TMB: a promising immune-response biomarker, and potential spearhead in advancing targeted therapy trials

Exploration of SUSD3 in pan-cancer: studying its role, predictive analysis, and biological significance in various malignant tumors in humans

Background

The SUSD3 protein, marked by the Sushi domain, plays a key role in cancer progression, with its expression linked to tumor advancement and patient prognosis. Altered SUSD3 levels could serve as a predictive biomarker for cancer progression. Recognized as a novel susceptibility marker, SUSD3 presents a promising target for antibody-based therapies, offering a potential approach for the prevention, diagnosis, and treatment of breast cancer.

Methods

Using the HPA and GeneMANIA platforms, the distribution of SUSD3 protein across tissues was analyzed, while expression levels in tumor and healthy tissues were compared using The Cancer Genome Atlas data. The TISCH and STOmics DB databases facilitated the mapping of SUSD3 expression in different cell types and its spatial relationship with cancer markers. Univariate Cox regression assessed the prognostic significance of SUSD3 expression in various cancers. Genomic alterations of SUSD3 were explored through the cBioPortal database. The potential of SUSD3 as a predictor of immunotherapy response was investigated using TIMER2.0, and GSEA/GSVA identified related biological pathways. Drugs targeting SUSD3 were identified through CellMiner, CTRP, and GDSC databases, complemented by molecular docking studies. In vitro experiments demonstrated that SUSD3 knockdown in breast cancer cell lines significantly reduced proliferation and migration.

Results

SUSD3 expression variations in pan-cancer cohorts are closely linked to the prognosis of various malignancies. In the tumor microenvironment (TME), SUSD3 is predominantly expressed in monocytes/macrophages and CD4+ T cells. Research indicates a strong correlation between SUSD3 expression and key cancer immunotherapy biomarkers, immune cell infiltration, and immunomodulatory factors. To explore its immune regulatory role, StromalScore, ImmuneScore, ESTIMATE, and Immune Infiltration metrics were employed. Molecular docking studies revealed that selumetinib inhibits tumor cell proliferation. Finally, SUSD3 knockdown reduced cancer cell proliferation and migration.

Conclusion

These findings provide valuable insights and establish a foundation for further exploration of SUSD3's role in pan-carcinomas. Additionally, they offer novel perspectives and potential targets for the development of innovative therapeutic strategies in cancer treatment.

Pan-cancer analysis predicts MBOAT2 as a potential new ferroptosis related gene immune checkpoint

BACKGROUND

The phospholipid-modifying enzyme MBOAT2 plays a crucial role in iron homeostasis by inhibiting iron sequestration, thus preventing iron-induced cell death. It achieves this by remodeling the phospholipid composition of cell membranes through phospholipid metabolism. Although multiple studies have highlighted the significance of MBOAT2 in tumorigenesis, a comprehensive pan-cancer analysis has not been conducted to date.

METHODS

In this study, we analyzed the expression levels of MBOAT2 using RNA sequencing data from the TCGA and GTEx databases. We also investigated MBOAT2 protein information using resources such as the Human Protein Atlas (HPA), GeneCards, and String databases. To assess the prognostic value of MBOAT2, we conducted survival analysis based on clinical data from TCGA. Additionally, we performed enrichment analysis using the R package "clusterProfiler" and explored the relationship between MBOAT2 expression and immune cell infiltration, as well as immune checkpoint interactions in TCGA datasets. Furthermore, we examined the correlation between MBOAT2 expression and clinical pathology through immunohistochemical analysis of breast, prostate, lung, and liver cancer tissues in the HPA database. Finally, western blotting was used to validate MBOAT2 protein expression in breast and prostate cancer cell lines.

RESULTS

Our analysis revealed that MBOAT2 was highly expressed in a wide range of cancer types, with its expression correlating with improved survival outcomes in the TCGA dataset. Moreover, we found a significant association between MBOAT2 expression and immune regulation, particularly in relation to immune cell infiltration and immune checkpoint interactions.

CONCLUSION

MBOAT2 holds promise as a prognostic biomarker and may serve as a target for immunotherapy in various malignancies. Further investigation into its role in cancer immunity could offer new insights into potential therapeutic strategies.

HOXD8 drives Glioma progression through epithelial-mesenchymal transition regulation: Implications for prognosis and targeted therapy

Glioma is one of the most common primary malignant tumors of the central nervous system. Here, we defined Homeobox D8 (HOXD8) as a novel biomarker for glioma utilizing RNA-sequencing and bioinformatics approaches. HOXD8 expression was significantly upregulated in glioma cell lines (U251 and U373) and clinical specimens compared to normal controls. Functional studies demonstrated that HOXD8 knockdown markedly inhibited glioma cell proliferation, migration, and invasion in vitro. Additionally, pan-cancer analysis revealed significant associations between HOXD8 expression and key tumor characteristics, including immune cell infiltratio, tumor mutational burde, and microsatellite instability. Meanwhile, transcriptomic profiling and pathway analysis identified HOXD8's involvement in epithelial-mesenchymal transition (EMT) regulation, with Western blot validation showing significant modulation of EMT markers following HOXD8 knockdown. Collectively, our results suggests that HOXD8 may serve as a satisfactory prognostic biomarker that promotes glioma cell proliferation, migration and invasion, potentially through regulation of EMT processes.

Immunotherapy-related neurotoxicity in the central nervous system of children with cancer

Significant gaps remain in our understanding of immunotherapy-related neurotoxicity in pediatric patients, largely because much of our knowledge comes from studies in adults. Accurately identifying the adverse effects of immunotherapy in children is also challenging, owing to variations in terminology and grading systems. Moreover, the manifestation of immunotherapy-related neurotoxicity differs greatly across different diseases, various modalities, dosages, and delivery methods. Combining immunotherapy with other treatments might improve outcomes but introduces new complexities and potential for increased toxicities. Additionally, pediatric patients with intracranial malignancy have unique responses to immunotherapies and distinct neurotoxicity compared to those with extracranial malignancy. Consequently, we must enhance our understanding of the pathophysiology, prevalence, severity, and management of immunotherapy's neurotoxic effects in this vulnerable group. This review consolidates the current knowledge of immunotherapy-related neurotoxicity in pediatric oncology, highlighting various types of neurotoxicity including cytokine release syndrome (CRS), immune effector cell-associated neurotoxicity syndrome (ICANS), and tumor inflammation-associated neurotoxicity (TIAN), among others. Furthermore, we examine the unique features of neurotoxicity associated with adoptive cellular therapy (ACT), antibody-based therapies, immune checkpoint inhibitors (ICIs), oncolytic viruses (OV), and cancer vaccines.

Pan-Cancer Molecular Biomarkers: Practical Considerations for the Surgical Pathologist

Traditional anatomic pathologic classification of cancer is based on tissue of origin and morphologic and immunohistochemical characterization of the malignant cells. With the technological improvements of massively parallel or next-generation sequencing, oncogenic drivers that are shared across different tumor types are increasingly being identified and used as pan-cancer biomarkers. This approach is reflected in the growing list of Food and Drug Administration-approved tumor-agnostic therapies, including pembrolizumab in the setting of microsatellite instability and high tumor mutational burden, larotrectinib and entrectinib for solid tumors with NTRK fusions, and combined dabrafenib-trametinib for BRAF V600E-mutated neoplasms. Several other biomarkers are currently under investigation, including fibroblast growth factor receptor (FGFR), RET, and ROS1 fusions; ERBB2 amplification; and mutations in the AKT1/2/3, NF1, RAS pathway and (mitogen-activated protein kinase (MAPK) pathway. As molecular assays are increasingly incorporated into routine tumor workup, the emergence of additional pan-cancer biomarkers is likely to be a matter more of "when" than "if." In this review, we first explore some of the conceptual and technical considerations at the intersection of surgical and molecular pathology, followed by a brief overview of both established and emerging molecular pan-cancer biomarkers and their diagnostic and clinical applications.

Prognostic and therapeutic potential of CXCR6 expression on CD8 + T cells in gastric cancer: a retrospective cohort study

BACKGROUND

Gastric cancer (GC) is a pressing global health concern, with prognosis intricately linked to the tumour stage and tumour microenvironment, especially, the presence of immune cells. Notably, CD8 + T cells play a pivotal role in the anti-tumour immune response, prompting investigations into their correlation with GC survival. This study aimed to investigate the intricate interplay between CD8 + T cells, particularly within the context of CXCR6, and survival outcomes in patients with GC.

METHODS

Utilising datasets from The Cancer Genome Atlas, Gene Expression Omnibus, and Tumor Immune Dysfunction and Exclusion, the study employed xCell and Weighted Gene Co-expression Network Analysis to assess CD8 + T cell infiltration and identify key gene clusters. The prognostic significance of CXCR6 was evaluated via immunohistochemical staining of a GC tissue microarray.

RESULTS

High CD8 + T cell infiltration correlated with improved survival in patients with GC. CXCR6 was identified as a prognostic gene and its expression was predominantly observed in CD8 + T cells. CXCR6 expression positively correlated with improved overall and disease-free survival. Furthermore, CXCR6 expression was associated with an immunoreactive microenvironment.

CONCLUSION

This study established that high CD8 + T-cell infiltration is related to CXCR6 expression, making it a key factor in predicting a favorable GC prognosis. The role of CXCR6 in shaping the tumour microenvironment and its potential utility in immunotherapy response prediction highlights its significance in GC management.

Tumour mutational burden using a targeted panel approach for comprehensive tumour profiling focusing on colorectal cancer

There is an increasing recognition that comprehensive tumour profiling (CTP) represents an important adjunct to the diagnosis of malignancy providing not only an assessment of how many mutations there are in any given tumour which reflects the probability of immune checkpoint inhibitor success, but also which mutations are associated with targeted therapies, a signature that reflects environmental insult and potentially the identification of cancers of unknown origin.This short review describes an approach to assaying tumour mutational burden (TMB), what the difficulties are in the assessment of the TMB and what it can be applied to in regards to improving patient outcomes. A final section of the review delves into some examples of colorectal cancer studies that identify findings that suggest there remains much to learn about tumour development.

