Immune response drives outcomes in prostate cancer: implications for immunotherapy

Exploring the interaction between immune cells in the prostate cancer microenvironment combining weighted correlation gene network analysis and single-cell sequencing: An integrated bioinformatics analysis

BACKGROUND

The rise of treatment resistance and variability across malignant profiles has made precision oncology an imperative in today's medical landscape. Prostate cancer is a prevalent form of cancer in males, characterized by significant diversity in both genomic and clinical characteristics. The tumor microenvironment consists of stroma, tumor cells, and various immune cells. The stromal components and tumor cells engage in mutual communication and facilitate the development of a low-oxygen and pro-cancer milieu by producing cytokines and activating pro-inflammatory signaling pathways.

METHODS

In order to discover new genes associated with tumor cells that interact and facilitate a hypoxic environment in prostate cancer, we conducted a cutting-edge bioinformatics investigation. This included analyzing high-throughput genomic datasets obtained from the cancer genome atlas (TCGA).

RESULTS

A combination of weighted gene co-expression network analysis and single-cell sequencing has identified nine dysregulated immune hub genes (AMACR, KCNN3, MME, EGFR, FLT1, GDF15, KDR, IGF1, and KRT7) that are believed to have significant involvement in the biological pathways involved with the advancement of prostate cancer enviriment. In the prostate cancer environment, we observed the overexpression of GDF15 and KRT7 genes, as well as the downregulation of other genes. Additionally, the cBioPortal platform was used to investigate the frequency of alterations in the genes and their effects on the survival of the patients. The Kaplan-Meier survival analysis indicated that the changes in the candidate genes were associated with a reduction in the overall survival of the patients.

CONCLUSIONS

In summary, the findings indicate that studying the genes and their genomic changes may be used to develop precise treatments for prostate cancer. This approach involves early detection and targeted therapy.

Integrative proteogenomic profiling of high-risk prostate cancer samples from Chinese patients indicates metabolic vulnerabilities and diagnostic biomarkers

Prostate cancer (PCa) exhibits significant geoethnic disparities as reflected by distinct variations in the cancer genome and disease progression. Here, we perform a comprehensive proteogenomic characterization of localized high-risk PCa utilizing paired tumors and nearby tissues from 125 Chinese male patients, with the primary objectives of identifying potential biomarkers, unraveling critical oncogenic events and delineating molecular subtypes with poor prognosis. Our integrated analysis highlights the utility of GOLM1 as a noninvasive serum biomarker. Phosphoproteomics analysis reveals the crucial role of Ser331 phosphorylation on FOXA1 in regulating FOXA1-AR-dependent cistrome. Notably, our proteomic profiling identifies three distinct subtypes, with metabolic immune-desert tumors (S-III) emerging as a particularly aggressive subtype linked to poor prognosis and BCAT2 catabolism-driven PCa progression. In summary, our study provides a comprehensive resource detailing the unique proteomic and phosphoproteomic characteristics of PCa molecular pathogenesis and offering valuable insights for the development of diagnostic and therapeutic strategies.

Telomerase related molecular subtype and risk model reveal immune activity and evaluate prognosis and immunotherapy response in prostate cancer

BACKGROUND

Prostate cancer ranks among the six most lethal malignancies worldwide. Telomerase, a reverse transcriptase enzyme, plays a pivotal role in extending cellular telomeres and is intimately associated with cell proliferation and division. However, the interconnection between prostate cancer and telomerase-related genes (TEASEs) remains unclear.

METHODS

Somatic mutations and copy number alterations of TEASEs were comprehensively analyzed. Subsequently, the transcripts of prostate cancer patients in TCGA and GEO databases were integrated to delineate new molecular subtypes. Followed by constructing a risk model containing nine characteristic genes through Lasso regression and Cox prognostic analysis among different subtypes. Various aspects including prognosis, tumor microenvironment (TME), landscape of immunity, tumor mutational burden (TMB), stem cell correlation, and median inhibitory concentration amongst different risk groups were compared. Finally, the expression, prognosis, and malignant biological behavior of ZW10 interactor (ZWINT) in vitro was explored.

RESULTS

TEASEs exhibited a notably high mutation frequency. Three distinct molecular subtypes and two gene subclusters based on TEASEs were delineated, displaying significant associations with prognosis, immune function regulation, and clinical characteristics. Low-risk patients demonstrated superior prognosis and better response to immunotherapy. Conversely, high-risk patients exhibited higher TMB and stronger stem cell correlations. It was also found that the patients' sensitivity to chemotherapy agents was impacted by the risk score. Finally, ZWINT's potential as a novel diagnostic and prognostic biomarker for prostate cancer was validated.

CONCLUSIONS

TEASEs play a pivotal role in modulating immune regulation and immunotherapeutic responses, thereby significantly impacting the diagnosis, prognosis, and treatment strategies for affected patients.

Machine learning-based integration develops a mitophagy-related lncRNA signature for predicting the progression of prostate cancer: a bioinformatic analysis

Prostate cancer remains a complex and challenging disease, necessitating innovative approaches for prognosis and therapeutic guidance. This study integrates machine learning techniques to develop a novel mitophagy-related long non-coding RNA (lncRNA) signature for predicting the progression of prostate cancer. Leveraging the TCGA-PRAD dataset, we identify a set of four key lncRNAs and formulate a riskscore, revealing its potential as a prognostic indicator. Subsequent analyses unravel the intricate connections between riskscore, immune cell infiltration, mutational landscapes, and treatment outcomes. Notably, the pan-cancer exploration of YEATS2-AS1 highlights its pervasive impact, demonstrating elevated expression across various malignancies. Furthermore, drug sensitivity predictions based on riskscore guide personalized chemotherapy strategies, with drugs like Carmustine and Entinostat showing distinct suitability for high and low-risk group patients. Regression analysis exposes significant correlations between the mitophagy-related lncRNAs, riskscore, and key mitophagy-related genes. Molecular docking analyses reveal promising interactions between Cyclophosphamide and proteins encoded by these genes, suggesting potential therapeutic avenues. This comprehensive study not only introduces a robust prognostic tool but also provides valuable insights into the molecular intricacies and potential therapeutic interventions in prostate cancer, paving the way for more personalized and effective clinical approaches.

Deciphering the role of zinc homeostasis in the tumor microenvironment and prognosis of prostate cancer

BACKGROUND

Dysregulation of zinc homeostasis is widely recognized as a hallmark feature of prostate cancer (PCa) based on the compelling clinical and experimental evidence. Nevertheless, the implications of zinc dyshomeostasis in PCa remains largely unexplored.

METHODS

In this research, the zinc homeostasis pattern subtype (ZHPS) was constructed according to the profile of zinc homeostasis genes. The identified subtypes were assessed for their immune functions, mutational landscapes, biological peculiarities and drug susceptibility. Subsequently, we developed the optimal signature, known as the zinc homeostasis-related risk score (ZHRRS), using the approach won out in multifariously machine learning algorithms. Eventually, clinical specimens, Bayesian network inference and single-cell sequencing were used to excavate the underlying mechanisms of MT1A in PCa.

RESULTS

The zinc dyshomeostasis subgroup, ZHPS2, possessed a markedly worse prognosis than ZHPS1. Moreover, ZHPS2 demonstrated a more conspicuous genomic instability and better therapeutic responses to docetaxel and olaparib than ZHPS1. Compared with traditional clinicopathological characteristics and 35 published signatures, ZHRRS displayed a significantly improved accuracy in prognosis prediction. The diagnostic value of MT1A in PCa was substantiated through analysis of clinical samples. Additionally, we inferred and established the regulatory network of MT1A to elucidate its biological mechanisms.

CONCLUSIONS

The ZHPS classifier and ZHRRS model hold great potential as clinical applications for improving outcomes of PCa patients.

Pro-inflammatory cytokines and CXC chemokines as game-changer in age-associated prostate cancer and ovarian cancer: Insights from preclinical and clinical studies' outcomes

Prostate cancer (PC) and Ovarian cancer (OC) are two of the most common types of cancer that affect the reproductive systems of older men and women. These cancers are associated with a poor quality of life among the aged population. Therefore, finding new and innovative ways to detect, treat, and prevent these cancers in older patients is essential. Finding biomarkers for these malignancies will increase the chance of early detection and effective treatment, subsequently improving the survival rate. Studies have shown that the prevalence and health of some illnesses are linked to an impaired immune system. However, the age-associated changes in the immune system during malignancies such as PC and OC are poorly understood. Recent research has suggested that the excessive production of inflammatory immune mediators, such as interleukin-6 (IL-6), interleukin-8 (IL-8), transforming growth factor (TGF), tumor necrosis factor (TNF), CXC motif chemokine ligand 1 (CXCL1), CXC motif chemokine ligand 12 (CXCL12), and CXC motif chemokine ligand 13 (CXCL13), etc., significantly impact the development of PC and OC in elderly patients. Our review focuses on the latest functional studies of pro-inflammatory cytokines (interleukins) and CXC chemokines, which serve as biomarkers in elderly patients with PC and OC. Thus, we aim to shed light on how these biomarkers affect the development of PC and OC in elderly patients. We also examine the current status and future perspective of cytokines (interleukins) and CXC chemokines-based therapeutic targets in OC and PC treatment for elderly patients.

