Tumor Purity Research Articles

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.

Exploring the role of UMP as a molecular marker in the tumor microenvironment of lung adenocarcinoma.

e20064 Background: Currently, there is a relatively extensive research emphasis on tumor microenvironment based on single-cell transcriptomics. However, the investigation of the metabolic aspects of tumor microenvironment is relatively rare due to technological limitations. To address this gap, our study employes scFEA and MEBOCOST, which are metabolic level prediction tools based on single-cell transcriptomics, to explore the metabolic landscape of tumor microenvironment in lung adenocarcinoma(LUAD). Methods: This study utilized four single-cell sequencing (scRNA-seq) datasets, two targeted metabolomics datasets, and the TCGA-LUAD RNA sequencing dataset obtained from the Cancer Genomics Data Portal. To perform dimensionality reduction, the Seurat package was employed. Cell annotation was carried out using scType, followed by manual correction using the FindAllMarkers function. Tumor cell clusters were identified by utilizing tumor marker genes and the R package inferCNV. Single-cell metabolic levels were inferred using scFEA. The TCGA-LUAD datasets underwent analysis to estimate and analyze immune levels using estimate and cibersort algorithms. Additionally, scFEA was used for metabolic level analysis, and survival analysis was conducted. UMP differential expression analysis was performed on the targeted metabolomics datasets. Results: Across all four single-cell sequence datasets, metabolites such as (GlcNAc)4 (Man)3 (Asn)1[G00015], B-Alanine[C00099], and UMP[C00105] exhibited significantly higher levels in immune cells compared to tumor cells (P < 0.05). These findings were further validated using the TCGA-LUAD datasets. Cox regression analysis was performed using immune scores and tumor purity scores and based on the median value of risk scores, high and low-risk groups were distinguished. it was observed that UMP levels were higher in the low-risk group. Moreover, higher UMP levels were associated with elevated immune levels and decreased tumor purity. Analysis of targeted metabolomics datasets from various pan-cancer cell lines revealed that UMP expression level in tumor cells was lower than that in B and T cells. Furthermore, in different subtypes of LUAD, including AAH, AIS, MIA, and IAC, UMP expression in tissues gradually decreased as the severity of the subtype increased (P < 0.05). Conclusions: The study revealed that UMP metabolites are expressed at higher levels in immune cells compared to tumor cells within LUAD. Moreover, UMP expression levels showed significant variations among different disease severities of LUAD. These findings indicate that UMP has the potential to serve as a molecular marker for distinguishing between different disease severities. Further research is needed to investigate the underlying mechanisms and validate the diagnostic usefulness of UMP in LUAD.

Ex vivo assessment of cellular mass response for personalized therapy selection of hyperthermic intraperitoneal chemotherapy (HIPEC) agents.

3132 Background: Despite progress in the development of HIPEC protocols for the treatment of peritoneal carcinomatosis, agent selection remains largely empiric with few biomarkers for guiding treatment. Ex vivo assessment of drug response using single-cell mass measurements offers a promising option for therapy selection. Previously, we have shown that mass response testing (MRT) is a malignancy- and drug-agnostic means of assessing drug response (1) and can predict a patient’s clinical response to therapy in a range of solid and hematological malignancies (2). Methods: Tissue specimens were collected from patients with peritoneal carcinomatosis as part of an ancillary study for a HIPEC clinical trial (NCT04847063) to explore the feasibility of performing MRT with these specimen types. Briefly, after overnight shipment of viable tumor tissue, tumor cells were isolated and treated with various therapies ex vivo. Single-cell mass distributions of vehicle and drug-treated populations were compared to determine the functional activity of each agent. Results: MRT was attempted for 60 patients with metastatic disease, 10 of whom had peritoneal carcinomatosis and ultimately received HIPEC. The HIPEC cases included histologies such as peritoneal mesothelioma (n=4), colorectal cancer (n=3), ovarian cancer (n=2), and small bowel adenocarcinoma (n=1). In total, 8 out of 10 peritoneal specimens had a sufficiently high tumor cell count, viability, and purity to perform MRT. These specimens displayed clear and statistically distinguishable mass response patterns of response and non-response to several different agents commonly used for HIPEC treatment such as cisplatin, oxaliplatin, doxorubicin, and mitomycin C. Study design:These feasibility results serve as the foundational data for launching a single-site phase II interventional study at the NCI’s Center for Cancer Research. The study will evaluate the potential benefit of personalized treatment regimens determined by MRT for patients with peritoneal carcinomatosis, particularly mesothelioma, a context where therapeutic options have relative equipoise in clinical efficacy. Tumor biopsies will be obtained via laparoscopy prior to HIPEC and submitted to a CLIA-certified lab for MRT to assess the responses of various clinically acceptable agents. The HIPEC regimen will be selected based on these MRT results returned within two days of sample collection. Enrolled patients will then undergo cytoreduction and HIPEC, and progression-free and overall survival will be monitored. As a single-arm, non-randomized trial, patient responses will be compared with a matched synthetic control to assess the impact of MRT on efficacy of HIPEC regimens. Conclusions: MRT is feasible for peritoneal carcinomatosis tissues, with future studies focusing on its role in guiding HIPEC treatment. 1. Nat Comm Bio,2022. 2. JCO PO, 2024. Clinical trial information: NCT04847063 .

