Objectives Adjuvant chemotherapy benefits in elderly patients with stage II colon cancer (CC) remain controversial. We aimed to construct a nomogram to estimate the chemotherapy survival benefits in elderly patients. Methods The training and testing cohort were patients with stage II CC older than 70 years from the Surveillance, Epidemiology, and End Results (SEER) database, while the external validation cohort included patients from the National Cancer Center (NCC). Cox proportional hazard models were used to determine the covariates associated with overall survival (OS). Using the risk factors identified by Cox proportional hazards regression, a nomogram was developed to predict OS. Nomogram precision was assessed using receiver operating characteristic and calibration curves. Results The present study recruited 42 097 and 504 patients from the SEER database and NCC, respectively. The OS of patients who underwent surgery plus adjuvant chemotherapy was considerably longer than patients who underwent surgery alone. The nomogram included variables related to OS, including age, year of diagnosis, sex, AJCC T stage, tumor location, tumor size, harvested lymph nodes, and chemotherapy. According to the nomogram score, the elderly patients were separated into high- and low-risk groups, with high-risk group nomogram scores being greater than the median value, and vice versa. Patients in the high-risk group witnessed worse prognosis and were more likely to benefit from postoperative chemotherapy. Conclusion This nomogram can be regarded as a useful clinical tool for assessing the potential adjuvant chemotherapy benefits and for predicting survival in elderly patients with stage II CC.

Background Programmed cell death protein 1 (PD-1) receptor has two ligands,programmed death-ligand 1 (PD-L1) and PD-L2. When compared with PD-L1, PD-L2 has not received much attention, and its role remains unclear. Methods The expression profiles of pdcd1lg2 (PD-L2-encoding gene) mRNA and PD-L2 protein were analyzed using TCGA, ICGC, and HPA databases. Kaplan-Meier and Cox regression analyses were used to assess the prognostic significance of PD-L2. We used GSEA, Spearman’s correlation analysis and PPI network to explore the biological functions of PD-L2. PD-L2-associated immune cell infiltration was evaluated using the ESTIMATE algorithm and TIMER 2.0. The expressions of PD-L2 in tumor-associated macrophages (TAMs) in human colon cancer samples, and in mice in an immunocompetent syngeneic setting were verified using scRNA-seq datasets, multiplex immunofluorescence staining, and flow cytometry. After fluorescence-activated cell sorting, flow cytometry and qRT-PCR and transwell and colony formation assays were used to evaluate the phenotype and functions of PD-L2+TAMs. Immune checkpoint inhibitors (ICIs) therapy prediction analysis was performed using TIDE and TISMO. Last, a series of targeted small-molecule drugs with promising therapeutic effects were predicted using the GSCA platform. Results PD-L2 was expressed in all the common human cancer types and deteriorated outcomes in multiple cancers. PPI network and Spearman’s correlation analysis revealed that PD-L2 was closely associated with many immune molecules. Moreover, both GSEA results of KEGG pathways and GSEA results for Reactome analysis indicated that PD-L2 expression played an important role in cancer immune response. Further analysis showed that PD-L2 expression was strongly associated with the infiltration of immune cells in tumor tissue in almost all cancer types, among which macrophages were the most positively associated with PD-L2 in colon cancer. According to the results mentioned above, we verified the expression of PD-L2 in TAMs in colon cancer and found that PD-L2+TAMs population was not static. Additionally, PD-L2+TAMs exhibited protumor M2 phenotype and increased the migration, invasion, and proliferative capacity of colon cancer cells. Furthermore, PD-L2 had a substantial predictive value for ICIs therapy cohorts. Conclusion PD-L2 in the TME, especially expressed on TAMs, could be applied as a potential therapeutic target.