Integrating single-cell RNA-sequencing and bulk RNA-sequencing data to explore the role of mitophagy-related genes in prostate cancer

Prostate cancer (PCa) is the most common malignancy of the male urinary system. Mitophagy, as a type of autophagy, can remove damaged mitochondria in cells. Mitophagy-related genes (MRGs) have been shown to play critical roles in the development of PCa. To this end, based on the comprehensive analysis of RNA-seq and scRNA-seq data of PCa samples and their controls, this paper identified PCa subtypes and constructed a prognostic model. In this paper, we downloaded scRNA-seq and RNA-seq data from Gene Expression Omnibus (GEO) and TCGA database. Based on the R package "Seurat" to process the scRNA-seq data, a total of five cell types were identified. Each cell population was scored based on the R package "AUCell" and using the intersection genes between MRGs and each cell population. The B cell population was then identified as a high-scoring cell population. Differentially expressed genes in RNA-seq data were identified based on the R package "limma" and intersected with previously intersected genes. Then, based on univariate Cox regression analysis and Lasso-Cox regression analysis, the prognostic genes were screened, and the risk model was constructed (composed of ADH5, CAT, BCAT2, DCXR, OGT, and FUS). The model is validated on internal and external test sets. Independent prognostic analysis identified age, N stage, and risk score as independent prognostic factors. This paper's risk models and prognostic genes can provide a reference for developing novel therapeutic targets for PCa.

Predictive value of systematic immune-inflammation index combined with Ki-67 index on prognosis of prostate cancer patients after laparoscopic radical prostatectomy

BACKGROUND

Prostate cancer (PCa) presents a wide spectrum. Systemic immune-inflammation index (SII) and Ki-67 index are new biomarkers that can predict prognosis in different types of cancer. We explored the predictive value of their combination on the prognosis of PCa patients after laparoscopic radical prostatectomy (LRP).

METHODS

In this retrospective study, 290 patients who underwent LRP at Nanjing Lishui People's Hospital between January 2016 and February 2021 were enrolled. They were divided into the good prognosis group (N = 235) and poor prognosis group (N = 55) based on the follow-up results. Both the baseline data and postoperative pathological results were collected. The Ki-67 index was determined using immunohistochemical kits, and the patients were allocated to the SII/Ki-67 index high/low expression groups according to the cut-off values to further analyze their relationship with clinical/pathological data of PCa patients. Logistics multivariate regression analysis was utilized to analyze the independent factors affecting post-LRP prognosis of CPa patients. ROC curve was plotted to assess the predictive value for post-LRP prognosis, and Kaplan-Meier curve/Log-rank were used for analysis.

RESULTS

Significant differences were found in PSA/Gleason score/T stage/lymph node metastasis/seminal vesicle invasion/neutrophils/lymphocytes/platelets/preoperative SII/Ki-67 index between the good/poor prognosis groups. Preoperative SII/Ki-67 were related to PSA/lymphocytes/platelets in PCa. Seminal vesicle invasion and preoperative SII + Ki-67 index were independent factors affecting post-LRP prognosis. Preoperative SII + Ki-67 index had a better predictive value than preoperative SII or Ki-67 index alone. Patients with high preoperative SII and Ki-67 index levels had an increased risk of poor prognosis after LRP.

CONCLUSION

Preoperative SII + Ki-67 index had a better predictive value for poor prognosis after LRP than SII or Ki-67 index alone.

A Novel Signature Based on Anoikis Associated with BCR-Free Survival for Prostate Cancer

This study aimed to elucidate the role of anoikis in the progression of prostate cancer (PCa) and to develop a prognostic signature based on anoikis-related genes (ARGs). To achieve this, PCa cases were subjected to nonnegative matrix factorization (NMF) analysis, which allowed for the identification of distinct patterns of anoikis modification. Additionally, immune infiltration was evaluated using single-sample gene-set enrichment analysis (ssGSEA). Survival analysis was performed using the Kaplan-Meier method, and a risk score was generated based on the expression levels of ARGs to quantitatively assess the modification of anoikis in PCa. Using the Least Absolute Shrinkage and Selection Operator (LASSO) method, four hub-genes were identified, and patients were classified into different risk groups based on their individual scores. Importantly, the low-risk subtype was characterized by a significantly improved biochemical recurrence-free survival, underscoring the clinical relevance of the ARG-based prognostic signature. To further improve the prognostic accuracy of the signature, patient age, pathological T stage, Gleason score, and prostate-specific antigen level were incorporated into the analysis, yielding a comprehensive prognostic signature. The clinical relevance of this signature was illustrated through a nomogram, providing a visual representation of the prognostic implications of the ARG-based signature. Taken together, these findings highlight the potential of ARGs in predicting the clinical outcomes of PCa patients and provide a novel and clinically relevant prognostic signature based on the modification of anoikis in PCa.

Silencing of genes by promoter hypermethylation shapes tumor microenvironment and resistance to immunotherapy in clear-cell renal cell carcinomas

The efficacy of immune checkpoint inhibitors varies in clear-cell renal cell carcinoma (ccRCC), with notable primary resistance among patients. Here, we integrate epigenetic (DNA methylation) and transcriptome data to identify a ccRCC subtype characterized by cancer-specific promoter hypermethylation and epigenetic silencing of Polycomb targets. We develop and validate an index of methylation-based epigenetic silencing (iMES) that predicts primary resistance to immune checkpoint inhibition (ICI) in the BIONIKK trial. High iMES is associated with VEGF pathway silencing, endothelial cell depletion, immune activation/suppression, EZH2 activation, BAP1/SETD2 deficiency, and resistance to ICI. Combination therapy with hypomethylating agents or tyrosine kinase inhibitors may benefit patients with high iMES. Intriguingly, tumors with low iMES exhibit increased endothelial cells and improved ICI response, suggesting the importance of angiogenesis in ICI treatment. We also develop a transcriptome-based analogous system for extended applicability of iMES. Our study underscores the interplay between epigenetic alterations and tumor microenvironment in determining immunotherapy response.

Molecular classifications of prostate cancer: basis for individualized risk stratification and precision therapy

Tumour classifications play a pivotal role in prostate cancer (PCa) management. It can predict the clinical outcomes of PCa as early as the disease is diagnosed and then guide therapeutic schemes, such as active monitoring, standalone surgical intervention, or surgery supplemented with postoperative adjunctive therapy, thereby circumventing disease exacerbation and excessive treatment. Classifications based on clinicopathological features, such as prostate cancer-specific antigen, Gleason score, and TNM stage, are still the main risk stratification strategies and have played an essential role in standardized clinical decision-making. However, mounting evidence indicates that clinicopathological parameters in isolation fail to adequately capture the heterogeneity exhibited among distinct PCa patients, such as those sharing identical Gleason scores yet experiencing divergent prognoses. As a remedy, molecular classifications have been introduced. Currently, molecular studies have revealed the characteristic genomic alterations, epigenetic modulations, and tumour microenvironment associated with different types of PCa, which provide a chance for urologists to refine the PCa classification. In this context, numerous invaluable molecular classifications have been devised, employing disparate statistical methodologies and algorithmic approaches, encompassing self-organizing map clustering, unsupervised cluster analysis, and multifarious algorithms. Interestingly, the classifier PAM50 was used in a phase-2 multicentre open-label trial, NRG-GU-006, for further validation, which hints at the promise of molecular classification for clinical use. Consequently, this review examines the extant molecular classifications, delineates the prevailing panorama of clinically pertinent molecular signatures, and delves into eight emblematic molecular classifications, dissecting their methodological underpinnings and clinical utility.

Machine learning-based establishment and validation of age-related patterns for predicting prognosis in non-small cell lung cancer within the context of the tumor microenvironment

Lung cancer (LC) is a leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) accounting for over 80% of cases. The impact of aging on clinical outcomes in NSCLC remains poorly understood, particularly with respect to the immune response. In this study, we explored the effects of aging on NSCLC using 307 genes associated with human aging from the Human Ageing Genomic Resources. We identified 53 aging-associated genes that significantly correlate with overall survival of NSCLC patients, including the clinically validated gene BUB1B. Furthermore, we developed an aging-associated enrichment score to categorize patients based on their aging subtypes and evaluated their prognostic and therapeutic response values in LC. Our analyses yielded two aging-associated subtypes with unique profiles in the tumor microenvironment, demonstrating varying responses to immunotherapy. Consensus clustering based on transcriptome profiles provided insights into the effects of aging on NSCLC and highlighted the potential of personalized therapeutic approaches tailored to aging subtypes. Our findings provide a new target and theoretical support for personalized therapeutic approaches in patients with NSCLC, offering insights into the potential impact of aging on cancer outcomes.

Multiomics characterization and verification of clear cell renal cell carcinoma molecular subtypes to guide precise chemotherapy and immunotherapy

Clear cell renal cell carcinoma (ccRCC) is a heterogeneous tumor with different genetic and molecular alterations. Schemes for ccRCC classification system based on multiomics are urgent, to promote further biological insights. Two hundred and fifty-five ccRCC patients with paired data of clinical information, transcriptome expression profiles, copy number alterations, DNA methylation, and somatic mutations were collected for identification. Bioinformatic analyses were performed based on our team's recently developed R package "MOVICS." With 10 state-of-the-art algorithms, we identified the multiomics subtypes (MoSs) for ccRCC patients. MoS1 is an immune exhausted subtype, presented the poorest prognosis, and might be caused by an exhausted immune microenvironment, activated hypoxia features, but can benefit from PI3K/AKT inhibitors. MoS2 is an immune "cold" subtype, which represented more mutation of VHL and PBRM1, favorable prognosis, and is more suitable for sunitinib therapy. MoS3 is the immune "hot" subtype, and can benefit from the anti-PD-1 immunotherapy. We successfully verified the different molecular features of the three MoSs in external cohorts GSE22541, GSE40435, and GSE53573. Patients that received Nivolumab therapy helped us to confirm that MoS3 is suitable for anti-PD-1 therapy. E-MTAB-3267 cohort also supported the fact that MoS2 patients can respond more to sunitinib treatment. We also confirm that SETD2 is a tumor suppressor in ccRCC, along with the decreased SETD2 protein level in advanced tumor stage, and knock-down of SETD2 leads to the promotion of cell proliferation, migration, and invasion. In summary, we provide novel insights into ccRCC molecular subtypes based on robust clustering algorithms via multiomics data, and encourage future precise treatment of ccRCC patients.