Development and validation of mFISHseq: A diagnostic test using multiplexed RNA-FISH–guided laser capture microdissection RNA sequencing.

3069 Background: Breast cancer (BCa) is a heterogeneous disease requiring precise diagnostic tools to guide effective treatment strategies. Current diagnostic assays, including various multigene assays, often fail to adequately address the complex biology of BCa subtypes. To address these limitations and enhance the understanding of BCa biology, we developed and validated a novel diagnostic, prognostic, and predictive tool, called mFISHseq. Methods: Our approach, mFISHseq, integrates multiplexed fluorescent in situ hybridization (FISH) of the four main BCa biomarkers, estrogen ( ESR1)/progesterone ( PGR)/Her2 ( ERBB2) receptors and Ki67 ( MKI67), which are used to guide laser capture microdissection (LCM) of regions of interest followed by RNA-sequencing. This technique ensures tumor purity, facilitates interrogation of tumor heterogeneity, consequently permitting unbiased analysis of whole transcriptome profiling data and explicitly quantifying the variability between different tumor regions. We validated mFISHseq on a retrospective cohort study involving 1,082 FFPE breast tumors with detailed clinicopathological data, informed consent, and ethical committee approval. Results: mFISHseq demonstrated excellent analytical validity with a 93% accuracy rate compared to standard immunohistochemistry (IHC), while providing more quantitative biomarker expression. Prespecified threshold values for mFISHseq derived from a split 70:30 training/test set showed exceptional concordance with IHC as demonstrated by area under the receiver operating characteristic (ROC) curves for all markers (AUC: MKI67=0.98, ERBB2=0.95, ESR1=0.95, PGR=0.93). Both RNA-FISH and -SEQ showed moderate to very strong correlations (Spearman’s r; ERBB2=0.41, MKI67=0.61, PGR=0.66, ESR1=0.75), thus highlighting the potential to use both orthogonal methodologies to cross-validate results. To demonstrate clinical validity, we developed a 293-gene intrinsic subtype classifier, showing substantial agreement to established classifiers like PAM50 and AIMS (Cohen’s κ= 0.75 and 0.73, respectively) and superior prognostic performance. We also report that LCM is an essential component of the mFISHseq workflow, since samples that did not undergo LCM showed reduced biomarker expression, elevated non-tumor gene expression, and misclassification of samples into less aggressive molecular subtypes (e.g., normal-like) and prognostic risk groups (e.g., high to low). Conclusions: The mFISHseq method showed excellent concordance with IHC and the use of LCM provides tumor-enriched samples that are devoid of contamination from non-tumor elements, thus providing unbiased spatially resolved interrogation of tumor heterogeneity. Altogether, mFISHseq solves a long-standing challenge in the precise diagnosis and classification of breast cancer subtypes.

Diverging acquired resistance evolutionary pathways in fusion-positive patients treated with tyrosine kinase inhibitors.