Histone H3 lysine 4 trimethylation (H3K4me3) is a canonical chromatin modification associated with active gene transcription, playing a pivotal role in regulating various cellular functions. Components of the H3K4me3 methyltransferase complex, known as the proteins associated with SET1 (COMPASS), have been implicated in exerting cancer-protective or cancer-inhibitory effects through inducive H3K4me3 modification. However, the role of the indispensable non-catalytic component of COMPASS CXXC-type zinc finger protein 1 (CFP1) in malignant progression remains unclear. We have unveiled that CFP1 promote lung adenocarcinoma (LUAD) cell proliferation, migration, and invasion while impairing cell apoptosis through in vitro and in vivo models. In addition, high CFP1 expression was identified as emerged as an adverse prognostic indicator across multiple public and in-house LUAD datasets. Notably, CFP1 deficiency led to dual effects on cancer cell transcriptome including extensive inactivation of cancer-promoting as well as activation of cancer repressors. Combining this with the chromatin immunoprecipitation sequencing (ChIP-seq) analysis, we showed that CFP1 ablation reshaped the genomic H3K4me3 distribution signature, with prominent effects on TGF-β and WNT signaling pathways. Collectively, our study proposes that CFP1 mediates tumorigenesis by genomic histone methylation reprogramming, offering insights for future investigations into epigenetic modifications in cancer progression and potential therapeutic advancements.

This study aimed to establish a nomogram for the prediction of cancer-specific survival (CSS) of CRC patients with synchronous LM. The final prognostic nomogram based on prognostic factors was evaluated by concordance index (C-index), time-dependent receiver operating characteristic curves, and calibration curves. In the training and validation groups, the C-index for the nomogram was 0.648 and 0.638, and the AUC was 0.793 and 0.785, respectively. The high quality of the calibration curves in the nomogram models for CSS at 1-, 3-, and 5-year was observed. The nomogram model provided a conventional and useful tool to evaluate the 1-, 3-, and 5-year CSS of CRC patients with synchronous LM.

Background Radiation therapy (RT) is a crucial modality for the local control of pelvic cancer (PC), but the effect of pelvic RT on the development of secondary malignancy is still unclear. This study aimed to identify the relationship between radiation therapy received for the treatment of primary PC and subsequent secondary bladder cancer (SBC). Methods The Surveillance, Epidemiology, and End Results (SEER) database (from 1975 to 2015) was queried for PC. Fine-gray competing risk regression and Cox regression analyses were employed to assess the cumulative incidence of SBC. Poisson regression and multiple primary standardized incidence ratios (SIR) were used to evaluate the radiotherapy-associated risk for patients receiving RT. Subgroup analyses of patients stratified by latency time since PC diagnosis, calendar year of PC diagnosis stage, and age at PC diagnosis were also performed. Overall survival (OS) was compared among different treatment groups with SBC by Kaplan–Meier analysis. Results A total of 318,165 observations showed that the primary cancers were located in pelvic cavity, 256,313 patients did not receive radiation therapy (NRT), 51,347 patients who underwent external beam radiation therapy (EBRT), and 10,505 patients receiving a combination of EBRT and brachytherapy (EBRT–BRT) who developed SBC. Receiving two types of radiotherapy was strongly consistent with a higher risk of developing SBC for PC patients in Fine-Gray competing risk regression (NRT vs. EBRT, adjusted HR= 1.71, 95% CI: 1.54-1.90, P<0.001; NRT vs. EBRT–BRT, adjusted HR= 2.16, 95% CI: 1.78-2.63, P<0.001). The results of the dynamic SIR and Poisson regression analysis for SBC revealed that a slightly increased risk of SBC was observed after RT in the early latency and was significantly related to the variations of age at PC diagnosis and decreased with time progress. For OS, the SBC after NRT, SBC after EBRT, and SBC after EBRT-BRT of 10-year survival rates were 37.9%, 29.2%, and 22.2%, respectively. Conclusion Radiotherapy for primary PC was associated with higher risks of developing SBC than patients unexposed to radiotherapy. Different pelvic RT treatment modalities had different effects on the risk of SBC.