Pan-Cancer Analysis of the Prognostic and Immunological Role of SMG5: A Biomarker for Cancers

INTRODUCTION

SMG5 is involved in tumor cell development and viewed as a potential target for immunotherapy. The purpose of this study was to systematically analyze the expression level, function, and prognostic value of SMG5 in pan-cancers.

METHODS

Differential expression of SMG5 in normal and tumor tissues was analyzed using The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression Database (GTEx) data. Survival analysis was performed by Kaplan-Meier method and Cox risk regression. The relationship between SMG5 expression and lymphocyte abundance, tumor cell immune infiltration level, molecular and immune subtypes as well as immune checkpoints was analyzed by tumor-immune system interactions database (TISIDB), Tumor Immune Estimation Resource (TIMER), and Sangerbox databases. The correlation between SMG5 and immune scores was studied using the Estimation of Stromal and Immune Cells in Malignant Tumours using Expression (ESTIMATE) data algorithm. Further, drug sensitivity analysis of SMG5 with low-grade glioma (LGG) was conducted using the CellMiner database.

RESULTS

SMG5 was highly expressed in 23 tumors and only had a significant impact on the prognosis of patients with LGG only. In addition, in tumor microenvironment and tumor immune analysis, we found that the level of immune infiltration, tumor mutational load, microsatellite instability, and immune checkpoints of LGG were significantly correlated with SMG5 expression. Furthermore, SMG5 was significantly associated with immune scores, stromal scores, and sensitivity of some drugs in LGG.

CONCLUSION

SMG5 is differentially expressed in several cancers and is significantly associated with prognosis, immune microenvironment, and immune checkpoints in LGG patients. Therefore, SMG5 could be a potential pan-cancer biomarker and an immunotherapeutic target for LGG.

Non-coding RNAs: emerging roles in the characterization of immune microenvironment and immunotherapy of prostate cancer

Prostate cancer is the most common tumor among men. Although the prognosis for early-stage prostate cancer is good, patients with advanced disease often progress to metastatic castration-resistant prostate cancer (mCRPC), which usually leads to death owing to resistance to existing treatments and lack of long-term effective therapy. In recent years, immunotherapy, especially immune checkpoint inhibitors (ICIs), has made great progress in the treatment of various solid tumors, including prostate cancer. However, the ICIs have only shown modest outcomes in mCRPC compared with other tumors. Previous studies have suggested that the suppressive tumor immune microenvironment (TIME) of prostate cancer leads to poor anti-tumor immune response and tumor resistance to immunotherapy. It has been reported that non-coding RNAs (ncRNAs) are capable of regulating upstream signaling at the transcriptional level, leading to a "cascade of changes" in downstream molecules. As a result, ncRNAs have been identified as an ideal class of molecules for cancer treatment. The discovery of ncRNAs provides a new perspective on TIME regulation in prostate cancer. ncRNAs have been associated with establishing an immunosuppressive microenvironment in prostate cancer through multiple pathways to modulate the immune escape of tumor cells which can promote resistance of prostate cancer to immunotherapy. Targeting these related ncRNAs presents an opportunity to improve the effectiveness of immunotherapy in this patient population.

Androgen deprivation therapy in men with prostate cancer is not associated with COVID-2019 infection

BACKGROUND

Androgens may play a role in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection and host responses as the virus is dependent on the androgen-regulated protein transmembrane serine protease 2 for cell entry. Studies have indicated that prostate cancer patients receiving androgen deprivation therapy (ADT) are at reduced risk of SARS-CoV-2 infection and serious complications compared with patients without ADT, but data are inconsistent.

METHODS

A total of 655 prostate cancer patients who were under surveillance at two urology departments in Sweden on April 1, 2020 were included in the study as well as 240 patients with benign prostatic hyperplasia (BPH). At follow-up early in 2021, the participants completed a questionnaire containing information about symptoms compatible with coronavirus disease 2019 (COVID-19). Blood samples were also collected for the assessment of SARS-CoV-2 IgG antibodies (SARS-CoV-2 Total; Siemens). We used multivariable logistic regression models to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between ADT and the risk of SARS-CoV-2 infection.

RESULTS

The cumulative incidence of SARS-CoV-2 seropositivity was 13.4% among patients receiving ADT and 10.4% among patients without ADT. After adjusting for potential confounders, we observed no differences in symptoms or risk of SARS-CoV-2 infection between patients with and without ADT (OR: 0.98; 95% CI: 0.52-1.85). Higher body mass index, Type 1 diabetes, and prostate cancer severity, defined by high Gleason score (8-10; OR: 2.06; 95% CI: 1.04-4.09) or elevated levels of prostate-specific antigen (>20 µg/l; OR: 2.15; 95% CI: 1.13-4.07) were associated with increased risk of SARS-CoV-2 infection. Overall, the risk of SARS-CoV-2 infection was not higher among men with prostate cancer than among men with BPH.

CONCLUSIONS

Our results do not support the hypothesis that ADT use in prostate cancer patients reduces the risk or symptom severity of SARS-CoV-2 infection or that prostate cancer patients are at increased risk of COVID-19 compared with men without prostate cancer.

TIMEAS, a promising method for the stratification of testicular germ cell tumor patients with distinct immune microenvironment, clinical outcome and sensitivity to frontline therapies

PURPOSE

With the heterogeneous genetic background, prognosis prediction and therapeutic targets for testicular germ cell tumors (TGCTs) are still unclear. We defined the tumor immune microenvironment activation status (TIMEAS).

METHODS

We collected a total of 314 TGCT patients from four cohorts, including a 48-case microarray. A nonnegative matrix factorization algorithm was applied to identify the "immune factor", derived the top 150 weighted genes to divide patients into immune and non-immune classes, and further separated the immune class into activated and exhausted subgroups by nearest template prediction. Tumor mutant burden, gene mutation, and copy number alteration were compared with our recently developed package "MOVICS". A random forest algorithm was performed to establish a prediction model with fewer genes. Immunohistochemistry staining was performed to identify TIMEAS in the microarray.

RESULTS

We constructed the TIMEAS in the TCGA-TGCT cohort and further validated it in the GSE3218 and GSE99420 cohorts. The immune class contained the activated status of T-lymphocytes, B-lymphocytes, and macrophages, while Treg cells and the WNT/TGFβ signature were more activated in the immune-suppressed subgroup. Patients in the immune-exhausted subgroup had the worst prognosis, and 22.9% of patients in the immune-activated subgroup had KRAS mutations, which might stimulate the response of the immune system and lead to a favorable prognosis. The immune-exhausted group benefited more from chemotherapy, while the immune-activated subgroup responded well to anti-PD-1/PD-L1 therapy. FSCN1 was validated as the target of the immune-exhausted microenvironment by immunohistochemistry.

CONCLUSION

TIMEAS classification can separate TGCT patients; patients in the immune-activated subgroup could benefit more from anti-PD-L1 immunotherapy, and those in the immune-exhausted subgroup are more suitable for chemotherapy.

Identification and validation of an E2F-related gene signature for predicting recurrence-free survival in human prostate cancer

BACKGROUND

It is well-established that biochemical recurrence is detrimental to prostate cancer (PCa). In the present study, we explored the mechanisms underlying PCa progression.

METHODS

Five cohorts from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases were used to perform gene set variation analysis (GSVA) between nonrecurrent and recurrent PCa patients. We obtained the intersection of pathway enrichment results and extracted the corresponding gene list. LASSO Cox regression analysis was used to identify recurrence-free survival (RFS)-related significant genes and establish an RFS prediction gene signature and nomogram. MTT and colony formation assays were conducted to validate our findings.

RESULTS

The E2F signaling pathway was activated in recurrent PCa patients compared to nonrecurrent patients. We established an E2F-related gene signature for RFS prediction based on the four identified E2F-related genes (CDKN2C, CDKN3, RACGAP1, and RRM2) using LASSO Cox regression in the Memorial Sloan Kettering Cancer Center (MSKCC) cohort. The risk score of each patient in MSKCC was calculated based on the expression levels of CDKN2C, CDKN3, RACGAP1, and RRM2. PCa patients with low-risk scores exhibited higher RFS than those with high-risk scores. Receiver operating characteristic (ROC) curve analysis validated the good performance and prognostic accuracy of the E2F-related gene signature, which was validated in the TCGA-prostate adenocarcinoma (TCGA-PRAD) cohort. Compared to patients with low Gleason scores and early T stages, PCa patients with high Gleason scores and advanced T stages had high-risk scores. Moreover, the E2F-related gene signature-based nomogram yielded good performance in RFS prediction. Functional experiments further confirmed these results.

CONCLUSIONS

The E2F signaling pathway is associated with biochemical recurrence in PCa. Our established E2F-related gene signature and nomogram yielded good accuracy in predicting the biochemical recurrence in PCa.

Molecular Cluster Mining of Adrenocortical Carcinoma via Multi-Omics Data Analysis Aids Precise Clinical Therapy

Adrenocortical carcinoma (ACC) is a malignancy of the endocrine system. We collected clinical and pathological features, genomic mutations, DNA methylation profiles, and mRNA, lncRNA, microRNA, and somatic mutations in ACC patients from the TCGA, GSE19750, GSE33371, and GSE49278 cohorts. Based on the MOVICS algorithm, the patients were divided into ACC1-3 subtypes by comprehensive multi-omics data analysis. We found that immune-related pathways were more activated, and drug metabolism pathways were enriched in ACC1 subtype patients. Furthermore, ACC1 patients were sensitive to PD-1 immunotherapy and had the lowest sensitivity to chemotherapeutic drugs. Patients with the ACC2 subtype had the worst survival prognosis and the highest tumor-mutation rate. Meanwhile, cell-cycle-related pathways, amino-acid-synthesis pathways, and immunosuppressive cells were enriched in ACC2 patients. Steroid and cholesterol biosynthetic pathways were enriched in patients with the ACC3 subtype. DNA-repair-related pathways were enriched in subtypes ACC2 and ACC3. The sensitivity of the ACC2 subtype to cisplatin, doxorubicin, gemcitabine, and etoposide was better than that of the other two subtypes. For 5-fluorouracil, there was no significant difference in sensitivity to paclitaxel between the three groups. A comprehensive analysis of multi-omics data will provide new clues for the prognosis and treatment of patients with ACC.