3015 Background: Tyrosine kinase fusions are recurrent, actionable oncogenic drivers across cancer types. Multiple tyrosine kinase inhibitors (TKIs) are approved in a disease-specific or tumor-agnostic fashion for these cancers. While TKI resistance includes the acquisition of on-target and off-target alterations, a large subset of resistance remains unexplained and may not simply be mediated by singular emergent alterations. As such, we sought to define how genomic complexity evolves under the selective pressure of TKI therapy. Methods: ALK, RET, NTRK, ROS1 or FGFR fusion-positive patient (pt) tumor samples that underwent clinical FDA-authorized tumor-normal panel sequencing (MSK-IMPACT) between April 2015 and January 2023 were selected. Genomic data assessed included chromosomal instability, inferred by the fraction of genome altered (FGA), fraction of loss-of-heterozygosity (F-LOH) and tumor mutational burden (TMB). Samples with low tumor purity ( < 0.2) or indeterminate copy number profiles were excluded. Treatment data were obtained from natural language processing of electronic medical records. Results: Of 68,920 tumors with sequencing, 49,910 samples met quality requirements. Of these, 1,283 samples (2.6%) from 1,111 pts harbored the queried fusions; among these 64 pts had at least 1 TKI-naïve baseline and 1 or more post-TKI progression of disease (PD) samples, yielding a total of 147 samples usable for evaluating the intra-patient evolution of genomic complexity. The most common cancer types were non-small-cell lung cancer (NSCLC, n = 42), biliary tract cancers (n = 4), and thyroid cancer (n = 4). Paired analysis of TKI-naïve and first post-TKI PD samples in all 64 pts showed increases in FGA (median = 1.1; 0.4~6.6), F-LOH (median = 1.1; 0.2~11.5), and TMB (median = 1.3; 0.2~9.9) upon TKI-resistance (p < 0.01). Pts with primary baseline tumors (n = 22) and pts with metastatic tumors (n-42) were next evaluated independently. Increases in FGA, F-LOH and TMB upon TKI PD were statistically significant in both groups (p < 0.05). Accounting for tumor type, all 3 metrics showed increase in NSCLCs (p < 0.05), whereas only F-LOH was increased in non-lung tumors upon TKI-PD (p < 0.05). Post-PD FGA increase was seen in 22 pts, these didn’t harbor significant increase in TMB (p = 0.07; 57% increasing, 43% not increasing). Similarly, among the 38 pts with post-PD TMB increase, no significant increase in FGA was seen (p = 0.21; 56% increasing, 44% not increasing). F-LOH was increased in both pt groups (p < 0.05). Conclusions: Fusion-positive cancers acquire additional genomic alterations post-TKI, potentially via at least two main diverging evolutionary pathways: the acquisition of additional mutations or an increase in chromosomal instability. Improved understanding of pathways by which fusion-positive cancers acquire genomic complexity may yield novel treatment strategies.

Discriminating subtypes in advanced breast cancer with ctDNA methylation profiling.

1013 Background: Immunohistochemical subtyping of advanced breast cancer is critical to direct appropriate therapy. Yet, biopsy of recurrent cancer may not be technically possible, single-site tumour biopsies sample only a single metastasis and subtype may change through therapy. We developed a non-invasive blood test to subtype tumours based on circulating tumor DNA (ctDNA) methylation profiling. Methods: We interrogated TCGA-BRCA (level 3) methylation data from 783 tumours to identify regions with aberrant CpG methylation that differed between breast cancers and normal tissues, and between different breast cancer subtypes. A capture based enzymatic ctDNA based methylation profile was developed targeting 1257 differentially methylated regions (TWIST Methyl custom panel, TWIST Bioscience, panel size 0.4Mb). Plasma samples from patients with breast cancer, and healthy donors, were sequenced with the capture assay. A machine learning (ML) classifier was built to detect the presence of breast cancer, and a second classifier was built to discriminate ER positive v ER negative, and HER2 positive v HER2 negative from ctDNA methylation profiles. A 10-fold stratified nested cross-validation was used to assess classifier characteristics. Results: Plasma samples from 427 people (126 health donor, 27 early breast cancer patients and 291 metastatic breast cancer patients), along with 133 tumor tissue samples, were sequenced and a ML classifier built to detect the presence of breast cancer. In cross-validation, a random forest classifier yielded a median AUC of 0.996 (SD 0.020), with sensitivity of 94.9% at 99% specificity. A total of 231 ER positive and 63 ER negative plasma samples from patients were used for IHC ER status differentiation. In cross-validation a LGBM classifier yielded a median AUC of 0.928 (SD 0.051). Median sensitivity was 76.7% at specificity 86-99%. A total of 11% (25/231) ER positive and 8% (5/63) ER negative samples were misclassified. A total of 41 HER2 positive and 253 HER2 negative plasma samples were used for IHC HER2 status differentiation. In cross-validation a LGBM classifier yielded a median AUC of 0.934 (SD 0.075). Median sensitivity was 77.5% at specificity 85-92%, A total of 7% (3/41) HER-2 positive and 13% (33/253) HER2 negative samples were misclassified. In both IHC classifiers, subtype misclassifications were likely due to multiple concurrent BC tumours of differing IHC subtypes, biopsy proven subtype transitions and low purity. Effects of tumor purity on IHC-based classifiers will also be presented. Conclusions: Non-invasivemethylation based ctDNA subtyping can detect the presence of breast cancer, and discriminate IHC subtypes, with high accuracy. Further assessment is warranted to assess whether methylation-based subtyping has the potential to report IHC subtypes when repeat biopsy is not possible, detect subtype transitions and direct advanced breast cancer treatment.

