Conserved immuno-collagenic subtypes predict response to immune checkpoint blockade.

BACKGROUND: Immune checkpoint blockade (ICB) has revolutionized the treatment of various cancer types. Despite significant preclinical advancements in understanding mechanisms, identifying the molecular basis and predictive biomarkers for clinical ICB responses remains challenging. Recent evidence, both preclinical and clinical, underscores the pivotal role of the extracellular matrix (ECM) in modulating immune cell infiltration and behaviors. This study aimed to create an innovative classifier that leverages ECM characteristics to enhance the effectiveness of ICB therapy. METHODS: We analyzed transcriptomic collagen activity and immune signatures in 649 patients with cancer undergoing ICB therapy. This analysis led to the identification of three distinct immuno-collagenic subtypes predictive of ICB responses. We validated these subtypes using the transcriptome data from 9,363 cancer patients from The Cancer Genome Atlas (TCGA) dataset and 1,084 in-house samples. Additionally, novel therapeutic targets were identified based on these established immuno-collagenic subtypes. RESULTS: Our categorization divided tumors into three subtypes: "soft & hot" (low collagen activity and high immune infiltration), "armored & cold" (high collagen activity and low immune infiltration), and "quiescent" (low collagen activity and immune infiltration). Notably, "soft & hot" tumors exhibited the most robust response to ICB therapy across various cancer types. Mechanistically, inhibiting collagen augmented the response to ICB in preclinical models. Furthermore, these subtypes demonstrated associations with immune activity and prognostic predictive potential across multiple cancer types. Additionally, an unbiased approach identified B7 homolog 3 (B7-H3), an available drug target, as strongly expressed in "armored & cold" tumors, relating with poor prognosis. CONCLUSION: This study introduces histopathology-based universal immuno-collagenic subtypes capable of predicting ICB responses across diverse cancer types. These findings offer insights that could contribute to tailoring personalized immunotherapeutic strategies for patients with cancer.

Prognostic nomogram in patients with gastrointestinal stromal tumors: a SEER-based study.

Background: Gastrointestinal stromal tumor (GIST) is a common mesenchymal tumor of the gastrointestinal system. They originate from the interstitial cells of Cajal located within the muscle layer and are characterized by over-expression of the tyrosine kinase receptor KIT. Methods: Data from the Surveillance Epidemiology, and End Results (SEER) database of 1,213 patients diagnosed with GIST between 2010 and 2019 were dichotomized into a modeling set and a validation set at a 2:1 ratio. For the modeling set, both univariate and multivariate Cox regression analyses were used to identify independent prognostic factors. A nomogram was then constructed based on these determinants. Model efficacy was tested using receiver operating characteristic (ROC) curves, calibration curves, clinical decision curves, and risk stratification analysis in both subsets. Results: Identified prognostic determinants included age, sex, pathological differentiation level, tumor-node-metastasis (TNM) stage, surgical intervention, radiotherapy, and marital status. The constructed nomogram showed area under the ROC curve (AUC) values of 0.822, 0.793, and 0.779 for 1-, 3-, and 5-year overall survival (OS) in the modeling set, respectively, while in the validation set, the values were 0.796, 0.823, and 0.806, respectively. Calibration plots from both sets confirmed the concordance between predicted and observed survival. Decision curve analysis (DCA) indicated significant clinical utility for the nomogram. Risk stratification of the patient data revealed distinct survival differences between high-risk and low-risk cohorts in both sets (P<0.001). Conclusions: A novel and potent nomogram for the prognosis of GIST has been introduced. This model's precision offers crucial insights for clinical decisions, yet further external validation remains essential.