BackgroundRadiation therapy (RT) is a standard treatment for the local control of primary pelvic cancers (PPC), yet the risk of second corpus uteri cancer (SCUC) in PPC patients undergoing RT is still controversial. This study investigated the impact of RT on the risk of SCUC and assessed the survival outcome.MethodsWe queried nine cancer registries for PPC cases in the Surveillance, Epidemiology, and End Results (SEER) database. The cumulative incidence of SCUC was analyzed using Cox regression and Fine–Gray competing risk regression analysis. The Poisson regression analysis was employed to assess the standardized incidence ratios (SIRs) and radiation-attributed risk (RR) for SCUC. We evaluated the overall survival of patients with SCUC using the Kaplan–Meier method.ResultsReceiving radiotherapy was strongly associated with a higher risk of developing SCUC for PPC patients in Fine–Gray competing risk regression (No-RT vs. RT: adjusted HR = 1.77; 95% CI, 1.40–2.28; p < 0.001). The incidence of SCUC in PPC patients who received RT was higher than in the US general population (SIR, 1.66; 95% CI, 1.41–1.93; p < 0.05), but the incidence of SCUC in patients who did not receive RT was lower than with the US general population (SIR, 0.68; 95% CI, 0.61–0.75; p < 0.05). The dynamic SIR and RR for SCUC decreased with decreasing age at PPC diagnosis and decreased with time progress. In terms of overall survival, 10-year survival rates with SCUC after No-RT (NRT) and SCUC after RT were 45.9% and 25.9% (HR = 1.82; 95% CI, 1.46–2.29; p < 0.001), respectively.ConclusionRadiotherapy for primary pelvic cancers is associated with a higher risk of developing SCUC than patients unexposed to radiotherapy. We suggest that patients with pelvic RT, especially young patients, should receive long-term monitoring for the risk of developing SCUC.

Surgery is the primary treatment method for colorectal malignancies, and laparoscopic surgery, the most common method of minimally invasive surgery, has become synonymous with minimally invasive surgery. However, laparoscopic-assisted colorectal cancer surgery frequently requires a 5-10 cm incision in the abdominal wall to remove the specimen, which weakening the minimally invasive effect. In recent years, NOSES (natural orifice specimen extraction surgery), as a new techniques in the field of minimally invasive surgery, has gradually attracted widespread attention of the surgical community and has been widely discussed internationally. NOSES combines the incision-free ideology of natural orifice transluminal endoscopic surgery (NOTES) with the surgical techniques of laparoscopic surgery. It has made significant innovation in the way of tumor specimen extraction, reducing the postoperative pain of patients greatly and improving the postoperative satisfaction of patients without affecting the oncology prognosis, which making it rapidly accepted by surgeons. It has finally achieved the result of 'no auxiliary abdominal incision' and has extended its indications to the entire colorectum. Currently, NOSES for colorectal neoplasms has been divided into ten modalities with a total of 21 approaches, depending on their location, size and patient's gender. There were five modalities for each of the rectal and colonic tumours. This article is the first time that the definition of NOSES, the classification method and the nomenclature of colorectal tumour NOSES are described in detail in the form of an international article, which will hopefully contribute to the promotion of NOSES in the international arena.

Abstract Background Obesity alters metabolic microenvironment and is thus associated with several tumours. The aim of the present study was to investigate the role, molecular mechanism of action, and potential clinical value of lipid metabolism–related long non‐coding RNA (lncRNA) SLC25A21‐AS1 in oesophageal squamous cell carcinoma (ESCC). Methods A high‐fat diets (HFDs)‐induced obesity nude mouse model was established, and targeted metabolomics analysis was used to identify critical medium‐long chain fatty acids influencing the growth of ESCC cells. Transcriptomic analysis of public dataset GSE53625 confirmed that lncRNA SLC25A21‐AS1 was a lipid metabolism–related lncRNA. The biological function of lncRNA SLC25A21‐AS1 in ESCC was investigated both in vivo and in vitro. Chromatin immunoprecipitation(ChIP)assay, RNA‐pull down, mass spectrometry, co‐IP, and RNA IP(RIP) were performed to explore the molecular mechanism. Finally, an ESCC cDNA microarray was used to determine the clinical prognostic value of SLC25A21‐AS1 by RT‐qPCR. Results Palmitic acid (PA) is an important fatty acid component of HFD and had an inhibitory effect on ESCC cell lines. LncRNA SLC25A21‐AS1 expression was downregulated by PA and associated with the proliferation and migration of ESCC cells in vitro and in vivo. Mechanistically, SLC25A21‐AS1 interacted with nucleophosmin‐1 (NPM1) protein to promote the downstream gene transcription of the c‐Myc in the nucleus. In the cytoplasm, SLC25A21‐AS1 maintained the stability of SLC25A21 mRNA and reduced the intracellular NAD+/NADH ratio by influencing tryptophan catabolism. Finally, we demonstrated that high expression of SLC25A21‐AS1 promoted resistance to cisplatin‐induced apoptosis and was correlated with poor tumour grade and overall survival. Conclusions HFD/PA has an inhibitory effect on ESCC cells and SLC25A21‐AS1 expression. SLC25A21‐AS1 promotes the proliferation and migration of ESCC cells by regulating the NPM1/c‐Myc axis and SLC25A21 expression. In addition, lncRNA SLC25A21‐AS1 may serve as a favourable prognostic biomarker and a potential therapeutic target for ESCC.