Multi-Omics Analysis Reveals Clinical Value and Possible Mechanisms of ATAD1 Down-Regulation in Human Prostate Adenocarcinoma

Prostate adenocarcinoma (PRAD) is the most common histological subtype of prostate cancer. Post-treatment biochemical recurrence is a challenging issue. ATAD1 (ATPase Family AAA Domain Containing 1) plays a vital role in mitochondrial proteostasis and apoptosis activity, while its clinical value in PRAD and its impact on the tumor microenvironment (TME) remain unanswered. In this study, we aimed to investigate the clinical value and possible mechanisms of ATAD1 in PRAD via multi-omics analysis. Using cBioPortal, we confirmed that ATAD1 alteration was associated with gene expression and unfavorable DFS. Deep deletion predominantly occurred in PRAD. By integrating DriverDBv3 and GEPIA2, we noted ATAD1 downregulation in PRAD tissues compared to normal tissues, associated with unfavorable DFS in PRAD patients. DNA repair genes ATM, PARP1and BRCA2 had positive associations with ATAD1 expression. We found that the generalization value of ATAD1 could be applied to other cancers such as KIRC and UCEC. In addition, LinkedOmics identified that the functional involvement of ATAD1 participates in mitochondrial structure and cell cycle progression. Using TIMER analysis, we demonstrated that ATAD1 downregulation correlated with an immunosuppressive TME. Furthermore, we accessed a GSE55062 dataset on UALCAN and discovered the involvement of ERG-mediated transcriptional repression on ATAD1 downregulation. Cross-association screening of shATAD1 efficacy vs. altered mRNAs identified 190 perturbed mRNAs. Then, functional enrichment analysis using the Metascape omics tool recognized that shATAD1-perturbed mRNAs are primarily in charge of the activation of Wnt/β-catenin pathway and lipid metabolic processes. In conclusion, multi-omics results reveal that ATAD1 downregulation is a clinical biomarker for pathological diagnosis and prognosis for patients with PRAD. Reduced ATAD1 may be involved in the enhanced activity of mitochondria and cell cycle, as well as possibly shaping an immunosuppressive TME. ERG serves as an upstream transcriptional repressor of ATAD1. Downstream mechanisms of ATAD1 are involved in Wnt/β-catenin pathway and lipid metabolic processes.

The established chemokine-related prognostic gene signature in prostate cancer: Implications for anti-androgen and immunotherapies

Background

Prostate cancer (PCa) was one of the most common malignancies among men, while the prognosis for PCa patients was poor, especially for patients with recurrent and advanced diseases.

Materials and methods

Five PCa cohorts were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases, and the biochemical recurrence (BCR)-related chemokine genes were identified by LASSO-Cox regression. The chemokine-related prognostic gene signature (CRPGS) was established, and its association with PCa patients’ clinical, pathological and immune characteristics was analyzed. The association between CRPGS and PCa patients’ responses to androgen deprivation therapy (ADT) and immunotherapy was analyzed. The CRPGS was compared with other previously published molecular signatures, and the CRPGS was externally validated in our real-world AHMU-PC cohort.

Results

Four recurrence-free survival (RFS)-related chemokine genes (CXCL14, CCL20, CCL24, and CCL26) were identified, and the CRPGS was established based on the four identified chemokine genes, and TCGA-PRAD patients with high riskscores exhibited poorer RFS, which was validated in the GSE70768 cohort. The CRPGS was associated with the clinical, pathological, and immune characteristics of PCa patients. Low-risk PCa patients were predicted to respond better to ADT and immunotherapy. By comparing with other molecular signatures, the CRPGS could classify PCa patients into two risk groups well, and the CRPGS was associated with the m6A level, as well as TP53 and SPOP mutation status of PCa patients. In the AHMU-PC cohort, the CRPGS was associated with the advanced pathology stage and Gleason score.

Conclusions

The identified chemokine genes and CRPGS were associated with the prognosis of PCa, which could predict PCa patients’ responses to anti-androgen and immunotherapies.

Establishment of a five-enzalutamide-resistance-related-gene-based classifier for recurrence-free survival predicting of prostate cancer

To identify prostate cancer (PCa) patients with a high risk of recurrence is critical before delivering adjuvant treatment. We developed a classifier based on the Enzalutamide treatment resistance‐related genes to assist the currently available staging system in predicting the recurrence‐free survival (RFS) prognosis of PCa patients. We overlapped the DEGs from two datasets to obtain a more convincing Enzalutamide‐resistance‐related‐gene (ERRG) cluster. The five‐ERRG‐based classifier obtained good predictive values in both the training and validation cohorts. The classifier precisely predicted RFS of patients in four cohorts, independent of patient age, pathological tumour stage, Gleason score and PSA levels. The classifier and the clinicopathological factors were combined to construct a nomogram, which had an increased predictive accuracy than that of each variable alone. Besides, we also compared the differences between high‐ and low‐risk subgroups and found their differences were enriched in cancer progression‐related pathways. The five‐ERRG‐based classifier is a practical and reliable predictor, which adds value to the existing staging system for predicting the RFS prognosis of PCa after radical prostatectomy, enabling physicians to make more informed treatment decisions concerning adjuvant therapy.

A nine–consensus–prognostic –gene–based prognostic signature, recognizing the dichotomized subgroups of gastric cancer patients with different clinical outcomes and therapeutic strategies

Background: The increasing prevalence and mortality of gastric cancer (GC) has promoted the urgent need for prognostic signatures to predict the long-term risk and search for therapeutic biomarkers.

Methods and materials: A total of 921 GC patients from three GEO cohorts were enrolled in the current study. The GSE15459 and GSE62254 cohorts were used to select the top prognostic gene via the evaluation of the area under the receiver operating characteristic (ROC) curve (AUC) values. The GSE84437 cohort was used as the external validation cohort. Least absolute shrinkage and selector operation (LASSO) regression analysis was applied to reduce the feature dimension and construct the prognostic signature. Furthermore, a nomogram was constructed by integrating the independent prognostic analysis and validated by calibration plot, decision curve analysis and clinical impact curve. The molecular features and response to chemo-/immunotherapy among risk subgroups were evaluated by the “MOVICS” and “ESTAMATE” R packages and the SubMap algorithm. Lauren classification and ACRG molecular subtype were obtained to compare with the risk model.

Results: Forty-four prognosis-associated genes were identified with a preset cutoff AUC value of 0.65 in both the GSE62254 and GSE15459 cohorts. With the 10-fold cross validation analysis of LASSO, nine genes were selected to construct the nine-consensus-prognostic-gene signature. The signature showed good prognostic value in the GSE62254 (p < 0.001, HR: 3.81, 95% CI: 2.44–5.956) and GSE15459 (p < 0.001, HR: 2.65, 95% CI: 1.892–3.709) cohorts and the external validation GSE84437 cohort (p < 0.001, HR: 2.06, 95% CI: 1.554–2.735). The nomogram constructed based on two independent predictive factors, tumor stage and the signature, predicted events tightly consistent with the actual (Hosmer–Lemeshow p value: 1-year, 0.624; 3-years, 0.795; 5-years, 0.824). For the molecular features, we observed the activation of apical junction, epithelial mesenchymal transition, and immune pathways in the high-risk group, while in the low-risk group, cell cycle associated G2M, E2F and MYC target pathways were activated. Based on the results we obtained, we indicated that gastric patients in the low-risk group are more suitable for 5-fluorouracil therapy, while high-risk group patients are more suitable for anti-CTLA4 immunotherapy, these results need more support in the further studies. After compare with proposed molecular subtypes, we realized that the nine-consensus prognostic gene signature is a powerful addition to identify the gastric patients with poor prognosis.

Conclusion: In summary, we constructed a robust nine-consensus-prognostic-gene signature for the prediction of GC prognosis, which can also predict the personalized treatment of GC patients.

EPM2A acts as a protective factor in prostate cancer, evidence from a real-world patient cohort

EPM2A encodes a dual specificity phosphatase and has been proven to be a potential biomarker in several cancers but has not been mentioned in prostate cancer (PCA). We investigated the prognostic and therapeutic value of EPM2A in PCA. The TCGA-PRAD cohort was collected to evaluate the differential expression, prognostic value, immunocyte infiltration and drug sensitivity of EPM2A in PCA. We constructed a nomogram model to predict the recurrence probability for PCA patients. Immunohistochemistry was used to validate the different transcript levels of EPM2A between tumor and normal tissues. A real-world AHMU-PC cohort was employed for validation. The results showed decreased expression of EPM2A in 95.65% of tumor tissues and was related to their prognosis, especially PCA (p = 0.008, HR = 0.57, 95% CI: 0.371–0.863). Further multiple analysis by adjusting clinical features revealed that EPM2A acted as an independent prognostic factor (p = 0.014, HR = 0.589, 95% CI: 0.386–0.898). Pathway enrichment analysis showed variable signaling activation between high EPM2A expression patients (HEXP) and low EPM2A expression patients (LEXP). The HEXP group contained higher infiltration of immunocytes than the LEXP group, as well as high levels of PD-1, PD-L1 and PD-L2, while LEXP patients were more sensitive to cisplatin, paclitaxel and bicalutamide therapy. The nomogram containing the EPM2A group, T stage and Gleason score showed a preferable prognostic value (AUC = 0.755; Hosmer‒Lemeshow, p = 0.486). In validation, we confirmed the lower transcript level of EPM2A in PCA than in normal tissues (120.5 ± 2.159 vs. 138.3 ± 1.83, p = 0.035) and correlated it with the expression level of PD-1 (R = 0.283). Among the 66 patients from the AHMU-PC cohort, we further validated the function of EPM2A in PCA patients. HEXP patients had longer recurrence-free survival times (1207 ± 110 vs. 794.2 ± 97.02, p = 0.0063) and favorable prognoses (HR: 0.417, 95% CI: 0.195–0.894, p = 0.0245). Collectively, we identified the prognostic value of EPM2A in PCa via a bioinformatics method. Patients with higher EPM2A may be more sensitive to immunotherapy, and patients with lower EPM2A were more suitable for bicalutamide, cisplatin and paclitaxel therapy.