A comprehensive prognostic and immune analysis of LAPTM4B in pan-cancer and Philadelphia chromosome-positive acute lymphoblastic leukemia

Introduction

Lysosomal-associated protein transmembrane-4 beta (LAPTM4B) protein expression was increased in solid tumors, whereas few studies were performed in hematologic malignancies. We aimed to study the effect of the LAPTM4B gene in pan-cancer and Philadelphia chromosome-positive acute B cell lymphoblastic leukemia (Ph+ B-ALL).

Methods

The differential expression, diagnosis, prognosis, genetic and epigenetic alterations, tumor microenvironment, stemness, immune infiltration cells, function enrichment, single-cell analysis, and drug response across cancers were conducted based on multiple computational tools. Additionally, Ph+ B-ALL transgenic mouse model with Laptm4b knockout was used to analyze the function of LAPTM4B in vivo. BrdU incorporation method, flow cytometry, and Witte-lock Witte culture were used to evaluate the roles of LAPTM4B in vitro.

Results

We identified that LAPTM4B expression was increased in various cancers, with significant associations with clinical outcomes. LAPTM4B expression correlated with DNA and RNA methylation patterns and was associated with drug resistance. It also influenced the tumor immune microenvironment, with implications for immunotherapy response. In leukemia, LAPTM4B was expressed in stem cells and associated with specific subtypes. Knockout of LAPTM4B impeded B-ALL progression in mice and reduced cell proliferation and caused G0/G1 arrest in vitro.

Discussion

Our study elucidated the role LAPTM4B that promoted the development and progression in Ph+ B-ALL. Furthermore, LAPTM4B played a diagnostic, prognostic, and immunological factor.

Ensemble transformer-based multiple instance learning to predict pathological subtypes and tumor mutational burden from histopathological whole slide images of endometrial and colorectal cancer

In endometrial cancer (EC) and colorectal cancer (CRC), in addition to microsatellite instability, tumor mutational burden (TMB) has gradually gained attention as a genomic biomarker that can be used clinically to determine which patients may benefit from immune checkpoint inhibitors. High TMB is characterized by a large number of mutated genes, which encode aberrant tumor neoantigens, and implies a better response to immunotherapy. Hence, a part of EC and CRC patients associated with high TMB may have higher chances to receive immunotherapy. TMB measurement was mainly evaluated by whole-exome sequencing or next-generation sequencing, which was costly and difficult to be widely applied in all clinical cases. Therefore, an effective, efficient, low-cost and easily accessible tool is urgently needed to distinguish the TMB status of EC and CRC patients. In this study, we present a deep learning framework, namely Ensemble Transformer-based Multiple Instance Learning with Self-Supervised Learning Vision Transformer feature encoder (ETMIL-SSLViT), to predict pathological subtype and TMB status directly from the H&E stained whole slide images (WSIs) in EC and CRC patients, which is helpful for both pathological classification and cancer treatment planning. Our framework was evaluated on two different cancer cohorts, including an EC cohort with 918 histopathology WSIs from 529 patients and a CRC cohort with 1495 WSIs from 594 patients from The Cancer Genome Atlas. The experimental results show that the proposed methods achieved excellent performance and outperforming seven state-of-the-art (SOTA) methods in cancer subtype classification and TMB prediction on both cancer datasets. Fisher's exact test further validated that the associations between the predictions of the proposed models and the actual cancer subtype or TMB status are both extremely strong (p<0.001). These promising findings show the potential of our proposed methods to guide personalized treatment decisions by accurately predicting the EC and CRC subtype and the TMB status for effective immunotherapy planning for EC and CRC patients.

Comprehensive Pan-cancer Analysis Revealed CASP10 As a Promising Biomarker For Diverse Tumor Types

We aimed to explore the comprehensive cancer landscape of Caspase-10 (CASP10). CASP10, a member of the caspase family, is located at the human chromosome locus 2q33-34. Studies have suggested its potential role in the development of certain cancers. To evaluate CASP10 expression in normal and pan-cancer tissues, we integrated data from The Cancer Genome Atlas (TCGA), GEO, Human Protein Atlas (HPA), and UALCAN databases. The diagnostic and prognostic significance of CASP10 was analyzed using Receiver Operating Characteristic (ROC), Cox regression, and Kaplan-Meier analysis. Correlations of CASP10 with clinical parameters were assessed via the Wilcoxon test, Kruskal-Wallis test, and logistic regression analysis. Genomic variations were explored with cBioPortal, GSCALite database, and UALCAN databases. LinkedOmics database was used to detect the function of CASP10 in pan-cancer. Interactions between CASP10 and the Tumor Immune Microenvironment (TIME) were investigated using TISIDB, TIMER2, and TISCH databases. The GSCALite database was utilized to assess the sensitivity of CASP10 to small-molecule drugs. In addition, Western Blotting (WB) was employed to detect the expression of the CASP10 in our clinical Liver Hepatocellular Carcinoma (LIHC) and Stomach Adenocarcinoma (STAD) cohorts. The transcription and protein expression of CASP10 significantly differ across cancer types, marking it as a biomarker for diagnosis and prognosis. Its expression correlated with certain clinical characteristics such as histological types and Alpha-Fetoprotein (AFP) levels. CASP10 gene exhibited a 2% alteration frequency across pan-cancer patients, with significant SNV and CNV profiles, and decreased methylation levels. CASP10 was closely related to the Nuclear Factor-κappa B (NF-κB), TNF, cell cycle, and JAK-STAT signal pathways. CASP10 showed correlation with immune components in the tumor microenvironment, including lymphocytes, immune stimulators, immune inhibitors, MHC molecules, chemokines, receptors, and Cancer-Associated Fibroblasts (CAFs). Importantly, CASP10 could predict the sensitivity of diverse anti-cancer drugs. Finally, WB analysis validated the overexpression of CASP10 in LIHC and STAD tissues. Our comprehensive bioinformatic analysis reveal the function of CASP10 on the diagnosis, prognosis, and progression of diverse cancer types.

Pan-cancer bioinformatics indicates zinc finger protein 207 is a promising prognostic biomarker and immunotherapeutic target

In the era of personalized cancer treatment, understanding the complexities of tumor biology and immune modulation is paramount. This comprehensive analysis delves into the multifaceted role of zinc finger protein 207 (ZNF207) in pan-cancer, shedding light on its involvement in tumorigenesis, immune evasion, and therapeutic implications. Through integrated genomic and clinical data analysis, we reveal consistent upregulation of ZNF207 across diverse cancer types, highlighting its potential as a prognostic marker and therapeutic target, particularly for liver cancers. Notably, ZNF207 demonstrates intricate associations with clinical-pathological features, immune subtypes, and molecular pathways, indicating its pervasive influence in cancer biology. Furthermore, our study uncovers ZNF207's involvement in immune escape mechanisms, suggesting its potential as a modulator of immune responses within the tumor microenvironment. These findings underscore the significance of ZNF207 in shaping cancer progression and immune landscape, presenting promising avenues for targeted therapy and immunomodulation. Recognizing ZNF207's multifaceted contributions to cancer progression and immune evasion suggests its central role in understanding tumor immunology, beyond mere therapeutic targeting. Nevertheless, further mechanistic studies are imperative to elucidate ZNF207's precise molecular mechanisms and therapeutic implications in cancer treatment. This study primarily utilized various bioinformatics tools such as TIMER 2.0, cProSite, UALCAN, SangerBox, GEPIA2, TISIDB, and TIDE to analyze the expression of ZNF207 in multiple cancer samples from the TCGA database.

Deep learning for endometrial cancer subtyping and predicting tumor mutational burden from histopathological slides

Endometrial cancer (EC) diagnosis traditionally relies on tumor morphology and nuclear grade, but personalized therapy demands a deeper understanding of tumor mutational burden (TMB), i.e., a key biomarker for immune checkpoint inhibition and immunotherapy response. Traditional TMB prediction methods, such as sequencing exomes or whole genomes, are costly and often unavailable in clinical settings. We present the first TR-MAMIL deep learning framework to predict TMB status and classify the EC cancer subtype directly from H&E-stained WSIs, enabling effective personalized immunotherapy planning and prognostic refinement of EC patients. Our models were evaluated on a large dataset from The Cancer Genome Atlas. TR-MAMIL performed exceptionally well in classifying aggressive and non-aggressive EC, as well as predicting TMB, outperforming seven state-of-the-art approaches. It also performed well in classifying normal and abnormal p53 mutations in EC using H&E WSIs. Kaplan-Meier analysis further demonstrated TR-MAMIL's ability to differentiate patients with longer survival in the aggressive EC.

Pan-cancer analysis shows that BCAP31 is a potential prognostic and immunotherapeutic biomarker for multiple cancer types

Background

B-cell receptor-associated protein 31 (BCAP31) is a widely expressed transmembrane protein primarily located in the endoplasmic reticulum (ER), including the ER-mitochondria associated membranes. Emerging evidence suggests that BCAP31 may play a role in cancer development and progression, although its specific effects across different cancer types remain incompletely understood.

Methods

The raw data on BCAP31 expression in tumor and adjacent non-tumor (paracancerous) samples were obtained from the Broad Institute Cancer Cell Line Encyclopedia (CCLE) and UCSC databases. We also examined the association between BCAP31 expression and clinicopathological factors. Using the Cox proportional hazards model, we found that high BCAP31 levels were linked to poor prognosis. To further explore BCAP31's role, we analyzed the relationship between copy number variations (CNV) and BCAP31 mRNA expression using data from The Cancer Genome Atlas (TCGA). Additionally, the association between BCAP31 expression and signature pathway scores from the MsigDB database provided insights into the tumor biology and immunological characteristics of BCAP31.We assessed the relationship between tumor immune infiltration and BCAP31 expression using the TIMER2 and ImmuCellAI databases. The ESTIMATE computational method was employed to estimate the proportion of immune cells infiltrating the tumors, as well as the stromal and immune components, based on TCGA data. To investigate drug sensitivity in relation to BCAP31 expression, we utilized GDSC2 data, which included responses to 198 medications. We explored the relationship between BCAP31 gene expression and response to immunotherapy. Additionally, the study involved culturing KYSE-150 cells under standard conditions and using siRNA-mediated knockdown of BCAP31 to assess its function. Key experiments included Western blotting (WB) to confirm BCAP31 knockdown, MTT assays for cell proliferation, colony formation assays for growth potential, Transwell assays for migration and invasion, and wound healing assays for motility. Additionally, immunohistochemistry (IHC) was performed on tumor and adjacent normal tissue samples to evaluate BCAP31 expression levels.

