Signature Score Research Articles

Single-cell sequencing reveals novel proliferative cell type: a key player in renal cell carcinoma prognosis and therapeutic response

Renal cell carcinoma (RCC) is characterized by a variety of subtypes, each defined by unique genetic and morphological features. This study utilizes single-cell RNA sequencing to explore the molecular heterogeneity of RCC. A highly proliferative cell subset, termed as “Prol,” was discovered within RCC tumors, and its increased presence was linked to poorer patient outcomes. An artificial intelligence network, encompassing traditional regression, machine learning, and deep learning algorithms, was employed to develop a Prol signature capable of predicting prognosis. The signature demonstrated superior performance in predicting RCC prognosis compared to other signatures and exhibited pan-cancer prognostic capabilities. RCC patients with high Prol signature scores exhibited resistance to targeted therapies and immunotherapies. Furthermore, the key gene CEP55 from the Prol signature was validated by both proteinomics and quantitative real time polymerase chain reaction. Our findings may provide new insights into the molecular and cellular mechanisms of RCC and facilitate the development of novel biomarkers and therapeutic targets.

Genomic biomarkers to predict response to atezolizumab plus bevacizumab immunotherapy in hepatocellular carcinoma: Insights from the IMbrave150 trial.

Combination immunotherapy, exemplified by atezolizumab plus bevacizumab, has become the standard of care for inoperable hepatocellular carcinoma (HCC). However, the lack of predictive biomarkers and limited understanding of response mechanisms remain a challenge. Using data from the IMbrave150plus cohort, we applied an immune signature score (ISS) predictor to stratify HCC patients treated with atezolizumab plus bevacizumab or with sorafenib alone into potential high and low response groups. By applying multiple statistical approaches including a Bayesian covariate prediction algorithm, we refined the signature to 10 key genes (ISS10) for clinical use while maintaining similar predictive power to the full model. We further validated ISS10 in an independent HCC cohort treated with nivolumab plus ipilimumab. The study identified a significant association between the ISS and treatment response. Among patients classified as high responders, those treated with the atezolizumab plus bevacizumab combination exhibited improved overall and progression-free survival as well as better objective response rate compared to those treated with sorafenib. We also observed a significant correlation between ISS10 and response to nivolumab plus ipilimumab treatment. Analysis of immune cell subpopulations revealed distinct characteristics associated with ISS subtypes. In particular, the ISS10 high subtype displayed a more favorable immune environment with higher proportions of antitumor macrophages and activated T-cells, potentially explaining its better response. Our study suggests that ISS and ISS10 are promising predictive biomarkers for enhanced therapeutic outcomes in HCC patients undergoing combination immunotherapy. These markers are crucial for refining patient stratification and personalized treatment approaches to advance the effectiveness of standard-of-care regimens.

Integrated single-cell and bulk RNA sequencing revealed an epigenetic signature predicts prognosis and tumor microenvironment colorectal cancer heterogeneity.

Colorectal cancer (CRC) prognosis prediction is currently a major challenge. Epigenetic regulation has been widely reported for its role in cancer development. To construct a robust prognostic signature, we used developed and validated across datasets. After constructing the signature, the prognostic value of the signature was evaluated in the TCGA cohort and six independent datasets (GSE17526, GSE17537, GSE33113, GSE37892, GSE39048 and GSE39582). The clinical, genomic and transcriptomic features related to the signature were identified. The correlations of the signature score with immune cell infiltration and cell-cell interactions were analyzed. The correlations between the signature score and the sensitivity to different drugs were also predicted. In the TCGA cohort, patients in the low-risk group according to the signature score had longer survival than those in the high-risk group, and this finding was validated in the validation datasets. The signature was a prognostic factor independent of age and sex and was correlated with stage and PD-1/PD-L1 expression. Area under the receiving operating characteristic curve was 0.72. Genomic association analyses revealed that samples from high-risk patients exhibited chromosomal instability. Transcriptomic analyses revealed that the signature score was significantly associated with multiple cellular pathways. Bulk RNA-seq and single-cell sequencing data revealed that the signature reflected differences in infiltrating immune cell-tumor cell interactions, especially for macrophages. The signature also predicted the putative drug sensitivity of CRC samples. The signature is a valuable biomarker for predicting CRC prognosis and reflects multiple features of CRC, especially macrophage infiltration in the microenvironment.

Blood transcriptomic signatures for symptomatic tuberculosis in an African multicohort study.

