The immune score as a new possible approach for the classification of cancer

Spatial profiling of ovarian clear cell carcinoma reveals immune-hot features

Ovarian clear cell carcinoma (OCCC) has a high incidence in Asia, with frequent occurrence at an early stage, but without sufficient data on molecular stratification for high-risk patients. Recently, immune-hot features have been proposed as indicators of poor prognosis in early stage OCCC. Specific patterns of intratumoral heterogeneity associated with immune-hot features must be defined. NanoString Digital Spatial Profiling technology was used to decipher the spatial distribution of the 18-plex protein panel. ROIs were collected based on the reference hematoxylin and eosin (H&E)-stained morphology. Areas of illumination (AOIs) were defined according to the ROI segmentation using the fluorescence signals of the visualization markers pan-cytokeratin (PanCK), CD45, or DNA. Unsupervised hierarchical clustering of 595 AOIs from 407 ROIs showed that the PanCK segments expressed different combinations of immune markers, suggestive of immune mimicry. Three immune-hot clusters were identified: granzyme B high (GZMB), immune signal high (IH), and immune-like cells (IL); two immune-cold clusters were identified: fibronectin high (FN) and immune checkpoint high cells (IC). In tumor samples at FIGO stage IC1/2 experiencing recurrence, there was an increased occurrence of PanCK+ AOIs with IH and IL groups in the papillary morphology surrounded by macrophage lineage tumor-infiltrating immune cells (TIIs). In contrast, for tumor samples at FIGO stage IC3/II with recurrence, PanCK + AOIs were prevalent in the FN group, particularly those with tubulocystic morphology surrounded by lymphoid lineage non-TIIs. Our work on the spatial profiling of early stage OCCC tumors revealed that the immune mimicry of tumor cells, presence of TIIs, and morphological patterns were associated with recurrence, which switched during tumor progression.

Honey and Aloe vera Solution Increases Survival and Modulates the Tumor Size In Vivo

SCOPE

The combination of honey and Aloe vera is used as a popular complementary treatment for cancer due to their nutraceutical properties. This study aims to investigate the anticancer activity of honey and A. vera solution and its ethanolic extraction through in vitro and in vivo approaches.

METHODS AND RESULTS

After comparisons of honey and A. vera (HA) solution and its ethanolic extraction solution (E) samples by UPLC-ESI-MS/MS, the study verifies HA-treatment affected only Walker tumor cells viability at the highest dose, and E-treatment has a more cytotoxic/antiproliferative effect in MCF-7 and Walker-256 cells. The in vivo results show a higher survival rate in Walker-256 tumor-bearing rats (WHA), with higher NK cell infiltration in tumor tissue and a tendency in the WE group. These results are possible due to decreased mannose-based immunomodulatory polysaccharides and aloin-A contents in the ethanolic extract solution compared to HA solution.

CONCLUSION

The current study provides compelling evidence of selectively cytotoxic against tumor cells under honey and A. vera solution and ethanolic extraction solution treatment, due to the cytotoxic/antiproliferative compounds. Therefore, the use of honey and A. vera solution could be used as a basis for coadjuvant therapy in cancer treatment.

Mucosal microbiota characterization in gastric cancer identifies immune-activated-related transcripts relevant gastric microbiome signatures

Tumor microenvironment (TME) immune cells and gastric mucosal microbiome constitute two vital elements of tumor tissue. Increasing evidence has elucidated their clinicopathological significance in predicting outcomes and therapeutic efficacy. However, comprehensive characterization of immune cell-associated microbiome signatures in the TME is still in the early stages of development. Here, we characterized the gastric mucosa microbiome and its associations with immune-activated related transcripts (IATs) in 170 GC tumor tissues and matched non-tumor tissues using 16s rRNA gene sequencing and quantitative reverse transcription-PCR. Microbial diversity and richness were significantly higher in GC tumor tissues than in non-tumor tissues. Differences in microbial composition between the groups were evident, with Firmicutes, Proteobacteria, Bacteroidota, Campilobacterota, Actinobacteria, Fusobacteriota, Verrucomicrobiota, Acidobacteriota, and Cyanobacteria being the dominant phyla in the gastric mucosal microbiota. Microbial interaction network analysis revealed distinctive centralities of oral bacteria (such as Fusobacterium, Porphyromonas, Prevotella, etc.) in both tumor and normal mucosae networks, suggesting their significant influence on GC microbial ecology. Furthermore, we analyzed the expression of IATs (CXCL9, CXCL10, GZMA, GZMB, PRF1, CD8A, IFNG, TBX2, and TNF) and characterized IAT-relevant gastric microbiome signatures in GC patients. Our results showed that the expression of CXCL9, CXCL10, GZMA, GZMB, PRF1 and IFNG was significantly higher in tumor tissues than in adjacent normal tissues in GC patients. Notably, high expression of IATs in tumor tissues was associated with improved survival in GC patients and could serve as a powerful predictor for disease-free survival. Additionally, analysis of IAT levels and mucosal microbiota diversity revealed a correlation between higher IAT expression and increased microbiota richness and evenness in the IATs high group, suggesting potential interactions between mucosal microbiota and tumor immunopathology. Spearman correlation analysis showed positive associations between IAT expression and specific mucosal bacterial species. Notably, Akkermansia muciniphila demonstrated potential involvement in modulating GZMB expression in the GC mucosal microenvironment. These findings underscore the importance of mucosal microbiota alterations in GC and suggest potential therapeutic targets focusing on modulating the tumor microbiota for improved clinical outcomes. The detailed characterization of these elements has profound implications for both treatment and survival prediction in GC. We observed that microbial diversity and richness were significantly higher in GC tumor tissues compared to non-tumor tissues. These differences highlight the unique microbial landscape of GC tumors and suggest that the microbiome could influence tumor development and progression. Importantly, our study demonstrated that high expression levels of IATs in GC tumor tissues were associated with improved patient survival. This suggests that IATs not only reflect immune activation but also serve as valuable biomarkers for predicting disease-free survival. The potential of IATs as predictive markers underscores their utility in guiding therapeutic strategies and personalizing treatment approaches. Moreover, the correlation between higher IAT expression and increased microbiota richness and evenness suggests that a diverse and balanced microbiome may enhance immune responses and contribute to better clinical outcomes. These findings highlight the critical need to consider mucosal microbiota alterations in GC management. Targeting the tumor microbiota could emerge as a promising therapeutic strategy, potentially leading to more effective treatments and improved patient outcomes. Understanding and modulating the microbiome's role in GC opens new avenues for innovative therapeutic interventions and personalized medicine.

Involvement of ICAM5 in Carcinostasis Effects on LUAD Based on the ROS1-Related Prognostic Model

Background

Lung cancer is the most common type of cancer in the world. In lung adenocarcinoma (LUAD), studies on receptor tyrosine kinase ROS proto-oncogene 1 (ROS1) have mainly focused on the oncogenic effects of its fusion mutations, whereas ROS1 has been reported to be aberrantly expressed in a variety of cancers and can extensively regulate the growth, survival, and proliferation of tumor cells through multiple signaling pathways. The comprehensive analysis of ROS1 expression has not been fully investigated regarding its predictive value for LUAD patients.

Methods

Gene expression profiles collected from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases were used to build and validate prognostic risk models. The association of ROS1 with overall survival and the immune landscape was obtained from the Tumor Immune Estimation Resource (TIMER) database. The following analyses were performed using the R package to determine the model's validity: pathway dysregulation analysis, gene set enrichment analysis, Gene Oncology analysis, immune invasion analysis, chemotherapy, radiotherapy, and immunotherapy sensitivity analysis. Finally, we conducted a pan-cancer analysis and performed in vitro experiments to explore the regulatory role of intercellular adhesion molecule 5 (ICAM5) in the progression of LUAD.

Results

We constructed a 17-gene model that categorized patients into two risk groups. The model had predictive accuracy for tumor prognosis and was specific for patients with high ROS1 expression. Comprehensive analysis showed that patients in the high-risk group were characterized by marked dysregulation of multiple pathways (eg, unfolded protein response), immune suppression of the tumor microenvironment, and poor benefit from immunotherapy and radiotherapy compared with patients in the low-risk group. PLX4720 may be a suitable treatment for the high-risk patient population. The ICAM5 gene has been demonstrated to inhibit the proliferation, cell cycle, invasion, and migration of LUAD cells.

Conclusion

We constructed a 17-gene prognostic risk model and found differences in immune-related cells, biological processes, and prognosis among patients in different risk groups based on the correlation between ROS1 and immunity. Personalized therapy may play an essential role in treatment. We further investigated the role of ICAM5 in inhibiting the malignant bioactivity of LUAD cells.

An overview of statistical methods for biomarkers relevant to early clinical development of cancer immunotherapies

Over the last decade, a new paradigm for cancer therapies has emerged which leverages the immune system to act against the tumor. The novel mechanism of action of these immunotherapies has also introduced new challenges to drug development. Biomarkers play a key role in several areas of early clinical development of immunotherapies including the demonstration of mechanism of action, dose finding and dose optimization, mitigation and prevention of adverse reactions, and patient enrichment and indication prioritization. We discuss statistical principles and methods for establishing the prognostic, predictive aspect of a (set of) biomarker and for linking the change in biomarkers to clinical efficacy in the context of early development studies. The methods discussed are meant to avoid bias and produce robust and reproducible conclusions. This review is targeted to drug developers and data scientists interested in the strategic usage and analysis of biomarkers in the context of immunotherapies.

Effect of trehalose on mortality and disease severity in ICU-admitted patients: Protocol for a triple-blind, randomized, placebo-controlled clinical trial

Background

Improvement in organ failure in intensive care unit (ICU) patients is accompanied by lower mortality rate. A disaccharide, trehalose is a candidate to improve organ failure and survival by autophagy induction and enhancing oxidative stress defense. The aim of this study is to assess the effectiveness of trehalose in improving clinical outcome and reducing mortality in ICU patients.