Results

BCAP31 was found to be significantly overexpressed in several prevalent malignancies and was associated with poor prognosis. Cox regression analysis across all cancer types revealed that higher BCAP31 levels were predominantly linked to worse overall survival (OS), disease-free interval (DFI), disease-specific survival (DSS), and progression-free interval (PFI). In most malignancies, increased BCAP31 expression was positively correlated with higher CNV. Additionally, BCAP31 expression was strongly associated with the tumor microenvironment (TME), influencing the levels of infiltrating immune cells, immune-related genes, and immune-related pathways. Drug sensitivity analysis identified six medications that showed a significant positive correlation with BCAP31 expression. Furthermore, BCAP31 expression impacted the outcomes and prognosis of cancer patients undergoing immune therapy. The functional assays demonstrated that BCAP31 knockdown in KYSE-150 cells significantly inhibited cell migration, invasion, and proliferation while enhancing colony formation ability. WB and immunohistochemistry analyses confirmed elevated BCAP31 expression in tumor tissues compared to adjacent normal tissues in esophageal cancer, lung adenocarcinoma, and gastric adenocarcinoma.

Conclusion

BCAP31 has the potential to serve as a biomarker for cancer immunology, particularly in relation to immune cell infiltration, and as an indicator of poor prognosis. These findings provide a new perspective that could inform the development of more targeted cancer therapy strategies.

Different characteristics of the tumor immune microenvironment among subtypes of salivary gland cancer

AIM

Although immune checkpoint inhibitors (ICPi) for salivary gland cancer (SGC) have been investigated in clinical trials, details of the tumor immune microenvironment (TIME) remain unclear. This research aimed to elucidate the TIME of SGC and its relationship with tumor mutation burden (TMB) and to explore the rationale for the applicability of ICPi.

MATERIALS AND METHODS

We selected five pathological types, namely adenoid cystic carcinoma (ACC); adenocarcinoma, not otherwise specified (ANOS); salivary duct carcinoma (SDC); and low/high-grade mucoepidermoid carcinoma (MEClow/high). We investigated the TIME and TMB of each pathological type. TIME was evaluated by multiplexed fluorescent immunohistochemistry. TMB was measured by next-generation sequencing.

RESULTS

ACC and MEChigh showed the lowest and highest infiltration of immune effector and suppressor cells in both tumor and stroma. ANOS, SDC, and MEClow showed modest infiltration of immune effector cells in tumors. Correlation analysis showed a positive correlation between CD3+CD8+ T cells in tumor and TMB (r = 0.647). CD3+CD8+ T cells in tumors showed a positive correlation with programmed cell death-ligand 1 expression in tumor cells (r = 0.513) and a weak positive correlation with CD3+CD4+Foxp3+ cells in tumors (r = 0.399). However, no correlation was observed between CD3+CD8+ T cells and CD204+ cells in tumors (r = -0.049).

CONCLUSION

The TIME of ACC was the so-called immune desert type, which may explain the mechanisms of the poor response to ICPi in previous clinical trials. On the other hand, MEChigh was the immune-inflamed type, and this may support the rationale of ICPi for this pathological subtype.

SLITRK2 as a prognostic and immunological biomarker in gastric cancer

BACKGROUND

SLIT and NTRK-like protein 2 (SLITRK2) encodes a transmembrane protein that regulates neurite outgrowth. Some studies have demonstrated that SLITRK2 overexpressed in glioma. But the expression pattern, prognostic value and immunologic function of SLITRK2 in tumors remains unknown.

METHODS

The expression pattern of SLITRK2 among pan-cancers was examined through the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). We analyzed the association between SLITRK2 expression level and tumor stage among pan-cancers. Kaplan-Meier survival analysis was utilized to investigate the prognostic relevance of SLITRK2 across 33 different types of cancers. Moreover, the correlations among SLITRK2 expression, immune cell infiltration, immunomodulatory related genes, tumor mutation burden (TMB), microsatellite instability (MSI) were evaluated. The relationship between SLITRK2 expression and crucial genes mutations was also illustrated. By using tissue microarray (TMA), the expression of SLITRK2 in 89 paired gastric cancer (GC) tissues was investigated.

RESULTS

Our study indicated that SLITRK2 expression varied across cancers. Elevated SLITRK2 expression was positively related to advanced tumor stage, poor overall survival (OS) and reduced disease-free survival (DFS). Bioinformatic analyses underscore SLITRK2's role in immune response, with its expression significantly tied to immune cell infiltration and marker expression. Based on TMA data, SLITRK2 expression level was positively associated with differentiation, lymph node metastasis, AJCC stage, TNM stage, and poor survival outcome in GC patients.

CONCLUSION

Our findings provided that SLITRK2 may function as a biomarker by regulating immune cell infiltration. In addition, we verified that high SLITRK2 expression was correlated with poor prognosis in GC.

Unlocking the potential of immunotherapy in platinum-resistant ovarian cancer: rationale, challenges, and novel strategies

Ovarian cancer is a significant global health challenge, with cytoreductive surgery and platinum-based chemotherapy serving as established primary treatments. Unfortunately, most patients relapse and ultimately become platinum-resistant, at which point there are limited effective treatment options. Given the success of immunotherapy in inducing durable treatment responses in several other cancers, its potential in platinum-resistant ovarian cancer (PROC) is currently being investigated. However, in unselected advanced ovarian cancer populations, researchers have reported low response rates to immune checkpoint inhibition, and thus far, no validated biomarkers are predictive of response. Understanding the intricate interplay between platinum resistance, immune recognition, and the tumour microenvironment (TME) is crucial. In this review, we examine the research challenges encountered thus far, the biological rationale for immunotherapy, the underlying mechanisms of immune resistance, and new strategies to overcome resistance.

Improving efficacy of TNBC immunotherapy: based on analysis and subtyping of immune microenvironment

Triple-negative breast cancer (TNBC) is a highly aggressive type of breast cancer that encompasses several distinct subtypes. Recent advances in immunotherapy offer a promising future for the treatment of these highly heterogeneous and readily metastatic tumors. Despite advancements, the efficacy of immunotherapy remains limited as shown by unimproved efficacy of PD-L1 biomarker and limited patient benefit. To enhance the effectiveness of TNBC immunotherapy, we conducted investigation on the microenvironment, and corresponding therapeutic interventions of TNBC and recommended further investigation into the identification of additional biomarkers that can facilitate the subtyping of TNBC for more targeted therapeutic approaches. TNBC is a highly aggressive subtype with dismal long-term survival due to the lack of opportunities for traditional endocrine and targeted therapies. Recent advances in immunotherapy have shown promise, but response rates can be limited due to the heterogeneous tumor microenvironments and developed therapy resistance, especially in metastatic cases. In this review, we will investigate the tumor microenvironment of TNBC and corresponding therapeutic interventions. We will summarize current subtyping strategies and available biomarkers for TNBC immunotherapy, with a particular emphasis on the need for further research to identify additional prognostic markers and refine tailored therapies for specific TNBC subtypes. These efforts aim to improve treatment sensitivity and ultimately enhance survival outcomes for advanced-stage TNBC patients.

Pan-cancer exploration of PNO1: A prospective prognostic biomarker with ties to immune infiltration

The partner of NOB1 homolog (PNO1) is an RNA-binding protein that participates in ribosome biogenesis and protein modification. The functions of this molecule are largely unknown in cancers, particularly breast cancer. We employed bioinformatics methods to probe the putative oncogenic functions of PNO1 based on expression profiles and clinical data from the cancer genome atlas (TCGA), genotype-tissue expression project (GTEx), human protein atlas (HPA), cancer cell line encyclopedia (CCLE), UALCAN, drug sensitivity in cancer (GDSC) and UCSC XENA databases. Our analyses revealed that PNO1 was overexpressed in 31 malignancies, which excluded kidney chromophobe (KICH) and acute myeloid leukemia (LAML). Prognostic assessments have demonstrated that high PNO1 expression was significantly correlated with poor overall and disease-specific survival in various cancers. The promoter methylation level of PNO1 is significantly decreased in breast invasive carcinoma (BRCA), head and neck squamous cell carcinoma (HNSC), kidney renal papillary cell carcinoma (KIRP), prostate adenocarcinoma (PRAD), thyroid carcinoma (THCA) and uterine corpus endometrial carcinoma (UCEC). Furthermore, inhibition of PNO1 decreased the viability, migration and invasion of breast cancer cells, and these results were confirmed by mouse xenograft models of breast cancer. In addition, we discovered that tumor microenvironment (TME), immune infiltration, and chemotherapy sensitivity were influenced by PNO1 expression. Concordantly, our analyses revealed a significant positive correlation between PNO1 and programmed cell death ligand 1 (PD-L1) expression across breast carcinoma samples. In conclusion, these findings indicate that PNO1 could act as a promising prognostic biomarker and adjunct diagnostic indicator, because it affects tumor growth and invasion. Our study offers valuable new perspectives on the oncogenic role of PNO1 in various types of cancers.

Integrating Bulk and Single-Cell RNA-Seq Data to Identify Prognostic Features Related to Activated Dendritic Cells in Clear-Cell Renal-Cell Carcinoma

Dendritic cells (DCs) serve as key regulators in tumor immunity, with activated DCs potentiating antitumor responses through the secretion of pro-inflammatory cytokines and the expression of co-stimulatory molecules. Most current studies focus on the relationship between DC subgroups and clear-cell renal-cell carcinoma (ccRCC), but there is limited research on the connection between DCs and ccRCC from the perspective of immune activation. In this study, activated DC genes were identified in both bulk and single-cell RNA-seq data. A prognostic model related to activated DCs was constructed using univariate, multivariate Cox regression and LASSO regression. The prognostic model was validated in three external validation sets: GSE167573, ICGC, and E-MTAB-1980. The prognostic model consists of five genes, PLCB2, XCR1, IFNG, HLA-DQB2, and SMIM24. The expression of these genes was validated in tissue samples using qRT-PCR. Stratified analysis revealed that the prognostic model was able to better predict outcomes in advanced ccRCC patients. The risk scores were associated with tumor progression, tumor mutation burden, immune cell infiltration, and adverse outcomes of immunotherapy. Notably, there was a strong correlation between the expression of the five genes and the sensitivity to JQ1, a BET inhibitor. Molecular docking indicated high-affinity binding of the proteins encoded by these genes with JQ1. In conclusion, our study reveals the crucial role of activated DCs in ccRCC, offering new insights into predicting immune response, targeted therapy effectiveness, and prognosis for ccRCC patients.