The role and mechanism of transmembrane proteins (TMEMs) in tumorigenesis remain unclear. Based on 4 independent cohorts containing 1,208 cases, we identified 3 TMEMs (TMEM273, TMEM164, and TMEM125), which were used to construct a risk model to predict the prognosis of LUAD. The two patterns based on the risk score exhibited a high degree of consistency with the characteristics of immune cell infiltration and epigenetic distribution. Patients with a low-risk score, characterized by an increased activation of immunity, H3K4me3 modification, tumor cell apoptosis, chemokine secretion, and TMB, had better disease-free survival (DFS) and overall survival (OS). Obvious immunosuppression, increased epithelial-mesenchymal transition, a low H3K4me3 level, shortened cell cycle, and accelerated cell division manifested in high-risk patients, with poorer DFS and OS. The model showed a better prognostic value than the tumor immune dysfunction and exclusion score. Correlation analysis told us that patients with high scores were suitable for treatment with CD276 inhibitors for their higher levels of CD276 expression. The risk score had a strong negative correlation with HAVCR2 and ICOS among patients with EGFR-WT, KRAS-WT, STK11-WT, or TP53-MUT, and patients with these mutation types with low scores were suitable for treatment with HAVCR2 or ICOS inhibitors. This work comprehensively analyzed the role and mechanism of TMEMs in LUAD and revealed the characteristics of histone methylation modification. The TMEM-based signature gave us deep insight into immune cell infiltration profiles and provided an individualized immunotherapy strategy.

Background: The type 2 mannose receptor C (MRC2) is involved in tumor biological processes and plays a new role in the remodeling of the extracellular matrix turnover. Previous studies have demonstrated MRC2 expression profiling and prognostic relevance in some tumor types. However, the clinical and immunotherapeutic value of MRC2 in pan-cancers remains controversial. Our study aimed to evaluate MRC2 expression pattern, clinical characteristics and prognostic significance in 33 cancers, explore the relationship between MRC2 and immune-related characteristics, and assess the prediction of MRC2 for the immunotherapeutic response. Methods: Transcriptional and clinical data of 33 cancers were downloaded from The Cancer Genome Atlas database (TCGA) database and two independent immunotherapeutic cohorts were obtained from GSE67501 and the IMvigor210 study. Next, patients stratified by MRC2 expression levels were displayed by Kaplan-Meier plot to compare prognosis-related indexes. Meanwhile, immune infiltrates of different cancers were estimated by tumor immune estimation resources (TIMER) and CIBERSORT. The ESTIMATE algorithm was used to estimate the immune and stromal scores in tumor tissues. MRC2 expression and immunological modulators, including immune inhibitors, immune stimulators, and MHC molecules, were screened through the TISIDB portal. Gene-set enrichment analysis analyses were performed to explore the underlying biological process of MRC2 across different cancers. The immunotherapeutic response prediction was performed in two independent cohorts (GSE78220: metastatic melanoma with pembrolizumab treatment and IMvigor210: advanced urothelial cancer with atezolizumab intervention). Results: MRC2 is expressed differently in many cancers and has been shown to have potential prognostic predicting significance. MRC2 was significantly associated with immune cell infiltration, immune modulators, and immunotherapeutic markers. Notably, the immunotherapeutic response group was associated with lower MRC2 expression in metastatic melanoma and advanced urothelial carcinoma cohort. Conclusion: This study demonstrated that MRC2 could be a prognostic indicator for certain cancer and is critical for tumor immune microenvironments. MRC2 expression level may influence and predict immune checkpoint blockade response as a potential indicator.