Methods

a triple-blind, randomized, placebo-controlled, two arm, parallel-group, superiority clinical trial will enroll 200 ICU-admitted patients at Imam Reza hospital, Mashhad, Iran. The patients will be randomly allocated to receive either a 100 ml solution of 15 % trehalose or normal saline intravenously. Primary outcomes include ICU mortality and 60-day mortality, while secondary outcomes focus on blood parameters on day 5 and length of hospital/ICU stay.

Conclusion

Trehalose has demonstrated beneficial effects in diverse patients; however, no study has evaluated its effect in all ICU-admitted patients. Consequently, this study provides an opportunity to investigate whether trehalose's anti-inflammatory effects, mediated by inducing autophagy and enhancing oxidative stress defense, can play a role in reducing mortality and improving clinical outcomes in the critically ill patients. If successful, trehalose could offer a potential therapeutic approach in the ICU setting.

Machine learning evaluation of immune infiltrate through digital tumour score allows prediction of survival outcome in a pooled analysis of three international stage III colon cancer cohorts

BACKGROUND

T-cell immune infiltrates are robust prognostic variables in localised colon cancer. Evaluation of prognosis using artificial intelligence is an emerging field. We evaluated whether machine learning analysis improved prediction of patient outcome in comparison with analysis of T cell infiltrate only or in association with clinical variables.

METHODS

We used data from two phase III clinical trials (Prodige-13 and PETACC08) and one retrospective Italian cohort (HARMONY). Cohorts were split into training (N = 692), internal validation (N = 297) and external validation (N = 672) sets. Tumour slides were stained with CD3mAb. CD3 Machine Learning (CD3ML) score was computed using graphical parameters within the tumour tiles obtained from CD3 slides. CD3 infiltrates in tumour core and invasive margin were automatically detected. Associations of CD3 infiltrates and CD3ML with 5-year Disease-Free Survival (DFS) were examined using univariate and multivariable survival models by Cox regression.

FINDINGS

CD3 density both in the invasive margin and the tumour core were significantly associated with DFS in the different sets. Similarly, CD3ML score was significantly associated with DFS in all sets. CD3 assessment did not provide added value on top of CD3ML assessment (Likelihood Ratio Test (LRT), p = 0.13). In contrast, CD3ML improved prediction of DFS when combined with a clinical risk stage (LRT, p = 0.001). Stratified by clinical risk score (High or Low), patients with low CD3ML score had better DFS.

INTERPRETATION

In all tested sets, machine learning analysis of tumour cells improved prediction of prognosis compared to clinical parameters. Adding tumour-infiltrating lymphocytes assessment did not improve prognostic determination.

FUNDING

This research received no external funding.

Pan-cancer prognosis, immune infiltration, and drug resistance characterization of lung squamous cell carcinoma tumor microenvironment-related genes

Background

The tumor microenvironment (TME) plays an important role in cancer development; however, its implications in lung squamous cell carcinoma (LUSC) and pan-cancer have been poorly understood.

Methods

In this study, The Cancer Genome Atlas (TCGA) and Estimation of Stromal and Immune cells in Malignant Tumor tissue using Expression Data (ESTIMATE) datasets were applied to identify differentially expressed genes. Additionally, online public databases were utilized for in-depth bioinformatics analysis of pan-cancer datasets to investigate the prognostic implications of TME-related genes further.

Results

Our study demonstrated a significant association between stromal scores, immune scores, and specific clinical characteristics in LUSC patients. C3AR1, CSF1R, CCL2, CCR1, and CD14 were identified as prognostic genes related to the TME. All TME-related prognostic genes demonstrated varying degrees of correlation with immune infiltration subtypes and tumor cell stemness. Moreover, our study revealed that TME-related prognostic genes, particularly C3AR1 and CCR1, might contribute to drug resistance in cancer cells.

Conclusions

The identified TME-related prognostic genes, particularly C3AR1 and CCR1, have potential implications for understanding and targeting drug resistance mechanisms in cancer cells.

Recent Advances in Thiourea Based Colorimetric and Fluorescent Chemosensors for Detection of Anions and Neutral Analytes: A Review

Thioureas and their derivatives are organosulfur compounds having excellent biological and non-biological applications. These compounds contain S- and N-, which are nucleophilic and allow for establishing inter-and intramolecular hydrogen bonding. These characteristics make thiourea moiety a very important chemosensor to detect various environmental pollutants. This article covers a broad range of thioureas and their derivatives that are used for highly sensitive, selective, and simple fluorimetric (turn-off and turn-on), and colorimetric chemosensors for the detection and determination of different types of anions, such as CN-, AcO-, F-, ClO- and citrate ions, etc., and neutral analytes such as ATP, DCP, and Amlodipine, etc., in biological, environmental, and agriculture samples. Further, the sensing performances of thioureas-based chemosensors have been compared and discussed, which could help the readers for the future design of organic fluorescent and colorimetric sensors to detect anions and neutral analytes. We hope this study will support the new thoughts to design highly efficient, selective, and sensitive chemosensors to detect different analytes in biological, environmental, and agricultural samples.

Exosomes as novel tools for renal cell carcinoma therapy, diagnosis, and prognosis

Background

Renal Cell Carcinoma (RCC) stands as a formidable challenge within the field of oncology, despite considerable research endeavors. The advanced stages of this malignancy present formidable barriers to effective treatment and management.

Objective

This review aims to explore the potential of exosomes in addressing the diagnostic and therapeutic challenges associated with RCC. Specifically, it investigates the role of exosomes as biomarkers and therapeutic vehicles in the context of RCC management.

Methods

For this review article, a comprehensive literature search was conducted using databases such as PubMed, employing relevant keywords to identify research articles pertinent to the objectives of the review. Initially, 200 articles were identified, which underwent screening to remove duplicates and assess relevance based on titles and abstracts, followed by a detailed examination of full texts. From the selected articles, relevant data were extracted and synthesized to address the review's objectives. The conclusions were drawn based on a thorough analysis of the findings. The quality was ensured through independent review and resolution of discrepancies among multiple reviewers.

Results

Exosomes demonstrate potential as diagnostic tools for early detection, prognosis, and treatment monitoring in RCC. Their ability to deliver various therapeutic agents, such as small interfering RNAs, lncRNAs, chemotherapeutic drugs, and immune-stimulating agents, allows for a personalized approach to RCC management. By leveraging exosome-based technologies, precision and efficacy in treatment strategies can be significantly enhanced.

Conclusion

Despite the promising advancements enabled by exosomes in the management of RCC, further research is necessary to refine exosome-based technologies and validate their efficacy, safety, and long-term benefits through rigorous clinical trials. Embracing exosomes as integral components of RCC diagnosis and treatment represents a significant step towards improving patient outcomes and addressing the persistent challenges posed by this malignancy in the field of oncology.

Dissecting the multifaceted roles of autophagy in cancer initiation, growth, and metastasis: from molecular mechanisms to therapeutic applications

Autophagy is a cytoplasmic defense mechanism that cells use to break and reprocess their intracellular components. This utilization of autophagy is regarded as a savior in nutrient-deficient and other stressful conditions. Hence, autophagy keeps contact with and responds to miscellaneous cellular tensions and diverse pathways of signal transductions, such as growth signaling and cellular death. Importantly, autophagy is regarded as an effective tumor suppressor because regular autophagic breakdown is essential for cellular maintenance and minimizing cellular damage. However, paradoxically, autophagy has also been observed to promote the events of malignancies. This review discussed the dual role of autophagy in cancer, emphasizing its influence on tumor survival and progression. Possessing such a dual contribution to the malignant establishment, the prevention of autophagy can potentially advocate for the advancement of malignant transformation. In contrast, for the context of the instituted tumor, the agents of preventing autophagy potently inhibit the advancement of the tumor. Key regulators, including calpain 1, mTORC1, and AMPK, modulate autophagy in response to nutritional conditions and stress. Oncogenic mutations like RAS and B-RAF underscore autophagy's pivotal role in cancer development. The review also delves into autophagy's context-dependent roles in tumorigenesis, metastasis, and the tumor microenvironment (TME). It also discusses the therapeutic effectiveness of autophagy for several cancers. The recent implication of autophagy in the control of both innate and antibody-mediated immune systems made it a center of attention to evaluating its role concerning tumor antigens and treatments of cancer.

Colorectal cancer: a comprehensive review of carcinogenesis, diagnosis, and novel strategies for classified treatments

Colorectal cancer is the third most common and the second deadliest cancer worldwide. To date, colorectal cancer becomes one of the most important challenges of the health system in many countries. Since the clinical symptoms of this cancer appear in the final stages of the disease and there is a significant golden time between the formation of polyps and the onset of cancer, early diagnosis can play a significant role in reducing mortality. Today, in addition to colonoscopy, minimally invasive methods such as liquid biopsy have received much attention. The treatment of this complex disease has been mostly based on traditional treatments including surgery, radiotherapy, and chemotherapy; the high mortality rate indicates a lack of success for current treatment methods. Moreover, disease recurrence is another problem of traditional treatments. Recently, new approaches such as targeted therapy, immunotherapy, and nanomedicine have opened new doors for cancer treatment, some of which have already entered the market, and many methods have shown promising results in clinical trials. The success of immunotherapy in the treatment of refractory disease, the introduction of these methods into neoadjuvant therapy, and the successful results in tumor shrinkage without surgery have made immunotherapy a tough competitor for conventional treatments. It seems that the combination of those methods with such targeted therapies will go through promising changes in the future of colorectal cancer treatment.

Prognostic value of neutrophil-to-lymphocyte ratio (NLR) and platelet-neutrophil (PN) index in locally advanced rectal cancer patients: a retrospective cohort study

Introduction

In locally advanced rectal cancers (LARC), tumour node metastasis (TNM) staging is far from optimal. The authors aimed to investigate the value of previously described circulating biomarkers as predictors of prognosis.