Gemogenovatucel-T (Vigil): bi-shRNA plasmid-based targeted immunotherapy

We describe in this review the historical evidence leading up to the concept and design of Vigil and subsequent clinical applications including safety and efficacy in a randomized, controlled Phase IIB trial. Vigil (gemogenovatucel-T) is a unique triple function targeted immunotherapy that demonstrates preclinical and clinical systemic anticancer activity. Construction of Vigil involves harvest of autologous malignant tissue for neoantigen targeting (ideally containing clonal neoantigens) followed by a two-day process involving transfection with a plasmid to provide a permissive 'training environment' for the patient's immune system. Transfected plasmid components contain an expressive human GMCSF DNA segment to enhance anticancer immune functional response and a second component expressing bi-shRNAfurin which reduces TGFβ isomers (TGFβ1 and TGFβ2) thereby reducing cancer inhibition of the targeted immune response. Results generated to date justify advancement to confirmatory clinical trials supporting product regulatory approval.

MIS18A upregulation promotes cell viability, migration and tumor immune evasion in lung adenocarcinoma

Lung adenocarcinoma (LUAD) presents a significant global health challenge owing to its poor prognosis and high mortality rates. Despite its involvement in the initiation and progression of a number of cancer types, the understanding of the precise impact of MIS18 kinetochore protein A (MIS18A) on LUAD remains incomplete. In the present study, the role of MIS18A in LUAD was investigated by analyzing the genomic and clinical data from multiple public datasets. The expression of MIS18A was validated using reverse transcription-quantitative polymerase chain reaction, and in vitro experiments involving small interfering RNA-induced downregulation of MIS18A in lung cancer cells were conducted to further explore its impact. These findings revealed that elevated MIS18A expression in LUAD was associated with advanced clinical features and poor prognosis. Functional analysis also revealed the role of MIS18A in regulating the cell cycle and immune-related pathways. Moreover, MIS18A altered the immune microenvironment in LUAD, influencing its response to immunotherapy and drug sensitivity. The results of the in vitro experiments indicated that suppression of MIS18A expression reduced the proliferative and migratory capacities of LUAD cells. In summary, MIS18A possesses potential as a biomarker and may serve as a possible therapeutic target for LUAD, with significant implications for tumor progression by influencing both cell cycle dynamics and immune infiltration.

Pan-cancer analysis of COL15A1: an immunological and prognostic biomarker

Collagen, type XV, alpha 1 (COL15A1) belongs to the collagen superfamily, which can influence disease progression by modulating immune pathways. Although the growing number of investigations demonstrating the indispensable role of COL15A1 in the progression of certain tumors, no pan-cancer assessment of COL15A1 is accessible to date. Therefore, the available data was used to explore the role of COL15A1 in 33 types of tumors and to investigate their potential immune function. Numerous bioinformatics approaches were used to research the potential oncogenic role of COL15A1, including analysis of tumor prognosis, microsatellite instability (MSI), tumor mutational burden (TMB), single nucleotide polymorphism (SNP), drug sensitivity, immune cell infiltration, and the correlation between cancer stem cells (CSCs) and COL15A1 expression. The outcome implies that most tumors had a high expression of COL15A1, and COL15A1 manifested different relationships with prognosis in different tumors, including both positive and negative correlations. COL15A1 was also found to have a significant correlation with MSI, TMB, and immune infiltrating cells. Our study suggests that COL15A1 may serve as a prognostic marker for malignancy because of its differential expression in tissues and their function in tumor immunity.

Systematic pan-cancer analysis insights into ICAM1 as an immunological and prognostic biomarker

Intercellular adhesion molecule 1 (ICAM1) is a cell surface adhesion glycoprotein in the immunoglobulin supergene family. It is associated with several epithelial tumorigenesis processes, as well as with inflammation. However, the function of ICAM1 in the prognosis of tumor immunity is still unclear. This study aimed to examine the immune function of ICAM1 in 33 tumor types and to investigate the prognostic value of tumors. Using datasets from the Cancer Genome Atlas (TCGA), Genotype Tissue Expression (GTEx), Cancer Cell Lines Encyclopedia (CCLE), Human Protein Atlas (HPA), and cBioPortal, we investigated the role of ICAM1 in tumors. We explored the potential correlation between ICAM1 expression and tumor prognosis, gene mutations, microsatellite instability, and tumor immune cell levels in various cancers. We observed that ICAM1 is highly expressed in multiple malignant tumors. Furthermore, ICAM1 is negatively or positively associated with different malignant tumor prognoses. The expression levels of ICAM1 were correlated with the tumor mutation burden (TMB) in 11 tumors and with MSI in eight tumors. ICAM1 is a gene associated with immune infiltrating cells, such as M1 macrophages and CD8+ T cells in gastric and colon cancer. Meanwhile, the expression of ICAM1 is associated with several immune-related functions and immune-regulation-related signaling pathways, such as the chemokine signaling pathway. Our study shows that ICAM1 can be used as a prognostic biomarker in many cancer types because of its function in tumorigenesis and malignant tumor immunity.

PCDH11X mutation as a potential biomarker for immune checkpoint therapies in lung adenocarcinoma

Immune checkpoint inhibitors (ICIs) have achieved impressive success in lung adenocarcinoma (LUAD). However, the response to ICIs varies among patients, and predictive biomarkers are urgently needed. PCDH11X is frequently mutated in LUAD, while its role in ICI treatment is unclear. In this study, we curated genomic and clinical data of 151 LUAD patients receiving ICIs from three independent cohorts. Relations between PCDH11X and treatment outcomes of ICIs were examined. A melanoma cohort collected from five published studies, a pan-cancer cohort, and non-ICI-treated TCGA-LUAD cohort were also examined to investigate whether PCDH11X mutation is a specific predictive biomarker for LUAD ICI treatment. Among the three ICI-treated LUAD cohorts, PCDH11X mutation (PCDH11X-MUT) was associated with better clinical response compared to wild-type PCDH11X (PCDH11X-WT). While in ICI-treated melanoma cohort, the pan-cancer cohort excluding LUAD, and the non-ICI-treated TCGA-LUAD cohort, no significant differences in overall survival (OS) were observed between the PCDH11X-MUT and PCDH11X-WT groups. PCDH11X mutation was associated with increased PD-L1 expression, tumor mutation burden (TMB), neoantigen load, DNA damage repair (DDR) mutations, and hot tumor microenvironment in TCGA-LUAD cohort. Our findings suggested that the PCDH11X mutation might serve as a specific biomarker to predict the efficacy of ICIs for LUAD patients. Considering the relatively small sample size of ICI-treated cohorts, future research with larger cohorts and prospective clinical trials will be essential for validating and further exploring the role of PCDH11X mutation in the context of immunotherapy outcomes in LUAD. KEY MESSAGES: PCDH11X mutation is associated with better clinical response compared to wild type PCDH11X in three ICIs-treated LUAD cohorts. In ICIs-treated melanoma cohort, the pan-cancer cohort excluding LUAD, and non-ICIs-treated TCGA-LUAD cohorts PCDH11X mutation is not associated with better clinical response, suggesting PCDH11X mutation might be a specific biomarker to predict the efficacy of ICIs treatment for LUAD patients. PCDH11X mutation is associated with increased PD-L1 expression, tumor mutation burden, and neoantigen load in TCGA-LUAD cohort. PCDH11X mutation is associated with hot tumor microenvironment in TCGA-LUAD cohort.

Assessing the predictive value of smoking history for immunotherapy outcomes in bladder cancer patients

BACKGROUND

The therapeutic effectiveness of immune checkpoint inhibitors (ICIs) in bladder cancer varies among individuals. Identifying reliable predictors of response to these therapies is crucial for optimizing patient outcomes.

METHODS

This retrospective study analyzed 348 bladder cancer patients treated with ICIs, with additional validation using data from 248 patients at our institution who underwent PD-L1 immunohistochemical staining. We examined patient smoking history, clinicopathological characteristics, and immune phenotypes. The main focus was the correlation between smoking history and immunotherapy outcomes. Multivariate logistic and Cox proportional hazard regressions were used to adjust for confounders.

RESULTS

The study cohort comprised 348 bladder cancer patients receiving ICIs. Among them, 116 (33.3%) were never smokers, 197 (56.6%) were former smokers (median pack-years = 28), and 35 (10.1%) were current smokers (median pack-years = 40). Analysis revealed no statistically significant difference in overall survival across different smoking statuses (objective response rates were 11.4% for current smokers, 17.2% for never smokers, and 22.3% for former smokers; P = 0.142, 0.410, and 0.281, respectively). However, a notable trend indicated a potentially better response to immunotherapy in former smokers compared to current and never smokers. In the validation cohort of 248 patients from our institution, immunohistochemical analysis showed that PD-L1 expression was significantly higher in former smokers (55%) compared to current smokers (37%) and never smokers (47%). This observation underscores the potential influence of smoking history on the tumor microenvironment and its responsiveness to ICIs.

CONCLUSION

In conclusion, our study demonstrates the importance of incorporating smoking history in predicting the response to immunotherapy in bladder cancer patients, highlighting its role in personalized cancer treatment approaches. Further research is suggested to explore the comprehensive impact of lifestyle factors on treatment outcomes.

Comparison of target agent treatment strategies for platinum-resistant recurrent ovarian cancer: A Bayesian network meta-analysis

BACKGROUND

We aimed to compare 7 newer immunotherapies and targeted therapies for platinum-resistant relapsed ovarian cancer.

METHODS

We conducted a comprehensive search of PubMed, EMBASE, and Cochrane Library electronic databases for phase III trials involving platinum-resistant recurrent ovarian cancer (PRrOC) patients treated with immunotherapy or targeted therapy in combination with chemotherapy. The quality of the included trials was assessed using the GRADE method. The primary outcome of comparison was progression-free survival, and secondary outcomes included overall survival and safety.