Abstract Background Colorectal cancer (CRC) is a common malignant cancer with a poor prognosis. Liver metastasis is the dominant cause of death in CRC patients, and it often involves changes in various gene expression profiling. This study proposed to construct and validate a risk model based on differentially expressed genes between primary and liver metastatic tumors from CRC for prognostic prediction. Methods Transcriptomic and clinical data of CRC were downloaded from The Cancer Genome Atlas database (TCGA) and Gene Expression Omnibus database (GEO). Identification and screening of candidate differentially expressed genes (DEGs) between liver metastatic tissues and corresponding primary tumors were conducted by R package “limma” and univariate Cox analysis in the GSE50760 and TCGA cohort. Last, absolute shrinkage and selection operator (LASSO) Cox regression was carried out to shrink DEGs and develop the risk model. CRC patients from the GSE161158 cohort were utilized for validation. Functional enrichment, CIBERSORT algorithm, and ESTIMATE algorithm for further analysis. Results An 8-gene signature risk model, including HPD, C8G, CDO1, FGL1, SLC2A2, ALDOB, SPINK4, and ITLN1, was developed and classified the CRC patients from TCGA and GEO cohorts into high and low-risk groups. The high-risk group has a worse prognosis compared with the low-risk group. The model was verified as an independent indicator for prognosis. Moreover, tumor immune infiltration analyses demonstrated that monocytes (P = 0.006), macrophage M0 (P < 0.001), and macrophage M1 (P < 0.001) were enriched in the high-risk group, while plasma cells (P = 0.010), T cells CD4 memory resting (P < 0.001) and dendritic cells activated (P = 0.006) were increased in the low-risk group. Conclusions We developed and validated a risk predictive model for the DEGs between liver metastases and primary tumor of CRC, which can be utilized for the clinical prognostic indicator in CRC.

DNA ploidy, tumor stroma, and chromatin organization have important implications in tumorigenesis and patient outcome. Automated image cytometry tools were developed to quantitatively measure DNA ploidy (P), stroma fraction (S), and chromatin organization or Nucleotyping (N). This study aimed to discover their clinical value in different stages of colorectal cancer (CRC) in a Chinese patient population. A total of 496 CRC patients of stages I, II, and LMCRC (liver metastatic CRC) were enrolled in this study. Stage II CRC patients with diploidy, low-stroma, or chromatin homogenous status predicted significantly higher 5-year OS and DFS. We constructed a PSN-panel enabled the stage II patients to be further stratified into low-, middle-, high-risk groups, the 5-year OS (89.5% vs 67.9% vs 60.9%, P<0.001) and DFS (86.0% vs 62.3% vs 53.6%, P<0.001) were stratified significantly. In addition, when combined the PSN-panel with T stage or MSS status in stage II patients, the PSN-low risk patients showed significant longer 5-year OS and DFS than the PSN-high risk patients in T3 (OS: 86.3% vs 65.3%, P=0.015; DFS: 83.5 vs 59.8%, P=0.013) or MSS (OS: 86.4% vs 63.9%, P=0.005; DFS: 85.5 vs 57.8%, P=0.003) patients. Finally, in the group of stage II patients with at least one high-risk factor (non-diploidy, high-stroma, chromatin heterogenous), patients who received adjuvant therapy showed significantly longer OS (72.1% vs 48.3%, P=0.007) and DFS (64.5% vs 43.9%, P=0.015) than those who did not receive adjuvant therapy. In contrast, P, S, N couldn't predict the prognosis of stage I and LMCRC patients. Overall, our data demonstrate that the PSN panel is an accurate prognostic tool that can guide treatment decisions for Chinese stage II CRC patients.