Multiple host blood transcriptional signatures have been developed as non-sputum triage tests for tuberculosis (TB). We aimed to compare the diagnostic performance of 20 blood transcriptomic TB signatures for differentiating between symptomatic patients who have TB versus other respiratory diseases (ORD). As part of a nested case-control study, individuals presenting with respiratory symptoms at primary healthcare clinics in Ethiopia, Malawi, Namibia, Uganda, South Africa and The Gambia were enrolled. TB was diagnosed based on clinical, microbiological and radiological findings. Transcriptomic signatures were measured in whole blood using microfluidic real-time quantitative PCR. Diagnostic performance was benchmarked against the World Health Organization Target Product Profile (TPP) for a non-sputum TB triage test. Among 579 participants, 158 had definite, microbiologically confirmed TB, 32 had probable TB, while 389 participants had ORD. Nine signatures differentiated between ORD and TB with equivalent performance (Satproedprai7: area under the curve 0.83 (95% CI 0.79-0.87); Jacobsen3: 0.83 (95% CI 0.79-0.86); Suliman2: 0.82 (95% CI 0.78-0.86); Roe1: 0.82 (95% CI 0.78-0.86); Kaforou22: 0.82 (95% CI 0.78-0.86); Sambarey10: 0.81 (95% CI 0.77-0.85); Duffy9: 0.81 (95% CI 0.76-0.86); Gliddon3: 0.8 (95% CI 0.75-0.85); Suliman4 0.79 (95% CI 0.75-0.84)). Benchmarked against a 90% sensitivity, these signatures achieved specificities between 44% (95% CI 38-49%) and 54% (95% CI 49-59%), not meeting the TPP criteria. Signature scores significantly varied by HIV status and country. In country-specific analyses, several signatures, such as Satproedprai7 and Penn-Nicholson6, met the minimal TPP criteria for a triage test in Ethiopia, Malawi and South Africa. No signatures met the TPP criteria in a pooled analysis of all countries, but several signatures met the minimum criteria for a non-sputum TB triage test in some countries.

Single cell transcriptomic analysis reveals tumor immune infiltration by NK cells gene signature in lung adenocarcinoma

BackgroundNatural Killer (NK) cells are vital components of the innate immune system, crucial for combating infections and tumor growth, making them pivotal in cancer prognosis and immunotherapy. We sought to understand the diverse characteristics of NK cells within lung adenocarcinoma (LUAD) by conducting single-cell RNA sequencing analyses. MethodsUsing the scRNA-seq dataset for multiple primary lung cancers (MPLCs), we examined two major NK cell groups, NK1 and NK2, comparing the expression profiles of 422 differentially expressed NK signature genes. We identified eight genes (SPON2, PLEKHG3, CAMK2N1, RAB27B, CTBP2, EFHD2, GOLM1, and PLOD1) that distinguish NK1 from NK2 cells. A prognostic signature, the NK gene signature (NKGS) score, was established through LASSO Cox regression. High NKGS scores were linked to poorer overall survival in TCGA-LUAD patients and consistently validated in other datasets (GSE31210 and GSE14814). ResultsFunctional analysis revealed an enrichment of genes related to the TGF-β signaling pathway in the high NKGS score group. Moreover, a high NKGS score correlated with an immunosuppressive tumor microenvironment (TME) driven by immune evasion mechanisms. We also observed reduced T-cell receptor (TCR) repertoire diversity in the high-risk NKGS group, indicating a negative association between inflammation and risk score. ConclusionThis study introduced the innovative NKGS score, differentiating NK1 from NK2 cells. High NKGS scores were associated with the TGF-β pathway and provided insights into LUAD prognosis and immune activities.

Single-Cell Analysis Identifies Distinct Populations of Cytotoxic CD4+ T Cells Linked to the Therapeutic Efficacy of Immune Checkpoint Inhibitors in Metastatic Renal Cell Carcinoma.

The involvement of cytotoxic CD4+ T cells (CD4+ CTLs) and their potential role in dictating the response to immune checkpoint inhibitors (ICIs) in patients with metastatic renal cell carcinoma (mRCC) remains an unexplored area of research. Utilizing single-cell RNA sequencing, we analyzed the immunophenotype and expression patterns of CD4+ T lymphocyte subtypes in mRCC patients, followed by preliminary validation via multi-immunofluorescent staining. In addition, we obtained a comprehensive immunotherapy dataset encompassing single-cell RNA sequencing datasets and bulk RNA-seq cohorts from the European Genome-Phenome Archive and ArrayExpress database. Utilizing the CIBERSORTx deconvolution algorithms, we derived a signature score for CD4+ CTLs from the bulk-RNA-seq datasets of the CheckMate 009/025 clinical trials. Single-cell analysis of CD4+ T lymphocytes in mRCC reveals several cancer-specific states, including diverse phenotypes of regulatory T cells. Remarkably, we observe that CD4+ CTLs cells constitute a substantial proportion of all CD4+ T lymphocyte sub-clusters in mRCC patients, highlighting their potential significance in the disease. Furthermore, within mRCC patients, we identify two distinct cytotoxic states of CD4+ T cells: CD4+GZMK+ T cells, which exhibit a weaker cytotoxic potential, and CD4+GZMB+ T cells, which demonstrate robust cytotoxic activity. Both regulatory T cells and CD4+ CTLs originate from proliferating CD4+ T cells within mRCC tissues. Intriguingly, our trajectory analysis indicates that the weakly cytotoxic CD4+GZMK+ T cells differentiate from their more cytotoxic CD4+GZMB+ counterparts. In comparing patients with lower CD4+ CTLs levels to those with higher CD4+ CTLs abundance in the CheckMate 009 and 25 immunotherapy cohorts, the latter group exhibited significantly improved OS and PFS probability. Our study underscores the pivotal role that intratumoral CD4+ CTLs may play in bolstering anti-tumor immunity, suggesting their potential as a promising biomarker for predicting response to ICIs in patients with mRCC.

