Mutations of PI3K-AKT-mTOR pathway as predictors for immune cell infiltration and immunotherapy efficacy in dMMR/MSI-H gastric adenocarcinoma

Background A significant subset of mismatch repair-deficient (dMMR)/microsatellite instability-high (MSI-H) gastric adenocarcinomas (GAC) are resistant to immune checkpoint inhibitors (ICIs), yet the underlying mechanism remains largely unknown. We sought to investigate the genomic correlates of the density of tumor-infiltrating immune cells (DTICs) and primary resistance to ICI treatment. Methods Four independent cohorts of MSI-H GAC were included: (i) the surgery cohort (n = 175) with genomic and DTIC data, (ii) the 3DMed cohort (n = 32) with genomic and PD-L1 data, (iii) the Cancer Genome Atlas (TCGA) cohort (n = 73) with genomic, transcriptomic, and survival data, and (iv) the ICI treatment cohort (n = 36) with pre-treatment genomic profile and ICI efficacy data. Results In the dMMR/MSI-H GAC, the number of mutated genes in the PI3K-AKT-mTOR pathway (NMP) was positively correlated with tumor mutational burden (P < 0.001) and sensitivity to PI3K-AKT-mTOR inhibitors and negatively correlated with CD3+ (P < 0.001), CD4+ (P = 0.065), CD8+ (P = 0.004), and FOXP3+ cells (P = 0.033) in the central-tumor rather than invasive-margin area, and the transcription of immune-related genes. Compared to the NMP-low (NMP = 0/1) patients, the NMP-high (NMP ≥ 2) patients exhibited a poorer objective response rate (29.4% vs. 85.7%, P < 0.001), progression-free survival (HR = 3.40, P = 0.019), and overall survival (HR = 3.59, P = 0.048) upon ICI treatment. Conclusions Higher NMP was identified as a potential predictor of lower DTICs and primary resistance to ICIs in the dMMR/MSI-H GAC. Our results highlight the possibility of using mutational data to estimate DTICs and administering the PI3K-AKT-mTOR inhibitor as an immunotherapeutic adjuvant in NMP-high subpopulation to overcome the resistance to ICIs. Supplementary Information The online version contains supplementary material available at 10.1186/s12916-022-02327-y.

In theory, dMMR/MSI-H solid tumors should acquire favorable benefits from immune checkpoint inhibitor (ICI) treatment, yet nearly 40% of them had progressive disease as the best response [11,12], suggesting the heterogeneity within this hypermutated subtype. Previous studies in MSI-H gastric adenocarcinoma (GAC) and colorectal cancer (CRC) suggested the association between mRNA-based clusters and survival of ICI therapy [13,14]. However, little is known about the heterogeneity of immune-related features in MSI-H tumors, including the density of tumor-infiltrating immune cells (DTICs). A better understanding of the heterogeneity within these hypermutated tumor subsets and the unrecognized mechanism of resistance to ICIs is crucial for patient selection.
GAC is a major cause of cancer deaths worldwide [15]. It is one of the solid tumors with high microsatellite instability [11,[16][17][18], characterized by high abundant leukocyte infiltration, high proportion of activated immunophenotype, and strong correlation between clonal heterogeneity and immunophenotype [19]. Therefore, we were interested to see whether GAC patients with dMMR/MSI-H could be further dissected according to their immune-related features by depicting the mutational landscape of dMMR/ MSI-H GAC and to investigate further the genomic correlates of immune cell infiltration and clinical benefits from ICI treatment.
The 3DMed cohort consisted of 32 cases selected from the 51718 cases of the 3D Medicines database tested between January 6, 2017, and April 14, 2020. Cases were included only if they had PD-L1 expression data as evaluated by PD-L1 IHC 22C3 pharmDx (Dako, Inc.) and genomic profiling data by NGS using a 381-gene panel (Additional file 1: Fig. S1B).