Methods

Retrospective analysis of 245 LARC patients diagnosed between January 2010 and December 2022, who underwent neoadjuvant chemoradiotherapy and surgery at two centres. A Cox regression and Kaplan-Meier analysis were performed.

Results

Post-treatment platelet-to-lymphocyte ratio (PLR) predicted pathological complete response. The neutrophil-to-lymphocyte ratio (NLR) in two timepoints of the treatment significantly predicted overall survival, whereas the platelet-neutrophil (PN) index significantly predicted disease-free survival. In pathological stage II, the PN index predicted patients with a higher risk of disease-free survival.

Conclusion

Blood parameters might allow the definition of subgroups of risk beyond TNM for the application of different therapeutic strategies.

Evaluation of immune infiltrate according to the HER2 status in colorectal cancer

BACKGROUND AND AIMS

In colorectal cancer (CRC), HER2 targeting is a promising treatment and immune infiltrate is an important area of research and strategy. Data regarding HER2 status and immune infiltrate are lacking. The aim of this study was to compare the immune infiltrate between HER2 amplified and non-amplified categories in proficient MisMatchRepair (pMMR)/microsatellite stable (MSS) CRC.

METHODS

HER2 immunohistochemistry (IHC) and fluorescence in situ hybridization were performed in a retrospective series of 654 CRC. Lymphocyte infiltrate was analysed by anti-CD3, CD8 and CD4 IHC and evaluated digitally using QuPath software.

RESULTS

Among the 654 CRC, we first observed a decreased CD3+ and CD8+ infiltrate between HER2 amplified (all IHC 3+ except one 2+) and non-amplified HER2 2+ IHC CRC (p = 0.059 and 0.072 respectively). A supplementary analysis of 258 pMMR/MSS CRC from the previous cohort, displaying all the IHC scores (0, 1+, 2+, 3+), showed a lower CD3+ infiltrate between HER2 amplified versus HER2 0 (p = 0.002), 1+ (p = 0.088) and non-amplified 2+ (p = 0.081) IHC cases.

CONCLUSIONS

Our original findings suggest that in pMMR/MSS CRC, the immune infiltrate is reduced in HER2 amplified versus other HER2 categories. These data might be useful for future strategies combining anti-HER2 treatments and immune checkpoint inhibitors and need to be confirmed in larger CRC cohorts.

Gastric cancer immune microenvironment score predicts neoadjuvant chemotherapy efficacy and prognosis

The efficacy of neoadjuvant chemotherapy (NACT) in patients with advanced gastric cancer (GC) varies greatly. Thus, we aimed to verify the predictive value of tumor-infiltrating immune cells (TIICs) on the treatment response to NACT and the prognosis of patients with advanced GC, and to explore the impact of NACT on the tumor immune microenvironment (TIME). Paired tumor tissues (pre- and post-NACT) from patients with advanced GC were collected for this study. TIICs were assessed using immunohistochemistry staining and analyzed using logistic regression to establish an immune microenvironment score for GC (ISGC score) and predict NACT efficacy. Kaplan-Meier curves were used to evaluate the survival outcome of patients. The results showed that TIME was dramatically heterogeneous between NACT response and nonresponse patients. In the validation cohort, the ISGC score demonstrated good predictive performance for treatment response to NACT. Moreover, high ISGC indicated better long-term survival in patients with advanced GC. Furthermore, tumor-infiltrated T cells (CD3+ and CD8+) and CD11c+ macrophages were significantly increased in the response group, while CD163+ macrophages and FOXP3+ Treg cells were decreased after NACT. However, opposite results were exhibited in the nonresponse group. Finally, we found that the percentage of programmed cell death ligand 1 (PD-L1)-positive tumors was 31% (32/104) pre-NACT and 49% (51/104) post-NACT, and almost all patients with elevated PD-L1 were in the NACT response group. The ISGC model accurately predicted NACT efficacy and classified patients with GC into different survival groups. NACT regulates the TIME in GC, which may provide strategies for personalized immunotherapy.

Prognostic Value of "Basal-like" Morphology, Tumor-Infiltrating Lymphocytes and Multi-MAGE-A Expression in Triple-Negative Breast Cancer

"Basal-like" (BL) morphology and the expression of cancer testis antigens (CTA) in breast cancer still have unclear prognostic significance. The aim of our research was to explore correlations of the morphological characteristics and tumor microenvironment in triple-negative breast carcinomas (TNBCs) with multi-MAGE-A CTA expression and to determine their prognostic significance. Clinical records of breast cancer patients who underwent surgery between January 2017 and December 2018 in four major Croatian clinical centers were analyzed. A total of 97 non-metastatic TNBCs with available tissue samples and treatment information were identified. Cancer tissue sections were additionally stained with programmed death-ligand 1 (PD-L1) Ventana (SP142) and multi-MAGE-A (mAb 57B). BL morphology was detected in 47 (49%) TNBCs and was associated with a higher Ki-67 proliferation index and histologic grade. Expression of multi-MAGE-A was observed in 77 (79%) TNBCs and was significantly associated with BL morphology. Lymphocyte-predominant breast cancer (LPBC) status was detected in 11 cases (11.3%) and significantly correlated with the Ki-67 proliferation index, increased number of intratumoral lymphocytes (itTIL), and PD-L1 expression. No impact of BL morphology, multi-MAGE-A expression, histologic type, or LPBC status on disease-free survival was observed. Our data suggest that tumor morphology could help identify patients with potential benefits from CTA-targeting immunotherapy.

Effect of intra-arrest transport, extracorporeal cardiopulmonary resuscitation and immediate invasive assessment in refractory out-of-hospital cardiac arrest: a long-term follow-up of the Prague OHCA trial

BACKGROUND

Randomized data evaluating the impact of the extracorporeal cardiopulmonary resuscitation (ECPR) approach on long-term clinical outcomes in patients with refractory out-of-hospital cardiac arrest (OHCA) are lacking. The objective of this follow-up study was to assess the long-term clinical outcomes of the ECPR-based versus CCPR approach.

METHODS

The Prague OHCA trial was a single-center, randomized, open-label trial. Patients with witnessed refractory OHCA of presumed cardiac origin, without return of spontaneous circulation, were randomized during ongoing resuscitation on scene to conventional CPR (CCPR) or an ECPR-based approach (intra-arrest transport, ECPR if ROSC is not achieved prehospital and immediate invasive assessment).

RESULTS

From March 2013 to October 2020, 264 patients were randomized during ongoing resuscitation on scene, and 256 patients were enrolled. Long-term follow-up was performed 5.3 (interquartile range 3.8-7.2) years after initial randomization and was completed in 255 of 256 patients (99.6%). In total, 34/123 (27.6%) patients in the ECPR-based group and 26/132 (19.7%) in the CCPR group were alive (log-rank P = 0.01). There were no significant differences between the treatment groups in the neurological outcome, survival after hospital discharge, risk of hospitalization, major cardiovascular events and quality of life. Of long-term survivors, 1/34 (2.9%) in the ECPR-based arm and 1/26 (3.8%) in the CCPR arm had poor neurological outcome (both patients had a cerebral performance category score of 3).

CONCLUSIONS

Among patients with refractory OHCA, the ECPR-based approach significantly improved long-term survival. There were no differences in the neurological outcome, major cardiovascular events and quality of life between the groups, but the trial was possibly underpowered to detect a clinically relevant difference in these outcomes. Trial registration ClinicalTrials.gov Identifier: NCT01511666, Registered 19 January 2012.

A novel CD8+ T cell-related gene signature as a prognostic biomarker in hepatocellular carcinoma

CD8+ T cells have great roles in tumor suppression and elimination of various tumors including hepatocellular carcinoma (HCC). Nonetheless, potential prognostic roles of CD8+ T cell-related genes (CD8Gs) in HCC remains unknown. In our study, 416 CD8Gs were identified in HCC, which were enriched in inflammatory and immune signaling pathways. Using The Cancer Genome Atlas dataset, a 5-CD8Gs risk model (KLRB1, FYN, IL2RG, FCER1G, and DGKZ) was constructed, which was verified in International Cancer Genome Consortium and gene expression omnibus datasets. Furthermore, we found that overall survival was independently correlated with the CD8Gs signature, and it was associated with immune- and cancer-related signaling pathways and immune cells infiltration. Finally, drug sensitivity data indicated that 10 chemotherapeutic drugs held promise as therapeutics for HCC patients with high-risk. In conclusion, multi-databases analysis showed that 5-CD8Gs and their signature could be an indicator to predict candidate drugs for HCC therapy.

Differential cytokine and chemokine expression after ablation vs. resection in colorectal cancer liver metastasis

Background

Surgical resection remains the main curative treatment for colorectal liver metastases (CRLM). Radiofrequency ablation (RFA) is increasingly employed for small, deep lying or otherwise inoperable lesions. However, RFA can induce pro-tumorigenic effects on residual tumor cells, hereby possibly promoting tumor recurrence. Contrastingly, post-RFA tumor debris as an antigen source can also generate anti-cancer immune responses. Utilizing this, current studies on combining RFA with immune therapy appear promising. Here, in an attempt to shed light on this controversy, cytokines involved in inflammation, (lymph)angiogenesis, immune cell recruitment and tumor cell invasion were investigated post-RFA versus post-resection in CRLM patients.

Methods

Cytokine and chemokine serum levels pre-operation, 4 h and 24 h post-operation were analyzed in CRLM patients undergoing RFA (n = 8) or partial hepatectomy (n = 9) using Multiplex immunoassays. Statistical analyses were performed between as well as within individual intervention groups.