High B7-H3 expression with low PD-L1 expression identifies armored-cold tumors in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is generally regarded as the most aggressive subtype among breast cancers, but exhibits higher chemotherapeutic and immunotherapeutic responses due to its unique immunogenicity. Thus, appropriate discrimination of subtypes is critical for guiding therapeutic options in clinical practice. In this research, using multiple in-house and public cohorts, we investigated the expression features and immuno-correlations of B7-H3 in breast cancer and checked the anti-tumor effect of the B7-H3 monoclonal antibody in a mouse model. We also developed a novel classifier combining B7-H3 and PD-L1 expression in TNBC. B7-H3 was revealed to be related to immuno-cold features and accumulated collagen in TNBC. In addition, targeting B7-H3 using the monoclonal antibody significantly suppressed mouse TNBC growth, reversed the armored-cold phenotype, and also boosted anti-PD-1 immunotherapy. In addition, patients with B7-H3 high and PD-L1 low expression showed the lowest anti-tumor immune infiltration, the highest collagen level, and the lowest therapeutic responses to multiple therapies, which mostly belong to armored-cold tumors. Overall, this research provides a novel subtyping strategy based on the combination of B7-H3/PD-L1 expression, which leads to a novel approach for the management of TNBC.

EgCF mediates macrophage polarisation by influencing the glycolytic pathway.

Human cystic echinococcosis (CE) is a zoonotic disorder triggered by the larval stage of Echinococcus granulosus (E. granulosus) and predominantly occurred in the liver and lungs. The M2 macrophage level is considerably elevated among the liver of patients with hepatic CE and performs an integral function in liver fibrosis. However, the mechanism of CE inducing polarisation of macrophage to an M2 phenotype is unknown. In this study, macrophage was treated with E. granulosus cyst fluid (EgCF) to explore the mechanism of macrophage polarisation. Consequently, the expression of the M2 macrophage and production of anti-inflammatory cytokines increased after 48 h treatment by EgCF. In addition, EgCF promoted polarisation of macrophage to an M2 phenotype by inhibiting the expression of transcriptional factor hypoxia-inducible factor 1-alpha (HIF-1α), which increased the expression of glycolysis-associated genes, including hexokinase 2 (HK2) and pyruvate kinase 2 (PKM2). The HIF-1α agonist ML228 also inhibited the induction of macrophage to an M2 phenotype by EgCF in vitro. Our findings indicate that E. granulosus inhibits glycolysis by suppressing the expression of HIF-1α.

Erratum: SECTM1 is upregulated in immuno-hot tumors and predicts immunotherapeutic efficacy in multiple cancers.

[This corrects the article DOI: 10.1016/j.isci.2023.106027.].

Multicenter phase I dose escalation and expansion study of pyrotinib in combination with camrelizumab and chemotherapy as first-line treatment for HER2-positive advanced gastric and gastroesophageal junction adenocarcinoma.

Background: Pembrolizumab plus trastuzumab and chemotherapy showed remarkable efficacy as first-line therapy for advanced HER2-positive gastric cancer. Pyrotinib is an irreversible pan-HER inhibitor. This single-arm, open-label phase 1 dose-escalation (1a) and expansion (1b) study investigated camrelizumab, an anti-PD-1 antibody, plus pyrotinib and chemotherapy as first-line treatment for advanced HER2-positive gastric and gastroesophageal junction (G/GEJ) adenocarcinoma. Methods: Between June 2020 and June 2022, 41 patients with previously untreated HER2-positive locally advanced unresectable or metastatic G/GEJ adenocarcinoma were enrolled. In phase 1a, patients underwent a 3 + 3 escalating dose design, receiving oral pyrotinib (240 mg, 320 mg, or 400 mg daily), intravenous camrelizumab (200 mg), and CapeOX (oxaliplatin 130 mg/m2 on day 1 and capecitabine 1000 mg/m2 twice daily for two weeks) every 3 weeks until progression, intolerable toxicity or consent withdrawal. The recommended phase 2 dose (RP2D) of pyrotinib was determined and used in the phase 1b. The primary endpoints were the safety, maximum tolerated dose (MTD), RP2D, and confirmed objective response rate (ORR). This trial was registered with chictr.org, number ChiCTR2000029717. Findings: Among 41 patients, 10 were in phase 1a (3 at 240 mg, 3 at 400 mg, and 4 at 320 mg due to one patient withdrawing consent), and 31 were in phase 1b. In phase 1a, the MTD of pyrotinib was 320 mg daily due to dose-limiting toxicities (diarrhea [n = 3] and vomiting [n = 1]) observed at 400 mg. Based on all available data, the RP2D of pyrotinib was set at 320 mg. Among 41 patients, 20 patients (48.8%) developed grade ≥3 treatment-emergent adverse events (TEAEs), and four patients (9.8%) had any grade serious adverse events. No deaths occurred due to TEAEs. Among 27 patients who received the RP2D of pyrotinib and had a post-baseline tumor assessment, two patients (7.4%) achieved a confirmed complete response, and 19 patients (70.4%) achieved a confirmed partial response, resulting in a confirmed ORR of 77.8% (95% CI: 57.7-91.4). Interpretation: Pyrotinib plus camrelizumab and chemotherapy showed promising efficacy in the first-line treatment of advanced HER2-positive G/GEJ cancer. The safety profile was consistent with known toxicities of the agents, and no new or unexpected safety signals were identified. Funding: This study was funded by the Beijing Xisike Clinical Oncology Research Foundation (Y-HR2019-0377).