The Cancer Genome Atlas (TCGA) cohort (n = 73) was obtained from the PanCancer stomach adenocarcinoma (STAD) dataset (Additional file 1: Fig. S1C), where patients were included if they had available mutational and transcriptional data, and an MSI-H phenotype diagnosed by the TCGA subtyping system [30]. Missense mutations in this cohort were evaluated by both Polyphen-2 and Sorting Intolerant From Tolerant to filter out potential benign alterations [31,32]. Gene set enrichment analysis (GSEA) was performed to investigate the transcriptional difference.
The ICI treatment cohort (n = 36) was retrieved from the medical records of the Department of Gastrointestinal Oncology, Peking University Cancer Hospital and Institute, where patients with dMMR/MSI-H GAC received at least 1 cycle of any ICI treatment regardless of the agent's target (PD-1, PD-L1, or CTLA-4) from September 1, 2017, to January 31, 2020. These patients had Conclusions: Higher NMP was identified as a potential predictor of lower DTICs and primary resistance to ICIs in the dMMR/MSI-H GAC. Our results highlight the possibility of using mutational data to estimate DTICs and administering the PI3K-AKT-mTOR inhibitor as an immunotherapeutic adjuvant in NMP-high subpopulation to overcome the resistance to ICIs.
Keywords: dMMR/MSI-H gastric adenocarcinoma, PI3K-AKT-mTOR pathway, Tumor-infiltrating immune cell, Immune checkpoint inhibitor their last follow-up before June 1, 2021, and NGS-based mutational data of pre-treatment tissue or plasma (Additional file 1: Fig. S1D). Moreover, ten patients had available data of pre-treatment peripheral blood lymphocyte subset counts via flow cytometry.
Human samples and clinical data were collected and used per the principles of the Declaration of Helsinki and approved by the Ethics committee of Peking University Cancer Hospital. All participants provided written informed consents. This report followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

Statistical analysis
The significance with categorical variables was evaluated by Fisher's exact test. The significance with disease-free survival, progression-free survival (PFS), and overall survival (OS) was assessed by the Log-rank method. Univariable and multivariable Cox regression was implemented to calculate the hazard ratio (HR) of survival data. The significance with continuous variables was assessed by non-parametric tests (e.g., rank-sum tests, Spearman correlation test) or corrected parametric tests for variance correction (e.g., unpaired t-test with Welch's correction). Receiver operating characteristic (ROC) curve and area under the curve (AUC) were used for seeking the best cutoff of the number of mutated genes in the PI3K-AKT-mTOR pathway (NMP) for predicting immunotherapeutic efficacy. All statistical analyses mentioned above were performed using IBM SPSS Statistics 22, and the graphs were drawn by GraphPad Prism 8 and RStudio (version 1.2.5042). We set the nominal significance level as 5%, and all 95% CIs were 2-sided.

Clinicopathological and genomic features of dMMR/MSI-H GAC
The clinicopathological and genomic features of 175 resected samples from patients with primary G/GEJ adenocarcinoma are described in Additional file 1: was able to correctly detect MSI status with 100% sensitivity and 100% specificity. Furthermore, among the 14 samples where IHC result showed incomplete loss of MMR protein expression (e.g., loss of MSH6 expression in 50% of tumor cells and intact expression of MLH1/PMS2/MSH2) or was inconsistent with PCR results (e.g., IHC-dMMR but PCR-MSS), NGS identified 7 NGS-MSI-H cases with the highest variability of the tested microsatellites and the highest frameshift burden in the tested coding sequence (Additional file 1: Table S7). Taken together, NGS performed better in identifying MSI-H cases compared to IHC and PCR, especially when geographical heterogeneity of MMR protein expression is observed, or IHC and PCR results are inconsistent.

Correlates of DTIC in dMMR/MSI-H GAC
Of the 115 concordant-dMMR/MSI-H cases, the evaluation of DTICs was missing in twelve cases (Additional file 1: Table S8), and another fourteen cases were excluded for prior neoadjuvant chemotherapy which could affect DTICs (Additional file 1: Table S9) [33][34][35]. Therefore, 89 samples were included for the following analysis of genomic correlates of DTICs.
