nucleus (C). 400 times magnification.
Figure 1 The immunohistochemical staining images of GSDMD in membrane (A), cytoplasm (B) and nucleus (C). 400 times magnification.
GSDMD expression is classified as negative or positive. There was no significant difference in the expression of membranous GSDMD between age, gender, location, histological type, histological grade, tertiary lymphatic structure, vascular infiltration, perineural infiltration, depth of infiltration, lymph node metastasis, distant metastasis, or TNM stage ( Table 1). Patients with cytoplasmic GSDMD expression are less likely to develop distant metastases (P=0.024) (Table 2). Table 1 Correlation between GSDMD expression in cell membrane and clinicopathological indexes Table 2 Correlation between GSDMD expression in cytoplasm and clinicopathological indexes
Table 1 The relationship between the expression of membranous GSDMD and clinicopathological indicators
Table 2 The relationship between cytoplasmic GSDMD expression and clinicopathological indicators
Interestingly, positive nuclear GSDMD expression is more common in women (P=0.063) and rectal cancer (P=0.053), and is associated with low histological grade (P=0.010), perineural infiltration (P=0.006), Tumor-related extraserous infiltration (P=0.007), positive lymph node metastasis (P=0.020) and higher TNM stage (P=0.068) (Table 3). Table 3 The correlation between nuclear GSDMD expression and clinicopathological indicators
Table 3 The correlation between nuclear GSDMD expression and clinicopathological indicators
Regardless of the position of GSDMD expression, the positive and negative groups are in terms of plasma albumin concentration, platelet count, total white blood cell count, neutrophil count, lymphocyte count, monocyte count, neutrophil percentage, and lymphocyte percentage There were no significant differences, or the percentage of monocytes (Supplementary Table 3-5).
The expression of GSDMD in the membrane, cytoplasm or nucleus has nothing to do with NLR, PLR, LMR or PNI. In addition, we group NLR, PLR, LMR, and PNI according to the median. 6 cases (6/6100%) with positive membrane GSDMD had lower NLR levels (NLR≤2.8), while 73/155 cases (47.1%) with negative membrane GSDMD had lower NLR levels (P=0.013, Table 1).
Immune cells infiltrating the tumor stroma were counted in TC and TIF respectively (Figure 2). In the membrane GSDMD positive expression group, there were more CD68+ macrophages in TC (P=0.002), and more CD8+ lymphocytes in TIF (P=0.007). In the cytoplasmic GSDMD positive group, TC (P=0.066) and TIF (P=0.008) had more CD3+ lymphocytes, while TC had fewer CD4+ lymphocytes (P=0.062). However, when the expression of nuclear GSDMD was positive, there were fewer CD68+ macrophages in TIF (P<0.001), and fewer CD8+ lymphocytes in TC (P=0.069) (Table 4). Table 4 Differences of immune cells in IME based on GSDMD expression Figure 2 CD3+ lymphocytes (A), CD4+ lymphocytes (B), CD8+ lymphocytes (C), CD20+ lymphocytes (D) and CD68+ macrophages (E) Immunohistochemical staining image. 400 times magnification.
Table 4 Immune cell differences in IME based on GSDMD expression
Figure 2 The immunohistochemical staining images of CD3+ lymphocytes (A), CD4+ lymphocytes (B), CD8+ lymphocytes (C), CD20+ lymphocytes (D) and CD68+ macrophages (E). 400 times magnification.
First, we compared the overall survival rate of GSDMD within each score. For the cytoplasmic GSDMD, the results showed that the group with a score of 2 had the worst survival rate (9/24 deaths). Specifically, 14 of the 65 patients in the 0 group died, 4 of the 41 patients in the 1 group died, 9 of the 24 patients in the 2 group died, and 0 of the 13 patients in the 3 group died, and 19 died One of the patients died in the score 4 group, and 1 of 16 patients died in the score 5 group (see Supplementary Figure 1A). Neither membranous GSDMD nor nuclear GSDMD showed a significant difference in survival between any scoring groups (Supplementary Figures 1B and C). Next, we divide the cytoplasmic GSDMD into low expression (score ≤ 2) and high expression (score> 2). At the end of the follow-up, 27/130 patients in the low expression group died, and 2/48 patients in the high expression group died (P=0.006) (Figure 3A). The 5-year overall survival rate of the cytoplasmic GSDMD low expression group was 72%, and the 5-year overall survival rate of the GSDMD high expression group was 95%. Therefore, it is clear that high expression of GSDMD is a favorable prognostic marker for CRC. Figure 3 The survival curve of GSDMD expressed by the "Survfit" function in R using the Kaplan-Meier method and Log rank test. The high and low cytoplasmic GSDMD expression groups (A). The positive and negative groups of cytoplasmic GSDMD expression (B). The cytoplasmic GSDMD expression positive group and negative group of patients with chemotherapy (C) or no chemotherapy (E). High and low cytoplasmic GSDMD expression of patients with chemotherapy (D) or no chemotherapy (F).
