Tumor immune infiltration estimated from gene expression profiles predicts colorectal cancer relapse

Comprehensive Analysis and Verification of the Prognostic Significance of Cuproptosis-Related Genes in Colon Adenocarcinoma

Colon adenocarcinoma (COAD) is a frequently occurring and lethal cancer. Cuproptosis is an emerging type of cell death, and the underlying pathways involved in this process in COAD remain poorly understood. Transcriptomic and clinical data for COAD patients were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We investigated alterations in DNA and chromatin of cuproptosis-related genes (CRGs) in COAD. In order to identify predictive differentially expressed genes (DEGs) and various molecular subtypes, we used consensus cluster analysis. Through univariate, multivariate, and Lasso Cox regression analyses, four CRGs were identified. A risk prognostic model for cuproptosis characteristics was constructed based on four CRGs. This study also examined the association between the risk score and the tumor microenvironment (TME), the immune landscape, and drug sensitivity. We distinguished two unique molecular subtypes using consensus clustering analysis. We discovered that the clinical characteristics, prognosis, and TME cell infiltration characteristics of patients with multilayer CRG subtypes were all connected. The internal and external evaluations of the predicted accuracy of the prognostic model built using data derived from a cuproptosis risk score were completed at the same time. A nomogram and a clinical pathological analysis make it more useful in the field of medicine. A significant rise in immunosuppressive cells was observed in the high cuproptosis risk score group, with a correlation identified between the cuproptosis risk score and immune cell infiltration. Despite generally poor prognoses, the patients with a high cuproptosis risk but low tumor mutation burden (TMB), cancer stem cell (CSC) index, or microsatellite instability (MSI) may still benefit from immunotherapy. Furthermore, the cuproptosis risk score positively correlated with immune checkpoint gene expression. Analyzing the potential sensitivity to medications could aid in the development of clinical chemotherapy regimens and decision-making. CRGs are the subject of our in-depth study, which exposed an array of regulatory mechanisms impacting TME. In addition, we performed additional data mining into clinical features, prognosis effectiveness, and possible treatment medications. COAD's molecular pathways will be better understood, leading to more precise treatment options.

Germline genetic regulation of the colorectal tumor immune microenvironment

OBJECTIVE

To evaluate the contribution of germline genetics to regulating the briskness and diversity of T cell responses in CRC, we conducted a genome-wide association study to examine the associations between germline genetic variation and quantitative measures of T cell landscapes in 2,876 colorectal tumors from participants in the Molecular Epidemiology of Colorectal Cancer Study (MECC).

METHODS

Germline DNA samples were genotyped and imputed using genome-wide arrays. Tumor DNA samples were extracted from paraffin blocks, and T cell receptor clonality and abundance were quantified by immunoSEQ (Adaptive Biotechnologies, Seattle, WA). Tumor infiltrating lymphocytes per high powered field (TILs/hpf) were scored by a gastrointestinal pathologist. Regression models were used to evaluate the associations between each variant and the three T-cell features, adjusting for sex, age, genotyping platform, and global ancestry. Three independent datasets were used for replication.

RESULTS

We identified a SNP (rs4918567) near RBM20 associated with clonality at a genome-wide significant threshold of 5 × 10- 8, with a consistent direction of association in both discovery and replication datasets. Expression quantitative trait (eQTL) analyses and in silico functional annotation for these loci provided insights into potential functional roles, including a statistically significant eQTL between the T allele at rs4918567 and higher expression of ADRA2A (P = 0.012) in healthy colon mucosa.

CONCLUSIONS

Our study suggests that germline genetic variation is associated with the quantity and diversity of adaptive immune responses in CRC. Further studies are warranted to replicate these findings in additional samples and to investigate functional genomic mechanisms.

Trial watch: beta-blockers in cancer therapy

Compelling evidence supports the hypothesis that stress negatively impacts cancer development and prognosis. Irrespective of its physical, biological or psychological source, stress triggers a physiological response that is mediated by the hypothalamic-pituitary-adrenal axis and the sympathetic adrenal medullary axis. The resulting release of glucocorticoids and catecholamines into the systemic circulation leads to neuroendocrine and metabolic adaptations that can affect immune homeostasis and immunosurveillance, thus impairing the detection and eradication of malignant cells. Moreover, catecholamines directly act on β-adrenoreceptors present on tumor cells, thereby stimulating survival, proliferation, and migration of nascent neoplasms. Numerous preclinical studies have shown that blocking adrenergic receptors slows tumor growth, suggesting potential clinical benefits of using β-blockers in cancer therapy. Much of these positive effects of β-blockade are mediated by improved immunosurveillance. The present trial watch summarizes current knowledge from preclinical and clinical studies investigating the anticancer effects of β-blockers either as standalone agents or in combination with conventional antineoplastic treatments or immunotherapy.