A T2-weighted MRI-based radiomic signature for disease-free survival in locally advanced cervical cancer following chemoradiation: An international, multicentre study

IntroductionTo develop and validate a T2-weighted magnetic resonance imaging (MRI)-based radiomic signature associated with disease-free survival (DFS) in locally advanced cervical cancer. Materials and MethodsThe study comprised a training dataset of 132 patients (93 Norwegian; 39 The Cancer Imaging Archive (TCIA) and an independent validation Canadian dataset of 199 patients with FIGO stage IB-IVA cervical cancer treated with chemoradiation. Radiomic features were extracted using PyRadiomics. A radiomic signature was developed based on a multivariable radiomic prognostic model for DFS built using the training dataset, with minimal redundancy maximum relevancy feature selection method. Univariate and multivariable Cox regression analyses were then conducted to examine the association of the derived radiomic signature with DFS. ResultsA radiomic signature was prognostic for DFS in the training cohort (Norwegian hazard ratio [HR] 5.54, p = 0.002; TCIA HR 3.59, p = 0.04). The radiomic signature remained independently associated with DFS (HR 3.70, p = 0.004) when adjusted for stage and tumor volume. The radiomic signature was also prognostic for DFS in the validation cohort, both on univariate analysis (HR 2.22, p = 0.003), and multivariable analysis adjusted for stage and tumor volume (HR 1.84, p = 0.04). The 4-year DFS rates of patients with radiomic signature score > 0 vs ≤ 0 were 48.2 % vs 87.9 %, and 56.4 % vs 80.8 % for training and validation cohorts respectively. ConclusionAn MRI-based radiomic signature can be used as a prognostic biomarker for DFS in patients with locally advanced cervical cancer undergoing chemoradiation.

A universal urinary cell gene signature of acute rejection in kidney allografts

IntroductionAcute rejection (AR) undermines the life-extending benefits of kidney transplantation and is diagnosed using the invasive biopsy procedure. T cell-mediated rejection (TCMR), antibody-mediated rejection (ABMR), or concurrent TCMR + ABMR (Mixed Rejection [MR]) are the three major types of AR. Development of noninvasive biomarkers diagnostic of AR due to any of the three types is a useful addition to the diagnostic armamentarium. MethodsWe developed customized RT-qPCR assays and measured urinary cell mRNA copy numbers in 145 biopsy-matched urine samples from 126 kidney allograft recipients. We determined whether the urinary cell three-gene signature diagnostic of TCMR (Suthanthiran et al., 2013) discriminates patients with no rejection biopsies (NR, n = 50) from those with ABMR (n = 28) or MR (n = 20) biopsies. ResultsThe urinary cell three-gene signature discriminated all three types of rejection biopsies from NR biopsies (P < 0.0001, One-way ANOVA). Dunnett's multiple comparisons test yielded P < 0.0001 for NR vs. TCMR; P < 0.001 for NR vs. ABMR; and P < 0.0001 for NR vs. MR. By bootstrap resampling, optimism-corrected area under the receiver operating characteristic curve (AUC) was 0.749 (bias-corrected 95% confidence interval [CI], 0.638 to 0.840) for NR vs. TCMR (P < 0.0001); 0.780 (95% CI, 0.656 to 0.878) for NR vs. ABMR (P < 0.0001); and 0.857 (95% CI, 0.727 to 0.947) for NR vs. MR (P < 0.0001). All three rejection categories were distinguished from NR biopsies with similar accuracy (all AUC comparisons P > 0.05). ConclusionThe urinary cell three-gene signature score discriminates AR due to TCMR, ABMR or MR from NR biopsies in human kidney allograft recipients.

Ocular Tuberculosis Diagnosis Through Biomarkers: Clinical Relevance of Serum C1q and Whole Blood Interferon Gene Signature Score

ABSTRACT Purpose To assess the clinical relevance of pathophysiology-based biomarkers, specifically serum C1q and whole blood interferon gene signature score (IGSS), in ocular tuberculosis (OTB) diagnosis by conducting an integrative analysis of clinical presentations and treatment response. Methods This retrospective cohort study analysed data from 70 patients with suspected OTB at a tertiary care uveitis practice in Indonesia. Serum C1q levels and whole blood IGSS were quantified. Patients were categorized into four quadrants based on their biomarker profiles: quadrant 1 (high C1q & low IGSS), quadrant 2 (high C1q & high IGSS), quadrant 3 (low C1q & high IGSS), and quadrant 4 (low C1q & low IGSS). Characteristics of clinical presentations, work-up results, and treatment outcomes were explored according to the predefined quadrants. Results We identified that the majority of OTB patients diagnosed with concurrent active pulmonary TB were in quadrant 1, 2, or 3 (20/23, 87.0%). Twenty-seven patients (27/47, 57.4%) with clinically undifferentiated uveitis were in quadrant 4 (p < 0.001). Among patients in quadrants 1, 2, and 3, completion of a full course of antitubercular treatment (ATT) was associated with a lower number of patients showing persistence or recurrence of ocular inflammation compared to those who were not fully treated with ATT (14.3% vs 85.7%, p = 0.001). Conclusions Based on the analysis of clinical features and treatment outcomes, patients with elevated levels of either or both serum C1q and whole blood IGSS may reflect active TB disease in the eye, necessitating full ATT management.