A comprehensive correlation matrix was created to seek the correlates of DTICs, including CD3 + , CD4 + , CD8 + , CD68 + , and FOXP3 + cells in central-tumor and invasive-margin areas (Fig. 2). The mutations of the members in the PI3K-AKT-mTOR pathway are illustrated in Additional file 1: Fig. S3. Among the clinicopathological and genomic characteristics, NMP exhibited the strongest negative correlation with DTICs, including CD3 + (P < 0.001), CD4 + (P = 0.065), CD8 + (P = 0.004), and FOXP3 + (P = 0.033) cells in the central tumor area (marked by a red arrow, Fig. 2). The correlations of NMP with central-tumor DTICs were markedly stronger than its correlations with invasive-margin DTICs, suggesting the potential difference of PI3K-AKT-mTOR function in central tumor and invasive margin. Sensitivity analysis further indicated the robustness of the results as mentioned above (Additional file 1: Table S10). The scatter diagrams of the above-mentioned results and representative images of immunohistochemical staining of tumor-infiltrating immune cells are displayed in Fig. 3.
Of note, TMB was strongly correlated with nearly all the numbers of mutated members in the pre-specified pathways (marked by a purple arrow, Fig. 2), including the PI3K-AKT-mTOR pathway, rather than DTICs (marked by a blue arrow, Fig. 2), consistent with previous results in MSI-H CRC [14,36].
Given the correlations of NMP with DTICs, we next sought to investigate the associations of NMP with other potential predictors of immunotherapy, including TMB, PD-L1 expression, and immune-related mRNA signatures.

Biological characteristics of the DTIC-enriched subtype with lower NMP
Higher TMB and PD-L1 levels were commonly associated with more clinical benefits from ICI treatment in MSS G/GEJ cancer [37][38][39][40][41][42][43][44]. Two recent retrospective studies with a small sample size suggested the association between TMB and immunotherapy efficacy in MSI-H GAC [45,46]. Given these findings, we set out to evaluate TMB and PD-L1 expression in the DTIC-enriched subtype of MSI-H GAC with lower NMP.
We retrieved the data of 32 MSI-H GACs (primary lesion) with assessments of mutations and PD-L1 from the 3DMed database. Among these, lower NMP was correlated with lower TMB (P < 0.001, Fig. 4A Table S11. The representative images of PD-L1 staining are shown in Fig. 4C, and the images of corresponding hematoxylin-eosin (HE) staining and positive/negative controls are enclosed in Additional file 1: Fig. S4.
In addition to the immune-related gene signatures, we further assessed the signatures of NOTCH signaling. We previously reported that the NOTCH pathway's downregulation was associated with a higher level of immune gene transcription and better immunotherapeutic efficacy in non-small cell lung cancer (NSCLC) [47]. Here, in the MSI-H GACs, the DTIC-enriched PI3K-AKT-mTOR WT group displayed trends towards downregulation of NOTCH-related signatures, especially the ones concerning transcriptional impact (Additional file 1: Fig.  S5C).

PI3K-AKT-mTOR inhibitor efficacy of MSI-H GAC cell lines with different NMPs
Furthermore, to discover the association between PI3K-AKT-mTOR mutation and drug sensitivity, we retrieved the data of STAD cell lines from the cBioPortal (Cancer Cell Line Encyclopedia, Broad, 2019).   Table S13. All mutations were pathogenic. The IC50 values of every cell line for the PI3K-AKT-mTOR inhibitors (targeting AKT/mTOR/PDK1/PI3K/S6K1), the inhibitors targeting VEGFR or EGFR, and chemotherapeutic drugs were presented in Additional file 1: Table S14. The PI3K-AKT-mTOR inhibitors exhibited lower IC 50 in the SNU-1, IM95, and 23132/87 cell lines (P < 0.001) than in NUGC-3 and TGBC11TKB cell lines, and the inhibitors targeting VEGFR (P = 0.142) or EGFR (P = 0.540) and chemotherapeutic drugs (P = 0.378) showed no  (Fig. 4D). Taken together, these results indicate that the MSI-H STADs with high NMP might benefit more from PI3K/AKT/ mTOR inhibitors compared to the ones with low NMP.