Prostate Cancer Tumor Stroma: Responsibility in Tumor Biology, Diagnosis and Treatment

Simple Summary

The crosstalk between prostate stroma and its epithelium is essential to tissue homeostasis. Likewise, reciprocal signaling between tumor cells and the stromal compartment is required in tumor progression to facilitate or stimulate key processes such as cell proliferation and invasion. The aim of the present work was to review the current state of knowledge on the significance of tumor stroma in the genesis, progression and therapeutic response of prostate carcinoma. Additionally, we addressed the future therapeutic opportunities.

Abstract

Prostate cancer (PCa) is a common cancer among males globally, and its occurrence is growing worldwide. Clinical decisions about the combination of therapies are becoming highly relevant. However, this is a heterogeneous disease, ranging widely in prognosis. Therefore, new approaches are needed based on tumor biology, from which further prognostic assessments can be established and complementary strategies can be identified. The knowledge of both the morphological structure and functional biology of the PCa stroma compartment can provide new diagnostic, prognostic or therapeutic possibilities. In the present review, we analyzed the aspects related to the tumor stromal component (both acellular and cellular) in PCa, their influence on tumor behavior and the therapeutic response and their consideration as a new therapeutic target.

Molecular classification of hormone-sensitive and castration-resistant prostate cancer, using nonnegative matrix factorization molecular subtyping of primary and metastatic specimens

BACKGROUND

Despite the rapidly evolving therapeutic landscape, immunotherapy has demonstrated limited activity in prostate cancer. A greater understanding of the molecular landscape, particularly the expression of immune-related pathways, will inform future immunotherapeutic strategies. Consensus nonnegative matrix factorization (cNMF) is a novel model of molecular classification analyzing gene expression data, focusing on biological interpretation of metagenes and selecting meaningful clusters.

OBJECTIVE

We aimed to identify molecular subtypes of prostate cancer using cNMF and correlate these with existing biomarkers to inform future immunotherapeutic strategies.

METHODS

A cohort of archival tumor specimens from hormone-sensitive and castration-resistant disease was studied. Whole transcriptomic profiles were generated using TruSeq RNA Access technology and subjected to cNMF. Comprehensive genomic profiling was performed with the FoundationOne assay. NMF subtypes were characterized by gene expression pathways, genomic alterations and correlated with clinical data, then applied to The Cancer Genome Atlas data set.

RESULTS

We studied 164 specimens, including 52 castration-resistant and 13 paired primary/metastatic specimens. cNMF identified four distinct subtypes. NMF1 (19%) is enriched for immune-related and stromal-related pathways with transforming growth factor β (TGFβ) signature. NMF2 (36%) is associated with FOXO-mediated transcription signature and AKT signaling, NMF3 (26%) is enriched for ribosomal RNA processing, while NMF4 (19%) is enriched for cell cycle and DNA-repair pathways. The most common gene alterations included TMPRSS22 (42%), TP53 (23%), and DNA-repair genes (19%), occurring across all subtypes. NMF4 is significantly enriched for MYC and Wnt-signaling gene alterations. TMB, CD8 density, and PD-L1 expression were low overall. NMF1 and NMF4 were NMF2 was associated with superior overall survival.

CONCLUSIONS

Using cNMF, we identified four molecularly distinct subtypes which may inform treatment selection. NMF1 demonstrates the most inflammatory signature with asuppressive TGFβ signature, suggesting potential benefit with immunotherapy combination strategies targeting TGFβ and PD-(L)1. Prospective studies are required to evaluate the use of this novel model to molecularly stratify patients for optimal treatment selection.

Molecular Subtypes Based on Genomic and Transcriptomic Features Correlate with the Responsiveness to Immune Checkpoint Inhibitors in Metastatic Clear Cell Renal Cell Carcinoma

Simple Summary

Immune checkpoint inhibitors (ICIs), such as programmed cell death protein 1 (PD-1) blockade, have proven to be the most effective agents for the management of many cancer types. Although ICIs are the current standard of care for treating metastatic clear cell renal cell carcinoma (ccRCC), 40–60% of patients still have intrinsic resistance to ICIs across multiple clinical trials. Therefore, identifying optimal biomarkers that can predict either responders or non-responders to ICIs has been of tremendous importance. Here, we generated targeted sequencing and whole transcriptomic sequencing of 60 patients with metastatic ccRCC treated with ICIs. Moreover, transcriptomic analysis was integrated to identify molecular subtypes using a total of 177 tumor samples by merging our data and published data derived from the CheckMate 025 trial. Our results show that these molecular subtypes are associated with specific genomic alterations, distinct molecular pathways, and differential clinical outcomes in patients with metastatic ccRCC treated with ICIs.

Abstract

Clear cell renal cell carcinoma (ccRCC) has been reported to be highly immune to and infiltrated by T cells and has angiogenesis features, but the effect of given features on clinical outcomes followed by immune checkpoint inhibitors (ICIs) in ccRCC has not been fully characterized. Currently, loss of function mutation in PBRM1, a PBAF-complex gene frequently mutated in ccRCC, is associated with clinical benefit from ICIs, and is considered as a predictive biomarker for response to anti-PD-1 therapy. However, functional mechanisms of PBRM1 mutation regarding immunotherapy responsiveness are still poorly understood. Here, we performed targeted sequencing (n = 60) and whole transcriptomic sequencing (WTS) (n = 61) of patients with metastatic ccRCC treated by ICIs. By integrating WTS data from the CheckMate 025 trial, we obtained WTS data of 177 tumors and finally identified three molecular subtypes that are characterized by distinct molecular phenotypes and frequency of PBRM1 mutations. Patient clustered subtypes 1 and 3 demonstrated worse responses and survival after ICIs treatment, with a low proportion of PBRM1 mutation and angiogenesis-poor, but were immune-rich and cell-cycle enriched. Notably, patients clustered in the subtype 2 showed a better response and survival after ICIs treatment, with enrichment of PBRM1 mutation and metabolic programs and a low exhausted immune phenotype. Further analysis of the subtype 2 population demonstrated that GATM (glycine amidinotransferase), as a novel gene associated with PBRM1 mutation, plays a pivotal role in ccRCC by using a cell culture model, revealing tumor, suppressive-like features in reducing proliferation and migration. In summary, we identified that metastatic ccRCC treated by ICIs have distinct genomic and transcriptomic features that may account for their responsiveness to ICIs. We also revealed that the novel gene GATM can be a potential tumor suppressor and/or can be associated with therapeutic efficacy in metastatic ccRCC treated by ICIs.

Oncogenic ACSM1 in prostate cancer is through metabolic and extracellular matrix-receptor interaction signaling pathways

Acyl-coenzyme A synthetase medium chain family member 1 (ACSM1) is a medium chain Acyl-CoA Synthetase family member and plays an important role in fatty acid metabolism. The oncogenic roles of ACSM1 are largely unknown. Using comprehensive approaches, we analyzed gene expression profiles and genomic datasets and identified that the expression of ACSM1 was specifically increased in prostate cancer in comparison to the adjacent non-tumor tissues. The increased expression of ACSM1 was associated with increased risks of poor prognosis and shorter survival time. Moreover, genomic copy number alterations of ACSM1, including deletion, amplification, and amino acid changes were frequently observed in prostate cancers, although these mutations did not correlate with gene expression levels. However, ACSM1 gene amplifications were significantly corrected with increased risks of prostate cancer metastasis, and ACSM1 genetic alterations were significantly associated with worse disease-free. And progress-free survival. Gene function stratification and gene set enrichment analysis revealed that the oncogenic roles of ACSM1 in prostate cancer were mainly through metabolic pathways and extracellular matrix (ECM)-receptor interaction signaling pathways, but not associated with microenvironmental immunological signaling pathways, and that ACSM1 expression was not associated with immune cell infiltration in the cancer microenvironment or prostate cancer immune subtypes. In conclusion, the present work has demonstrated that ACSM1 can be specifically and significantly elevated in prostate cancer. ACSM1 gene expression and genomic amplification exhibit important clinical significance through metabolic and ECM-receptor interaction signaling pathways. Thus, ACSM1 may be a novel oncogene and serve as a biomarker for prostate cancer screening and prognosis prediction, and/or a therapeutic target.

Selective estrogen receptor modulators contribute to prostate cancer treatment by regulating the tumor immune microenvironment

Prostate cancer (PC) has previously been established as a cold tumor and develops in an inert immunosuppressive environment. Current research focuses on altering the immune microenvironment of PC from cold to hot; thus, in the present review, the diverse roles of estrogen and estrogen receptor (ER) signaling was examined in the tumor cell and tumor immune microenvironment (TIM). We hypothesized that ERα promotes PC progression and ERβ impedes epithelial-mesenchymal transition in PC cells, while in the TIM, ERβ mediates the immunosuppressive environment, and low levels of ERα is associated with disease development. Selective estrogen receptor modulators (SERMs) or selective ER degraders play diverse roles in the regulation of ER isoforms. Patients with PC may benefit from the use of SERMs, including raloxifene, in combination with anti-PD1/PD-L1 checkpoint immunotherapy, or TGF-β or Wnt antagonists. The present review demonstrated that immunotherapy-based strategies combined with SERMs may be an option for the future of PC-targeting therapy.

Nomogram for predicting the overall survival of patients with early-onset prostate cancer: A population-based retrospective study

Background

The incidence of early‐onset prostate cancer (PCa) has increased significantly over the past few decades. It is necessary to develop a prognostic nomogram for the prediction of overall survival (OS) in early‐onset PCa patients.