Formin protein FMNL1 is a biomarker for tumor-infiltrating immune cells and associated with well immunotherapeutic response.

Background: Increased studies on the basis of bulk RNA-sequencing (RNA-seq) data of cancer identify numbers of immune-related genes which may play potential regulatory roles in the tumor microenvironment (TME) without in-depth validation. Methods: In the current study, the immunological correlation and cell subpopulation expression pattern of FMNL1 were analyzed using public data. In addition, the cell subpopulation expression pattern of FMNL1 was also deeply validated using single-cell RNA-sequencing (scRNA-seq) and multiplexed quantitative immunofluorescence (mQIF). Results: Bulk FMNL1 mRNA was related to better prognosis in hepatocellular carcinoma (HCC) and was able to identify immuno-hot tumor in not only HCC but also multiple cancer types. Bulk FMNL1 mRNA also predicted the response to immunotherapy in multiple cancers. Further validation using scRNA-seq and mQIF revealed that FMNL1 was a biomarker for immune cells. Conclusions: FMNL1 is a biomarker for immune cells in not only hepatocellular carcinoma, but also multiple cancer types. Moreover, immune infiltration analysis using the bulk RNA-seq data would be further validated using scRNA-seq and/or mQIF to describe the cell subpopulation expression pattern in tumor tissues for more in-depth and appropriate understanding.

HOXC10 promotes esophageal squamous cell carcinoma progression by targeting FOXA3 and indicates poor survival outcome.

Background: Esophageal cancer is one of the most unknown and deadliest cancers in the world. Although recent studies have identified some mutations linked to the development of squamous cell carcinoma of the esophagus (ESCC), the specific role of HomeoboxC10 (HOXC10) in the pathogenesis still requires further investigation. Methods: Agilent mRNA single-channel gene expression was employed to identify genome-wide gene signatures in ESCC. These signatures were also verified using qRT-PCR, immunohistochemical staining as well as Western blot. The biological functions of HOXC10 were further investigated through cellular studies conducted on ESCC cells. Survival analysis was conducted utilizing the Kaplan-Meier method. The GEPIA database and the STRING website were utilized to predict the potential targets that bind to HOXC10. Co-immunoprecipitation assays were performed to investigate the binding interaction between HOXC10 and Forkhead Box A3 (FOXA3). Animal models were established to analyze the effects of HOXC10 silencing on tumorigenesis in vivo. Results: The expression levels of HOXC10 mRNA were found to be upregulated in ESCC. Survival analysis revealed a significant association between abnormally elevated levels of HOXC10 mRNA and an unfavorable prognosis in patients with ESCC. In vitro studies revealed that the knockdown of HOXC10 expression resulted in the inhibition of the proliferation, invasion, and migrating ability of ESCC cells through the upregulation of FOXA3. Furthermore, tumor-bearing mouse models studies demonstrated that HOXC10 through knockdown techniques significantly suppressed ESCC tumor growth. HOXC10 was found to enhance the activation of the MAPK signaling pathway by regulating FOXA3 in ESCC cells. Conclusion: These results support a key role for HOXC10 in the tumorigenesis of ESCC by upregulating FOXA3 via the MAPK pathway and highlight its potential as a promising diagnostic and prognostic marker for ESCC.

PSMC2 is a Novel Prognostic Biomarker and Predicts Immunotherapeutic Responses: From Pancreatic Cancer to Pan-Cancer.