Background/Aims: Long non-coding ribonucleic acids (lncRNAs) are involved in the progression of cancers and affect the response to radiation therapy. This study was to investigate the mechanism of lncRNA EGOT in the radiosensitivity of rectal cancer. Methods: The mRNA expression of EGOT, miR-211-5p and ErbB4 in rectal cancer tissues and cells was detected by qRT-PCR. The protein expression of ErbB4 was detected by Western blot. Dual-luciferase reporter assay and ribonucleic acid immunoprecipitation (RIP) were used to confirm the interaction between EGOT and miR-211-5p or miR-211-5p and ErbB4. Transfection technology was used to down-regulate and up-regulate the expression of EGOT and miR-211-5p in rectal cancer cells, respectively. MTT, colony formation and flow cytometry were used to detect the effect of EGOT and miR-211-5p on proliferation, invasion, migration and apoptosis of rectal cancer cells. Results: The expression of EGOT was up-regulated in rectal cancer tissues and cells, and the expression of EGOT was related to the late stage of pathology. EGOT knockdown inhibited the proliferation and colony formation of rectal cancer cells and induced the apoptosis of rectal cancer cells. Moreover, EGOT knockdown was significantly enhanced the effects of radiotherapy on rectal cancer in vivo and in vitro. Furthermore, EGOT was found to serve as a sponge of miR-211-5p, and ErbB4 was a downstream target of miR-211-5p. EGOT enhanced the expression of ErbB4 by regulating miR-211-5p. MiR-211-5p inhibitor restored the effect of EGOT knockdown on the radiosensitivity of rectal cancer. Conclusion: Down-regulation of EGOT could inhibit the growth of rectal cancer cells by regulating the miR-211-5p/ErbB4 axis and improve the radiosensitivity of rectal cancer cells. EGOT may be a new therapeutic target for rectal cancer.

Background: Cancer stem cells (CSCs), which are characterized by self-renewal and plasticity, are highly correlated with tumor metastasis and drug resistance. To fully understand the role of CSCs in colorectal cancer (CRC), we evaluated the stemness traits and prognostic value of stemness-related genes in CRC.Methods: In this study, the data from 616 CRC patients from The Cancer Genome Atlas (TCGA) were assessed and subtyped based on the mRNA expression-based stemness index (mRNAsi). The correlations of cancer stemness with the immune microenvironment, tumor mutational burden (TMB), and N6-methyladenosine (m6A) RNA methylation regulators were analyzed. Weighted gene co-expression network analysis (WGCNA) was performed to identify the crucial stemness-related genes and modules. Furthermore, a prognostic expression signature was constructed using the Lasso-penalized Cox regression analysis. The signature was validated via multiplex immunofluorescence staining of tissue samples in an independent cohort of 48 CRC patients.Results: This study suggests that high-mRNAsi scores are associated with poor overall survival in stage IV CRC patients. Moreover, the levels of TMB and m6A RNA methylation regulators were positively correlated with mRNAsi scores, and low-mRNAsi scores were characterized by increased immune activity in CRC. The analysis identified 34 key genes as candidate prognosis biomarkers. Finally, a three-gene prognostic signature (PARPBP, KNSTRN, and KIF2C) was explored together with specific clinical features to construct a nomogram, which was successfully validated in an external cohort.Conclusion: There is a unique correlation between CSCs and the prognosis of CRC patients, and the novel biomarkers related to cell stemness could accurately predict the clinical outcomes of these patients.

Metabolic reprogramming is a hallmark of malignancy. Understanding the characteristics of metabolic reprogramming in esophageal squamous cell carcinoma (ESCC) helps uncover novel targets for cancer progression. In this study, 880 metabolism-related genes were identified from microarray data and then filtered to divide patients into two subgroups using consensus clustering, which exhibits significantly different overall survival. After a differential analysis between two subtypes, 3 genes were screened out to construct a two subtypes decision model on the training cohort (GSE53624), defined as high-risk and low-risk subtypes. These risk models were then verified in two public databases (GSE53622 and TCGA-ESCC), an independent cohort of 49 ESCC patients by RT-qPCR and an external cohort of 95 ESCC patients by immunohistochemistry analysis (IHC). Furthermore, the immune cell infiltration of regulatory T cells (Tregs) and plasma cells showed a significant difference between the high and low-risk subtypes in the IHC experiment with 119 ESCC patients. In conclusion, our study indicated that three metabolism-related prognostic genes could stratify patients into subgroups and were associated with immune infiltration, clinical features and clinical outcomes.