Immunotherapy efficacy of the DTIC-enriched subtypes with lower NMP
The subtype with lower NMP was characterized by higher DTICs and immune-related gene transcription (potentially associated with better ICI response) [42,48] and lower TMB (potentially associated with poorer ICI response) in MSI-H GAC [37,38,49]. Given these opposite predictive values, we sought to investigate the ICI efficacy of this subtype.
In total, 36 patients with locally advanced or metastatic concordant-dMMR/MSI-H G/GEJ adenocarcinoma were included. The key baseline characteristics, individual response to ICI treatment, and mutational events of the members of the PI3K-AKT-mTOR pathway are illustrated in Fig. 5A and Additional file 1: Table S15. The best responses are shown in Fig. 5D. To explore the optimal cutoff of the NMP for predicting immunotherapy efficacy in dMMR/MSI-H G/GEJ adenocarcinoma, a ROC curve was plotted based on the objective response in patients with evaluable target lesion (n = 31). The AUC of NMP was significantly higher than 0.5 (AUC = 0.792, 95% CI 0.628-0.956, P = 0.006, Fig. 5D), suggesting the feasibility of using NMP to predict response to ICIs. The optimal cutoff was set as 1 when the largest Youden index was achieved. In the NMP-high patients (NMP ≥ 2), objective response rate (ORR) was 29.4%, and 4-month PFS rate was 35.3%, while in the NMP-low patients (NMP = 0/1), ORR and 4-month PFS rate were significantly higher as 85.7% (P = 0.002) and 93.3% (P = 0.001), respectively (Table 1).  Consistent with our previous findings, the NMP-high group exhibited higher TMB than the NMP-low group (Fig. 5B), and NMP was not associated with PD-L1 CPS (Fig. 5C). In addition, the ROC curves based on the objective response demonstrate that TMB (AUC = 0.582, 95% CI 0.377-0.787, P = 0.44) and PD-L1 CPS (AUC = 0.529, 95% CI 0.291-0.767, P = 0.82) were not associated with the response to ICI treatment in the dMMR/MSI-H G/ GEJ adenocarcinomas (Additional file 1: Fig. S6).
The clinical characteristics were comparable between the NMP-high and NMP-low groups (Additional file 1: Table S15). The median time to progression or death was 3.4 months in the NMP-high patients versus not reached in the NMP-low patients (HR = 3.40, 95% CI 1.16-10.00, Log-rank P = 0.019, Fig. 5E). Similarly, shorter median OS was observed in the NMP-high patients as 15.0 months, compared with not reached in the NMP-low patients (HR = 3.59, 95% CI 0.94-13.78, Log-rank P = 0.048, Fig. 5F). The maturity of OS was 30.6%, contributing to the slight difference between the results of Cox regression and Log-rank statistics (P = 0.063 and 0.048, respectively), and therefore, we set PFS as the major outcome in the following analyses.
In addition, to exclude the possibility that the association between NMP and ICI efficacy was impacted by the pre-treatment immune cell concentration in peripheral blood (reflecting systemic immunity), we detected the correlation between NMP and the pre-treatment Table 1 Response to immunotherapy in the ICI treatment cohort Abbreviations: CR complete response, ORR objective response rate, PD progressive disease, PFS progressive-free disease, PR partial response a No assessment represents the patients who had a baseline assessment but no post-baseline assessment at the time of the data cutoff date, due to death before the first post-baseline radiologic imaging assessment b Modified population represents the patients with evaluable target lesion c Four patients who have been followed up for less than 4 months and have not yet progressed were excluded from the analysis of 4-month PFS rate  Fig. S8). Moreover, PI3K-AKT-mTOR mut was not associated with the disease-free survival (P = 0.37) and OS (P = 0.37) in the MSI-H GAC cases of the TCGA database (Additional file 1: Fig. S9). Collectively, NMP-high was identified as a predictive rather than prognostic biomarker, associated with inferior clinical benefit from ICI treatment in patients with dMMR/MSI-H G/GEJ adenocarcinoma.