Methods

A total of 23,730 early‐onset PCa patients (younger than 55 years old) between 2010 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were enrolled for the current study, and randomly separated into the training cohort and the validation cohort. 361 eligible early‐onset PCa patients from The Cancer Genome Atlas‐Prostate Adenocarcinoma (TCGA‐PRAD) cohort were obtained as the external validation cohort. Independent predictors were selected by univariate and multivariate Cox regression analysis, and a prognostic nomogram was constructed for 1‐, 3‐, and 5‐year OS. The accurate and discriminative abilities of the nomogram were evaluated by the concordance index (C‐index), receiver operating characteristic curve (ROC), calibration plot, net reclassification index (NRI), and integrated discrimination improvement (IDI).

Results

Multivariate Cox analysis showed that race, marital status, TNM stage, prostate‐specific antigen, Gleason score, and surgery were significantly associated with poor prognosis of PCa. A nomogram consisting of these variables was established, which had higher C‐indexes than the TNM system (training cohort: 0.831 vs. 0.746, validation cohort: 0.817 vs. 0.752). Better AUCs of the nomogram than the TNM system at 1, 3, and 5 years were found in both the training cohort and the validation cohort. The 3‐year and 5‐year AUCs of the nomogram in the TCGA‐PRAD cohort were 0.723 and 0.679, respectively. The calibration diagram, NRI, and IDI also showed promising prognostic value in OS.

Conclusions

We developed an effective prognostic nomogram for OS prediction in early‐onset PCa patients, which will further assist both the precise clinical treatment and the assessment of long‐term outcomes.

Inflammation and Prostate Cancer: A Multidisciplinary Approach to Identifying Opportunities for Treatment and Prevention

Prostate cancer is a major cause of disease for men globally. Inflammation, an established hallmark of cancer, is frequently observed in the prostate, though its contribution to prostate cancer risks and outcomes is not fully understood. Prostate cancer is biologically and clinically heterogeneous, and there is now evidence that inflammation and immunological characteristics vary by the genomic and mutational landscape of the tumor. Moreover, it is now recognized that risk factor profiles vary between tumor subgroups, as defined by histopathological and molecular features. Here, we provide a review centered around the relationship between inflammation and prostate cancer, with a consideration of molecular tumor features and a particular focus on the advanced and lethal stages of disease. We summarize findings from epidemiological studies of the etiology and role of inflammation in prostate cancer. We discuss the pathology of prostate inflammation, and consider approaches for assessing the tumor immune microenvironment in epidemiological studies. We review emerging clinical therapies targeting immune biology within the context of prostate cancer. Finally, we consider potentially modifiable risk factors and corresponding lifestyle interventions that may affect prostate inflammation, impacting outcomes. These emerging insights will provide some hints for the development of treatment and prevention strategies for advanced and lethal prostate cancer.

Comprehensive Characterization of Ageing-Relevant Subtypes Associated With Different Tumorigenesis and Tumor Microenvironment in Prostate Cancer

Objective: Accumulated evidence demonstrates that ageing is a robust risk factor of prostate cancer prognosis. Herein, we conducted a systematic analysis about ageing-relevant molecules and relevant tumor microenvironment features in prostate cancer.

Methods: Transcriptome data, clinical information, and mutational data of prostate cancer patients were retrospectively collected from the Cancer Genome Atlas cohort. In accordance with the expression of specific ageing-relevant genes, prostate cancer patients were clustered with consensus clustering analyses. WGCNA was adopted for determination of subtype-associated co-expression modules and genes. Thereafter, characteristic genes were further screened with random forest algorithm and a prognostic model was conducted with multivariate cox regression analyses. Tumor microenvironment-infiltrating immune cells were estimated with ssGSEA and ESTIMATE. Activities of the cancer immunity cycle and expressions of HLA and immune checkpoint molecules were then quantified across prostate cancer cases. A serious experiment was conducted to investigate the roles of EIF2S2 in prostate tumorigenesis.

Results: This study characterized three ageing-relevant subtypes (C1, C2, and C3) with diverse clinical prognosis. Subtype C1 presented the features of low mutational frequency and immune activation; C2 was characterized by stromal and immune activation; and C3 showed immune suppression. An ageing-derived gene signature was conducted, which independently and robustly predicted patients’ prognosis. Additionally, this signature was in relation to immune inactivation. Among the genes in the signature, EIF2S2 triggered proliferation, invasion, and migration of LNCaP and PC-3 cells.

Conclusion: Collectively, ageing-relevant molecular subtypes and gene signature might be of great significance to determine clinical outcomes and tumor microenvironment features and immunotherapeutic responses in prostate cancer.

What Do We Have to Know about PD-L1 Expression in Prostate Cancer? A Systematic Literature Review (Part 6): Correlation of PD-L1 Expression with the Status of Mismatch Repair System, BRCA, PTEN, and Other Genes

Pembrolizumab (anti-PD-1) is allowed in selected metastatic castration-resistant prostate cancer (PC) patients showing microsatellite instability/mismatch repair system deficiency (MSI-H/dMMR). BRCA1/2 loss-of-function is linked to hereditary PCs and homologous recombination DNA-repair system deficiency: poly-ADP-ribose-polymerase inhibitors can be administered to BRCA-mutated PC patients. Recently, docetaxel-refractory metastatic castration-resistant PC patients with BRCA1/2 or ATM somatic mutations had higher response rates to pembrolizumab. PTEN regulates cell cycle/proliferation/apoptosis through pathways including the AKT/mTOR, which upregulates PD-L1 expression in PC. Our systematic literature review (PRISMA guidelines) investigated the potential correlations between PD-L1 and MMR/MSI/BRCA/PTEN statuses in PC, discussing few other relevant genes. Excluding selection biases, 74/677 (11%) PCs showed dMMR/MSI; 8/67 (12%) of dMMR/MSI cases were PD-L1+. dMMR-PCs included ductal (3%) and acinar (14%) PCs (all cases tested for MSI were acinar-PCs). In total, 15/39 (39%) PCs harbored BRCA1/2 aberrations: limited data are available for PD-L1 expression in these patients. 13/137 (10%) PTEN- PCs were PD-L1+; 10/29 (35%) PD-L1+ PCs showed PTEN negativity. SPOP mutations may increase PD-L1 levels, while the potential correlation between PD-L1 and ERG expression in PC should be clarified. Further research should verify how the efficacy of PD-1 inhibitors in metastatic castration-resistant PCs is related to dMMR/MSI, DNA-damage repair genes defects, or PD-L1 expression.

Oncological Response and Predictive Biomarkers for the Checkpoint Inhibitors in Castration-Resistant Metastatic Prostate Cancer: A Systematic Review and Meta-Analysis

Recently, checkpoint inhibitors have been investigated in metastatic prostate cancer, however their overall effect is unclear and needs to be further investigated. Objectives: The aim of this systematic review is to investigate the oncological response of metastatic castration-resistant prostate cancer patients to immune checkpoint inhibitors. Methods: Based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement, a systematic review of the literature was conducted through online electronic databases and the American Society of Clinical Oncology (ASCO) Meeting Library. Eligible publications were selected after a staged screening and selection process. RevMan 5.4 software was employed to run the quantitative analysis and forest plots. Risk of bias assessment was conducted using the Cochrane tool and Newcastle–Ottawa Scale for the randomized and non-randomized trials, respectively. Results: From the 831 results retrieved, 8 studies including 2768 patients were included. There was no significant effect on overall survival (OS) (overall response (OR) = 0.98; Z = 0.42; p = 0.67). Meanwhile, progression-free survival (PFS) was significantly better with immune checkpoint inhibitors administration (OR = 0.85; Z = 3.9; p < 0.0001). The subgroup analysis for oncological outcomes based on programmed death ligand 1 (PD-L1) positivity status displayed no significant effect, except on prostate-specific antigen response rate (PSA RR) (OR = 3.25; Z = 2.29; p = 0.02). Based on DNA damage repair (DDR), positive patients had a significantly better PFS and a trend towards better OS and overall response rate (ORR); the ORR was 40% in positive patients compared to 20% in the negative patients (OR = 2.46; Z = 1.3; p = 0.19), while PSA RR was 23.5% compared to 14.3% (OR = 1.88; Z = 0.88; p = 0.38). Better PFS was clearly associated with DDR positivity (OR = 0.70; Z = 2.48; p = 0.01) with a trend towards better OS in DDR positive patients (OR = 0.71; Z = 1.38; p = 0.17). Based on tumor mutation burden (TMB), ORR was 46.7% with high TMB versus 8.8% in patients with low TMB (OR = 11.88; Z = 3.0; p = 0.003). Conclusions: Checkpoint inhibitors provide modest oncological advantages in metastatic castration-resistant prostate cancer. There are currently no good predictive indicators that indicate a greater response in some patients.

What Do We Have to Know about PD-L1 Expression in Prostate Cancer? A Systematic Literature Review. Part 7: PD-L1 Expression in Liquid Biopsy

Liquid biopsy is an accessible, non-invasive diagnostic tool for advanced prostate cancer (PC) patients, potentially representing a real-time monitoring test for tumor evolution and response to treatment through the analysis of circulating tumor cells (CTCs) and exosomes. We performed a systematic literature review (PRISMA guidelines) to describe the current knowledge about PD-L1 expression in liquid biopsies of PC patients: 101/159 (64%) cases revealed a variable number of PD-L1+ CTCs. Outcome correlations should be investigated in larger series. Nuclear PD-L1 expression by CTCs was occasionally associated with worse prognosis. Treatment (abiraterone, enzalutamide, radiotherapy, checkpoint-inhibitors) influenced PD-L1+ CTC levels. Discordance in PD-L1 status was detected between primary vs. metastatic PC tissue biopsies and CTCs vs. corresponding tumor tissues. PD-L1 is also released by PC cells through soluble exosomes, which could inhibit the T cell function, causing immune evasion. PD-L1+ PC-CTC monitoring and genomic profiling may better characterize the ongoing aggressive PC forms compared to PD-L1 evaluation on primary tumor biopsies/prostatectomy specimens (sometimes sampled a long time before recurrence/progression). Myeloid-derived suppressor cells and dendritic cells (DCs), which may have immune-suppressive effects in tumor microenvironment, have been found in PC patients circulation, sometimes expressing PD-L1. Occasionally, their levels correlated to clinical outcome. Enzalutamide-progressing castration-resistant PC patients revealed increased PD-1+ T cells and circulating PD-L1/2+ DCs.