Results

Post-RFA, significantly increased levels of acute phase proteins SAA1 and S100A8, IL-6, IL-1Ra, MIP3b (CCL19) and MMP9 were observed along with decreases in Fibronectin, MCP-1 (CCL2), and Tie-2. Post-resection, increased levels of PDGFbb, I309 (CCL1), Apelin, MIF, IL-1b and TNFα were seen. All p-values <0.05.

Conclusion

Pro-inflammatory responses mediated by different cytokines were seen after both RFA and resection, possibly influencing residual tumor cells and tumor recurrence. As both ablation and resection trigger inflammation and immune cell recruitment (albeit via distinct mechanisms), these data suggest that further research may explore combining immune therapy with not only RFA but also resection.

Key message

Analysis of patients' serum after radiofrequency ablation versus resection of colorectal liver metastases (CRLM) showed that these interventions trigger inflammation and immune cell recruitment, via different cyto- and chemokine pathways. This suggests a possible future strategy of combining immune therapy with not only ablative techniques but also with resection of CRLM.

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Development and implementation of a prognostic model for clear cell renal cell carcinoma based on heterogeneous TLR4 expression

Objective

Clear cell renal cell carcinoma (ccRCC) is the most common subtype among renal cell carcinomas and has the worst prognosis, originating from renal tubular epithelial cells. Toll-like receptor 4 (TLR4) plays a crucial role in ccRCC proliferation, infiltration, and metastasis. The aim of this study was to construct a prognostic scoring model for ccRCC based on TLR4 expression heterogeneity and to explore its association with immune infiltration, thereby providing insights for the treatment and prognostic evaluation of ccRCC.

Methods

Using R software, a differential analysis was conducted on normal samples and ccRCC samples, and in conjunction with the KEGG database, a correlation analysis for the clear cell renal cell carcinoma pathway (hsa05211) was carried out. We observed the expression heterogeneity of TLR4 in the TCGA-KIRC cohort and identified its related differential genes (TRGs). Based on the expression levels of TRGs, consensus clustering was employed to identify TLR4-related subtypes, and further clustering heatmaps, principal component, and single-sample gene set enrichment analyses were conducted. Overlapping differential genes (ODEGs) between subtypes were analysed, and combined with survival data, univariate Cox regression, LASSO, and multivariate Cox regression were used to establish a prognostic risk model for ccRCC. This model was subsequently evaluated through ROC analysis, risk factor correlation analysis, independent prognostic factor analysis, and intergroup differential analysis. The ssGSEA model was employed to explore immune heterogeneity in ccRCC, and the performance of the model in predicting patient prognosis was evaluated using box plots and the oncoPredict software package.

Results

In the TCGA-KIRC cohort, TLR4 expression was notably elevated in ccRCC samples compared to normal samples, correlating with improved survival in the high-expression group. The study identified distinct TLR4-related differential genes and categorized ccRCC into three subtypes with varied survival outcomes. A risk prognosis model based on overlapping differential genes was established, showing significant associations with immune cell infiltration and key immune checkpoints (PD-1, PD-L1, CTLA4). Additionally, drug sensitivity differences were observed between risk groups.

Conclusion

In the TCGA-KIRC cohort, the expression of TLR4 in ccRCC samples exhibited significant heterogeneity. Through clustering analysis, we identified that the primary immune cells across subtypes are myeloid-derived suppressor cells, central memory CD4 T cells, and regulatory T cells. Furthermore, we successfully constructed a prognostic risk model for ccRCC composed of 17 genes. This model provides valuable references for the prognosis prediction and treatment of ccRCC patients.

Construction of a New Immune-Related Competing Endogenous RNA Network with Prognostic Value in Lung Adenocarcinoma

Tumor microenvironment has significant influence on the gene expression of tumor tissues and on the clinical outcomes in lung adenocarcinoma. Infiltrating immune and stromal cells not only perturb the tumor signal in molecular studies, but also play crucial roles in cancer biology. The competing endogenous RNAs (ceRNAs) are useful to explain the post-transcriptional layer regulated by gene translation and play an important role in the occurrence and progression of lung adenocarcinoma. Therefore, identifying novel molecular markers by constructing ceRNA associated with immune infiltration is of great significance to guide the treatment of lung adenocarcinoma in the future. According to the immune and stromal scores of lung adenocarcinoma samples in The Cancer Genome Atlas (TCGA) database calculated by the ESTIMATE algorithm, we identified differentially expressed lncRNAs, miRNAs and mRNAs associated with immune infiltration, including 60 dysregulated lncRNAs, 38 dysregulated mRNAs, and 29 dysregulated miRNAs. Based on the PPI network and Cox regression analysis, 5 mRNAs including CNR2, P2RY12, ZNF831, RSPO1, and F2 were identified to be related to immune infiltration and prognosis in lung adenocarcinoma, and their differential expression, prognosis and correlation with immune cells were verified. Next, through target binding prediction, pearson correlation analysis and expression analysis, a novel immune-related ceRNA network containing 6 lncRNAs, 4 miRNAs, and 3 mRNAs was finally constructed. The present study constructed a novel immune-associated lncRNA-miRNA-mRNA ceRNA network, which deepens our understanding on the molecular network mechanism of lung adenocarcinoma and provides potential prognostic markers and novel therapeutic targets for the patients with lung adenocarcinoma.

Prognosis and immunotherapy response prediction based on M2 macrophage-related genes in colon cancer

BACKGROUND

M2 macrophage were revealed to play a crucial role in immune evasion and immunotherapies. This study aims to explore the potential significance of M2 macrophage-related genes in colon adenocarcinoma (COAD) by analysizing the transcriptome data in a comprehensive way.

METHODS

We collected RNA-sequencing (RNA-seq) data of COAD from The Cancer Genome Atlas (TCGA) and Gene Expression Ominibus (GEO) databases. We calculated the immune infiltration scores of every sample using CIBERSORT algorithm. Through weighted gene co-expression network analysis (WGCNA), we picked out M2 macrophage-related genes. With these genes we screened out prognosis related genes which were utilized to construct a signature to assess the prognosis of patients. To extend the potential application of the signature, we also calculated the correlations with immune infiltration. Finally, we applied techniques such as quantitative reverse transcription polymerase chain reaction (qRT-PCR) and immunoblotting (Western Blotting) to validate the RNF32 gene in cellular in vitro assays.

RESULTS

Seven M2 macrophage-related genes signature was constructed, which was an excellent prognostic predictor in two independent groups. The high-risk group showed lower immune infiltration and poorer response to immunotherapies than those of the low-risk group. The cell vitro experiments showed that the expression level of RNF32 was upregulated in colon cancer cell lines compared with normal cell lines. Moreover, we found that RNF32 may promote the proliferation, migration and invasion of cancer cells in vitro by inhibiting apoptosis.

CONCLUSION

A novel M2 macrophage-related gene signature affects the prognosis and immune characteristics of colon cancer.

Tumor Heterogeneity Confounds Lymphocyte Metrics in Diagnostic Lung Cancer Biopsies

CONTEXT.—

The immune microenvironment is involved in fundamental aspects of tumorigenesis, and immune scores are now being developed for clinical diagnostics.

OBJECTIVE.—

To evaluate how well small diagnostic biopsies and tissue microarrays (TMAs) reflect immune cell infiltration compared to the whole tumor slide, in tissue from patients with non-small cell lung cancer.

DESIGN.—

A TMA was constructed comprising tissue from surgical resection specimens of 58 patients with non-small cell lung cancer, with available preoperative biopsy material. Whole sections, biopsies, and TMA were stained for the pan-T lymphocyte marker CD3 to determine densities of tumor-infiltrating lymphocytes. Immune cell infiltration was assessed semiquantitatively as well as objectively with a microscopic grid count. For 19 of the cases, RNA sequencing data were available.

RESULTS.—

The semiquantitative comparison of immune cell infiltration between the whole section and the biopsy displayed fair agreement (intraclass correlation coefficient [ICC], 0.29; P = .01; CI, 0.03-0.51). In contrast, the TMA showed substantial agreement compared with the whole slide (ICC, 0.64; P < .001; CI, 0.39-0.79). The grid-based method did not enhance the agreement between the different tissue materials. The comparison of CD3 RNA sequencing data with CD3 cell annotations confirmed the poor representativity of biopsies as well as the stronger correlation for the TMA cores.

CONCLUSIONS.—

Although overall lymphocyte infiltration is relatively well represented on TMAs, the representativity in diagnostic lung cancer biopsies is poor. This finding challenges the concept of using biopsies to establish immune scores as prognostic or predictive biomarkers for diagnostic applications.

Prediction of prognosis of patients with hepatocellular carcinoma based on immune-related score

BACKGROUND

Immune-related scores are currently used for prognostic evaluation and as an immunotherapy reference in various cancers. However, the relationship between immune-related score and hepatocellular carcinoma (HCC) prognosis has not yet been investigated. This study aimed to explore the clinical application value of immune-related score for predicting HCC prognosis-related indicators including disease-free survival (DFS) and overall survival (OS), and to construct a clinical nomogram prediction model related to verification.

METHODS

This study included 284 HCC patients who were selected from the Cancer Genome Atlas (TCGA) database and linked to the immune-related score downloaded from the public platform. A Cox proportional hazards regression model was used to estimate the adjusted risk ratio, and a nomogram was constructed based on multivariate analysis results and clinical significance. The model was internally verified by bootstrap. The performance of the prediction model was evaluated using the C-index and calibration curves.

RESULTS

Patients were divided into three subgroups according to the immune-related score level. Compared with patients in the low immune-related score group, the DFS of patients in the medium and high immune-related score groups was significantly prolonged (HR: 0.53, 95% CI: 0.32-0.87; HR: 0.37, 95% CI: 0.21-0.63, respectively). The OS of patients in the medium and high immune-related score groups was also significantly prolonged (HR: 0.43, 95% CI: 0.20-0.95, p = 0.038; HR: 0.29, 95% CI: 0.14-0.58, p < 0.001, respectively). The C-indexes for predicting DFS and OS were 0.687 (95% CI: 0.665-0.700) and 0.743 (95% CI: 0.709-0.776), respectively. The calibration curves of 3-year and 5-year DFS and OS showed that the results predicted by the nomogram were in good agreement with the actual observations.