RESULTS

This analysis included 7 randomized phase III controlled trials, encompassing 2485 PRrOC patients. Combining bevacizumab plus chemotherapy and lurbinectedin demonstrated statistically significant differences in progression-free survival compared to all other regimens of interest. However, no statistically significant differences were observed in the overall survival. Nivolumab and mirvetuximab exhibited fewer serious adverse events than the other regimens of interest.

CONCLUSIONS

Our findings indicate that bevacizumab combined with chemotherapy and lurbinectedin monotherapy has significant efficacy in patients with PRrOC. For patients with PRrOC who have exhausted treatment options, nivolumab and mirvetuximab may be considered as alternatives because of their better safety profiles.

Assessing personalized responses to anti-PD-1 treatment using patient-derived lung tumor-on-chip

There is a compelling need for approaches to predict the efficacy of immunotherapy drugs. Tumor-on-chip technology exploits microfluidics to generate 3D cell co-cultures embedded in hydrogels that recapitulate simplified tumor ecosystems. Here, we present the development and validation of lung tumor-on-chip platforms to quickly and precisely measure ex vivo the effects of immune checkpoint inhibitors on T cell-mediated cancer cell death by exploiting the power of live imaging and advanced image analysis algorithms. The integration of autologous immunosuppressive FAP+ cancer-associated fibroblasts impaired the response to anti-PD-1, indicating that tumors-on-chips are capable of recapitulating stroma-dependent mechanisms of immunotherapy resistance. For a small cohort of non-small cell lung cancer patients, we generated personalized tumors-on-chips with their autologous primary cells isolated from fresh tumor samples, and we measured the responses to anti-PD-1 treatment. These results support the power of tumor-on-chip technology in immuno-oncology research and open a path to future clinical validations.

GJB3: a comprehensive biomarker in pan-cancer prognosis and immunotherapy prediction

BACKGROUND

A wide range of connexins are situated between normal-normal cells, cancer-cancer cells, and cancer-normal cells. Abnormalities in connexin expression are typically accompanied by cancer development; however, no systematic studies have examined the role of Gap Junction Protein Beta 3 (GJB3) in the context of tumor progression and immunity, especially when considering a broad range of cancer types.

METHODS

In this study, data on GJB3 expression were gathered from Genotype-Tissue Expression, Cancer Cell Line Encyclopedia, and The Cancer Genome Atlas databases. Then, we analyzed the relationship between GJB3 expression and tumor characteristics. In vitro experiments using colony formation, EdU, CCK8, transwell migration assays, immunohistochemistry and western blot were performed to investigate the function of GJB3 in tumor progression of various cell lines. A drug sensitivity analysis of GJB3 was performed using the Genomics of Drug Sensitivity in Cancer database.

RESULT

Our findings demonstrate that GJB3 is widely expressed in various cancers and correlates significantly with disease stages, patient survival, immunotherapy response, and pharmaceutical guidance. Additionally, GJB3 plays a role in different cancer pathways, as well as in different immune and molecular subtypes of cancer. Co-expression of GJB3 with immune checkpoint genes was observed. Further experiments showed that knockdown of GJB3 inhibited the PI3K/AKT pathway and resulted in reduced proliferation, migration, and viability of different cancer cells.

CONCLUSION

Overall, GJB3 shows potential as a molecular biomarker and therapeutic target for various cancers, particularly lung adenocarcinomas, mesothelioma, pancreatic adenocarcinoma. Thus, GJB3 may represent a new therapeutic target for a wide range of cancers.

Characteristics of Ovarian Cancer Immune Cell Invasion and Bioinformatics to Predict the Effect of Immunotherapy

Recent studies have confirmed that tumor immune cell infiltration (ICI) is associated with sensitivity of ovarian cancer (OC) immunotherapy and disease progression of OC patients. However, studies related to immune infiltration in OC, has not been elucidated. Two algorithms are used to analyze the OC data in the TCGA and GEO databases. After combining the two data sets, the immune cell content of the sample was estimated by Cell-type Identification By Estimate Relative Subsets of RNA Transcripts (CIBERSORT method). An unsupervised consistent clustering algorithm was used to analyze ICI subtypes and their differentially expressed genes (DEGs). Two subgroups and three ICI gene clusters were identified by unsupervised consensus clustering algorithm. The ICI score was obtained by analyzing the gene characteristics through principal component analysis (PCA). The ICI score ranged from -15.8132 to 18.7211, which was associated with the prognosis of OC patients with immunotherapy. The Toll-like receptor pathway, B-cell receptor pathway, antigen processing and presentation pathway, NK-cell-mediated cytotoxicity pathway, and arginine-proline metabolism pathway were activated in the high ICI score group, suggesting that immune cells in the high ICI score group were activated, thus leading to a better prognosis in this group of patients. Patients with G3-G4 in the high ICI rating group were more sensitive to immunotherapy and had a better prognosis in patients with high tumor mutation burden (TMB). This study suggests that ICI scores can be used as a feasible auxiliary indicator for predicting the prognosis of patients with OC.

Pan-cancer analysis of SERPINE family genes as biomarkers of cancer prognosis and response to therapy

Background: Serine protease inhibitor E (SERPINE) family genes participate in the tumor growth, cancer cell survival and metastasis. However, the SERPINE family members role in the prognosis and their clinical therapeutic potentials in various human cancer types have not been elaborately explored. Methods: We preliminarily analyzed expression levels and prognostic values of SERPINE family genes, and investigated the correlation between SERPINEs expression and tumor microenvironment (TME), Stemness score, clinical characteristic, immune infiltration, tumor mutational burden (TMB), immune subtype, and drug sensitivity in pan-cancer, which based on updated public databases and integrated some bioinformatics analysis methods. In addition, we conducted the enrichment analysis of SERPINEs from DAVID and KOBAS databases. Results: SERPINE1, SERPINE2, and SERPINE3 expression were upregulated in nine cancers, twelve cancers, and six cancers, respectively. The expression of SERPINE family genes was associated with the prognosis in several cancers from The Cancer Genome Atlas (TCGA). Furthermore, SERPINE family genes expression also had a significant relation to stromal and immune scores, and RNA stemness score and DNA stemness score in pan-cancer. SERPINE1 and SERPINE2 expression significantly increased in tumor advanced stage in colon adenocarcinoma (COAD). Results showed that SERPINE1 and SERPINE2 expression were negatively related with B cells and Monocytes, respectively. SERPINE2 expression had a significantly positive relation with B cells and Macrophages. In terms of TMB, SERPINE1, SERPINE2, and SERPINE3 were found to associated with TMB in seven cancers, fourteen cancers, and four cancers, respectively. Moreover, all SERPINE gene family members were significantly correlated with immune subtypes. SERPINE1 expression had a significantly positive or negative correlation with drug sensitivity. Conclusion: The study indicated the great potential of SERPINE family genes as biomarkers for prognosis and provided valuable strategies for further investigation of SERPINE family genes as potential targets in cancer.

A tumor-infiltrating immune cells-related pseudogenes signature based on machine-learning predicts outcomes and immunotherapy responses in ovarian cancer

Previous researches have provided evidence for the significant involvement of pseudogenes in immune-related functions across different types of cancer. However, the mechanisms by which pseudogenes regulate immunity in ovarian cancer (OV) and their potential impact on clinical outcomes remain unclear. To address this gap in knowledge, our study utilized a novel computational framework to analyze a total of 491 samples from three public datasets. We employed a combination of 10 machine-learning algorithms to construct a signature known as the tumor-infiltrating immune cells-related pseudogenes signature (TIICPS). The TIICPS, consisting of 12 pseudogenes, demonstrated independent prognostic value for overall survival, surpassing conventional clinical traits, 62 published signatures, and TP53 and BRCA mutation status in three cohorts. Patients with low TIICPS exhibited heightened immune-related pathways, intricate genomic alterations, substantial immune infiltration, and greater potential for immunotherapy efficacy. Consequently, TIICPS holds promise as a predictive tool for prognosis and immunotherapy response in ovarian cancer.

Comprehensive pan-cancer investigation: unraveling the oncogenic, prognostic, and immunological significance of Abelson interactor family member 3 gene in human malignancies

Background: Abelson interactor Family Member 3 (ABI3) encodes protein that not only suppresses the ectopic metastasis of tumor cells but also hinders their migration. Although ABI3 had been found to modulate the advancement of diverse neoplasms, there is no comprehensive pan-cancer analysis of its effects. Methods: The transcriptomics data of neoplasm and normal tissues were retrieved from the Genomic Data Commons (GDC) data portal, and UCSC XENA database. To gather protein information for ABI3, Human Protein Atlas (HPA) and GeneMANIA websites were utilized. Additionally, Tumor Immune Single-cell Hub (TISCH) database was consulted to determine the primary cell types expressing ABI3 in cancer microenvironments. Univariate Cox regression approach was leveraged to evaluate ABI3's prognostic role across cancers. The Cbioportal and Gene Set Cancer Analysis (GSCA) website were leveraged to scrutinize the genomic landscape information across cancers. TIMER2.0 was leveraged to probe the immune cell infiltrations associated with ABI3 across cancers. The associations of ABI3 with immune-related genes were analyzed through Spearman correlation method. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were utilized to search associated biological pathways. The CellMiner database and molecular docking were implemented to identify potential interactions between the ABI3 protein and specific anticarcinogen. Findings: ABI3 expression and its ability to predict prognosis varied distinct tumor, with particularly high expression observed in Tprolif cells and monocytes/macrophages. Copy number variation (CNV) and methylation negatively correlated with ABI3 expression in the majority of malignancies. Corresponding mutation survival analysis indicated that the mutation status of ABI3 was strongly connected to the prognosis of LGG patients. ABI3 expression was linked to immunotherapeutic biomarkers and response in cancers. ESTIMATE and immune infiltrations analyses presented ABI3 association with immunosuppression. ABI3 was significantly correlated with immunoregulators and immune-related pathways. Lastly, prospective ABI3-targeted drugs were filtered and docked to ABI3 protein. Interpretation: Our study reveals that ABI3 acts as a robust tumor biomarker. Its functions are vital that could inhibit ectopic metastasis of tumor cells and modulate cellular adhesion and migration. The discoveries presented here may have noteworthy consequences for the creation of fresh anticancer suppressors, especially those targeting BRCA.