MDB-70. SYSTEMATIC TRANSCRIPTOMIC ANALYSIS OF CHILDHOOD MEDULLOBLASTOMA IDENTIFIES M6A-LNCRNA SIGNATURES ASSOCIATED WITH PROGNOSIS, MOLECULAR SUBTYPE, AND IMMUNE CELL INFILTRATION

Abstract BACKGROUND Medulloblastoma (MB) is the predominant pediatric brain tumor, subdivided into four molecular subgroups, with group 3 and group 4 tumors posing significant clinical challenges due to poor prognosis and classification. This study investigates the roles of N6-methyladenosine (m6A) and long non-coding RNAs (lncRNAs) in MB, aiming to develop diagnostic and prognostic tools. METHODS We analyzed transcriptome from 1236 samples to identify m6A-associated lncRNA signature (M6LSig). A multivariate-cox analysis identified a gene signature significantly associated with overall survival (OS) of patients. Risk score was calculated based on the sum of weighted gene expression of these genes. Nomograms were calculated for predicting OS and PFS probability. We did feature selection with Boruta to identify minimum gene signature for subgroup classification. We performed correlation analysis of gene signature and risk score with immune-cell abundance. We depleted METTL3 and METTL14 in G3-MB cell-line (D425) to measure impact on cell proliferation and dysregulation of M6LSig genes as a result of loss of m6A. RESULTS Nomogram was constructed using risk score derived from 24 M6LSig significantly associated with OS and PFS of the patients. A 171 gene signature was identified that can accurately classify samples into one of four major subgroups of MB with more than 90% accuracy including between Grp3/Grp4 samples. M6LSig genes and risk score showed significant correlation with immune cell type abundance in MB tumors. Expression of CD155 and 4-1BB was significantly different between high and low risk samples. m6A writer genes knockdown in D425 cells resulted in decreased cell proliferation and upregulation of many M6LSig genes. CONCLUSION M6LSig based risk can accurately predict OS and PFS and 171 genes signature can classify patients into subgroups with more than 90% accuracy. Risk score can also be used for determining high risk versus low-risk patient and design tailor made immune-therapy for better survival.

Nature and distribution of methyl thioadenosine phosphorylase (MTAP) genomic loss in human tumors.

3067 Background: MTAP genomic loss, often but not exclusively a bi-allelic homozygous deletion, has recently emerged as important biomarker guiding a novel synthetic lethality mechanism for drugs in the class of PRMT5 and MAT2A inhibitors. In the current study, we assessed the nature and distribution of MTAP complete and partial loss in a variety of tumor samples. Methods: A total of 291,391 tissue samples underwent comprehensive genomic profiling (CGP) using a hybrid-capture method to evaluate all classes of genomic alterations (GA), and determine the microsatellite instability (MSI) status, tumor mutational burden (TMB), homologous recombination deficiency (HRD) score and genomic ancestry. The distribution of both complete and partial loss of MTAP was also determined. Results: MTAP GA were found in 8.6% of total with 9.3% genomic loss and 0.1% each short variant mutations and rearrangements. Important (not rare) tumor types with the most frequent MTAP loss included: 42.6% of glioblastoma (GBM), 13.4% of non-small cell lung cancer (NSCLC), 22.3% of pancreatic ductal and 24.9% of bladder urothelial carcinomas. The most frequently co-altered GA included CDKN2A (99.7%), CDKN2B (95.1%), TP53 (55.4%), KRAS (30.1%), TERT(20.5%) and PIK3CA (12%). In tumor types with frequent known targetable driver GA including short variant mutations in EGFR, ERBB2, BRAF, FGFR2-3and MET and fusions involving ALK, RET, ROS1 and NTRK1-3, MTAP loss was not associated with decreased frequencies of GA in these genes. The frequencies of MSI-high status was 0.3% and of TMB≥10 mut/Mb was 17%. In total, 63.7% of the MTAP loss cases involved deletion of all 8 MTAP exons (complete loss) with partial loss accounting for 36.3% of cases. All partial loss cases involved loss of multiple exons (35.8%) except for loss of only exon 8 (0.5%). There was no impact of MTAP loss status on genomic ancestry, cosmic trinucleotide signature and HRD score. The multiple exon loss frequencies included exons 2-8 loss in 24.7%, exons 5-8 loss in 4.1%, exons 6-8 loss in 3.3%, exons 3-8 loss in 1.6%, exons 7-8 in 1.1%, exon 4-8, 1-5, 2-7,2-5, 1-4, 2-6, 3-7 and 5-7 all at less than 1% frequencies. Conclusions: MTAPloss is a frequent GA of emerging clinical importance as the trials using PRMT5 and MTA-2 inhibitors progress. MTAPloss is frequent in common cancers of the brain, lung, pancreas and bladder and not associated with diminishment of other targetable driver mutations. Although one-third of MTAP loss is a partial loss, the partial loss cases involve near total (exons 2-8) loss and may well also be indicative of PRMT5/MAT2A inhibitor benefit. This study strengthens the opportunity to consider a tumor-agnostic approach to targeted therapies. [Table: see text]