CONCLUSIONS

Moderate/high-grade immune-related score was significantly associated with better DFS and OS in HCC patients. In addition, a nomogram for prognosis estimation can help clinicians predict the survival status of patients.

CD3-CD8 immune score associated with a clinical score stratifies PDAC prognosis regardless of adjuvant or neoadjuvant chemotherapy

Stratification of the prognosis of pancreatic cancer (PDAC) patients treated by surgery is based solely on clinical variables, such as tumor stage and node status. The development of biomarkers of relapse is needed, especially to drive administration of adjuvant therapy in this at-risk population. Our study evaluates the prognostic performance of a CD3- and CD8-based immune score. CD3, CD8 and Foxp3 expression were evaluated on whole slides in two retrospective PDAC cohorts totaling 334 patients. For this study, we developed an immune score to estimate CD3 and CD8 infiltration in both tumor core and invasive margin using computer-guided analysis with QuPath software. Variables were combined in a dichotomous immune score. The association between immune and clinical scores, and both PFS and OS was investigated. We observed that a dichotomous immune score predicts both PFS and OS of localized PDAC. By univariate and multivariate analysis, immune score, tumor grade, adjuvant therapy, lymph node status, and adjuvant chemotherapy administration were associated with PFS and OS. We subsequently associated the PDAC immune score and clinical variables in a combined score. This combined score predicted patient outcomes independently of adjuvant or neoadjuvant treatment, and improved patient prognostic prediction compared to clinical variables or immune score alone.

MTHFR gene polymorphisms and susceptibility to myocardial infarction: Evidence from meta-analysis and trial sequential analysis

Background

This meta-analysis aimed to provide a comprehensive assessment of the association between Methylenetetrahydrofolate reductase (MTHFR) gene polymorphisms, specifically C677T and A1298C, and the susceptibility to myocardial infarction (MI).

Methods

A systematic literature search was conducted in MEDLINE, Web of Science, and Scopus until April 2023 to identify studies investigating the relationship between MTHFR gene polymorphisms (C677T and A1298C) and the risk of MI.

Results

The analysis included 66 studies involving 16,860 cases and 20,403 controls for the C677T polymorphism and 18 studies comprising 3162 cases and 3632 controls for the A1298C polymorphism. Significant associations were observed between the C677T polymorphism and MI risk in various genetic models: dominant (OR = 1.16, 95 % CI = 1.06-1.28, P = 0.008), recessive (OR = 1.20, 95 % CI = 1.12-1.28, P < 0.001), allelic (OR = 1.13, 95 % CI = 1.06-1.21, P < 0.001), TT vs. CC (OR = 1.19, 95 % CI = 1.05-1.36, P < 0.001), and CT vs. CC (OR = 1.11, 95 % CI = 1.02-1.21, P = 0.01). Furthermore, an overall analysis indicated a marginally significant association between the A1298C polymorphism and MI risk in the recessive model (OR = 1.27, 95 % CI = 1.06-1.51, P = 0.008), allelic model (OR = 1.18, 95 % CI = 1.01-1.39, P = 0.03), and CC vs. AA model (OR = 1.22, 95 % CI = 1.01-1.47, P = 0.04). Meta-regression analysis revealed that none of the potential factors contributed to the observed heterogeneity.

Conclusions

This meta-analysis revealed an association between MTHFR gene C677T and A1298C polymorphisms and the risk of MI.

[Profile and immune environment of upper tract urothelial carcinoma]

INTRODUCTION AND OBJECTIVES

Upper Tract Urothelial Carcinoma (UTUC) are tumors that share similarities with bladder tumors. Immunotherapy is already used for bladder locations and appears to have interest for UTUC. In order to rationalize the immunotherapy development pipeline it seemed necessary to describe the immune infiltrate of a cohort of UTUC treated with nephroureterectomy and to determine the expression of a panel of immune checkpoints and co-stimulatory molecules on tumor cells as well as on infiltrating and circulating lymphocytes.

MATERIALS AND METHODS

This is a monocentric, prospective and exploratory work. Patients treated with total nephroureterectomy or segmental ureterectomy for presumably infiltrative (≥ T1) UTUC managed at the Saint-Louis Hospital were included from January 2019 to July 2020. A set of markers and immune checkpoints were studied by flow fluorocytometry on circulating lymphocytes (PBMCs) and tumor-infiltrating lymphocytes (TILs). Some markers were also studied by immunohistochemistry on tumor sample.

RESULTS

In total, 14 patients were included and 13 patients could be analyzed. 1 patient had no residual tumor. 5 tumors out of the 12 (41.7%) showed a lymphocytic inflammatory infiltrate. PD1 was the most represented checkpoint with a median expression rate of 41.4% on CD4+ TILs and 3.89% on circulating CD4+ T cells. This rate was 62.4% and 7.45% respectively on CD8+ T cells. TIGIT was the second most represented marker with a median expression rate on tumor-infiltrating CD4+ T cells of 25% and 2.9% on circulating CD4+ T cells. The median expression level of TIGIT on tumor-infiltrating CD8+ T cells was 23.3% and 3.2% on circulating CD8+ T cells. ICOS was highly expressed on CD4+ TILS with a median of 33.9% in contrast to CD8+ TILS (median: 6.67%). Variable expression of other checkpoints (ILT2, TIM3, LAG3 and OX40) was found without clear trend.

CONCLUSION

This exploratory work highlighted that PD1 was the most represented checkpoint. TIGIT was the second most represented checkpoint while ICOS, TIM3 and LAG3 were 3 other checkpoints whose expression was found to be less important. ILT2 and OX40 appeared to be weakly expressed.

LEVEL OF EVIDENCE

II.

New insights of miRNA molecular mechanisms in breast cancer brain metastasis and therapeutic targets

Brain metastases in breast cancer (BC) patients are often associated with a poor prognosis. Recent studies have uncovered the critical roles of miRNAs in the initiation and progression of BC brain metastasis, highlighting the disease's underlying molecular pathways. miRNA-181c, miRNA-10b, and miRNA-21, for example, are all overexpressed in BC patients. It has been shown that these three miRNAs help tumors grow and metastasize by targeting genes that control how cells work. On the other hand, miRNA-26b5p, miRNA-7, and miRNA-1013p are all downregulated in BC brain metastasis patients. They act as tumor suppressors by controlling the expression of genes related to cell adhesion, angiogenesis, and invasion. Therapeutic miRNA targeting has considerable promise in treating BC brain metastases. Several strategies have been proposed to modulate miRNA expression, including miRNA-Mimics, antagomirs, and small molecule inhibitors of miRNA biogenesis. This review discusses the aberrant expression of miRNAs and metastatic pathways that lead to the spread of BC cells to the brain. It also explores miRNA therapeutic target molecular mechanisms and BC brain metastasis challenges with advanced strategies. The targeting of certain miRNAs opens a new door for the development of novel therapeutic approaches for this devastating disease.

Identification of M5c regulator-medicated methylation modification patterns for prognosis and immune microenvironment in glioma

Glioma is a common intracranial tumor and is generally associated with poor prognosis. Recently, numerous studies illustrated the importance of 5-methylcytosine (m5C) RNA modification to tumorigenesis. However, the prognostic value and immune correlation of m5C in glioma remain unclear. We obtained RNA expression and clinical information from The Cancer Genome Atlas (TCGA) and The Chinese Glioma Genome Atlas (CGGA) datasets to analyze. Nonnegative matrix factorization (NMF) was used to classify patients into two subgroups and compare these patients in survival and clinicopathological characteristics. CIBERSORT and single-sample gene-set algorithm (ssGSEA) methods were used to investigate the relationship between m5C and the immune environment. The Weighted correlation network analysis (WGCNA) and univariate Cox proportional hazard model (CoxPH) were used to construct a m5C-related signature. Most of m5C RNA methylation regulators presented differential expression and prognostic values. There were obvious relationships between immune infiltration cells and m5C regulators, especially NSUN7. In the m5C-related module from WGCNA, we found SEPT3, CHI3L1, PLBD1, PHYHIPL, SAMD8, RAP1B, B3GNT5, RER1, PTPN7, SLC39A1, and MXI1 were prognostic factors for glioma, and they were used to construct the signature. The great significance of m5C-related signature in predicting the survival of patients with glioma was confirmed in the validation sets and CGGA cohort.

Could immunoscore improve the prognostic and therapeutic management in patients with solid tumors?

The Immunoscore (ISc) is an emerging immune-based scoring system that has shown potential in improving the prognostic and therapeutic management of patients with solid tumors. The ISc evaluates the immune infiltrate within the tumor microenvironment (TME) and has demonstrated superior predictive ability compared to traditional histopathological parameters. It has been particularly promising in colorectal, lung, breast, and melanoma cancers. This review summarizes the clinical evidence supporting the prognostic value of the ISc and explores its potential in guiding therapeutic decisions, such as the selection of adjuvant therapies and recognizing patients likely to profit from immune checkpoint inhibitors (ICIs). The challenges and future directions of ISc implementation are also discussed, including standardization and integration into routine clinical practice.

Proteomic-Based Discovery of Predictive Biomarkers for Drug Therapy Response and Personalized Medicine in Chronic Immune Thrombocytopenia

Purpose

ITP is the most prevalent autoimmune blood disorder. The lack of predictive biomarkers for therapeutic response is a major challenge for physicians caring of chronic ITP patients. This study is aimed at identifying predictive biomarkers for drug therapy responses.