Background: Proteasome 26S subunit ATPase 2 (PSMC2) is a part of the 19S regulatory complex, which catalyzes the unfolding and transport of substrates into the 20S proteasome. Our previous research demonstrated that PSMC2 participates in the tumorigenesis and progression of pancreatic cancer (PC). However, no systematic analysis has been conducted to conclude its expression pattern and correlation with tumor immunity. Aim: To investigate the expression level of PSMC2 in PC, its prognostic value and its relationship with tumor immunity. Methods: In numerous public and internal cohorts, the expression, prognostic significance, and immunological connections of PSMC2 in PC were investigated. Additionally, using data from The Cancer Genome Atlas (TCGA), a pan-cancer analysis was carried out to examine PSMC2's immunological assocaition, and the predictive power of PSMC2 for immunotherapy was also evaluated in numerous public cohorts. Results: PSMC2 was overexpressed in tumor tissues and linked to unfavorable prognosis in PC. PSMC2 was not only positively correlated with TIICs, also positively correlated with immune checkpoints in PC. In addition to PC, PSMC2 was expected to be an indicator of high immunogenicity in most cancer types. Importantly, PSMC2 could predict the immunotherapeutic responses in various cancer types, including urothelial carcinoma and breast cancer. Conclusion: From PC to pan-cancer analysis, we report that PSMC2 is a novel prognostic biomarker in multiple cancer types. PSMC2 is related to the immuno-hot phenotype and predicts the outcome of immunotherapy. Therefore, the current study emphasizes that cancer patients with high PMSC2 expression should actively receive immunotherapy to improve their prognosis.

Total T Cell Density and Expression of T Memory Stem Cell Markers are Associated with Better Prognosis in Colon Cancer.

Background: Immune checkpoint inhibitors have achieved limited clinical effectiveness in colon cancer. Stem memory T cells (TSCMs) and in-situ cytotoxic T cells are dominant contributors to host immunity. Currently, data on the correlation between TSCM and T cell abundance and clinicopathological characteristics in colon cancer are largely unavailable. Methods: In-situ cytotoxic T cells are identified based on the quantification of CD3+ and CD8+ markers using immunohistochemistry (IHC) in the core of the tumor and the invasive margin of the tumor. The expression of representative markers of TSCMs, CD27 and CD95, was assayed using IHC in colon cancer tissues. Correlations between the levels of each marker and the clinicopathological characteristics as well as prognosis were evaluated. Results: High densities of CD3+ and CD8+ T cells correlated with stage I-II tumors, whereas a lower infiltration of cytotoxic T cells correlated with advanced-stage tumors. CD27 and CD95 were both expressed in the membrane of T cells present in the tumor stroma and their levels showed a negative correlation with the TNM stage. CD3, CD8, and CD27 were expressed at the same locations simultaneously, indicating their coordinated action against cancer. In addition, cytotoxic T cell densities and CD27 and CD95 expression remained independent prognostic factors for overall survival. Conclusion: In-situ cytotoxic T cells and TSCMs play important roles in colon cancer development. TSCMs marker CD27 and CD95 were both indicators of survival in patients with colon cancer. Thus, it is believed that TSCMs represent a desirable population for future use in combination immunotherapy.

GBP5 Identifies Immuno-Hot Tumors and Predicts the Therapeutic Response to Immunotherapy in NSCLC.

Background: Immunotherapy drugs, immune checkpoint inhibitors (ICIs), have been approved for first- and second-line treatment of non-small cell lung cancer (NSCLC), but only a portion of patients respond to ICIs. It is crucial to screen the beneficiaries of immunotherapy through biomarkers accurately. Methods: Several datasets were used to explore the predictive value for immunotherapy and immune relevance of guanylate binding protein 5 (GBP5) in NSCLC, including the GSE126044 dataset, The Cancer Genome Atlas (TCGA) dataset, Clinical Proteomic Tumor Analysis Consortium (CPTAC) dataset, the Kaplan-Meier plotter dataset, the HLuA150CS02 cohort, and the HLugS120CS01 cohort. Results: GBP5 was upregulated in tumor tissues but associated with a good prognosis in NSCLC. Moreover, our findings demonstrated that GBP5 was strongly correlated with the expression of many immune-related genes, TIIC levels, and PD-L1 expression based on RNA-seq data onto online databases and validation of the NSCLC tissue microarray using IHC staining. Moreover, pan-cancer analysis has shown that GBP5 was a factor in identifying immuno-hot tumors, except for a few tumor types. Conclusion: In summary, our current research suggests that GBP5 expression is a potential biomarker for predicting the outcome of NSCLC patients treated with ICIs. More research with large-scale samples is needed to determine their value as biomarkers of ICIs benefit.