Immune checkpoint inhibition for the treatment of metastatic breast cancer with high tumor mutational burden: Real world clinical and genomic correlates of response.

1078 Background: Pembrolizumab has received tumor-agnostic approval for the treatment of unresectable/metastatic solid tumors carrying a tumor mutational burden (TMB) &gt;10 mut/Mb. The registrational KEYNOTE-158 study, however, did not include any patients with metastatic breast cancer (MBC). Here we present a retrospective study of patients with TMB-high MBC treated with immune checkpoint inhibition (ICI) and report real-world efficacy endpoints, including progression free survival as well as clinical and genomic characteristics that may be associated with duration of response. Methods: All patients with MBC treated with an ICI at MSK and with TMB-high tumors (&gt;10 mut/Mb) assessed by tumor-normal targeted sequencing (MSK-IMPACT) were included. Clinicopathological and demographic data were obtained via the MSK Breast Cancer Translational Program. Mutational signatures were determined using the Signature Multivariate Analysis (SigMA) algorithm. Real world progression free survival (PFS) was determined clinically and analyzed using Kaplan-Meier estimates. Univariate and multivariate analyses were performed using Cox-proportional hazards models. Results: Of 688 patients with TMB-high breast cancer at MSKCC, 87 had received ICI-based therapy for estrogen receptor positive (ER+), triple negative breast cancer (TNBC), and HER2+ MBC. Of those, 45 patients were treated with ICI monotherapy (29 ER+, 11 TNBC, 5 HER2), 31 were treated with ICI + chemotherapy (12 ER+, 19 TNBC), and 11 were treated with combinations of ICI and targeted therapy (8 ER+, 1 TNBC, 2 HER2). Median age at time of ICI treatment across all patients was 60. ICI was the median 5th line therapy for all patients (range 1-16). Median PFS of ICI for all patients was 3.17 months (95%CI 2.27-5.5). Multivariable analysis did not show statistically significant differences in PFS based upon treatment regimen (monotherapy vs. chemoIO HR 1.03, 95%CI 0.54-1.96, p= 0.92, monotherapy vs combination IO HR 1.66, 95%CI 0.69-4.02, p=0.26), ER status (ER- vs ER+, HR 1.20, 95%CI 0.63-2.28, p=0.57), or HER2 status (HER2- vs HER2+, HR 1.63, 95%CI 0.51-5.20, p=0.41. However, longer PFS was significantly associated with TMB&gt;30 (HR 0.35, 95%CI 0.13-0.92, p=0.03) and dominant APOBEC signature score (APOBEC- vs APOBEC+, HR 0.49, 95%CI 0.25-0.98, p=0.04). Shorter PFS was significantly associated with later treatment line at the time of ICI exposure (continuous, HR 1.22, 95%CI 1.11-1.36, p=0.0001). Conclusions: In this heavily pretreated real-world cohort, ICI in TMB high MBC shows modest clinical activity. Our analysis suggests that ICI may be more effective in MBC patients that are less heavily pre-treated, have TMB&gt;30, and have a predominantly APOBEC mutational signature. Further translational work is necessary to explore the mechanisms of these findings.

Cervical cancer-specific long non-coding RNA landscape reveals the favorable prognosis predictive performance of an ion-channel-related signature model.

Ion channels play an important role in tumorigenesis and progression of cervical cancer. Multiple long non-coding RNA genes are widely involved in ion channel-related signaling regulation. However, the association and potential clinical application of lncRNAs in the prognosis of cervical cancer are still poorly explored. Thirteen patients with cervical cancer were enrolled in current study. Whole transcriptome (involving both mRNAs and lncRNAs) sequencing was performed on fresh tumor and adjacent normal tissues that were surgically resected from patients. A comprehensive cervical cancer-specific lncRNA landscape was obtained by our custom pipeline. Then, a prognostic scoring model of ion-channel-related lncRNAs was established by regression algorithms. The performance of the predictive model as well as its association with the clinical characteristics and tumor microenvironment (TME) status were further evaluated. To comprehensively identify cervical cancer-specific lncRNAs, we sequenced 26 samples of cervical cancer patients and integrated the transcriptomic results. We built a custom analysis pipeline to improve the accuracy of lncRNA identification and functional annotation and obtained 18,482 novel lncRNAs in cervical cancer. Then, 159 ion channel- and tumorigenesis-related (ICTR-) lncRNAs were identified. Based on nine ICTR-lncRNAs, we also established a prognostic scoring model and validated its accuracy and robustness in assessing the prognosis of patients with cervical cancer. Besides, the TME was characterized, and we found that B cells, activated CD8+ T, and tertiary lymphoid structures were significantly associated with ICTR-lncRNAs signature scores. We provided a thorough landscape of cervical cancer-specific lncRNAs. Through integrative analyses, we identified ion-channel-related lncRNAs and established a predictive model for assessing the prognosis of patients with cervical cancer. Meanwhile, we characterized its association with TME status. This study improved our knowledge of the prominent roles of lncRNAs in regulating ion channel in cervical cancer.