Methods

2D gel electrophoresis (2-DE) was performed to find differentially expressed proteins. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometer (MALDI-TOF MS) analysis was performed to identify protein spots. The Cytoscape software was employed to visualize and analyze the protein-protein interaction (PPI) network. Then, enzyme-linked immunosorbent assays (ELISA) were used to confirm the results of the proteins detected in the blood. The DAVID online software was used to explore the Gene Ontology and pathways involved in the disease.

Results

Three proteins, including APOA1, GC, and TF, were identified as hub-bottlenecks and confirmed by ELISA. Enrichment analysis results showed the importance of several biological processes and pathway, such as the PPAR signaling pathway, complement and coagulation cascades, platelet activation, vitamin digestion and absorption, fat digestion and absorption, cell adhesion molecule binding, and receptor binding. Conclusion and Clinical Relevance. Our results indicate that plasma proteins (APOA1, GC, and TF) can be suitable biomarkers for the prognosis of the response to drug therapy in ITP patients.

The T Cell Immunoscore as a Reference for Biomarker Development Utilizing Real-World Data from Patients with Advanced Malignancies Treated with Immune Checkpoint Inhibitors

BACKGROUND

We aimed to determine the prognostic value of an immunoscore reflecting CD3+ and CD8+ T cell density estimated from real-world transcriptomic data of a patient cohort with advanced malignancies treated with immune checkpoint inhibitors (ICIs) in an effort to validate a reference for future machine learning-based biomarker development.

METHODS

Transcriptomic data was collected under the Total Cancer Care Protocol (NCT03977402) Avatar® project. The real-world immunoscore for each patient was calculated based on the estimated densities of tumor CD3+ and CD8+ T cells utilizing CIBERSORTx and the LM22 gene signature matrix. Then, the immunoscore association with overall survival (OS) was estimated using Cox regression and analyzed using Kaplan-Meier curves. The OS predictions were assessed using Harrell's concordance index (C-index). The Youden index was used to identify the optimal cut-off point. Statistical significance was assessed using the log-rank test.

RESULTS

Our study encompassed 522 patients with four cancer types. The median duration to death was 10.5 months for the 275 participants who encountered an event. For the entire cohort, the results demonstrated that transcriptomics-based immunoscore could significantly predict patients at risk of death (p-value < 0.001). Notably, patients with an intermediate-high immunoscore achieved better OS than those with a low immunoscore. In subgroup analysis, the prediction of OS was significant for melanoma and head and neck cancer patients but did not reach significance in the non-small cell lung cancer or renal cell carcinoma cohorts.

CONCLUSIONS

Calculating CD3+ and CD8+ T cell immunoscore using real-world transcriptomic data represents a promising signature for estimating OS with ICIs and can be used as a reference for future machine learning-based biomarker development.

Prognostic risk of immune-associated signature in the microenvironment of brain gliomas

Understanding the key factors in the tumor microenvironment (TME) that affect the prognosis of gliomas is crucial. In this study, we sought to uncover the prognostic significance of immune cells and immune-related genes in the TME of gliomas. We incorporated data of 970 glioma patient samples from the Chinese Glioma Genome Atlas (CGGA) database as the training set, and an additional set of 666 samples from The Cancer Genome Atlas (TCGA) database served as the validation set. From our analysis, we identified 21 immune-related differentially expressed genes (DEGs) in the TME, which holds implications for glioma prognosis. Based on these genes, we constructed a prognostic risk model on the 21 genes. The prognostic risk model demonstrated robust performance with an area under the curve (AUC) value of 0.848. Notably, the risk score derived from the model emerged as an independent prognostic factor of gliomas, with high risk scores indicative of an unfavorable prognosis. Furthermore, we observed that high infiltration levels of certain immune cells, namely, activated dendritic cells, M0 macrophages, M2 macrophages, and regulatory T cells (Tregs), correlated with an unfavorable glioma prognosis. In conclusion, our findings suggested that the TME of gliomas harbored a distinct immune-associated signature, comprising 21 immune-related genes and specific immune cells. These elements significantly influence the prognosis and present potential as novel indicators in the clinical assessment of glioma patient outcomes.

Dynamic cytokines signature predicts survival outcome from severe Immune-related hepatitis with PD-1/PD-L1 blockade in lung cancer

BACKGROUND

Immune-related adverse events (irAEs), particularly immune-related hepatitis (IRH) is a potentially serious complication of immune checkpoint inhibitor (ICI) therapy. This retrospective cohort study investigated potential prognostic and predictive biomarkers for IRH.

METHOD

This study included 37 patients with advanced lung cancer who received ICIs and were divided into two groups: ≥Grade 3 (G3)-IRH group (n = 17) and without irAE (no-irAE) group (n = 20). Blood samples collected at three different time points and pre-treatment tumor biopsy samples were analyzed using multi-omics assays.

RESULTS

The IL-1B RNA expression was significantly increased (limma, fold = 1.94) in the ≥ G3-IRH group than the no-irAE group. Compared with no-irAE group, ≥G3-IRH group had higher monocyte and eosinophil infiltration and lower macrophage infiltration, particularly macrophage M2. Transcriptomics analyses of pre-treatment tumor samples revealed significant upregulation of various inflammation-related genes in the ≥ G3-IRH group (False discovery rate < 0.05). Moreover, various proinflammatory cytokines and chemokines were significantly lower in the plasma of the ≥ G3-IRH group than in the no-irAE group. Subgroup analyses of the ≥ G3-IRH group revealed that plasma IL-1A was significantly higher among those whose IRH resolved than those who had IRH-related death. Patients who died had a greater increase in immune score and Euclidean distance from the baseline to the seventh day of IRH onset, with a dramatic increase in Euclidean distance after immunosuppression, suggesting overstimulated immune status.

CONCLUSION

Our study demonstrated the association between IL-1B overexpression and IRH susceptibility. Immune score and Euclidean distance of inflammatory cytokines may provide predictive value on the survival outcome from ≥ G3 IRH.

The future of affordable cancer immunotherapy

The treatment of cancer was revolutionized within the last two decades by utilizing the mechanism of the immune system against malignant tissue in so-called cancer immunotherapy. Two main developments boosted cancer immunotherapy: 1) the use of checkpoint inhibitors, which are characterized by a relatively high response rate mainly in solid tumors; however, at the cost of serious side effects, and 2) the use of chimeric antigen receptor (CAR)-T cells, which were shown to be very efficient in the treatment of hematologic malignancies, but failed to show high clinical effectiveness in solid tumors until now. In addition, active immunization against individual tumors is emerging, and the first products have reached clinical approval. These new treatment options are very cost-intensive and are not financially compensated by health insurance in many countries. Hence, strategies must be developed to make cancer immunotherapy affordable and to improve the cost-benefit ratio. In this review, we discuss the following strategies: 1) to leverage the antigenicity of "cold tumors" with affordable reagents, 2) to use microbiome-based products as markers or therapeutics, 3) to apply measures that make adoptive cell therapy (ACT) cheaper, e.g., the use of off-the-shelf products, 4) to use immunotherapies that offer cheaper platforms, such as RNA- or peptide-based vaccines and vaccines that use shared or common antigens instead of highly personal antigens, 5) to use a small set of predictive biomarkers instead of the "sequence everything" approach, and 6) to explore affordable immunohistochemistry markers that may direct individual therapies.

Prognostic Impact of the Immunoscore Based on Whole-Slide Image Analysis of CD3+ Tumor-Infiltrating Lymphocytes in Diffuse Large B-Cell Lymphoma

An Immunoscore based on tumor-infiltrating T-cell density was validated as a prognostic factor in patients with solid tumors. However, the potential utility of the Immunoscore in predicting the prognosis of patients with diffuse large B-cell lymphoma (DLBCL) is unclear. Here, the prognostic value of an Immunoscore based on tumor-infiltrating CD3+ T-cell density was evaluated in 104 patients with DLBCL who underwent R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisolone) therapy. Digitally scanned whole-slide images were analyzed using Aperio ImageScope software. CD3+ cell densities in the whole tumor area were quantitated using 3 different methods, including number of CD3+ cells/area (mm2), ratio of CD3+ cells to total cells, and ratio of CD3+ cells to CD20+ cells. There was a high concordance among the 3 methods. Patients with low CD3+ cell density had an elevated serum lactate dehydrogenase level and a high Ki-67 proliferation index (all, P < .05). Patients with low CD3+ cell density, according to all 3 methods, had worse overall survival (OS) and worse progression-free survival (P < .05, all). They also had poor OS, independent of MYC/BCL2 double expression (DE) status, Eastern Cooperative Oncology Group performance status, or Ann Arbor stage (all, P < .05). These results were validated using 2 publicly available data sets. In both validation cohorts, patients with low CD3E mRNA expression had an elevated serum lactate dehydrogenase level, extranodal site involvement, and DE status (P < .05). They also had worse progression-free survival (P = .067 and P = .002, respectively) and OS (both P < .05). A low CD3E mRNA level was predictive of poor OS, independent of DE status. An Immunoscore based on whole-slide image analysis of CD3+ T-cell infiltration was sufficient to predict survival in patients with DLBCL. Low CD3+ cell density was a poor prognostic factor, independent of other prognostic parameters and DE status.

Integrated single-cell and bulk RNA sequencing analysis identifies a prognostic signature related to ferroptosis dependence in colorectal cancer

Ferroptosis is an iron-dependent form of cell death induced by lipid oxidation with an essential role in diseases, including cancer. Since prognostic value of ferroptosis-dependent related genes (FDRGs) in colorectal cancer (CRC) remains unclear, we explored the significance of FDRGs in CRC through comprehensive single-cell analysis. We downloaded the GSE161277 dataset for single-cell analyses and calculated the ferroptosis-dependent gene score (FerrScore) for each cell type. According to each cell type-specific median FerrScore, we categorized the cells into low- and high-ferroptosis groups. By analyzing differentially-expressed genes across the two groups, we identified FDRGs. We further screened these prognosis-related genes used to develop a prognostic signature and calculated its correlation with immune infiltration. We also compared immune checkpoint gene efficacy among different risk groups, and qRT-PCR was performed in colorectal normal and cancer cell lines to explore whether the signature genes could be used as clinical prognostic indicators. In total, 523 FDRGs were identified. A prognostic signature including five signature genes was constructed, and patients were divided into two risk groups. The high-risk group had poor survival rates and displayed high levels of immune infiltration. Our newly developed ferroptosis-based prognostic signature possessed a high predictive ability for CRC.