The clinical significance and comprehensive features of chemokines and their receptors in lung adenocarcinoma (LUAD) have not been clarified. We aimed to characterize the expression profiles of chemokine and chemokine receptor family members and construct a chemokine- and chemokine receptor-based prognosis signature. A total of 1511 patients with LUAD from seven independent cohorts were included in the study. The training set collected from The Cancer Genome Atlas (TCGA) database containing 468 cases. The validation was performed on the basis of six different cohorts downloaded from Gene Expression Omnibus (GEO) database. A five-chemokine- and chemokine receptor-(CXCL2, CXCL13, CCL26, CCL20, CX3CR1) based prognosis signature was constructed with TCGA dataset using LASSO Cox regression and Cox proportional hazards regression analysis. A multivariate analysis verified that this signature was an independent prognostic factor. The predictive value of this signature was further verified by other six independent cohorts and multiple clinical subtypes. We performed immune cell infiltration analysis and biological pathway analysis which provided more insight into this signature-related immune and inflammatory landscape and clarified the intrinsic molecular mechanism by which this signature could be used to predict clinical prognosis. Furthermore, we explored the close relationship between this signature and tumor mutation burden (TMB), neoantigen burden, PD-1, PD-L1, CTLA4, TIDE score, T cell-inflamed score. This signature provided a robust prognostic biomarker for LUAD and could serve as a predictor for immunotherapy response, which may be used as an important supplement to immunotherapy to achieve individualized tumor treatment by optimizing the prognostic management and immunotherapy for patients with LUAD.

Background: Colon cancer (CC) remains one of the most common malignancies with a poor prognosis. Pyroptosis, referred to as cellular inflammatory necrosis, is thought to influence tumor development. However, the potential effects of pyroptosis-related regulators (PRRs) on the CC immune microenvironment remain unknown. Methods: In this study, 27 PRRs reported in the previous study were used to cluster the 1,334 CC samples into three pyroptosis-related molecular patterns. Through subtype pattern differential analysis and structure network mining using Weighted Gene Co-expression Network Analysis (WGCNA), 854 signature genes associated with the PRRs were discovered. Further LASSO-penalized Cox regression of these genes established an eight-gene assessment model for predicting prognosis. Results: The CC patients were subtyped based on three distinct pyroptosis-related molecular patterns. These pyroptosis-related patterns were correlated with different clinical outcomes and immune cell infiltration characteristics in the tumor microenvironment. The pyroptosis-related eight-signature model was established and used to assess the prognosis of CC patients with medium-to-high accuracy by employing the risk scores, which was named “PRM-scores.” Greater inflammatory cell infiltration was observed in tumors with low PRM-scores, indicating a potential benefit of immunotherapy in these patients. Conclusions: This study suggests that PRRs have a significant effect on the tumor immune microenvironment and tumor development. Evaluating the pyroptosis-related patterns and related models will promote our understanding of immune cell infiltration characteristics in the tumor microenvironment and provide a theoretical basis for future research targeting pyroptosis in cancer.

Objective: Stage II colorectal cancer (CRC) manifests various treatment responses and outcomes. To assess the recurrence risk, we established a molecular subtype classification for stage II CRC. Methods: We developed a novel molecular subtyping clustering algorithm CRC-MSC for determining molecular subtypes in stage II CRC using only whole exome sequencing (WES). It utilized a specified distance estimate, calculated according to the shared alterations among samples. CRC-MSC was qualified for classification and risk stratification on samples from National Cancer Center (NCC) and The Cancer Genome Atlas (TCGA). To facilitate application to individual management decision, this algorithm was simplified by a decision tree classifier (CRC-MDTC). Phylogenetic analysis was conducted to clarify the mutated genes constituting the decision tree. Results: Using CRC-MSC successfully subtyped 60 stage II CRC samples from NCC into three groups, favorable prognosis (S-I), unfavorable prognosis (S-II) and intermediate (S-III) groups, which was verified in TCGA dataset. These subtypes feature unique molecular, clinicopathological phenotypes and clinical outcomes, especially immune traits.A simplified version of decision tree classifier (CRC-MDTC), TMB, PRKDA and KRAS alterations are three top classification indications, could also reliably categorize samples into three groups. It was validated in an independent cohort with an accuracy of 74.7%. CRC-MSC and CRC-MDTC were available at https://bioinfo.org/crcmsc. Conclusions: In addition to the initial risk evaluation, we developed a framework for the classification of stage II CRC subtypes based on genome profiling, which may shed new light on the management of patients with stage II CRC, especially with regarded to individualized chemotherapy and immunotherapy. Funding: This work was supported by National Program Project for Precision Medicine in National Research and Development Plan of China (2016YFC0905300), and CAMS Innovation Fund for Medical Sciences (CIFMS) (2019-I2M-2-002). Declaration of Interest: None to declare. Ethical Approval: The ethical approval of this study was granted by the Institutional Review Board of Chinese Academy of Medical Sciences (CHCAMS, Beijing, China)/National Cancer Center (NCC, Beijing, China).