TERT-associated DNA polymerases genes link CAF and CD8+ T Cells to improve immunotherapy response rate across multiple cancers.

e14669 Background: The cancer cells exhibit heightened basal levels of responses to DNA breaks, accumulating DNA polymerases family (DNA-pol) as repair protein, thereby increasing DNA mutation and neoantigens. Based on this, we investigated the potential of DNA-pol as an immunotherapy biomarker and its underlying mechanism. Methods: We conducted a pan-cancer analysis of DNA-pol gene dysregulation in 6366 samples. Normal fibroblast, cancer-associated fibroblast, and CD8+ T cells were cultured from cancer patients (3 esophagus, 5 lung, 5 renal, and 3 liver cancer), then treated them with PD-L1 inhibitor or overexpressing TERT for RNA-seq and proteomics. 996 multiple cancer cases with ICIs were collected to test biomarker efficiency. A phase II clinical trial is evaluating and exploring our biomarker in mechanism prospectively. Results: We defined a distinct signature score of DNA-pol genes upregulated in cancer (DNA-pol-up) and linked to worse prognosis (HR=1.2). DNA-pol-up program dysregulation led to immune processes alteration and was related to upstream activation of TERT signaling (z-score=3.6) in ingenuity pathway analysis and linked to immunologically active tumors by recruiting CD8+ T cell and downregulating CAF. DNA-pol-up score was elevated in PD-L1-treated CAF and TERT-overexpressed CD8+ T cell, in MSI-H cancer, also related to more neoepitope peptides, TMB (Rho=0.54), cancer stemness (Rho=0.78), and tumor purity (Rho=0.29). Cancers that activate this program carried distinct genomic profiles with PIK3CA, KRAS, and TP53 mutations. This signature was an independent predictor for ICIs response (OR=2.52), even outperforming cytolytic activity, MSI, TMB (OR=0.9). In 12 clinical trial datasets, this signature could stratify the responding patients (maxAUC=0.762). In our phase II clinical trial, 34 liver cancer were enrolled with 4-year follow-up, it also has a satisfactory performance in predicting the ORR (AUC=0.699) and classifies mortality rate (HR=2.5), meanwhile verified its relationship with detailed potential molecular mechanism. Conclusions: Our findings identify a distinct transcriptional pattern of DNA-pol genes across cancers, which highlighted the role of DNA-pol family genes in predicting the immunotherapy response for the first time, and TERT could be a novel vaccine candidate for improving immunotherapy response.

The role of the ubiquitin ligase UBE4B in neural tumors in adults and children.

e14034 Background: In cancers of the nervous system such as neuroblastoma (NB), the ubiquitin ligase UBE4B directly ubiquitinates growth factor receptors (GFRs), influencing their trafficking and lysosomal degradation. While the diverse functions of UBE4B are acknowledged, we hypothesize that UBE4B expression has distinct associations with outcomes in pediatric versus adult nervous system cancers. We examined the impact of UBE4B expression on glioblastoma (GBM) development, growth, and metastasis by correlating its expression with patient outcomes across age groups. Methods: Glioblastoma samples that were IDH1/2 wild type (n = 2072) underwent DNA (592-gene/whole-exome) and RNA (whole transcriptome) sequencing at Caris Life Sciences. Samples were stratified by UBE4B expression (transcripts per million – TPM) quartiles for all GBM tumors (Q4: H and Q1: L) and by patient age at the time of tissue collection (younger: &lt; 30 years; older: &gt; 60 years). Cell infiltration in the tumor microenvironment was inferred by quanTIseq. Gene expression profiles were analyzed for transcriptomic signature predictive of response to immunotherapy. Overall survival (OS) was derived from insurance claims data, and Kaplan-Meier estimates were calculated. Mann-Whitney U and Chi-square/Fisher-Exact tests were applied were appropriate, with p-values adjusted for multiple comparison. Results: UBE4B expression was similar between younger (n = 57) and older (n = 1115) glioblastoma patients (median: 24.7 vs. 21.6 TPM, p = 0.17). In younger patients, those with high UBE4B expression showed improved OS compared to low expressors (24.9 vs 19.2 months [mos]; HR = 0.41, 95% CI 0.15 – 1.11, p = 0.07). However, UBE4B expression was not associated with OS among older GBM patients (13.5 vs 12.9 mos; HR 1.10 95% CI 0.9 – 1.3, p = 0.33). Within the younger cohorts, higher expression of growth factor receptor genes was observed in high compared to low UBE4B expression ( EGFR: 96.57 vs. 7.07 TPM, p = 0.0092; RET: 0.99 vs. 0.30 TPM, p = 0.018; NTRK2: 236.9 vs. 29.5 TPM, p = 0.084). Concurrent mutation of PDGFRA was also exclusively observed in UBE4B-high tumors (42.9% vs. 0% in UBE4B-L, p = 0.024). Transcriptomic analysis, however, showed that UBE4B-high tumors had lower IFN-g signature scores compared to UBE4B-L (-0.62 vs. -0.41 arbitrary units, p = 0.02). M1 macrophage cell fractions were lower in UBE4B-high compared to UBE4B-low (median: 0.33% vs. 3.38%, p = 0.005), while the fraction of B cells was significantly higher (median: 9.57% vs. 8.14%, p = 0.009). Conclusions: Higher UBE4B expression in younger GBM cases correlated with improved OS suggesting it may have utility as a prognostic biomarker. Increased expression of GFRs in younger patients with high UBE4B expression may provide rationale for new treatment strategies in these patients. Future work may prioritize designing drug targets for UBE4B, offering therapeutic opportunities, especially for younger GBM patients.