Discussion
This study represents one of the first reports to dissect further dMMR/MSI-H GAC from the aspects including genome, transcriptome, DTIC, and response to ICI treatment. NMP-low was correlated with lower TMB, higher DTICs, greater transcription of immune-related genes, and superior outcome from ICI treatment. The status of dMMR/MSI-H could be determined by IHC, PCR, and NGS, wherein IHC is the first test choice. In case of doubt of IHC, a confirmatory molecular analysis must be performed. For molecular analysis of dMMR/ MSI-H, the NCCN Guidelines for gastric cancer indicate that MSI can be assessed by PCR to measure gene expression levels of microsatellite markers (i.e., BAT25, BAT26, MONO27, NR21, NR24) [50]. The panel with these five poly-A repeats has been widely used in important clinical trials, including Keynote-016 and Keynote-059 [42,51]. Based on these findings, we adopted the panel with five poly-A mononucleotide repeats for determining MSI status. For the surgery cohort which was used to explore associations between specific pathways and DTICs, only samples with IHC-dMMR, PCR-MSI-H and NGS-MSI-H were included. The strict criteria made the following analysis reliable and convincing. In addition, among the three methods, NGS demonstrates the perfect accuracy and the potential superiority in identifying MSI-H cases, especially when IHC and PCR results are inconsistent.
DTIC is a crucial predictive biomarker of ICI efficacy [52]. Higher TMB was generally correlated with greater DTICs, due to the immune activation via MHC-mediated neoantigen presentation [53]. However, within the hypermutated MSI-H subtype with numerous neoantigens, the impact of more mutations on greater immune activation might have reached a plateau. A similar phenomenon has been reported in MSI-H CRC [14,36]. Consistently, we found no correlation between TMB and DTICs in dMMR/MSI-H GAC. As for the association between TMB and ICI benefit in MSI-H gastrointestinal cancers, Chida et al. set the cutoff as 10 mutations/Mb to identify TMB-low cases who exhibited a poor response to ICI treatment in their MSI-H gastrointestinal cohort [45]. TCGA network analyzed the pan-gastrointestinal adenocarcinomas, including MSS and MSI-H tumors, and defined the MSI subtype by TMB > 10 mutations/ Mb, indel burden > 1, and indel/SNV ratio > 1/150 [54]. Based on this, the extremely low TMB (< 10 mutations/ Mb) in some MSI-H cases in the study by Chida et al. is more likely to indicate the false positivity of their assessments of MSI-H by PCR and/or dMMR by IHC. In addition, Kwon et al. found that TMB < 26mutations/ Mb was associated with poorer PFS on pembrolizumab in a small cohort of MSI-H GAC (n = 15) [46]. However, in our cohort involving 36 G/GEJ adenocarcinomas patients with concordant MSI-H status by NGS and IHC assessments, the TMB-based AUC for ICI response was merely 0.582 (P = 0.44), and no cutoff value can dissect the patients into subgroups with distinct survival outcomes. These findings suggest that TMB might not be a valid predictive factor for the benefit of ICI treatment in MSI-H GAC. Instead, some specific mutated genes and their functional impacts on the DTICs and expression of immune-related genes might be more important in determining the immunotherapy efficacy.
In the tumors with fewer mutations (e.g., MSS and POLD1/POLE-wildtype GAC), one singular genetic aberration may induce crucial influence. However, in the hypermutated tumors (e.g., MSI-H or POLD1/POLEmutant tumors), the effect of a single mutation might be diluted. Therefore, in this study, we investigated the association between tumor immune microenvironments and specific pathways instead of specific gene alterations.
The PI3K-AKT-mTOR pathway controls most hallmarks of cancer, including cell cycle, motility, survival, metabolism, and genomic instability. Mutations of the members in the PI3K-AKT-mTOR pathway generally activate this signaling [55]. The activation-induced extensive carcinogenicity of this pathway has prompted the development of therapeutic reagents to inhibit this pathway. Of note, this signaling has also been welldocumented to be involved in the tumor immune microenvironments, regulating the secretion of immunosuppressive cytokines, the expression of PD-L1, the infiltration of myeloid-derived suppressor cells, regulatory T cells and CD8 + T cell into tumor tissues, and the development of memory T cells [56]. In this study, it was also found that multiple immune-related signatures were significantly enriched and the activity of TGFβ signaling was decreased in the PI3K-AKT-mTOR WT group compared to those in the PI3K-AKT-mTOR mut group. Some research showed that pharmacological inhibition of this pathway not only restored immune-related signal transduction and improved antigen presentation but also increased DTICs, facilitating immune recognition on tumor cells [57][58][59]. The degree of pathway's activation was further assessed by the number of mutated genes.