Lung adenocarcinoma is one of the most malignant diseases worldwide. The immune checkpoint inhibitors targeting programmed cell death protein 1 (PD-1) and programmed cell death-ligand 1 (PD-L1) have changed the paradigm of lung cancer treatment; however, there are still patients who are resistant. Further exploration of the immune infiltration status of lung adenocarcinoma (LUAD) is necessary for better clinical management. In our study, the CIBERSORT method was used to calculate the infiltration status of 22 immune cells in LUAD patients from The Cancer Genome Atlas (TCGA). We clustered LUAD based on immune infiltration status by consensus clustering. The differentially expressed genes (DEGs) between cold and hot tumor group were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed. Last, we constructed a Cox regression model. We found that the infiltration of M0 macrophage cells and follicular helper T cells predicted an unfavorable overall survival of patients. Consensus clustering of 22 immune cells identified 5 clusters with different patterns of immune cells infiltration, stromal cells infiltration, and tumor purity. Based on the immune scores, we classified these five clusters into hot and cold tumors, which are different in transcription profiles. Hot tumors are enriched in cytokine–cytokine receptor interaction, while cold tumors are enriched in metabolic pathways. Based on the hub genes and prognostic-related genes, we developed a Cox regression model to predict the overall survival of patients with LUAD and validated in other three datasets. In conclusion, we developed an immune-related signature that can predict the prognosis of patients, which might facilitate the clinical application of immunotherapy in LUAD.

Background: Metabolic reprogramming is associated with tumor heterogeneity and progression. Understanding the characteristics of metabolic reprogramming in esophageal squamous cell carcinoma (ESCC) might help us to uncover new biomarkers for patient outcomes and targets for therapies. Methods: In this study, metabolism-related genes were screened from mRNA microarray data (GSE53624, GSE53622). Consensus clustering analysis was used to divide tumors into subgroups. Survival analysis and univariate Cox analysis were performed to select prognostic genes. A metabolism-related gene signature was established with multivariate Cox proportional hazards regression (PHR) analysis in the training group (GSE53624). Gene set enrichment analysis (GSEA) and CIBERSORT were used to analyze functional enrichment and immune cell infiltration.The gene signature and immune infiltration were verified in two public databases (GSE53622, TCGA-ESCC) and in two independent cohorts, 95 and 119 ESCC patients, by immunohistochemistry (IHC) analysis. Results: Based on prognosis-related metabolic gene expression, three cluster subgroups (k = 3) were identified with significantly different immune cell infiltration patterns, clinical features and overall survival (OS) times. Then, we developed a multigene (INPP5E, CD38 and POLR3G) prognostic signature that showed better predictive ability and was found to be an independent prognostic risk factor in ESCC database and two public database analyses. This result could also be verified by multicenter IHC experiment and indicated the clinical application potential. In addition, GSEA showed that several tumor-related pathways were associated with the prognostic signature. Furthermore, the immune cell infiltration of regulatory T cells (Tregs) and plasma cells displayed an obvious correlation with prognostic signature and IHC experiment in 119 cohort also support this result. Conclusions: Our study indicated that the metabolism-related prognostic gene could stratify patients into subgroups and was associated with immune infiltration, clinical features and outcomes. The three-gene prognostic signature from metabolic-related gene displays a good ability to predict OS and the infiltration of immunosuppressive Tregs and plasma cells.