Ibero-American Consensus Review and Incorporation of New Biomarkers for Clinical Practice in Colorectal Cancer

Advances in genomic technologies have significantly improved the management of colorectal cancer (CRC). Several biomarkers have been identified in CRC that enable personalization in the use of biologic agents that have shown to enhance the clinical outcomes of patients. However, technologies used for their determination generate massive amounts of information that can be difficult for the clinician to interpret and use adequately. Through several discussion meetings, a group of oncology experts from Spain and several Latin American countries reviewed the latest literature to provide practical recommendations on the determination of biomarkers in CRC based on their clinical experience. The article also describes the importance of looking for additional prognostic biomarkers and the use of histopathology to establish an adequate molecular classification. Present and future of immunotherapy biomarkers in CRC patients are also discussed, together with several techniques for marker determination, including liquid biopsy, next-generation sequencing (NGS), polymerase chain reaction (PCR), and fecal immunohistochemical tests. Finally, the role of Molecular Tumor Boards in the diagnosis and treatment of CRC is described. All of this information will allow us to highlight the importance of biomarker determination in CRC.

Identification of a Twelve-microRNA Signature with Prognostic Value in Stage II Microsatellite Stable Colon Cancer

We aimed to identify and validate a set of miRNAs that could serve as a prognostic signature useful to determine the recurrence risk for patients with COAD. Small RNAs from tumors of 100 stage II, untreated, MSS colon cancer patients were sequenced for the discovery step. For this purpose, we built an miRNA score using an elastic net Cox regression model based on the disease-free survival status. Patients were grouped into high or low recurrence risk categories based on the median value of the score. We then validated these results in an independent sample of stage II microsatellite stable tumor tissues, with a hazard ratio of 3.24, (CI_95% = 1.05-10.0) and a 10-year area under the receiver operating characteristic curve of 0.67. Functional analysis of the miRNAs present in the signature identified key pathways in cancer progression. In conclusion, the proposed signature of 12 miRNAs can contribute to improving the prediction of disease relapse in patients with stage II MSS colorectal cancer, and might be useful in deciding which patients may benefit from adjuvant chemotherapy.

ORC6, a novel prognostic biomarker, correlates with T regulatory cell infiltration in prostate adenocarcinoma: a pan-cancer analysis

BACKGROUND

The origin recognition complex (ORC), a six-subunit DNA-binding complex, participates in DNA replication in cancer cells. Specifically in prostate cancers, ORC participates the androgen receptor (AR) regulated genomic amplification and tumor proliferation throughout the entire cell cycle. Of note, ORC6, the smallest subunit of ORC, has been reported to be dysregulated in some types of cancers (including prostate cancer), however, its prognostic and immunological significances remain yet to be elucidated.

METHODS

In the current study, we comprehensively investigated the potential prognostic and immunological role of ORC6 in 33 human tumors using multiple databases, such as TCGA, Genotype-Tissue Expression, CCLE, UCSC Xena, cBioPortal, Human Protein Atlas, GeneCards, STRING, MSigDB, TISIDB, and TIMER2 databases.

RESULTS

ORC6 expression was significantly upregulated in 29 types of cancers compared to the corresponding normal adjacent tissues. ORC6 overexpression correlated with higher stage and worse prognostic outcomes in most cancer types analyzed. Additionally, ORC6 was involved in the cell cycle pathway, DNA replication, and mismatch repair pathways in most tumor types. A negative correlation was observed between the tumor endothelial cell infiltration and ORC6 expression in almost all tumors, whereas the immune infiltration of T regulatory cell was noted to be statistically positively correlated with the expression of ORC6 in prostate cancer tissues. Furthermore, in most tumor types, immunosuppression-related genes, especially TGFBR1 and PD-L1 (CD274), exhibited a specific correlation with the expression of ORC6.

CONCLUSIONS

This comprehensive pan-cancer analysis revealed that ORC6 expression serves as a prognostic biomarker and that ORC6 is involved in the regulation of various biological pathways, the tumor microenvironment, and the immunosuppression status in several human cancers, suggesting its potential diagnostic, prognostic, and therapeutic value in pan-cancer, especially in prostate adenocarcinoma.