The role of systemic inflammatory response index (SIRI) and tumor-infiltrating lymphocytes (TILs) in the prognosis of patients with laryngeal squamous cell carcinoma

OBJECTIVE

Systemic inflammatory response index (SIRI) values and tumor-infiltrating lymphocytes (TILs) are associated with the prognosis of various tumors. There is minimal evidence of those two as prognostic markers in laryngeal squamous cell carcinoma (LSCC). In this study, we aimed to examine the predictive value of SIRI and tumor-infiltrating CD3+/CD4+/CD8+ T cells in the prognosis of patients who underwent partial or total laryngectomy.

STUDY DESIGN

A total of 78 patients with LSCC who underwent total or partial laryngectomy at the Eye, Ear, Nose, and Throat Hospital of Fudan University between 2013 and 2015 were retrospectively analyzed.

METHODS

The tumor tissues of 78 LSCC patients were retrospectively evaluated using immunohistochemical staining for CD3+ /CD4+ /CD8+ -cells. The overall survival (OS) and disease-free survival (DFS) rates were recorded using the Kaplan-Meier method.

RESULTS

Patients with high immunoscore (IS) (3-4) had prolonged survival (P < 0.001 for OS). High SIRI values were independently associated with poorer OS and DFS (P = 0.018 for OS; P = 0.016 for DFS). CD8+ TILs and SIRI values showed a- negative association (P < 0.01). Patients with low SIRI values and high IS had better 5-year OS and DFS than those with high SIRI values and low IS (P < 0.001 for OS; P = 0.0014 for DFS). Patients with 'hot' tumor had a higher 5-year OS than those with 'excluded' or 'cold' phenotype.

CONCLUSIONS

The SIRI values and the density of TILs may help predict LSCC patients' outcomes after surgery. The combination of SIRI and IS may be a new component of the tumor, nodes, and metastases (TNM) classification of cancer and prognostic factor for T-cell-target immunotherapy.

Immuno-Contexture and Immune Checkpoint Molecule Expression in Mismatch Repair Proficient Colorectal Carcinoma

Colorectal carcinoma (CRC) represents a lethal disease with heterogeneous outcomes. Only patients with mismatch repair (MMR) deficient CRC showing microsatellite instability and hyper-mutated tumors can obtain clinical benefits from current immune checkpoint blockades; on the other hand, immune- or target-based therapeutic strategies are very limited for subjects with mismatch repair proficient CRC (CRC^pMMR). Here, we report a comprehensive typing of immune infiltrating cells in CRC^pMMR. We also tested the expression and interferon-γ-modulation of PD-L1/CD274. Relevant findings were subsequently validated by immunohistochemistry on fixed materials. CRC^pMMR contain a significantly increased fraction of CD163⁺ macrophages (TAMs) expressing TREM2 and CD66⁺ neutrophils (TANs) together with decrease in CD4^-CD8^-CD3⁺ double negative T lymphocytes (DNTs); no differences were revealed by the analysis of conventional and plasmacytoid dendritic cell populations. A fraction of tumor-infiltrating T-cells displays an exhausted phenotype, co-expressing PD-1 and TIM-3. Remarkably, expression of PD-L1 on fresh tumor cells and TAMs was undetectable even after in vitro stimulation with interferon-γ. These findings confirm the immune suppressive microenvironment of CRC^pMMR characterized by dense infiltration of TAMs, occurrence of TANs, lack of DNTs, T-cell exhaustion, and interferon-γ unresponsiveness by host and tumor cells. Appropriate bypass strategies should consider these combinations of immune escape mechanisms in CRC^pMMR.

Bioinformatics and network biology approach to identifying type 2 diabetes genes and pathways that influence the progression of breast cancer

Breast cancer is the second most prevalent malignancy affecting women. Postmenopausal women breast tumor is one of the top causes of death in women, accounting for 23% of cancer cases. Type 2 diabetes, a worldwide pandemic, has been connected to a heightened risk of several malignancies, although its association with breast cancer is still uncertain. In comparison to non-diabetic women, women with T2DM had a 23% elevated likelihood of developing breast cancer. It is difficult to determine causative or genetic susceptibility that connect T2DM and breast cancer. We created a large-scale network-based quantitative approach employing unbiased methods to discover abnormally amplified genes in both T2DM and breast cancer, to solve these issues. We performed transcriptome analysis to uncover identical genetic biomarkers and pathways to clarify the connection between T2DM and breast cancer patients. In this study, two RNA-seq datasets (GSE103001 and GSE86468) from the Gene Expression Omnibus (GEO) are used to identify mutually differentially expressed genes (DEGs) for breast cancer and T2DM, as well as common pathways and prospective medicines. Firstly, 45 shared genes (30 upregulated and 15 downregulated) between T2D and breast cancer were detected. We employed gene ontology and pathway enrichment to characterize prevalent DEGs' molecular processes and signal transduction pathways and observed that T2DM has certain connections to the progression of breast cancer. Using several computational and statistical approaches, we created a protein-protein interactions (PPI) network and revealed hub genes. These hub genes can be potential biomarkers, which may also lead to new therapeutic strategies for investigated diseases. We conducted TF-gene interactions, gene-microRNA interactions, protein-drug interactions, and gene-disease associations to find potential connections between T2DM and breast cancer pathologies. We assume that the potential drugs that emerged from this study could be useful therapeutic values. Researchers, doctors, biotechnologists, and many others may benefit from this research.

The immunopeptidome landscape associated with T cell infiltration, inflammation and immune editing in lung cancer

One key barrier to improving efficacy of personalized cancer immunotherapies that are dependent on the tumor antigenic landscape remains patient stratification. Although patients with CD3⁺CD8⁺ T cell-inflamed tumors typically show better response to immune checkpoint inhibitors, it is still unknown whether the immunopeptidome repertoire presented in highly inflamed and noninflamed tumors is substantially different. We surveyed 61 tumor regions and adjacent nonmalignant lung tissues from 8 patients with lung cancer and performed deep antigen discovery combining immunopeptidomics, genomics, bulk and spatial transcriptomics, and explored the heterogeneous expression and presentation of tumor (neo)antigens. In the present study, we associated diverse immune cell populations with the immunopeptidome and found a relatively higher frequency of predicted neoantigens located within HLA-I presentation hotspots in CD3⁺CD8⁺ T cell-excluded tumors. We associated such neoantigens with immune recognition, supporting their involvement in immune editing. This could have implications for the choice of combination therapies tailored to the patient's mutanome and immune microenvironment.

Identification of Prominent Genes between 3D Glioblastoma Models and Clinical Samples via GEO/TCGA/CGGA Data Analysis

A paradigm shift in preclinical evaluations of new anticancer GBM drugs should occur in favour of 3D cultures. This study leveraged the vast genomic data banks to investigate the suitability of 3D cultures as cell-based models for GBM. We hypothesised that correlating genes that are highly upregulated in 3D GBM models will have an impact in GBM patients, which will support 3D cultures as more reliable preclinical models for GBM. Using clinical samples of brain tissue from healthy individuals and GBM patients from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Chinese Glioma Genome Atlas (CGGA), and Genotype-Tissue Expression (GTEx) databases, several genes related to pathways such as epithelial-to-mesenchymal transition (EMT)-related genes (CD44, TWIST1, SNAI1, CDH2, FN1, VIM), angiogenesis/migration-related genes (MMP1, MMP2, MMP9, VEGFA), hypoxia-related genes (HIF1A, PLAT), stemness-related genes (SOX2, PROM1, NES, FOS), and genes involved in the Wnt signalling pathway (DKK1, FZD7) were found to be upregulated in brain samples from GBM patients, and the expression of these genes were also enhanced in 3D GBM cells. Additionally, EMT-related genes were upregulated in GBM archetypes (wild-type IDH1^R132 ) that historically have poorer treatment responses, with said genes being significant predictors of poorer survival in the TCGA cohort. These findings reinforced the hypothesis that 3D GBM cultures can be used as reliable models to study increased epithelial-to-mesenchymal transitions in clinical GBM samples.

A narrative review of genetic biomarkers in non-small cell lung cancer: an update and future perspectives

Background and Objective

Lung cancer has long been the leading cause of cancer deaths in the United States. Lung cancer has a poor prognosis, and our understanding of who will maximally benefit from different therapies is incomplete. This article discusses genetic biomarkers that may help in this regard.

Methods

From origin until February 25, 2022, PubMed database was searched for terms "non-small cell lung cancer", "genomics" and "biomarker", with special attention paid to literature published within the past 10 years. Search was language restricted to English. Additional literature was identified through hand searches of the references of retrieved literature.

Key Content and Findings

The most robustly described biomarkers for non-small cell lung cancer (NSCLC) are assessment of specific gene mutations. These are currently used in clinical practice for both prediction and prognostication. Abnormal mutation status of STK11/LKB1 and KEAP1-NFE2L2 are associated with poor response to radiotherapy (RT), and STK11/LKB1 is further associated with resistance to PD-L1 immunotherapy. Abnormal TP53 is associated with decreased benefit from cisplatin in squamous cell carcinoma (SCC). In terms of prognostication, RB1 mutations are associated with decreased overall survival (OS) in NSCLC and KEAP1-NFE2L2 mutations are associated with increased local recurrence (LR).Additional work has focused on gene expression levels, as well as analysis of genetic factors and signaling molecules affecting the tumor microenvironment (TME). High levels of Rad51c and NFE2L2 are associated with resistance to chemotherapy, and high Rad51c levels are further associated with resistance to RT. High nuclear expression of β-catenin has additionally been associated with poor RT response. Further, there is increasing evidence that some long non-coding RNAs (lncRNAs) may play a crucial role in regulation of tumor radiosensitivity. Much of this work has had promising early results but will require further validation before routine clinical use. Finally, there is evidence that quantification of some signaling molecules and microRNAs (miRNAs) may have clinical utility in predicting adverse outcomes in RT.