Protocol to identify novel immunotherapy biomarkers based on transcriptomic data in human cancers.

Immune checkpoint inhibitors have transformed the management of advanced cancers, but biomarkers for the prediction of therapeutic responses have not been fully uncovered. Here, we provide a step-by-step approach for the identification of novel biomarkers from public transcriptomic datasets. We comprehensively summarize the available transcriptomic datasets containing immunotherapy information and describe the necessary procedures to evaluate the effectiveness of a novel immunotherapy biomarker, which may accelerate the identification of novel immunotherapy biomarkers. For complete details on the use and execution of this protocol, please refer to Mei et al.1.

SECTM1 is upregulated in immuno-hot tumors and predicts immunotherapeutic efficacy in multiple cancers.

Immune checkpoint inhibitors (ICIs) have transformed the management of advanced cancers. However, many patients could not benefit from ICIs therapy, and thus several biomarkers for therapeutic prediction have been uncovered. In this research, more than ten public and in-house cohorts were used to explore the predictive value and immunological correlations of secreted and transmembrane 1 (SECTM1) in cancers. SECTM1 expression was enhanced in tumors from patients with well immunotherapeutic responses in multiple cancers. In addition, SECTM1 was immuno-correlated in pan-cancer and enhanced in immuno-hot tumors. In vitro assays revealed that SECTM1 was upregulated by the IFN-γ/STAT1 signaling. Moreover, analysis of in-house immunotherapy cohorts suggested both tumor-expressed and circulating SECTM1 are promising biomarkers to predict therapeutic responses. Overall, this study reveals that SECTM1 is a biomarker of benefit to ICIs in cancer patients. Further studies including large-scale patients are needed to establish its utilization as a biomarker of benefit to ICIs.

Formin protein DIAPH1 positively regulates PD-L1 expression and predicts the therapeutic response to anti-PD-1/PD-L1 immunotherapy.

Formins are evolutionarily conserved genes and profoundly affect cancer progression. This study aims to explore the expressions, prognostic values, and immunological correlations of Formins in cancer. Specific Formins were dysregulated and immuno-biologically correlated in breast cancer (BRCA). Formins showed different expression patterns, namely some were enriched in immune cells while some were enriched in tumor cells. Among all Formins, DIAPH1 was enriched in tumor cells and associated with an inflamed tumor microenvironment (TME). DIAPH1 functioned as an oncogene in BRCA and mediated TGF-ß1-induced epithelial-mesenchymal transformation (EMT) and PD-L1 expression. Moreover, DIAPH1 was overexpressed in most cancers and functioned as a novel pan-cancer immuno-marker, which could predict the response to anti-PD-1/PD-L1 immunotherapy. Overall, DIAPH1 functions as an oncogene and is immunologically correlated, which could be utilized as an alternative biomarker for predicting the immunotherapeutic response.

High expression COL10A1 promotes breast cancer progression and predicts poor prognosis.