PHF5A is a potential diagnostic, prognostic, and immunological biomarker in pan-cancer

Studying the molecular mechanisms and regulatory functions of genes is crucial for exploring new approaches and tactics in cancer therapy. Studies have shown that the aberrant expression of PHF5A in tumors is linked to the origin and advancement of multiple cancers. However, its role in diagnosis, prognosis, and immunological prediction has not been comprehensively investigated in a pan-cancer analysis. Using several bioinformatic tools, we conducted a systematic examination of the potential carcinogenesis of PHF5A in various tumors from multiple aspects. Our analysis indicated that PHF5A expression varied between normal and tumor tissues and was linked to clinical diagnosis and prognosis in various cancers. The results confirmed a notable variation in the levels of PHF5A promoter methylation among several types of primary tumor and normal tissues and methylation of the PHF5A promoter played a guiding role in prognosis in some cancers. According to our findings, PHF5A played a critical role in tumor immunity and it might be an excellent target for anticancer immunotherapy. To sum up, PHF5A can be used in pan-cancer diagnostics, prognostics, and immunotherapy.

Pan-cancer analysis of IFN-γ with possible immunotherapeutic significance: a verification of single-cell sequencing and bulk omics research

Background

Interferon-gamma (IFN-γ), commonly referred to as type II interferon, is a crucial cytokine that coordinates the tumor immune process and has received considerable attention in tumor immunotherapy research. Previous studies have discussed the role and mechanisms associated with IFN-γ in specific tumors or diseases, but the relevant role of IFN-γ in pan-cancer remains uncertain.

Methods

TCGA and GTEx RNA expression data and clinical data were downloaded. Additionally, we analyzed the role of IFN-γ on tumors by using a bioinformatic approach, which included the analysis of the correlation between IFN-γ in different tumors and expression, prognosis, functional status, TMB, MSI, immune cell infiltration, and TIDE. We also developed a PPI network for topological analysis of the network, identifying hub genes as those having a degree greater than IFN-γ levels.

Result

IFN-γ was differentially expressed and predicted different survival statuses in a majority of tumor types in TCGA. Additionally, IFN-γ expression was strongly linked to factors like infiltration of T cells, immune checkpoints, immune-activating genes, immunosuppressive genes, chemokines, and chemokine receptors, as well as tumor purity, functional statuses, and prognostic value. Also, prognosis, CNV, and treatment response were all substantially correlated with IFN-γ-related gene expression. Particularly, the IFN-γ-related gene STAT1 exhibited the greatest percentage of SNVs and the largest percentage of SNPs in UCEC. Elevated expression levels of IFN-γ-related genes were found in a wide variety of tumor types, and this was shown to be positively linked to drug sensitivity for 20 different types of drugs.

Conclusion

IFN-γ is a good indicator of response to tumor immunotherapy and is likely to limit tumor progression, offering a novel approach for immunotherapy's future development.

TERT expression is associated with metastasis from thin primaries, exhausted CD4+ T cells in melanoma and with DNA repair across cancer entities

Telomerase reverse transcriptase (TERT) promoter mutations occur frequently in cancer, have been associated with increased TERT expression and cell proliferation, and could potentially influence therapeutic regimens for melanoma. As the role of TERT expression in malignant melanoma and the non-canonical functions of TERT remain understudied, we aimed to extend the current knowledge on the impact of TERT promoter mutations and expression alterations in tumor progression by analyzing several highly annotated melanoma cohorts. Using multivariate models, we found no consistent association for TERT promoter mutations or TERT expression with the survival rate in melanoma cohorts under immune checkpoint inhibition. However, the presence of CD4+ T cells increased with TERT expression and correlated with the expression of exhaustion markers. While the frequency of promoter mutations did not change with Breslow thickness, TERT expression was increased in metastases arising from thinner primaries. As single-cell RNA-sequencing (RNA-seq) showed that TERT expression was associated with genes involved in cell migration and dynamics of the extracellular matrix, this suggests a role of TERT during invasion and metastasis. Co-regulated genes found in several bulk tumors and single-cell RNA-seq cohorts also indicated non-canonical functions of TERT related to mitochondrial DNA stability and nuclear DNA repair. This pattern was also evident in glioblastoma and across other entities. Hence, our study adds to the role of TERT expression in cancer metastasis and potentially also immune resistance.

Pan-cancer analysis of Homeobox B9 as a predictor for prognosis and immunotherapy in human tumors

BACKGROUND

Although several animal and cell studies have described the association between HOXB9 and cancers, there is no pan-cancer investigation of HOXB9. In this article, we explored the expression levels and prognosis of HOXB9 in pan-cancer. We evaluated the correlation of HOXB9 expression level with the efficacy of immunotherapy.

METHODS

We conducted a survival analysis of HOXB9 in various types of cancer using publicly available databases. We also examined the relationship between HOXB9 expression levels and several factors including prognosis, immune infiltration, immune checkpoint genes, tumor mutational burden, microsatellite instability, mismatch repair, and DNA methylation. TIMER2.0 tool was conducted to explore the immune cell infiltrations related to HOXB9 in this analysis.

RESULTS

It was discovered through a comprehensive analysis of multiple public datasets that HOXB9 expression was highly expressed in most tumor tissues and cancer cell lines and that distinct associations exist between HOXB9 expression and tumor patient prognosis. Besides, HOXB9 expression was closely associated with immune cell infiltration and checkpoint genes in many cancers. Further, HOXB9 was associated with immune cell infiltration, TMB, MSI, MMR, and DNA methylation. It was also confirmed that HOXB9 was highly expressed in clinical GBM tissues. Experiments further revealed that knockdown of HOXB9 expression could suppress proliferation, migration, and invasion of glioma cells.

CONCLUSIONS

The results revealed that HOXB9, a robust tumor biomarker, has a significant prognostic value. HOXB9 may act as a new predictor to assess cancer prognosis and therapeutic efficacy of the immune in various cancers.

Comprehensive pan-cancer analysis of PTGES3 and its prognostic role in hepatocellular carcinoma

Introduction

PTGES3, also known as p23, is a molecule chaperone of Hsp90 that is involved in the pathogenesis of malignant tumors. Increasing studies have shown that PTGES3 plays a nonnegligible role in tumor development. However, analysis of PTGES3 in pan-cancer has not been performed yet.

Methods

We explored the role of PTGES3 in 33 types of tumors and depicted the potentialimmune-related pathways among them. Using multiple databases includingTCGA, LinkedOmics, GDSC, and TIMER, we made a comprehensive analysis to explore whether there was an interaction between PTGES3 and prognosis, DNA methylation, copy number variation (CNV), tumor mutational burden (TMB), microsatellite instability (MSI), and tumor immune microenvironment (TME).

Results

Our study revealed that PTGES3 expression level was upregulated in most cancers. PTGES3 was also associated with a positive or negative prognosis in a variety of cancers, which was mainly associated with DNA methylation, CNV, MSI, TMB, andmismatch repair-related genes. High PTGES3 expression was related to the infiltration of Th2 subsets of CD4+ T cells and immune checkpoint-related genes in most cancers, especially in hepatocellular carcinoma (HCC). Enrichment analysis demonstrated that PTGES3 was involved in cellular processes including DNA replication and spliceosome. The relationship between PTGES3 expression and HCC progression was verified at the protein level through immune histochemical analysis.

Conclusions

Our research demonstrated theprognostic predictive value of PTGES3 in a wide range of cancers, which was alsoassociated with the process of tumor immune infiltration. As a result, it suggestedthat PTGES3 was a valuable prognostic biomarker in HCC treatment.

Multi-omics integration analysis of GPCRs in pan-cancer to uncover inter-omics relationships and potential driver genes

G protein-coupled receptors (GPCRs) are the largest drug target family. Unfortunately, applications of GPCRs in cancer therapy are scarce due to very limited knowledge regarding their correlations with cancers. Multi-omics data enables systematic investigations of GPCRs, yet their effective integration remains a challenge due to the complexity of the data. Here, we adopt two types of integration strategies, multi-staged and meta-dimensional approaches, to fully characterize somatic mutations, somatic copy number alterations (SCNAs), DNA methylations, and mRNA expressions of GPCRs in 33 cancers. Results from the multi-staged integration reveal that GPCR mutations cannot well predict expression dysregulation. The correlations between expressions and SCNAs are primarily positive, while correlations of the methylations with expressions and SCNAs are bimodal with negative correlations predominating. Based on these correlations, 32 and 144 potential cancer-related GPCRs driven by aberrant SCNA and methylation are identified, respectively. In addition, the meta-dimensional integration analysis is carried out by using deep learning models, which predict more than one hundred GPCRs as potential oncogenes. When comparing results between the two integration strategies, 165 cancer-related GPCRs are common in both, suggesting that they should be prioritized in future studies. However, 172 GPCRs emerge in only one, indicating that the two integration strategies should be considered concurrently to complement the information missed by the other such that obtain a more comprehensive understanding. Finally, correlation analysis further reveals that GPCRs, in particular for the class A and adhesion receptors, are generally immune-related. In a whole, the work is for the first time to reveal the associations between different omics layers and highlight the necessity of combing the two strategies in identifying cancer-related GPCRs.

Biomarkers and factors in small cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis

OBJECTIVE

The aim of this meta-analysis was to summarize the available results of immunotherapy predictors for small cell lung cancer (SCLC) and to provide evidence-based information for their potential predictive value of efficacy.

METHODS

We searched PubMed, EMBASE, Web of Science, The Cochrane Library, and ClinicalTrials (from January 1, 1975 to November 1, 2021). The hazard ratios (HR) and its 95% confidence intervals (CIs) and tumor response rate of the included studies were extracted.