Molecular classification reveals the diverse genetic and prognostic features of gastric cancer: A multi-omics consensus ensemble clustering

BACKGROUND

Globally, gastric cancer (GC) is the fifth most common tumor. It is necessary to identify novel molecular subtypes to guide patient selection for specific target therapeutic benefits.

METHODS

Multi-omics data, including transcriptomics RNA-sequencing (mRNA, LncRNA, miRNA), DNA methylation, and gene mutations in the TCGA-STAD cohort were used for the clustering. Ten classical clustering algorithms were executed to recognize patients with different molecular features using the "MOVICS" package in R. The activated signaling pathways were evaluated using the single-sample gene set enrichment analysis. The differential distribution of gene mutations, copy number alterations, and tumor mutation burden was compared, and potential responses to immunotherapy and chemotherapy were also assessed.

RESULTS

Two molecular subtypes (CS1 and CS2) were recognized by ten clustering algorithms with consensus ensembles. Patients in the CS1 group had a shorter average overall survival time (28.5 vs. 68.9 months, P = 0.016), and progression-free survival (19.0 vs. 63.9 months, P = 0.008) as compared to those in the CS2 group. Extracellular associated biological process activation was higher in the CS1 group, while the CS2 group displayed the enhanced activation of cell cycle-associated pathways. Significantly higher total mutation numbers and neoantigens were observed in the CS2 group, along with specific mutations in TTN, MUC16, and ARID1A. Higher infiltration of immunocytes was also observed in the CS2 group, reflective of the potential immunotherapeutic benefits. Moreover, the CS2 group could also respond to 5-fluorouracil, cisplatin, and paclitaxel. The similar diversity in clinical outcomes between CS1 and CS2 groups was successfully validated in the external cohorts, GSE62254, GSE26253, GSE15459, and GSE84437.

CONCLUSION

The findings provided novel insights into the GC subtypes through integrative analysis of five -omics data by ten clustering algorithms. These could provide potential clinical therapeutic targets based on the specific molecular features.

What Do We Have to Know about PD-L1 Expression in Prostate Cancer? A Systematic Literature Review. Part 5: Epigenetic Regulation of PD-L1

Epigenetic alterations (including DNA methylation or miRNAs) influence oncogene/oncosuppressor gene expression without changing the DNA sequence. Prostate cancer (PC) displays a complex genetic and epigenetic regulation of cell-growth pathways and tumor progression. We performed a systematic literature review (following PRISMA guidelines) focused on the epigenetic regulation of PD-L1 expression in PC. In PC cell lines, CpG island methylation of the CD274 promoter negatively regulated PD-L1 expression. Histone modifiers also influence the PD-L1 transcription rate: the deletion or silencing of the histone modifiers MLL3/MML1 can positively regulate PD-L1 expression. Epigenetic drugs (EDs) may be promising in reprogramming tumor cells, reversing epigenetic modifications, and cancer immune evasion. EDs promoting a chromatin-inactive transcriptional state (such as bromodomain or p300/CBP inhibitors) downregulated PD-L1, while EDs favoring a chromatin-active state (i.e., histone deacetylase inhibitors) increased PD-L1 expression. miRNAs can regulate PD-L1 at a post-transcriptional level. miR-195/miR-16 were negatively associated with PD-L1 expression and positively correlated to longer biochemical recurrence-free survival; they also enhanced the radiotherapy efficacy in PC cell lines. miR-197 and miR-200a-c positively correlated to PD-L1 mRNA levels and inversely correlated to the methylation of PD-L1 promoter in a large series. miR-570, miR-34a and miR-513 may also be involved in epigenetic regulation.

What Do We Have to Know about PD-L1 Expression in Prostate Cancer? A Systematic Literature Review. Part 3: PD-L1, Intracellular Signaling Pathways and Tumor Microenvironment

The tumor microenvironment (TME) includes immune (T, B, NK, dendritic), stromal, mesenchymal, endothelial, adipocytic cells, extracellular matrix, and cytokines/chemokines/soluble factors regulating various intracellular signaling pathways (ISP) in tumor cells. TME influences the survival/progression of prostate cancer (PC), enabling tumor cell immune-evasion also through the activation of the PD-1/PD-L1 axis. We have performed a systematic literature review according to the PRISMA guidelines, to investigate how the PD-1/PD-L1 pathway is influenced by TME and ISPs. Tumor immune-escape mechanisms include suppression/exhaustion of tumor infiltrating cytotoxic T lymphocytes, inhibition of tumor suppressive NK cells, increase in immune-suppressive immune cells (regulatory T, M2 macrophagic, myeloid-derived suppressor, dendritic, stromal, and adipocytic cells). IFN-γ (the most investigated factor), TGF-β, TNF-α, IL-6, IL-17, IL-15, IL-27, complement factor C5a, and other soluble molecules secreted by TME components (and sometimes increased in patients' serum), as well as and hypoxia, influenced the regulation of PD-L1. Experimental studies using human and mouse PC cell lines (derived from either androgen-sensitive or androgen-resistant tumors) revealed that the intracellular ERK/MEK, Akt-mTOR, NF-kB, WNT and JAK/STAT pathways were involved in PD-L1 upregulation in PC. Blocking the PD-1/PD-L1 signaling by using immunotherapy drugs can prevent tumor immune-escape, increasing the anti-tumor activity of immune cells.

What Do We Have to Know about PD-L1 Expression in Prostate Cancer? A Systematic Literature Review. Part 1: Focus on Immunohistochemical Results with Discussion of Pre-Analytical and Interpretation Variables

Immunotherapy targeting the PD-1-PD-L1 axis yielded good results in treating different immunologically ''hot'' tumors. A phase II study revealed good therapeutic activity of pembrolizumab in selected prostatic carcinoma (PC)-patients. We performed a systematic literature review (PRISMA guidelines), which analyzes the immunohistochemical expression of PD-L1 in human PC samples and highlights the pre-analytical and interpretation variables. Interestingly, 29% acinar PCs, 7% ductal PCs, and 46% neuroendocrine carcinomas/tumors were PD-L1+ on immunohistochemistry. Different scoring methods or cut-off criteria were applied on variable specimen-types, evaluating tumors showing different clinic-pathologic features. The positivity rate of different PD-L1 antibody clones in tumor cells ranged from 3% (SP142) to 50% (ABM4E54), excluding the single case tested for RM-320. The most tested clone was E1L3N, followed by 22C3 (most used for pembrolizumab eligibility), SP263, SP142, and 28-8, which gave the positivity rates of 35%, 11-41% (depending on different scoring systems), 6%, 3%, and 15%, respectively. Other clones were tested in <200 cases. The PD-L1 positivity rate was usually higher in tumors than benign tissues. It was higher in non-tissue microarray specimens (41-50% vs. 15%), as PC cells frequently showed heterogenous or focal PD-L1-staining. PD-L1 was expressed by immune or stromal cells in 12% and 69% cases, respectively. Tumor heterogeneity, inter-institutional preanalytics, and inter-observer interpretation variability may account for result biases.

What Do We Have to Know about PD-L1 Expression in Prostate Cancer? A Systematic Literature Review. Part 4: Experimental Treatments in Pre-Clinical Studies (Cell Lines and Mouse Models)

In prostate cancer (PC), the PD-1/PD-L1 axis regulates various signaling pathways and it is influenced by extracellular factors. Pre-clinical experimental studies investigating the effects of various treatments (alone or combined) may discover how to overcome the immunotherapy-resistance in PC-patients. We performed a systematic literature review (PRISMA guidelines) to delineate the landscape of pre-clinical studies (including cell lines and mouse models) that tested treatments with effects on PD-L1 signaling in PC. NF-kB, MEK, JAK, or STAT inhibitors on human/mouse, primary/metastatic PC-cell lines variably down-modulated PD-L1-expression, reducing chemoresistance and tumor cell migration. If PC-cells were co-cultured with NK, CD8+ T-cells or CAR-T cells, the immune cell cytotoxicity increased when PD-L1 was downregulated (opposite effects for PD-L1 upregulation). In mouse models, radiotherapy, CDK4/6-inhibitors, and RB deletion induced PD-L1-upregulation, causing PC-immune-evasion. Epigenetic drugs may reduce PD-L1 expression. In some PC experimental models, blocking only the PD-1/PD-L1 pathway had limited efficacy in reducing the tumor growth. Anti-tumor effects could be increased by combining the PD-1/PD-L1 blockade with other approaches (inhibitors of tyrosine kinase, PI3K/mTOR or JAK/STAT3 pathways, p300/CBP; anti-RANKL and/or anti-CTLA-4 antibodies; cytokines; nitroxoline; DNA/cell vaccines; radiotherapy/Radium-223).