Longitudinal tumor-wide sampling of glioblastoma reveals diverse genomic drivers of the earliest clonal expansion at diagnosis and recurrence.

2009 Background: Despite decades of clinical trials, glioblastoma (GBM) remains a rapidly fatal disease. Much of therapy resistance in GBM is attributed to intratumoral heterogeneity in which subclones rapidly evolve and treatment-resistant cell populations emerge. Understanding heterogeneity at diagnosis and its relationship to the origins of recurrence are critical to selecting therapies that are efficacious across the entire tumor. However, few genomic studies go beyond analyzing single tumor samples per patient. Methods: A spatially oriented, whole tumor sampling approach was used to obtain 43 biopsies from 3 GBMs at diagnosis and recurrence. Pyclone and ClonEvol were applied to whole exome sequencing to reconstruct clonal evolution, FACETs identified copy number variations and HATCHet estimated tumor purity. Candidate driver mutations were evaluated in relation to the Catalogue of Somatic Mutations In Cancer. Results: A single founding clone and multiple subclones were identified for each diagnosis-recurrence pair. Tumor-wide clonal alterations representing initial clonal expansions of these GBMs included both canonical changes (Chr 7 gain, Chr 10 loss, CDKN2A deletion, EGFR amplification) and a diverse set of large-scale copy number variations (Chr 19, 20 gain), driver mutations (PTEN, KDR, CDH11, CNTNAP2), and fusions (LIMCH1::UCHL1, KANK::DOCK8). A second subset of alterations (Chr 8 gain, ATRX mutation), appeared to be tumor wide at diagnosis but were not identified at recurrence. Cancer drivers were also present subclonally, including CDKN2A deletion, MDM2 amplification, and mutations in NF1, and GRM3. Evolutionary trees consisted of 5 generations of clones in Patient 323 (P323), 3 in P454, and 4 in P534. Divergence of the recurrent tumors from their matched primary occurred in the second generation in P454 and P534 and in the third in P323. As a result, an average of 37% of potential drivers of oncogenesis and clonal expansion across the cohort appear after divergence. Furthermore, each recurrent tumor contained at least one tumor wide driver alteration that was subclonal or undetected at diagnosis. Conclusions: Whole-tumor sampling of three GBM patients at both diagnosis and recurrence identified a diversity of genomic drivers and deeper and more complex genetic roots of individual GBM than previously seen in single-biopsy studies. Tumor recurrences consistently arose from a single subclone that diverged early in evolution of the primary tumor and contained clonal drivers either not detected or subclonal in the primary—suggesting a role for these drivers in persistence and expansion. In the age of personalized medicine, our study highlights the clinical potential of tumor wide sampling in identifying therapeutic targets that could avoid heterogeneity-related therapeutic failures.

Proteomic analysis of pleomorphic dermal sarcoma reveals a fibroblastic cell of origin and distinct immune evasion mechanisms