Figure 3 The survival curve of GSDMD expressed by the "Survfit" function in R using the Kaplan-Meier method and Log rank test. The high and low cytoplasmic GSDMD expression groups (A). The positive and negative groups of cytoplasmic GSDMD expression (B). The cytoplasmic GSDMD expression positive group and negative group of patients with chemotherapy (C) or no chemotherapy (E). High and low cytoplasmic GSDMD expression of patients with chemotherapy (D) or no chemotherapy (F).
We also compared the overall survival rate between the negative and positive cytoplasmic GSDMD groups. At the end of the follow-up, 14/65 patients in the negative group died, and 15/113 patients in the positive group died (P=0.1) (Figure 3B).
In order to explore whether the expression of cytoplasmic GSDMD affects the efficacy of chemotherapy, we conducted survival analysis on 5-Fu-based postoperative chemotherapy group or non-chemotherapy group. The results showed that both positive (P=0.072) and high (P=0.012) cytoplasmic GSDMD expression improved the efficacy of chemotherapy (Figure 3C and D). In the absence of chemotherapy, the expression of cytoplasmic GSDMD had no effect on survival (P>0.1) (Figure 3E and F).
Finally, our multivariate Cox proportional hazards model includes age, gender, histological type, histological grade, vascular infiltration, perineural infiltration, TNM staging, chemotherapy, and cytoplasmic GSDMD expression. The results showed that TNM staging and cytoplasmic GSDMD expression were independent prognostic factors (Table 5). The high expression of cytoplasmic GSDMD increased the overall survival rate (RR (95 CI): 0.196 (0.046–0.834), P=0.027). Table 5 Results of the multivariate Cox proportional hazard model
Table 5 Results of the multivariate Cox proportional hazard model
Currently, more than 10 regulated cell deaths have been defined. Pyrolysis is a regulated form of lytic cell death that relies on the perforation of the plasma membrane mediated by the gasdermin family. 16 Initially, pyrolysis was observed in monocytes or macrophages that had undergone classic Caspase 1 activation, but later it was also found in some epithelial cells. 17 NLRP1 (NLR family pyrin domain contains 1), NLRP3 and AIM2 (not present in melanoma 2) can participate in the formation of inflammasomes and activate Caspase 1. Caspase-1/4/11 can cut GSDMD human or mouse LLSD in the central junction region (FLTD) to form GSDMD N-terminal fragment (NT) and GSDMD C-terminal fragment (CT). Functionally speaking, GSDMD-NT forms transmembrane pores in cell membranes and organelle membranes (such as mitochondria or nuclear membranes). The GSDMD-NT pores in the cell membrane cause material exchange and pyrolysis. The GSDMD-NT pores in the organelle membrane also contribute to cell pyrolysis or other reactions. For example, when GSDMD-NT targets the mitochondrial membrane, it promotes the production of reactive oxygen species. 18 Our results indicate that GSDMD is located in the cell membrane, cytoplasm and nucleus. Among the membrane type, cytoplasm type and karyotype GSDMD, the membrane type GSDMD has the lowest positive rate, but the cytoplasmic type GSDMD and the karyotype GSDMD have similar positive rates.
Membranous GSDMD is associated with lower NLR, more CD68+ macrophages in TC, and more CD8+ lymphocytes in TIF, but has nothing to do with other clinicopathological parameters in this study. The cytoplasmic GSDMD predicts fewer distant metastases, more CD3+ lymphocytes in TC and TIF, and fewer CD4+ lymphocytes in TC, and the prognosis is better. However, there is no relationship between cytoplasmic GSDMD and systemic inflammation indicators. Karyotype GSDMD is more common in women, rectal cancer, and cancers with lower histological grades, indicating perineural infiltration, deeper infiltration, more lymph node metastasis, higher TNM stage, fewer CD68+ macrophages in TIF, and TC There are fewer CD8+ lymphocytes in.
In summary, membranous GSDMD is related to systemic inflammation and tumor immune microenvironment. Cytoplasmic GSDMD tends to recruit CD3+ lymphocytes in TIF, reducing distant metastasis, and improving prognosis, while nuclear GSDMD leads to a decrease in the density of macrophages and CD8+ lymphocytes and more aggressive cancers. Functional and mechanism studies are needed to confirm the phenomenon in our research. Our results are only the tip of the iceberg of the role of GSDMD. Further mechanism studies are needed to confirm the correlation between GSDMD subcellular location and function, such as the downstream signaling pathways activated by GSDMD at different subcellular locations.
As a powerful executor of pyrolysis, GSDMD is closely related to the immune response of local IME and systemic immune response. Membranous GSDMD does not always mean pyrolysis. Membrane perforated by GSDMD can be repaired by ESCRT-III mechanism. 19 In conformation, the front pore of GSDMD is very short, similar to the self-inhibited GSDMD-NT. 20 GSDMD pores or anterior pores mediate the release of cell contents, such as pro-inflammatory cytokines and endogenous damage-related molecular patterns (DAMP) in tumor cells and immune cells (such as macrophages and NK cells). 21 As the link between innate immunity and adaptive immunity, these contents play a complex role in anti-tumor immunity. For example, the IL-1 family is the most studied cytokine released by pyrolyzed cells. Among them, IL-1β can induce the differentiation of Th1 and Th17 cells. 22 IL-18 can not only up-regulate the levels of tumor-infiltrating CD8+ T lymphocytes and natural killer cells (NK), but also promote the activity of IFN-γ. 23 Up-regulated tumor-infiltrating cytotoxic T lymphocytes are dependent on caspase 3 Sex or other mechanisms induce tumor cell apoptosis, which further leads to the release of more cytokines and chemokines to recruit lymphocytes, forming a positive feedback pathway. 24 On the other hand, DAMP HMGB1, which is most related to cancer, can abnormally trigger anti-tumor immune inflammation or immune tolerance by causing the recruitment of white blood cells or inducing the release of IL-10. 25 Generally speaking, GSDMD-mediated tumor cell pyrolysis and its released contents may jointly regulate the recruitment of immune cells in IME.