RESULTS

Eleven studies were eventually included and the pooled results showed that programmed cell death ligand 1 (PD-L1) positive: objective response rate (ORR) (relative risk [RR] = 1.39, 95% CI [0.48, 4.03], p = 0.54), with high heterogeneity (p = 0.05, I²  = 56%); disease control rate [DCR] (RR = 1.31, 95% CI [0.04, 38.57], p = 0.88), with high heterogeneity (p = 0.04, I²  = 75%); overall survival (OS) (HR = 0.89, 95% CI [0.74, 1.07], p = 0.22); and progression-free survival (PFS) (HR = 0.83, 95% CI [0.59, 1.16], p = 0.27), with high heterogeneity (p = 0.005, I²  = 73.1%). TMB-High (TMB-H): OS (HR = 0.86, 95% CI [0.74, 1.00], p = 0.05); PFS (HR = 0.71, 95% CI [0.6, 0.85], p < 0.001). Lactate dehydrogenase (LDH) >upper limit of normal (ULN): OS (HR = 0.95, 95% CI [0.81, 1.11], p = 0.511). Asian patients: OS (HR = 0.87, 95% CI [0.72, 1.04], p = 0.135); White/Non-Asian patients: OS (HR = 0.83, 95% CI [0.76, 0.90], p < 0.001). Liver metastasis patients: OS (HR = 0.93, 95% CI [0.83, 1.05], p = 0.229); PFS (HR = 0.84, 95% CI [0.67, 1.06], p = 0.141). Central nervous system (CNS) metastasis patients: OS (HR = 0.91, 95% CI [0.71, 1.17], p = 0.474); PFS (HR = 1.03, 95% CI [0.66, 1.60], p = 0.903).

CONCLUSION

The available research results do not support the recommendation of PD-L1 positive and TMB-H as predictors for the application of immune checkpoint inhibitors (ICIs) in SCLC patients. LDH, baseline liver metastasis and CNS metastasis may be used as markers/influencing factors for predicting the efficacy of ICIs in SCLC patients. Non-Asian SCLC patients had better efficacy with ICIs in our results.

Influence of Genomic Landscape on Cancer Immunotherapy for Newly Diagnosed Ovarian Cancer: Biomarker Analyses from the IMagyn050 Randomized Clinical Trial

PURPOSE

To explore whether patients with BRCA1/2-mutated or homologous recombination deficient (HRD) ovarian cancers benefitted from atezolizumab in the phase III IMagyn050 (NCT03038100) trial.

PATIENTS AND METHODS

Patients with newly diagnosed ovarian cancer were randomized to either atezolizumab or placebo with standard chemotherapy and bevacizumab. Programmed death-ligand 1 (PD-L1) status of tumor-infiltrating immune cells (IC) was determined centrally (VENTANA SP142 assay). Genomic alterations, including deleterious BRCA1/2 alterations, genomic loss of heterozygosity (gLOH), tumor mutation burden (TMB), and microsatellite instability (MSI), were evaluated using the FoundationOne assay. HRD was defined as gLOH ≥ 16%, regardless of BRCA1/2 mutation status. Potential associations between progression-free survival (PFS) and genomic biomarkers were evaluated using standard correlation analyses and log-rank of Kaplan-Meier estimates.

RESULTS

Among biomarker-evaluable samples, 22% (234/1,050) harbored BRCA1/2 mutations and 46% (446/980) were HRD. Median TMB was low irrespective of BRCA1/2 or HRD. Only 3% (29/1,024) had TMB ≥10 mut/Mb, and 0.3% (3/1,022) were MSI-high. PFS was better in BRCA2-mutated versus BRCA2-non-mutated tumors and in HRD versus proficient tumors. PD-L1 positivity (≥1% expression on ICs) was associated with HRD but not BRCA1/2 mutations. PFS was not improved by adding atezolizumab in BRCA2-mutated or HRD tumors; there was a trend toward enhanced PFS with atezolizumab in BRCA1-mutated tumors.

CONCLUSIONS

Most ovarian tumors have low TMB despite BRCA1/2 mutations or HRD. Neither BRCA1/2 mutation nor HRD predicted enhanced benefit from atezolizumab. This is the first randomized double-blind trial in ovarian cancer demonstrating that genomic instability triggered by BRCA1/2 mutation or HRD is not associated with improved sensitivity to immune checkpoint inhibitors. See related commentary by Al-Rawi et al., p. 1645.

A pan-cancer analysis identifies SOAT1 as an immunological and prognostic biomarker

Sterol o-acyltransferase1 (SOAT1) is an enzyme that regulates lipid metabolism. Nevertheless, the predictive value of SOAT1 regarding immune responses in cancer is not fully understood. Herein, we aimed to expound the predictive value and the potential biological functions of SOAT1 in pan-cancer. Raw data related to SOAT1 expression in 33 different types of cancer were acquired from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. SOAT1 expression was significantly increased in most cancers and showed a distinct correlation with prognosis. This enhanced expression of the SOAT1 gene was confirmed by evaluating SOAT1 protein expression using tissue microarrays. In addition, we found significant positive associations between SOAT1 expression levels and infiltrating immune cells, including T cells, neutrophils, and macrophages. Moreover, the co-expression analysis between SOAT1 and immune genes showed that many immune-related genes were increased with enhanced SOAT1 expression. A gene set enrichment analysis (GSEA) revealed that the expression of SOAT1 correlated with the tumor microenvironment, adaptive immune response, interferon signaling, and cytokine signaling. These findings indicate that SOAT1 is a potential candidate marker for predicting prognosis and a promising target for tumor immunotherapy in cancers.

Diabetes mellitus induces a novel inflammatory network involving cancer progression: Insights from bioinformatic analysis and in vitro validation

Background

Patients with diabetes mellitus (DM) have a higher incidence of malignant tumors than people without diabetes, but the underlying molecular mechanisms are still unclear.

Methods

To investigate the link between DM and cancer, we screened publicly available databases for diabetes and cancer-related genes (DCRGs) and constructed a diabetes-based cancer-associated inflammation network (DCIN). We integrated seven DCRGs into the DCIN and analyzed their role in different tumors from various perspectives. We also investigated drug sensitivity and single-cell sequencing data in colon adenocarcinoma as an example. In addition, we performed in vitro experiments to verify the expression of DCRGs and the arachidonic acid metabolic pathway.

Results

Seven identified DCRGs, including PPARG, MMP9, CTNNB1, TNF, TGFB1, PTGS2, and HIF1A, were integrated to construct a DCIN. The bioinformatics analysis showed that the expression of the seven DCRGs in different tumors was significantly different, which had varied effects on diverse perspectives. Single-cell sequencing analyzed in colon cancer showed that the activity of the DCRGs was highest in Macrophage and the lowest in B cells among all cell types in adenoma and carcinoma tissue. In vitro experiments showed that the DCRGs verified by western bolt and PEG2 verified by ELISA were all highly expressed in COAD epithelial cells stimulated by high glucose.

Conclusion

This study, for the first time, constructed a DCIN, which provides novel insights into the underlying mechanism of how DM increases tumor occurrence and development. Although further research is required, our results offer clues for new potential therapeutic strategies to prevent and treat malignant tumors.

Prognostic value of pretreatment immune inflammation indices in patients with immune-related tumors

BACKGROUND

Pretreatment high levels of lactate dehydrogenase (LDH), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), monocyte-lymphocyte ratio (MLR), modified Glasgow prognostic scores (mGPS), prognostic nutritional index (PNI), and other prognostic biomarkers have been associated with poor overall survival (OS) in immune-related tumor types. Therefore, we explored a simple, inexpensive and effective method for cancer prognosis.

METHODS

Between March 2017 and June 2022, 111 individuals who had immunotherapy were retrospectively examined. Oncologic outcomes of patients with immune-related tumor types, include OS and progression-free survival (PFS), and response rates (RR).

RESULTS

Pretreatment ECOG (Eastern Cooperative Oncology Group) performance quality was independently linked with poor OS ECOG ≥2 (HR 4.80, 95% CI 2.57-8.96, p < .001) and inferior PFS (HR 3.31, 95% CI 2.023-5.445, p < .001). Additionally, a high LDH status prior to therapy was independently linked to an inferior OS (HR 1.004, 95% CI 1.001-1.007, p = .003) and inferior PFS (HR 1.004, 95% CI 1.002-1.006, p < .001). Higher MLR at baseline was a prognostic factor for both shorter PFS (HR = 3.691, 95% CI 1.582-8.610, p = .003) and OS (HR = 2.876, 95% CI 1.127-7.342, p = .027).

CONCLUSIONS

In our cohort, elevated pre-treatment MLR, LDH and ECOG ≥2 were associated with poor OS and PFS. Prospective studies need to determine the utility of them.

Immune checkpoint PTPN2 predicts prognosis and immunotherapy response in human cancers

Background

PTPN2, a member of the non-receptor protein tyrosine phosphatases family, holds a crucial role in tumorigenesis and cancer immunotherapy. However, most studies on the role of PTPN2 in cancer are limited to specific cancer types. Therefore, this study aimed to investigate the prognostic significance of PTPN2 in human cancers and its function in the tumor microenvironment.

Methods

To shed light on this matter, we investigated the expression level, prognostic value, genomic alterations, molecular function, immune function, and immunotherapeutic predictive ability of PTPN2 in human cancers using the TCGA, GTEx, CGGA, GEO, cBioPortal, STRING, TISCH, TIMER2.0, ESTIMATE, and TIDE databases. Furthermore, the CCK-8 assay was utilized to detect the effect of PTPN2 on cell proliferation. Cell immunofluorescence analysis was performed to probe the cellular localization of PTPN2. Western blot was applied to examine the molecular targets downstream of PTPN2. Finally, a Nomogram model was constructed using the TCGA-LGG cohort and evaluated with calibration curves and time-dependent ROCs.

Results

PTPN2 was highly expressed in most cancers and was linked to poor prognosis in ACC, GBM, LGG, KICH, and PAAD, while the opposite was true in OV, SKCM, and THYM. PTPN2 knockdown promoted the proliferation of melanoma cells, while significantly inhibiting proliferation in colon cancer and glioblastoma cells. In addition, TC-PTP, encoded by the PTPN2 gene, was primarily localized in the nucleus and cytoplasm and could negatively regulate the JAK/STAT and MEK/ERK pathways. Strikingly, PTPN2 knockdown significantly enhanced the abundance of PD-L1. PTPN2 was abundantly expressed in Mono/Macro cells and positively correlated with multiple immune infiltrating cells, especially CD8⁺ T cells. Notably, DLBC, LAML, OV, and TGCT patients in the PTPN2-high group responded better to immunotherapy, while the opposite was true in ESCA, KIRC, KIRP, LIHC, and THCA. Finally, the construction of a Nomogram model on LGG exhibited a high prediction accuracy.

Conclusion

Immune checkpoint PTPN2 is a powerful biomarker for predicting prognosis and the efficacy of immunotherapy in cancers. Mechanistically, PTPN2 negatively regulates the JAK/STAT and MEK/ERK pathways and the abundance of PD-L1.