Pleomorphic dermal sarcomas are infrequent neoplastic skin tumors, manifesting in regions of the skin exposed to ultraviolet radiation. Diagnosing the entity can be challenging and therapeutic options are limited. We analyzed 20 samples of normal healthy skin tissue (SNT), 27 malignant melanomas (MM), 20 cutaneous squamous cell carcinomas (cSCC), and 24 pleomorphic dermal sarcomas (PDS) using mass spectrometry. We explored a potential cell of origin in PDS and validated our findings using publicly available single-cell sequencing data. By correlating tumor purity (TP), inferred by both RNA- and DNA-sequencing, to protein abundance, we found that fibroblasts shared most of the proteins correlating to TP. This observation could also be made using publicly available SNT single cell sequencing data. Moreover, we studied relevant pathways of receptor/ligand (R/L) interactions. Analysis of R/L interactions revealed distinct pathways in cSCC, MM and PDS, with a prominent role of PDGFRB-PDGFD R/L interactions and upregulation of PI3K/AKT signaling pathway. By studying differentially expressed proteins between cSCC and PDS, markers such as MAP1B could differentiate between these two entities. To this end, we studied proteins associated with immunosuppression in PDS, uncovering that immunologically cold PDS cases shared a “negative regulation of interferon-gamma signaling” according to overrepresentation analysis.

Defining three ferroptosis-based molecular subtypes and developing a prognostic risk model for high-grade serous ovarian cancer.

As a newly defined regulated cell death, ferroptosis is a potential biomarker in ovarian cancer (OV). However, its underlying mechanism in tumor microenvironment (TME) and clinical prediction significance in OV remained to be elucidated. The transcriptome data of high-grade serous OV from The Cancer Genome Atlas (TCGA) database were downloaded. Molecular subtypes were classified based on ferroptosis-correlated genes from the FerrDb database by performing consensus clustering analysis. The associations between the subtypes and clinicopathologic characteristics, mutation, regulatory pathways and immune landscape were assessed. A ferroptosis-related prognostic model was constructed and verified using International Cancer Genome Consortium (ICGC) cohort and GSE70769. Three molecular subtypes of OV were defined. Patients in subtype C3 tended to have the most favorable prognosis, while subtype C1 showing more mesenchymal cells, increased immune infiltration of Macrophages_M2, lower tumor purity, and epithelial-to-mesenchymal transition (EMT) features had the poorest prognosis. A ferroptosis-related risk model was constructed using 8 genes (PDP1, FCGBP, EPHA4, GAS1, SLC7A11, BLOC1S1, SPOCK2, and CXCL9) and manifested a strong prediction performance. High-risk patients had enriched EMT pathways, more Macrophages_M2, less plasma cells and CD8 cell infiltration, greater tendency of immune escape and worse prognosis. The risk score has negatively correlated relation with LAG3, TIGIT, CTLA4, IDO1, CD27, ICOS, and IL2RB but positively correlated with PVR, CD276, and CD28. Moreover, low-risk patients were more sensitive to Cisplatin and Gefitinib, Gemcitabine. Our results could improve the understanding of ferroptosis in OV, providing promising insights for the clinical targeted therapy for the cancer.

KIF23 promotes cervical cancer progression via inhibiting NLRP3-mediated pyroptosis.

Cervical cancer (CC), closely linked to persistent human papillomavirus infection, represents a major health problem for women worldwide. The objective of this study is to elucidate KIF23's role in the development of CC and its regulatory mechanism. The bioinformatics methods were utilized to extract pyroptosis-associated differentially expressed genes (DEGs) and pivot genes from the GSE9750 and GSE63678 datasets, followed by immune infiltration analysis and quantification of these genes' expression. The effects of kinesin family member 23 (KIF23) were verified through functional experiments invitro and a mouse xenograft model. The NLPR3 activator, nigericin, was applied for further analyzing the potential regulatory mechanism of KIF23 in CC. A total of 8 pyroptosis-related DEGs were screened out, among which 4 candidate core genes were identified as candidate hub genes and confirmed upregulation in CC tissues and cells. These genes respectively showed a positive correlation with the infiltration of distinct immune cells or tumor purity. Downregulation of KIF23 could suppress the proliferation, migration, and invasion abilities in CC cells and tumorigenesis through enhancing pyroptosis. Conversely, KIF23 overexpression accelerated the malignant phenotypes of CC cells and inhibited pyroptosis activation, which was blocked by nigericin treatment. KIF23 may play an oncogenic role in CC progression via inhibition of the NLRP3-mediated pyroptosis pathway.