The results from the surgery cohort showed that higher NMP was associated with poorer immune cell infiltration. Analysis of drug sensitivity in MSI-H GAC cell lines revealed higher sensitivities to PI3K-AKT-mTOR inhibitors in the cell lines with higher NMP. These findings were further validated in MSI-H GAC patients treated with ICIs, wherein NMP-low patients (NMP = 0/1) were DTIC-enriched and had better response and longer survival durations on ICI treatment compared to those with high NMP (NMP ≥ 2). Taken together, higher NMP might be one of the mechanisms underlying immune evasion and primary resistance to immunotherapy in dMMR/MSI-H gastric adenocarcinomas. In addition, the impacts of the PI3K-AKT-mTOR pathway on PD-1 signaling might be independent of regulating PD-L1 expression, based on our negative findings and a previous report in melanoma [60].
Preclinical data suggest the upregulation of DTIC via administrating pan-PI3K inhibitor (BKM120), and its synergistic effect with anti-PD-1 in the mouse model bearing breast cancer or muscle-invasive bladder cancer patient-derived xenograft [58,59]. Currently, multiple trials are ongoing to evaluate the anti-tumor activity of this combination. For example, the NCT03673787 trial (ipatasertib plus atezolizumab) enrolls patients with pathogenic mutations in PIK3CA, AKT1, and AKT2 identified by NGS, or PTEN loss by IHC. Several treatment schedules for the combination of ipatasertib and atezolizumab have been proposed in patients with advanced solid tumors [61][62][63]. These treatment schedules mainly fall into two categories: (i) ipatasertib and atezolizumab are co-administrated directly, and (ii) ipatasertib is given priority for a period of time, followed by combining with atezolizumab. Given our findings and previous studies showing that NMP was negatively correlated with DTICs, and the treatment with 2 weeks of single-agent ipatasertib induced the decrease of CD4 + FOXP3 + regulatory T cells in the tumor microenvironment [61], there may be more advantages to the second category of treatment schedules. Furthermore, a manageable safety profile is observed with ipatasertib plus atezolizumab across multiple tumor types [61][62][63]. Taken together, despite the inferior benefit from ICIs in the NMP-high cases, combination therapy with PI3K-AKT-mTOR inhibitors might be a promising choice to increase DTICs and enhance immunotherapy efficacy in this population.
Although DTICs were associated with ICI efficacy [52], it has not been widely used in clinical practice due to the lack of standard evaluation method and sufficient tumor samples after the multiple recommended tissue-based assessments, including protein expression of HER2, MMR, and PD-L1 by IHC, and Epstein-Barr virus-encoded small RNA by in situ hybridization in gastric cancer. Under these circumstances, NGS testing of circulating tumor DNA (ctDNA), as a technique providing mutational data with high credibility and validity, may be an alternative method to evaluate the DTICs in tumor tissues by leveraging the correlations between DTICs and genetic aberrations. Meanwhile, given the high level of intratumoral heterogeneity in GACs, ctDNA-based NGS testing could provide more reliable MSI status, TMB, and genetic indicators for precision therapy (e.g., the fusion of NTRK) than tissue-based testing.
As for limitations, first, the DTIC results are based on several common tumor-infiltrating immune cell subsets used for evaluation of tumor microenvironment, and these results detected by IHC might not be as ample as the one calculated in silico from RNA-seq data. However, IHC provides histological illustration, enabling pathologists to score the DTIC in different regions. In the present study, we separately assess the DTICs in the central tumor area and invasive margin area. The correlations of NMP with invasive-margin DTICs were much weaker than its correlations with central-tumor DTICs, suggesting the potential distinction of the impacts of PI3K-AKT-mTOR on DTICs in the tumor center and margin. Additionally, given the complexity and trickiness of the tumor microenvironments, the correlations of NMP with the tumor-infiltrating lymphocytes need to be further explored in more tumor-infiltrating immune cell subsets. Second, the retrospective setting of our study may introduce biases, but this limitation has been minimized by the balanced characteristics in the NMP-high and NMP-low subgroups, and the implementation of subgroup analysis and multivariable analysis to exclude the confounding impacts from these variables. NMP held great promise by its broad applicability for the high predictive value of ICI efficacy regardless of treatment lines, ECOG, pathology, NGS testing technique, TMB, and PD-L1 CPS, making it meaningful for patient selection.