A five ferroptosis-related genes risk score for prognostic prediction of osteosarcoma

BACKGROUND

Osteosarcoma (OS) is the most common bone cancer in adolescents, and has a high propensity to metastasize. Ferroptosis is a unique modality of cell death, driving the metastasis of cancer cells. Identifying ferroptosis-related genes (FRGs) as prognostic factors will be critical to predict the outcomes of OS. This study aimed to explore the prognostic value of FRGs in OS and build a prognostic model to indirectly improve OS patients' outcomes.

METHODS

OS data were downloaded from the TARGET database and 2 Gene Expression Omnibus datasets. Univariate Cox regression was conducted to assess FRGs. A risk score model basing on 5 FRGs was constructed via LASSO-Cox regression. Multivariate Cox regression analysis was used to determine the independent prognostic factors. The Nomogram model was built using independent prognostic factors. The relationship between the risk score and the immune cell infiltration was estimated by CIBERSORT, and the correlation between the risk score and immune checkpoints was also analyzed.

RESULTS

Based on the prognosis-related FRGs, we built a regression model: Risk score = (-0.01382853 × ACSL4) - (0.05371778 × HMOX1) - (0.02434655 × GPX4) - (0.16432810 × PRNP) - (0.15567120 × ATG7). OS patients with high risk score tended to suffer from poor prognosis, validated in 2 Gene Expression Omnibus datasets. The Nomogram model showed the combination of the risk score and the tumour-node-metastasis stage improved predictive effectiveness. The risk score was also related to immune cell infiltration and immune checkpoint expression.

CONCLUSION

The risk score model based on 5 FRGs was a reliable prognostic predictive indicator for OS patients.

Adoptive NK Cell Transfer as a Treatment in Colorectal Cancer Patients: Analyses of Tumour Cell Determinants Correlating With Efficacy In Vitro and In Vivo

Background

Colorectal cancer (CRC) is a heterogeneous disease with variable mutational profile and tumour microenvironment composition that influence tumour progression and response to treatment. While chemoresistant and poorly immunogenic CRC remains a challenge, the development of new strategies guided by biomarkers could help stratify and treat patients. Allogeneic NK cell transfer emerges as an alternative against chemoresistant and poorly immunogenic CRC.

Methods

NK cell-related immunological markers were analysed by transcriptomics and immunohistochemistry in human CRC samples and correlated with tumour progression and overall survival. The anti-tumour ability of expanded allogeneic NK cells using a protocol combining cytokines and feeder cells was analysed in vitro and in vivo and correlated with CRC mutational status and the expression of ligands for immune checkpoint (IC) receptors regulating NK cell activity.

Results

HLA-I downmodulation and NK cell infiltration correlated with better overall survival in patients with a low-stage (II) microsatellite instability-high (MSI-H) CRC, suggesting a role of HLA-I as a prognosis biomarker and a potential benefit of NK cell immunotherapy. Activated allogeneic NK cells were able to eliminate CRC cultures without PD-1 and TIM-3 restriction but were affected by HLA-I expression. In vivo experiments confirmed the efficacy of the therapy against both HLA⁺ and HLA⁻ CRC cell lines. Concomitant administration of pembrolizumab failed to improve tumour control.

Conclusions

Our results reveal an immunological profile of CRC tumours in which immunogenicity (MSI-H) and immune evasion mechanisms (HLA downmodulation) favour NK cell immunosurveillance at early disease stages. Accordingly, we have shown that allogeneic NK cell therapy can target tumours expressing mutations conferring poor prognosis regardless of the expression of T cell-related inhibitory IC ligands. Overall, this study provides a rationale for a new potential basis for CRC stratification and NK cell-based therapy.

Molecular characterization of extrahepatic cholangiocarcinoma: perihilar and distal tumors display divergent genomic and transcriptomic profiles

BACKGROUND

Extrahepatic cholangiocarcinoma (ECC) is classified into two subtypes based on anatomic origin: distal extrahepatic (DECC) and perihilar (PHCC) cholangiocarcinoma. This study aimed to shed light on its genomic and transcriptomic profiles.

RESEARCH DESIGN AND METHODS

The genomic alterations of 99 ECC (47 PHCC and 52 DECC) were investigated by next-generation sequencing of 96 genes. A subgroup of cases, representative of each subtype, was further investigated using transcriptomic analysis. Bioinformatics tools were applied for clustering and pathway analysis and defining the immune composition of the tumor microenvironment.