Distinct cuproptosis patterns in hepatocellular carcinoma patients correlate with unique immune microenvironment characteristics and cell-cell communication, contributing to varied overall survival outcomes.

Hepatocellular carcinoma (HCC), a prevalent cancer, is linked to cuproptosis in tumor progression. However, cuproptosis's impact on HCC prognosis and its role in the tumor microenvironment remain unclear. We aimed to explore the correlation between cellular cuproptosis and the immune microenvironment in HCC, providing potential immunotherapeutic insights. Examining cuproptosis-related genes and the immune microenvironment through consensus clustering and WGCNA. Risk models were constructed using LASSO Cox analysis and validated in an independent cohort. Gene expression data from The Cancer Genome Atlas (TCGA) database and single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database were utilized. We scored cuproptosis expression and explored immunoinfiltration and cell-cell communication. Differential signals in T_memory cells were compared across different cuproptosis levels. Cuproptosis genes associated with fibroblast recruitment (GLS) and macrophage infiltration (FDX1). Liver cancer patients categorized into two subtypes based on cuproptosis gene expression. High expression of DLAT, GLS, and CDKN2A linked to immunosuppression (TGF-β), while high FDX1, MTF1, LIAS, and LIPT1 expression enhanced communication with non-immune cells. Developed reliable prognostic signature score and nomogram using cuproptosis-related genes. Single-cell analysis revealed differences in T_memory and TAM infiltration based on cuproptosis scores, with SPP1 and MIF as dominant signaling molecules. Finally, the results of in vitro experiments showed that when DLAT or CDKN2A was knocked down, the proliferation, migration, and invasion of HCC cells were significantly decreased. Our study demonstrates that cuproptosis affects the immune microenvironment and cell-cell communication. Identified 9 genetic markers predicting survival outcomes and immunotherapy responses. Evaluating cuproptosis signaling can optimize immunotherapeutic strategies for hepatocellular carcinoma.

A blood-based 3-gene signature score for therapeutic monitoring in patients with pulmonary tuberculosis

ObjectiveTo assess the validity of Xpert Tuberculosis Fingerstick score for monitoring treatment response and analyze factors influencing its performance. Methods122 adults with pulmonary tuberculosis were recruited and stratified into three cohorts: Diabetic-drug-susceptible-TB (DM-TB), Non-diabetic-drug-susceptible-TB (NDM-TB) and Non-diabetic Multidrug-resistant TB (MDR-TB). Fingerstick blood specimens were tested at treatment initiation (M0) and the end of the first (M1), second (M2), and sixth month (M6) to generate a TB-score. ResultsThe TB-score in all participants yielded an AUC of 0.707 (95% CI: 0.579–0.834) at M2 when its performance was evaluated against sputum culture conversion. In all non-diabetes patients, the AUC reached 0.88 (95% CI: 0.756–1.000) with an optimal cut-off value of 1.95 at which sensitivity was 90.0% (95% CI: 59.6–98.2%) and specificity was 81.3% (95% CI: 70.0–88.9%). The mean TB score was higher in patients with low bacterial loads (n = 31) than those with high bacterial loads (n = 91) at M0, M1, M2, and M6, and was higher in non-cavitary patients (n = 71) than those with cavitary lesions (n = 51) at M0, M1, and M2. ConclusionXpert TB-score shows promising predictive value for culture conversion in non-diabetic TB patients. Sputum bacterial load and lung cavitation status have an influence on the value of TB score.