Genomic Signatures from Clinical Tumor Sequencing in Patients with Breast Cancer Having Germline BRCA1/2 Mutation

PURPOSE

BRCA1 and BRCA2 are among the most important genes involved in DNA repair via homologous recombination (HR). Germline BRCA1/2 (gBRCA1/2)-related cancers have specific characteristics and treatment options but conducting gBRCA1/2 testing and interpreting the genetic imprint are sometimes complicated. Here, we describe the concordance of gBRCA1/2 derived from a panel of clinical tumor tissues using next-generation sequencing (NGS) and genetic aspects of tumors harboring gBRCA1/2 pathogenic variants.

MATERIALS AND METHODS

Targeted sequencing was performed using available tumor tissue from patients who underwent gBRCA1/2 testing. Comparative genomic analysis was performed according to gBRCA1/2 pathogenicity.

RESULTS

A total of 321 patients who underwent gBRCA1/2 testing were screened, and 26 patients with gBRCA1/2 pathogenic (gBRCA1/2p) variants, eight patients with gBRCA1/2 variants of uncertain significance (VUS; gBRCA1/2v), and 43 patients with gBRCA1/2 wild-type (gBRCA1/2w) were included in analysis. Mutations in TP53 (49.4%) and PIK3CA (23.4%) were frequently detected in all samples. The number of single-nucleotide variants (SNVs) per tumor tissue was higher in the gBRCA1/2w group than that in the gBRCA1/2p group (14.81 vs. 18.86, p=0.278). Tumor mutation burden (TMB) was significantly higher in the gBRCA1/2w group than in the gBRCA1/2p group (10.21 vs. 13.47, p=0.017). Except for BRCA1/2, other HR-related genes were frequently mutated in patients with gBRCA1/2w.

CONCLUSION

We demonstrated high sensitivity of gBRCA1/2 in tumors analyzed by NGS using a panel of tumor tissues. TMB value and aberration of non-BRCA1/2 HR-related genes differed significantly according to gBRCA1/2 pathogenicity in patients with breast cancer.

A novel natural killer cell-related signatures to predict prognosis and chemotherapy response of pancreatic cancer patients

Background: Natural killer (NK) cells are involved in monitoring and eliminating cancers. The purpose of this study was to develop a NK cell-related genes (NKGs) in pancreatic cancer (PC) and establish a novel prognostic signature for PC patients. Methods: Omic data were downloaded from The Cancer Genome Atlas Program (TCGA), Gene Expression Omnibus (GEO), International Cancer Genome Consortium (ICGC), and used to generate NKG-based molecular subtypes and construct a prognostic signature of PC. NKGs were downloaded from the ImmPort database. The differences in prognosis, immunotherapy response, and drug sensitivity among subtypes were compared. 12 programmed cell death (PCD) patterns were acquired from previous study. A decision tree and nomogram model were constructed for the prognostic prediction of PC. Results: Thirty-two prognostic NKGs were identified in PC patients, and were used to generate three clusters with distinct characteristics. PCD patterns were more likely to occur at C1 or C3. Four prognostic DEGs, including MET, EMP1, MYEOV, and NGFR, were found among the clusters and applied to construct a risk signature in TCGA dataset, which was successfully validated in PACA-CA and GSE57495 cohorts. The four gene expressions were negatively correlated with methylation level. PC patients were divided into high and low risk groups, which exerts significantly different prognosis, clinicopathological features, immune infiltration, immunotherapy response and drug sensitivity. Age, N stage, and the risk signature were identified as independent factors of PC prognosis. Low group was more easily to happened on PCD. A decision tree and nomogram model were successfully built for the prognosis prediction of PC patients. ROC curves and DCA curves demonstrated the favorable and robust predictive capability of the nomogram model. Conclusion: We characterized NKGs-derived molecular subtypes of PC patients, and established favorable prognostic models for the prediction of PC prognosis, which may serve as a potential tool for prognosis prediction and making personalized treatment in PC.

Comprehensive genomics analysis of aging related gene signature to predict the prognosis and drug resistance of colon adenocarcinoma

Background: Colon adenocarcinoma (COAD) is a heterogeneous tumor and senescence is crucial in the occurrence of cancer. This study aimed to identify senescence-based subtypes and construct a prognostic signature to predict the prognosis and guide immunotherapy or chemotherapy decisions for COAD patients. Methods: Based on the single-cell RNA sequencing (scRNA-seq) data of 13 samples from the Gene Expression Omnibus (GEO) database, we assessed cellular senescence characteristics. Transcriptome data, copy number variations (CNVs) and single nucleotide variations (SNVs) data were obtained from The Cancer Genome Atlas (TCGA) database. GSE39582 and GSE17537 were used for validation. Senescence subtypes were identified using unsupervised consensus clustering analysis, and a prognostic signature was developed using univariate Cox analysis and least absolute shrinkage and selection operator (LASSO). Response of risk groups to chemotherapy was predicted using the half-maximal inhibitory concentration (IC50) values. We further analyzed the relationship between risk gene expression and methylation level. The prediction performance was assessed by nomogram. Results: Senescence-related pathways were highly enriched in malignant cells and bulk RNA-seq verified cellular senescence. Three senescence subtypes were identified, in which patients in clust3 had poorest prognosis and higher T stage, accompanied with higher tumor mutation burden (TMB) and mutations, activated inflammatory response, more immune cell infiltration, and higher immune escape tendency. A senescence-based signature using 11 genes (MFNG, GPRC5B, TNNT1, CCL22, NOXA1, PABPC1L, PCOLCE2, MID2, CPA3, HSPA1A, and CALB1) was established, and accurately predicted a lower prognosis in high risk patients. Its robustness was validated by external cohort. Low risk patients were more sensitive to small molecule drugs including Erlotinib, Sunitinib, MG-132, CGP-082996, AZ628, Sorafenib, VX-680, and Z-LLNle-CHO. Risk score was an independent prognostic factor and nomogram confirmed its reliability. Four risk genes (CALB1, CPA3, NOXA1, and TNNT1) had significant positive correlation with their methylation level, while six genes (CCL22, GPRC5B, HSPA1A, MFNG, PABPC1L, and PCOLCE2) were negatively correlated with their methylation level. Conclusion: This study provides novel understanding of heterogeneity in COAD from the perspective of senescence, and develops signatures for prognosis prediction in COAD.

Implementation of Comprehensive Genomic Profiling in Ovarian Cancer Patients: A Retrospective Analysis

Comprehensive genomic profiling (CGP) allows for the detection of driver alterations at high resolution, but the limited number of approved targeted therapies and their high costs have contributed to its limited clinical utilization. We retrospectively compared data of 946 women with ovarian cancer (11.4% were referred to CGP, and 88.6% served as control) to examine whether CGP provides a prognosis benefit. Patient baseline parameters were similar between the groups. Cox regression analysis adjusted for age, disease stage at diagnosis, and recurrence status showed statistically significantly longer median overall survival (mOS) in the CGP group versus the control (73.4 versus 54.5 months, p < 0.001). Fifty-four patients (52.9%) had actionable mutations with potential treatments; twenty-six (48.2%) were treated with matched targeted therapy, showing a trend for longer mOS than the eighty-six women in the CGP group who were not given a suggested treatment (105.5 versus 63.6 months, p = 0.066). None of the genomic alterations predicted metastasis location. CCNE1 amplification and KRAS mutations were associated with shorter mOS. Patients with tumor mutation burden ≥4 mutations/megabase had longer mOS. High loss of heterozygosity was associated with longer mOS (99.0 versus 48.2 months, p = 0.004). CGP testing may provide both prognostic and predictive insights for treatment of patients with ovarian cancer. Prospective studies of larger cohorts are warranted.

A bile acid-related prognostic signature in hepatocellular carcinoma

Due to the high mortality of hepatocellular carcinoma (HCC), its prognostic models are urgently needed. Bile acid (BA) metabolic disturbance participates in hepatocarcinogenesis. We aim to develop a BA-related gene signature for HCC patients. Research data of HCC were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) online databases. After least absolute shrinkage and selection operator (LASSO) regression analysis, we developed a BA-related prognostic signature in TCGA cohort based on differentially expressed prognostic BA-related genes. Then, the predictive performance of the signature was evaluated and verified in TCGA and ICGC cohort respectively. We obtained the risk score of each HCC patient according to the model. The differences of immune status and drug sensitivity were compared in patients that were stratified based on risk score. The protein and mRNA levels of the modeling genes were validated in the Human Protein Atlas database and our cell lines, respectively. In TCGA cohort, we selected 4 BA-related genes to construct the first BA-related prognostic signature. The risk signature exhibited good discrimination and predictive ability, which was verified in ICGC cohort. Patients were classified into high- and low-risk groups according to their median scores. The occurrence of death increased with increasing risk score. Low-risk patients owned favorable overall survival. High-risk patients possessed high immune checkpoint expression and low IC50 values for sorafenib, cisplatin and doxorubicin. Real-time quantitative PCR and immunohistochemical results validate expression of modeling genes in the signature. We constructed the first BA-related gene signature, which might help to identify HCC patients with poor prognosis and guide individualized treatment.

Spatial heterogeneity of infiltrating T cells in high-grade serous ovarian cancer revealed by multi-omics analysis

Tumor-infiltrating lymphocytes (TILs), especially CD8⁺ TILs, represent a favorable prognostic factor in high-grade serous ovarian cancer (HGSOC) and other tumor lineages. Here, we analyze the spatial heterogeneity of different TIL subtypes in HGSOC. We integrated RNA sequencing, whole-genome sequencing, bulk T cell receptor (TCR) sequencing, as well as single-cell RNA/TCR sequencing to investigate the characteristics and differential composition of TILs across different HGSOC sites. Two immune "cold" patterns in ovarian cancer are identified: (1) ovarian lesions with low infiltration of mainly dysfunctional T cells and immunosuppressive Treg cells and (2) omental lesions infiltrated with non-tumor-specific bystander cells. Exhausted CD8 T cells that are preferentially enriched in ovarian tumors exhibit evidence for expansion and cytotoxic activity. Inherent tumor immune microenvironment characteristics appear to be the main contributor to the spatial differences in TIL status. The landscape of spatial heterogeneity of TILs may inform potential strategies for therapeutic manipulation in HGSOC.