Conclusions
Our findings demonstrate the heterogeneity of genotypes, DTICs, immune-related signatures, and immunotherapy efficacy in the dMMR/MSI-H GACs. Higher NMP, identified as a genomic correlate of lower DTICs in this population, might serve as a potential predictor of intrinsic resistance to anti-PD-(L)1 treatment. Additional studies are warranted to determine the synergistic effect of PI3K-AKT-mTOR inhibitors to overcome the resistance to ICI treatment in the NMP-high dMMR/MSI-H G/GEJ adenocarcinomas.
Additional file 1. Fig. S1. Work flow and patient selection. Fig. S2. Association between the results of IHC, PCR, and NGS testing for identifying dMMR/MSI-H gastric adenocarcinoma. Fig. S3. Mutations of PI3K-AKT-mTOR pathway of the concordant MSI-H cases in the surgery cohort. Fig.  S4. Representative images of hematoxylin-eosin and PD-L1 staining of MSI-H STAD samples in the 3DMed cohort. Fig. S5. GSEA of gene signatures related to immune activation, interleukin pathways, and NOTCH signaling in comparisons between samples with or without mutation in PI3K-AKT-mTOR pathway. Fig. S6. ROC curves illustrating the association of response rate with TMB and PD-L1 CPS. Fig. S7. Predictive effect of PTEN mutation and NMP in PTEN WT dMMR/MSI-H gastric adenocarcinomas. Fig. S8. Association between mutations in PI3K-AKT-mTOR pathway and concentration of peripheral blood immune cells in patients with dMMR/MSI-H G/GEJ adenocarcinoma in the ICI treatment cohort. Fig. S9. Prognostic effect of the genetic aberration in PI3K-AKT-mTOR pathway in the TCGA cohort. Table S1. List of the genes in the 3DMed 733-gene panel. Table S2. Members of the analyzed signaling pathways in the surgery cohort. Table S3. Antibodies used in flow cytometry. Table S4. List of gene signatures in GSEA. Table S5. Clinicopathological and genomic characteristics in the surgery cohort. Table S6. Association between the results of IHC, PCR, and NGS testing for identifying dMMR/MSI-H gastric adenocarcinoma. Table S7. Genomic characteristics of the discordant samples. Table S8. Clinicopathological characteristics of concordant dMMR/MSI-H samples according to the evaluation of immune infiltration in the surgery cohort. Table S9. Clinicopathological characteristics of dMMR/MSI-H samples with evaluation of immune infiltration according to the history of neoadjuvant chemotherapy in the surgery cohort. Table S10. Sensitivity analysis of the correlation between mutations in PI3K-AKT-mTOR pathway and immune cell infiltration. Table S11. Detailed information of the MSI-H gastric adenocarcinoma samples evaluated by both 381-gene panel and PD-L1 kit retrieved from the 3DMed database. Table S12. Clinicopathological characteristics of MSI-H STAD according to the genetic aberration in PI3K-AKT-mTOR pathway in the TCGA cohort. Table S13. The mutations of the members in the PI3K-AKT-mTOR pathway and mutation sites in the five MSI-H GAC cell lines. Table S14. The IC50 values of every cell line for the PI3K-AKT-mTOR inhibitors, the inhibitors targeting VEGFR or EGFR, and chemotherapeutic drugs. Table S15. Baseline characteristics of the patients with dMMR/MSI-H G/GEJ adenocarcinoma in the ICI treatment cohort. Table S16. Univariable and multivariable analysis of PFS and OS in the ICI treatment cohort.