Luminal androgen receptor subtype and tumor-infiltrating lymphocytes groups based on triple-negative breast cancer molecular subclassification.

In our previous study, we developed a triple-negative breast cancer (TNBC) subtype classification that correlated with the TNBC molecular subclassification. In this study, we aimed to evaluate the predictor variables of this subtype classification on the whole slide and to validate the model's performance by using an external test set. We explored the characteristics of this subtype classification and investigated genomic alterations, including genomic scar signature scores. First, TNBC was classified into the luminal androgen receptor (LAR) and non-luminal androgen receptor (non-LAR) subtypes based on the AR Allred score (≥ 6 and < 6, respectively). Then, the non-LAR subtype was further classified into the lymphocyte-predominant (LP), lymphocyte-intermediate (LI), and lymphocyte-depleted (LD) groups based on stromal tumor-infiltrating lymphocytes (TILs) (< 20%, > 20% but < 60%, and ≥ 60%, respectively). This classification showed fair agreement with the molecular classification in the test set. The LAR subtype was characterized by a high rate of PIK3CA mutation, CD274 (encodes PD-L1) and PDCD1LG2 (encodes PD-L2) deletion, and a low homologous recombination deficiency (HRD) score. The non-LAR LD TIL group was characterized by a high frequency of NOTCH2 and MYC amplification and a high HRD score.

Transcript and protein signatures derived from shared molecular interactions across cancers are associated with mortality

BackgroundCharacterization of shared cancer mechanisms have been proposed to improve therapy strategies and prognosis. Here, we aimed to identify shared cell–cell interactions (CCIs) within the tumor microenvironment across multiple solid cancers and assess their association with cancer mortality.MethodsCCIs of each cancer were identified by NicheNet analysis of single-cell RNA sequencing data from breast, colon, liver, lung, and ovarian cancers. These CCIs were used to construct a shared multi-cellular tumor model (shared-MCTM) representing common CCIs across cancers. A gene signature was identified from the shared-MCTM and tested on the mRNA and protein level in two large independent cohorts: The Cancer Genome Atlas (TCGA, 9185 tumor samples and 727 controls across 22 cancers) and UK biobank (UKBB, 10,384 cancer patients and 5063 controls with proteomics data across 17 cancers). Cox proportional hazards models were used to evaluate the association of the signature with 10-year all-cause mortality, including sex-specific analysis.ResultsA shared-MCTM was derived from five individual cancers. A shared gene signature was extracted from this shared-MCTM and the most prominent regulatory cell type, matrix cancer-associated fibroblast (mCAF). The signature exhibited significant expression changes in multiple cancers compared to controls at both mRNA and protein levels in two independent cohorts. Importantly, it was significantly associated with mortality in cancer patients in both cohorts. The highest hazard ratios were observed for brain cancer in TCGA (HR [95%CI] = 6.90[4.64–10.25]) and ovarian cancer in UKBB (5.53[2.08–8.80]). Sex-specific analysis revealed distinct risks, with a higher mortality risk associated with the protein signature score in males (2.41[1.97–2.96]) compared to females (1.84[1.44–2.37]).ConclusionWe identified a gene signature from a comprehensive shared-MCTM representing common CCIs across different cancers and revealed the regulatory role of mCAF in the tumor microenvironment. The pathogenic relevance of the gene signature was supported by differential expression and association with mortality on both mRNA and protein levels in two independent cohorts.

Transcriptomic signatures of progression to TB disease among close contacts in Brazil.

Approximately 5% of people infected with Mycobacterium tuberculosis progress to tuberculosis (TB) disease without preventive therapy. There is a need for a prognostic test to identify those at highest risk of incident TB, so that therapy can be targeted. We evaluated host blood transcriptomic signatures for progression to TB disease. Close contacts (≥4 hours exposure per week) of adult patients with culture-confirmed pulmonary TB were enrolled in Brazil. Investigation for incident, microbiologically-confirmed or clinically-diagnosed pulmonary or extra-pulmonary TB disease through 24 months of follow-up was symptom-triggered. Twenty previously validated blood TB transcriptomic signatures were measured at baseline by real-time quantitative PCR. Prognostic performance for incident TB was tested using receiver operating characteristic curve (ROC) analysis at 6, 9, 12, and 24 months of follow-up. Between June 2015 and June 2019, 1,854 close contacts were enrolled; Twenty-five progressed to incident TB, of whom 13 had microbiologically-confirmed disease. Baseline transcriptomic signature scores were measured in 1,789 close contacts. Prognostic performance for all signatures was best within 6 months of diagnosis. Seven signatures (Gliddon4, Suliman4, Roe3, Roe1, Penn-Nicholson6, Francisco2, and Rajan5) met the minimum World Health Organization target product profile (TPP) for a prognostic test through 6 months; three (Gliddon4, Rajan5, and Duffy9) through 9 months. None met the TPP threshold through 12 or more months of follow-up. Blood transcriptomic signatures may be useful for predicting TB risk within 9 months of measurement among TB-exposed contacts, to target preventive therapy administration.