In the systemic inflammatory response of CRC, neutrophils can interact with tumor cells and promote tumor cell invasion and metastasis. 14 Some studies have reported that elevated NLR may lead to poor immune response to malignant tumors. 26,27 It is worth noting that among all systemic inflammation indicators, we only found an association between positive membranous GSDMD and lower NLR levels in our study. Our results indicate that the expression of membranous GSDMD may promote the immune response.
Recent studies have shown that GSDMD is related to the prognosis of a variety of cancers. As mentioned above, Wu et al. found that GSDMD is associated with poor prognosis of CRC. 11 However, some studies have also shown that important molecules involved in the pyrolysis pathway, such as NLRP1, NLRP3, and AIM2, have low levels in CRC. 28,29 In addition, high GSDMD expression has been shown to be associated with longer overall survival and less cancer cell invasion in breast cancer. However, in adenoid cystic carcinoma (ACC), GSDMD enhances the invasion ability of ACC cells, which indicates that high expression of GSDMD is related to poor prognosis. 30 As for the mechanism, Wang et al. reported that decreased expression of GSDMD can promote tumor cell proliferation by activating extracellular signal-regulated kinase 1/2 (ERK1/2), signal transducer and activator of transcription 3 (STAT3) and phosphatidylinositol 3- The kinase (PI3K)/protein kinase B (AKT) signaling pathway regulates cell cycle related proteins. 21 Studies also show that lncRNA RP1-85F18.6 can induce the occurrence of CRC cell pyrolysis by activating GSDMD, which has certain prognostic value. 31
From these conflicting previous research results, we found that the existing research did not distinguish the expression of GSDMD in the membrane, cytoplasm, and nucleus. Significantly, in our research, we found that nuclear GSDMD seems to be the opposite of cytoplasmic GSDMD in terms of cancer progression. High nuclear GSDMD levels promote CRC invasion and metastasis, and reduce the density of CD68+ macrophages and CD8+ T lymphocytes. At the same time, patients with high cytoplasmic GSDMD levels have a lower risk of distant metastasis, better overall survival, and more CD3+ lymphocytes.
Some researchers have put forward the theory of the dual mechanism of scorching death. On the one hand, pyrolysis may inhibit the occurrence and development of tumors, but as a pro-inflammatory death, it may also create a suitable microenvironment for the growth of tumor cells, which means that it has a dual mechanism of promoting and inhibiting tumorigenesis. . 32 Perhaps these dual mechanisms are related to the difference between nuclear and cytoplasmic GSDMD expression.
What is the impact of nuclear GSDMD accumulation? Why does GSDMD in the cytoplasm and nucleus have opposite functions? Did something special happen during the nuclear-mass transport process of GSDMD? Finding the answers to these questions will help assess the value of GSDMD as a candidate cancer target with therapeutic potential. Our research only focuses on the relationship between GSDMD and clinicopathological parameters, and further mechanism studies are needed.
Wang et al. revealed that chemotherapeutic drugs can effectively inhibit tumor proliferation and metastasis by inducing cell pyrolysis. 33 Most studies have found that chemotherapeutic drugs can convert caspase-3 dependent cell apoptosis into pyrolysis through GSDME. Interestingly, in our study, GSDMD expression clearly helped patients benefit from chemotherapy. This provides new insights for anti-cancer treatment. However, we still know very little about how GSDMD inhibits cancer progression and improves the effect of chemotherapy. Considerable effort should be made to identify GSDMD target molecules for new drug development.
Our results show that the expression of membranous GSDMD is closely related to the immune response, and the cytoplasmic GSDMD is related to the tumor immune microenvironment and improves patient prognosis; however, the expression of GSDMD in the nucleus of cancer cells promotes tumor invasion and metastasis. In other words, the function of GSDMD depends on its subcellular location. Our research provides a new perspective for the future research of GSDMD, and also provides new support for the further development of GSDMD as a prognostic biomarker and therapeutic target.
Thank you for the technical support of the core facilities of Zhejiang University School of Medicine. Wang Jiahui, Kang Yixin and Li Yuxuan are the co-first authors of this study.
This work was funded by the National Natural Science Foundation of China Project 81772570; the State Key Laboratory of Molecular Oncology Open Project (SKLMO-KF2021-17) and the B13026 Fund Disciplinary Talent Introduction Program.
The authors report no conflicts of interest in this work.
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