RESULTS

PHCC had more frequent KRAS mutations (p = 0.0047), whereas TP53 mutations were more common in DECC (p = 0.006). Potentially actionable alterations included high-tumor mutational burden and/or microsatellite instability (7.1%), PI3KCA mutations (8.1%), and MYC (10.1%) and ERBB2 amplification (5.1%). The transcriptomic profiles showed the presence of three distinct clusters, which followed the anatomic origin and differed in immune microenvironment. DECC appeared to contain two distinct tumor subgroups, one enriched for druggable alterations and one lacking actionable opportunities.

CONCLUSIONS

This study provides new insights into the molecular landscape and the actionable alterations of ECC. Our findings represent a step toward improved ECC molecular taxonomy and therapeutic strategies for precision oncology.

Identification of Cancer Hub Gene Signatures Associated with Immune-Suppressive Tumor Microenvironment and Ovatodiolide as a Potential Cancer Immunotherapeutic Agent

Despite the significant advancement in therapeutic strategies, breast, colorectal, gastric, lung, liver, and prostate cancers remain the most prevalent cancers in terms of incidence and mortality worldwide. The major causes ascribed to these burdens are lack of early diagnosis, high metastatic tendency, and drug resistance. Therefore, exploring reliable early diagnostic and prognostic biomarkers universal to most cancer types is a clinical emergency. Consequently, in the present study, the differentially expressed genes (DEGs) from the publicly available microarray datasets of six cancer types (liver, lung colorectal, gastric, prostate, and breast cancers), termed hub cancers, were analyzed to identify the universal DEGs, termed hub genes. Gene set enrichment analysis (GSEA) and KEGG mapping of the hub genes suggested their crucial involvement in the tumorigenic properties, including distant metastases, treatment failure, and survival prognosis. Notably, our results suggested high frequencies of genetic and epigenetic alterations of the DEGs in association with tumor staging, immune evasion, poor prognosis, and therapy resistance. Translationally, we intended to identify a drug candidate with the potential for targeting the hub genes. Using a molecular docking platform, we estimated that ovatodiolide, a bioactive anti-cancer phytochemical, has high binding affinities to the binding pockets of the hub genes. Collectively, our results suggested that the hub genes were associated with establishing an immune-suppressive tumor microenvironment favorable for disease progression and promising biomarkers for the early diagnosis and prognosis in multiple cancer types and could serve as potential druggable targets for ovatodiolide.

Challenges and Opportunities in the Statistical Analysis of Multiplex Immunofluorescence Data

Simple Summary

Immune modulation is considered a hallmark of cancer initiation and progression, and has offered promising opportunities for therapeutic manipulation. Multiplex immunofluorescence (mIF) technology has enabled the tumor immune microenvironment (TIME) to be studied at an increased scale, in terms of both the number of markers and the number of samples. Another benefit of mIF technology is the ability to measure not only the abundance but also the spatial location of multiple cells types within a tissue sample simultaneously, allowing for assessment of the co-localization of different types of immune markers. Thus, the use of mIF technologies have enable researchers to characterize patient, clinical, and tumor characteristics in the hope of identifying patients whom might benefit from immunotherapy treatments. In this review we outline some of the challenges and opportunities in the statistical analyses of mIF data to study the TIME.

Abstract

Immune modulation is considered a hallmark of cancer initiation and progression. The recent development of immunotherapies has ushered in a new era of cancer treatment. These therapeutics have led to revolutionary breakthroughs; however, the efficacy of immunotherapy has been modest and is often restricted to a subset of patients. Hence, identification of which cancer patients will benefit from immunotherapy is essential. Multiplex immunofluorescence (mIF) microscopy allows for the assessment and visualization of the tumor immune microenvironment (TIME). The data output following image and machine learning analyses for cell segmenting and phenotyping consists of the following information for each tumor sample: the number of positive cells for each marker and phenotype(s) of interest, number of total cells, percent of positive cells for each marker, and spatial locations for all measured cells. There are many challenges in the analysis of mIF data, including many tissue samples with zero positive cells or “zero-inflated” data, repeated measurements from multiple TMA cores or tissue slides per subject, and spatial analyses to determine the level of clustering and co-localization between the cell types in the TIME. In this review paper, we will discuss the challenges in the statistical analysis of mIF data and opportunities for further research.