Background: As a common malignant disease in females, breast cancer (BCa) causes increasing numbers of cancer-related death. Collagen X alpha 1 chain (COL10A1) plays a critical role in the oncogenesis and progression of malignant tumors. However, a systematic analysis of COL10A1 in BCa has not been conducted. Methods: The COL10A1 expression level and prognostic value in BCa were defined through the Cancer Genome Atlas (TCGA) as well as the Kaplan-Meier plotter data respectively. The expression pattern of COL10A1 was subsequently confirmed on tissue microarray (TMA) by immunochemistry (IHC) staining. Moreover, cellular functional assays which aimed to evaluate cell proliferation, migration, invasion, and apoptosis, were conducted to investigate the oncogenic activity of COL10A1 in BCa. Then, Tumor Immune Estimation Resource (TIMER) was adopted to determine the association between COL10A1 expression and immune cell infiltration. Results: Bioinformatics analysis revealed that COL10A1 was significantly overexpressed and had notable prognostic value, especially for distant metastasis-free survival (DMFS) in BCa. Moreover, IHC analysis of 140 BCa tissues on TMA chips exhibited the overexpression of COL10A1 was correlated to advanced clinical stage, poor overall survival (OS), and worse recurrence-free survival (RFS). Besides, knockdown of COL10A1 remarkably suppressed cell proliferation, migration, and invasion in BCa cells, and notably promoted cell apoptosis as well. Furthermore, COL10A1 was positively associated with immune cell infiltration including B cell, CD8+ T cell, CD4+ T cell, macrophage, neutrophil, and dendritic cell. Conclusion: The results revealed that COL10A1 is a novel oncogene and could serve as a potential prognostic biomarker in BCa. Besides, the downregulation of COL10A1 could inhibit BCa progression, which could be a potential target for BCa therapy.

NEUROD1 predicts better prognosis in pancreatic cancer revealed by a TILs-based prognostic signature.

It has been well-defined that tumor-infiltrating lymphocytes (TILs) play critical roles in pancreatic cancer (PaCa) progression. This research aimed to comprehensively explore the composition of TILs in PaCa and their potential clinical significance. A total of 178 samples from the TCGA and 63 samples from the GSE57495 dataset were enrolled in our study. ImmuCellAI was applied to calculate the infiltrating abundance of 24 immune cell types in PaCa and further survival analysis revealed the prognostic values of TILs in PaCa. Moreover, the Hallmark enticement analysis of differentially expressed genes (DEGs) between low- and high-risk groups was performed as well. Immunohistochemistry staining was used to evaluate NEUROD1 expression. As result, different kinds of TILs had distinct infiltrating features. In addition, Specific TILs subsets had notable prognostic values in PaCa. We further established a 6-TILs signature to assess the prognosis of PaCa patients. Kaplan-Meier and Cox regression analyses both suggested the significant prognostic value of the signature in PaCa. Based on the prognostic signature, we screened a great deal of potential prognostic biomarkers and successfully validated NEUROD1 as a novel prognostic biomarker in PaCa. Overall, the current study illuminated the immune cells infiltrating the landscape in PaCa and identified a TILs-dependent signature and NEUROD1 for prognostic prediction in PaCa patients.

ZEB1: Catalyst of immune escape during tumor metastasis.

The transcription factor zinc finger E-box binding homeobox 1 (ZEB1) is a critical inducer of epithelial mesenchymal transformation (EMT) and plays a robust role in tumor metastasis. It can promote not only the movement and diffusion of tumor cells but also cell stemness, treatment resistance, tumor metastasis and immune escape. The expression of ZEB1 is strictly regulated by a variety of pretranscriptional and posttranscriptional signaling pathways and molecules. Increasing evidence indicates that protein modifications such as methylation and acetylation of ZEB1 can also affect tumor metastasis. More importantly, ZEB1 induces immunosuppressive cells and chemokines into the tumor microenvironment (TME), leading to the formation of a tumor immunosuppressive microenvironment. This review summarizes the regulatory factors involved in ZEB1 expression and its important role. The areas of research covered in this review contribute to providing new thoughts and new treatment insights for targeted ZEB1 therapy of malignant tumors.

Microfluidic devices: The application in TME modeling and the potential in immunotherapy optimization.

With continued advances in cancer research, the crucial role of the tumor microenvironment (TME) in regulating tumor progression and influencing immunotherapy outcomes has been realized over the years. A series of studies devoted to enhancing the response to immunotherapies through exploring efficient predictive biomarkers and new combination approaches. The microfluidic technology not only promoted the development of multi-omics analyses but also enabled the recapitulation of TME in vitro microfluidic system, which made these devices attractive across studies for optimization of immunotherapy. Here, we reviewed the application of microfluidic systems in modeling TME and the potential of these devices in predicting and monitoring immunotherapy effects.