Conclusions

An improved understanding of tumor genetics in NSCLC has led to the development of targeted therapies and improved prognostication. As more work is done in this field, more and more genetic biomarkers will become candidates for clinical use. Much work will be required to validate these findings in the clinical setting.

Development and validation of ferroptosis-related lncRNA signature and immune-related gene signature for predicting the prognosis of cutaneous melanoma patients

Ferroptosis, a form of cell death caused by iron-dependent peroxidation of lipids, plays an important role in cancer. Recent studies have shown that long noncoding RNAs (lncRNAs) are involved in the regulation of ferroptosis in tumor cells and are also closely related to tumor immunity. Immune cell infiltration in the tumor microenvironment affects the prognosis and clinical outcome of immunotherapy in melanoma patients, and immune cell classification may be able to accurately predict the prognosis of melanoma patients. However, the prognostic value of ferroptosis-related lncRNAs (FRLs) in melanoma has not been thoroughly explored, and it is difficult to define the immune characteristics of melanoma. We used The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) database, and the FerrDb database to identify FRLs. FRLs with prognostic value were evaluated in an experimental cohort utilizing univariate, LASSO (least absolute shrinkage and selection operator) and multivariate Cox regression, followed by in vitro assays evaluating the expression levels and the biological functions of three candidate FRLs. Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curve analyses were used to assess the validity of the risk model, and the drug sensitivity of FRLs was examined by drug sensitivity analysis. The differentially expressed genes between the high- and low-risk groups in the risk model were enriched in the immune pathway, and we further found immune gene signatures (IRGs) that could predict the prognosis of melanoma patients through a series of methods including single-sample Gene Set Enrichment Analysis (ssGSEA). Finally, two GEO cohorts were used to validate the predictive accuracy and reliability of these two signature models. Our findings suggest that FRLs and IRGs have the potential to predict the prognosis of patients with cutaneous melanoma.

A model based on immune-related lncRNA pairs and its potential prognostic value in immunotherapy for melanoma

A model based on long non-coding RNA (lncRNA) pairs independent of expression quantification was constructed to evaluate prognosis melanoma and response to immunotherapy in melanoma. RNA sequencing data and clinical information were retrieved and downloaded from The Cancer Genome Atlas and the Genotype-Tissue Expression databases. We identified differentially expressed immune-related lncRNAs (DEirlncRNAs), matched them, and used least absolute shrinkage and selection operator and Cox regression to construct predictive models. The optimal cutoff value of the model was determined using a receiver operating characteristic curve and used to categorize melanoma cases into high-risk and low-risk groups. The predictive efficacy of the model with respect to prognosis was compared with that of clinical data and ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data). Then, we analyzed the correlations of risk score with clinical characteristics, immune cell invasion, anti-tumor, and tumor-promoting activities. Differences in survival, degree of immune cell infiltration, and intensity of anti-tumor and tumor-promoting activities were also evaluated in the high- and low-risk groups. A model based on 21 DEirlncRNA pairs was established. Compared with ESTIMATE score and clinical data, this model could better predict outcomes of melanoma patients. Follow-up analysis of the model's effectiveness showed that patients in the high-risk group had poorer prognosis and were less likely to benefit from immunotherapy compared with those in the low-risk group. Moreover, there were differences in tumor-infiltrating immune cells between the high-risk and low-risk groups. By pairing the DEirlncRNA, we constructed a model to evaluate the prognosis of cutaneous melanoma independent of a specific level of lncRNA expression.

Phenotypic subtypes predict outcomes in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths globally. The Colorectal Cancer Subtyping Consortium used the transcriptome-based method to classify CRC according to four molecular subtypes, each showing different genomic alterations and prognoses: CMS1 (microsatellite instable [MSI] immune), CMS2 (canonical), CMS3 (metabolic), and CMS4 (mesenchymal). To expedite the clinical implementation of such methods, easier and preferably tumor phenotype-based methods are needed. In this study, we describe a method to divide patients into four phenotypic subgroups using immunohistochemistry. Moreover, we analyze disease-specific survival (DSS) among different phenotypic subtypes and the associations between the phenotypic subtypes and clinicopathological variables.

METHODS

We categorized 480 surgically treated CRC patients into four phenotypic subtypes (immune, canonical, metabolic, and mesenchymal) using the immunohistochemically determined CD3-CD8 tumor-stroma index, proliferation index, and tumor-stroma percentage. We analyzed survival rates for the phenotypic subtypes in different clinical patient subgroups using the Kaplan-Meier method and Cox regression analysis. Associations between phenotypic subtypes and clinicopathological variables were examined using the chi-square test.

RESULTS

Patients with immune subtype tumors exhibited the best 5-year DSS, while mesenchymal subtype tumors accompanied the worst prognosis. The prognostic value of the canonical subtype showed wide variation among different clinical subgroups. Immune subtype tumors were associated with being female, stage I disease, and a right-side colon location. Metabolic tumors, however, were associated with pT3 and pT4 tumors, and being male. Finally, a mesenchymal subtype associated with stage IV disease, a mucinous histology, and a rectal tumor location.

CONCLUSIONS

Phenotypic subtype predicts patient outcome in CRC. Associations and prognostic values for subtypes resemble the transcriptome-based consensus molecular subtypes (CMS) classification. In our study, the immune subtype stood out with its exceptionally good prognosis. Moreover, the canonical subtype showed wide variability among clinical subgroups. Further studies are needed to investigate the concordance between transcriptome-based classification systems and the phenotypic subtypes.

Immunoscore Signatures in Surgical Specimens and Tumor-Infiltrating Lymphocytes in Pretreatment Biopsy Predict Treatment Efficacy and Survival in Esophageal Cancer

OBJECTIVES

Tumor-infiltrating lymphocytes (TILs) have long been recognized as playing an important role in tumor immune microenvironment. Lately, the Immunoscore (IS) has been proposed as a new method of quantifying the number of TILs in association with patient survival in several cancer types.

METHODS

In 300 preoperatively untreated esophageal cancer (EC) patients who underwent curative resection at two different institutes, immunohistochemical staining using CD3 and CD8 antibodies was performed to evaluate IS, as objectively scored by auto-counted TILs in the tumor core and invasive margin. In addition, in pre-neoadjuvant chemotherapy (pre-NAC) endoscopic biopsies of a different cohort of 146 EC patients who received NAC, CD3, and CD8 were immunostained to evaluate TIL density.

RESULTS

In all cases, the IS-high (score 3-4) group tended to have better survival [5-year overall survival (OS) of the IS-high vs low group: 77.6 vs 65.8%, P = 0.0722] than the IS-low (score 1-2) group. This trend was more remarkable in cStage II-IV patients (70.2 vs 54.5%, P = 0.0208) and multivariate analysis of OS further identified IS (hazard ratio 2.07, P = 0.0043) to be an independent prognostic variable. In preNAC biopsies, NAC-responders had higher densities than non-responders of both CD3 + ( P = 0.0106) and CD8 + cells ( P = 0.0729) and, particularly CD3 + cell density was found to be an independent prognostic factor (hazard ratio 1.75, P = 0.0169).

CONCLUSIONS

The IS signature in surgical specimens and TIL density in preNAC- biopsies could be predictive markers of clinical outcomes in EC patients.

Up-regulation of PUM1 by miR-218-5p promotes colorectal tumor-initiating cell properties and tumorigenesis by regulating the PI3K/AKT axis

Background

Colorectal cancer (CRC) is the third most common cancer and the fourth most common cause of cancer-related death worldwide. Advanced stage CRC, during the recent past, had a dismal prognosis and only a few available treatments. Pumilio homologous protein 1 (PUM1) is reportedly aberrant in human malignancies, including CRC. However, the role of PUM1 in the regulation of tumor-initiating cells (T-ICs) remains unknown.

Methods

The levels of messenger RNAs (mRNAs) were determined by quantitative reverse transcription polymerase chain reaction (qRT-PCR) and immunoblot analyses. Statistical analyses were performed to determine the associations between the levels of PUM1 and tumor features and patient outcomes. Whether PUM1 is a downstream target of miR-218-5p was verified by bioinformatics target gene prediction and qRT-PCR.

Results

Herein, it was found that T-ICs, chemoresistance, and recurrent CRC samples all manifest increased PUM1 expression. Functional investigations have shown that PUM1 increased the self-renewal, tumorigenicity, malignant proliferation, and chemoresistance of colorectal cells. PUM1 activates the phosphatidylinositol-3-kinase (PI3K)/protein kinase B (AKT) signaling pathway biochemically. Furthermore, it was discovered that miR-218-5p specifically targets T-ICs' PUM1 3'-untranslated region (3'-UTR). More importantly, the PUM1/PI3K/AKT axis regulates CRC cells' responses to treatment with cetuximab, and PUM1 overexpression increased cetuximab resistance. More evidence points to the possibility that low PUM1 may predict cetuximab benefits in CRC patients after analysis of the patient cohort, patient-derived tumor organoids, and patient-derived xenografts (PDXs).

Conclusions

Taken together, the result of this work points to the critical function of the miR-218-5p/PUM1/PI3K/AKT regulatory circuit in regulating T-ICs characteristics and thus suggests possible therapeutic targets for CRC.