What Do We Have to Know about PD-L1 Expression in Prostate Cancer? A Systematic Literature Review. Part 2: Clinic-Pathologic Correlations

Many studies have investigated the potential prognostic and predictive role of PD-L1 in prostatic carcinoma (PC). We performed a systematic literature review (PRISMA guidelines) to critically evaluate human tissue-based studies (immunohistochemistry, molecular analysis, etc.), experimental research (cell lines, mouse models), and clinical trials. Despite some controversial results and study limitations, PD-L1 expression by tumor cells may be related to clinic-pathologic features of adverse outcome, including advanced tumor stage (high pT, presence of lymph node, and distant metastases), positivity of surgical margins, high Grade Group, and castration resistance. Different PD-L1 positivity rates may be observed in matched primary PCs and various metastatic sites of the same patients. Over-fixation, type/duration of decalcification, and PD-L1 antibody clone may influence the immunohistochemical analysis of PD-L1 on bone metastases. PD-L1 seemed expressed more frequently by castration-resistant PCs (49%) as compared to hormone-sensitive PCs (17%). Some series found that PD-L1 positivity was associated with decreased time to castration resistance. Treatment with ipilimumab, cyclophosphamide/GVAX/degarelix, or degarelix alone may increase PD-L1 expression. Correlation of PD-L1 positivity with overall survival and outcomes related to tumor recurrence were rarely investigated; the few analyzed series produced conflicting results and sometimes showed limitations. Further studies are required. The testing and scoring of PD-L1 should be standardized.

Establishment of a tumor immune microenvironment-based molecular classification system of breast cancer for immunotherapy

Antitumor immunotherapy can enable promising and durable responses following their clinical application. However, heterogeneity in the tumor immune microenvironment leads to differences in the individual response rates. In this study, we identified novel immune-related molecular subclasses of breast cancer using a non-negative matrix factorization analysis. We enrolled 4184 patients with breast cancer, including 1104 patients from The Cancer Genome Atlas as a training cohort and 3080 patients from another four independent datasets as validation cohorts. In the training cohort, 36.9% of patients who exhibited significantly higher immunocyte infiltration and enrichment of immune response-associated signatures were categorized into an immune class, which was confirmed by probing the expression of immunocyte markers (CD3, CD19, and CD163). Within the immune class, 53.3% of patients belonged to an immune-suppressed subclass, characterized by the activation of stroma-related signatures and immune-suppressive cells. The remaining patients in the immune class were allocated to an immune-activated subclass. The interferon-γ and granzyme B levels were higher in the immune-activated subclass, whereas the transforming growth factor-β1 and programmed cell death-1 (PD-1) levels were higher in the immune-suppressed subclass. The established molecular classification system was recapitulated in validation cohorts. The immune-activated subclass was predicted to have a better response to anti-PD-1 immunotherapy. The immune-related subclasses were associated with differences in copy number alterations, tumor mutation burden, neoantigens, tumor-infiltrating lymphocyte enrichment, PD-1/programmed death-ligand 1 expression, mutation landscape, and various infiltration immunocytes. Overall, we established a novel immune-related molecular classification of breast cancer, which may be used to select candidate patients for immunotherapy.

Extracellular Matrix-Associated Pathways Promote the Progression of Gastric Cancer by Impacting the Dendritic Cell Axis

BACKGROUND

Gastric cancer (GC) is the third most frequent malignant tumour in the Chinese population, let alone the whole world. Recently, most prognostic models have only focused on the levels of several genes, miRNAs, lncRNAs, gene mutations, or DNA methylation; however, the activation status of biological pathways is more stable and can reflect the comprehensive inner conditions of tumours.

METHODS

We collected samples from the Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) cohort and GSE62254 cohort, with a total of 594 patients. We employed GSEA to first compare the diverse activated signalling pathways between dead GC patients and living patients. The least absolute shrinkage and selection operator (LASSO) regression analysis was subsequently performed by the "glmnet" package to generate a prognostic signature.

RESULTS

We extracted a total of 218 genes from the KEGG Focal Adhesion and KEGG ECM Receptor Interaction pathways, which showed significant activation in dead GC patients in two enrolled cohorts, for subsequent LASSO analysis. In the TCGA-STAD cohort, patients in the high-risk group faced a significantly poorer prognosis than those in the low-risk group (P < 0.001, HR: 4.62, 95% CI: 3.447-6.183), with an AUC of 0.694. In the GSE62254 cohort, the HR value was 4.94 (95% CI: 3.413-7.165), and the AUC value was as high as 0.834. A high-risk score and poor prognosis correlated with infiltrated dendritic cells, and the receptor of IFN-α was also positively linked with the risk score, as well as poor prognosis. GC patients with high-risk scores were more likely to respond to CTLA4 treatment but not PD1 treatment.

CONCLUSION

Taken together, we established and verified an extracellular matrix prognostic model of gastric cancer patients. The model can be used to evaluate the risk of death of GC patients, as well as the response to anti-CTLA4 immunotherapy.

A Novel Tool for the Risk Assessment and Personalized Chemo-/Immunotherapy Response Prediction of Adenocarcinoma and Squamous Cell Carcinoma Lung Cancer

Background

The prevalence and cancer-specific death rate of lung cancer (LC) have risen in recent decades. A universally applicable prognostic signature for both adenocarcinoma LC (LUAD) and squamous cell carcinoma LC (LUSC) is still lacking.

Methods

A total of 453 patients from The Cancer Genome Atlas (TCGA)-LUAD cohort and 452 patients from TCGA-LUSC cohort were enrolled, and a prognostic model was constructed using least absolute shrinkage and selection operator (LASSO) regression analysis based on the consensus prognostic genes in both cohorts. The newly defined pan-lung cancer risk count (PLCRC) of each patient was calculated via the summation formula.

Results

A total of 23 genes were selected for the calculation of the PLCRC. The PLCRC showed a moderate prognostic value in the entire (p < 0.001, HR: 2.75, AUC: 0.643), LUAD (p < 0.001, HR: 2.51, AUC: 0.636) and LUSC (p < 0.001, HR: 2.89, AUC: 0.656) cohorts. The PLCRC was an independent prognostic factor after adjusting the clinical features. The PLCRC was also effective in nine external validation cohorts and in patients with different clinical features. Activation of extracellular matrix pathways and infiltration of immunocytes promoted the tumorigenesis and development of both LUAD and LUSC. We generated a universally applicable prognostic signature, the PLCRC, which could dichotomize patients with significantly different clinical outcomes and guide the clinical treatment of LC patients. Chemotherapy is more suitable for patients with a low PLCRC, while anti-cytotoxic T-lymphocyte-associated protein 4 immunotherapy is more suitable for patients with a high PLCRC.

Conclusion

We established and validated a newly defined prognostic signature, the PLCRC, for both LUAD and LUSC patients and provided clinical strategies for patients from different risk subgroups.

Early B-cell factors involve in the tumorigenesis and predict the overall survival of gastric cancer

Gastric cancer (GC) is a heavy health burden around the world, which is the fifth most frequent tumor and leads to the third most common cancer-related deaths. It is urgent to identify prognostic markers as the guideline for personalized treatment and follow-up. We accessed the prognostic value of Early B-cell factors (EBFs) in GC. A total of 415 GC tissues and 34 normal tissues from The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) cohort, 616 external patients from GSE15459, GSE22377, GSE51105, GSE62245 were enrolled for analysis. Univariate and multivariate Cox regression analyses were employed to evaluate the sole and integrative prognostic value of EBFs, respectively. Genetic alterations, DNA methylation of EBFs were also evaluated, as well as the involved signaling pathways. We revealed that increased EBFs associated with the poor prognosis of GC patients, the prognostic model was established in TCGA-STAD cohort, and validated in Gene Expression Omnibus (GEO) cohorts, with effectiveness in both HER2 positive and negative patients. DNA methylation was involved in the impact on prognosis. Cell cycle, immune-associated, and MAPK pathways were influenced by EBFs. Anti-CTLA4 immunotherapy is more suitable for EBFs determining high-risk groups, but not anti-PD-1/PD-L1 therapy. 5-Fluorouracil, methotrexate, vorinostat are suitable to inhibit the function of EBFs. Our new findings provide novel insight into the prediction of prognosis and clinical treatment of GC patients based on EBFs.

Multi-Omics Profiling Identifies Risk Hypoxia-Related Signatures for Ovarian Cancer Prognosis

Background

Ovarian cancer (OC) has the highest mortality rate among gynecologic malignancy. Hypoxia is a driver of the malignant progression in OC, which results in poor prognosis. We herein aimed to develop a validated model that was based on the hypoxia genes to systematically evaluate its prognosis in tumor immune microenvironment (TIM).

Results

We identified 395 hypoxia-immune genes using weighted gene co-expression network analysis (WGCNA). We then established a nine hypoxia-related genes risk model using least absolute shrinkage and selection operator (LASSO) Cox regression, which efficiently distinguished high-risk patients from low-risk ones. We found that high-risk patients were significantly related to poor prognosis. The high-risk group showed unique immunosuppressive microenvironment, lower antigen presentation, and higher levels of inhibitory cytokines. There were also significant differences in somatic copy number alterations (SCNAs) and mutations between the high- and low-risk groups, indicating immune escape in the high-risk group. Tumor immune dysfunction and exclusion (TIDE) and SubMap algorithms showed that low-risk patients are significantly responsive to programmed cell death protein-1 (PD-1) inhibitors.

Conclusions

In this study, we highlighted the clinical significance of hypoxia in OC and established a hypoxia-related model for predicting prognosis and providing potential immunotherapy strategies.

Cancer immunotherapy: A comprehensive appraisal of its modes of application

Conventional cancer treatments such as chemotherapy and radiation therapy have reached their therapeutic potential, leaving a gap for developing more effective cancer therapeutics. Cancer cells evade the immune system using various mechanisms of immune tolerance, underlying the potential impact of immunotherapy in the treatment of cancer. Immunotherapy includes several approaches such as activating the immune system in a cytokine-dependent manner, manipulating the feedback mechanisms involved in the immune response, enhancing the immune response via lymphocyte expansion and using cancer vaccines to elicit long-lasting, robust responses. These techniques can be used as monotherapies or combination therapies. The present review describes the immune-based mechanisms involved in tumor cell proliferation and maintenance and the rationale underlying various treatment methods. In addition, the present review provides insight into the potential of immunotherapy used alone or in combination with various types of therapeutics.