TMErisk score: A tumor microenvironment-based model for predicting prognosis and immunotherapy in patients with head and neck squamous cell carcinoma

Tumor microenvironment (TME) is closely associated with the progression and prognosis of head and neck squamous cell carcinoma (HNSCC). To investigate potential biomarkers for predicting therapeutic outcomes in HNSCC, we analyzed the immune and stromal status of HNSCC based on the genes associated with TME using the ESTIMATE algorithm. Immune and stromal genes were identified with differential gene expression and weighted gene co-expression network analysis (WGCNA). From these genes, 118 were initially selected through Cox univariate regression and then further input into least absolute shrinkage and selection operator (LASSO) regression analysis. As a result, 11 genes were screened out for the TME-related risk (TMErisk) score model which presented promising overall survival predictive potential. The TMErisk score was negatively associated with immune and stromal scores but positively associated with tumor purity. Individuals with high TMErisk scores exhibited decreased expression of most immune checkpoints and all human leukocyte antigen family genes, and reduced abundance of infiltrating immune cells. Divergent genes were mutated in HNSCC. In both high and low TMErisk score groups, the tumor protein P53 exhibited the highest mutation frequency. A higher TMErisk score was found to be associated with reduced overall survival probability and worse outcomes of immunotherapy. Therefore, the TMErisk score could serve as a valuable model for the outcome prediction of HNSCC in clinic.

Down-regulation of KLRB1 is associated with increased cell growth, metastasis, poor prognosis, as well as a dysfunctional immune microenvironment in LUAD

Killer cell lectin-like receptor B1 (KLRB1) is implicated in cancer progression and immunity. In this study, we aimed to evaluate the expression levels of KLRB1 in lung adenocarcinoma (LUAD) and analyze the relationship between KLRB1 expression levels, LUAD progression, and the tumor immune microenvironment. KLRB1 levels in LUAD were analyzed using data from the TCGA and XENA databases. Additionally, the diagnostic values of KLRB1 were analyzed in patients with LUAD. Survival and meta-analyses were employed to investigate the relationship between KLRB1 levels and other prognostic factors in patients with LUAD. Bioinformatics and cellular experiments were used to understand the functions and mechanisms of KLRB1. In addition, correlation analysis was used to investigate the relationship between KLRB1 levels and the immune microenvironment in LUAD. Reduced KLRB1 expression in LUAD was found to positively correlate with tumor size, distant metastasis, pathological stage, age, overall survival, diagnostic value, and disease-specific survival in patients with LUAD (P < 0.05). Conversely, increased KLRB1 expression was found to positively correlate with the overall survival and disease-specific survival in patients with LUAD (P < 0.05). We also found that the overexpression of KLRB1 can inhibit the proliferation, migration, and invasion of LUAD cells and promote apoptosis. KLRB1 was involved in immune cell differentiation, NF-kB, PD-L1, and PD-1 checkpoint pathways and others. Additionally, KLRB1 expression was linked to tumor purity, stromal, immune, and estimate scores, the levels of immune cells including B cells, CD8+ T cells, and CD4+ T cells, and immune cell markers in LUAD. Reduced KLRB1 expression has a significant positive correlation with diagnosis, poor prognosis, and immunity to cancer in patients with LUAD. KLRB1 inhibited cell proliferation and migration in patients with LUAD. These results suggest that KLRB1 may serve as a potential therapeutic target in patients with LUAD.

Rapid DNA methylation-based classification of pediatric brain tumors from ultrasonic aspirate specimens

BackgroundAlthough cavitating ultrasonic aspirators are commonly used in neurosurgical procedures, the suitability of ultrasonic aspirator-derived tumor material for diagnostic procedures is still controversial. Here, we explore the feasibility of using ultrasonic aspirator-resected tumor tissue to classify otherwise discarded sample material by fast DNA methylation-based analysis using low pass nanopore whole genome sequencing.MethodsUltrasonic aspirator-derived specimens from pediatric patients undergoing brain tumor resection were subjected to low-pass nanopore whole genome sequencing. DNA methylation-based classification using a neural network classifier and copy number variation analysis were performed. Tumor purity was estimated from copy number profiles. Results were compared to microarray (EPIC)-based routine neuropathological histomorphological and molecular evaluation.Results19 samples with confirmed neuropathological diagnosis were evaluated. All samples were successfully sequenced and passed quality control for further analysis. DNA and sequencing characteristics from ultrasonic aspirator-derived specimens were comparable to routinely processed tumor tissue. Classification of both methods was concordant regarding methylation class in 17/19 (89%) cases. Application of a platform-specific threshold for nanopore-based classification ensured a specificity of 100%, whereas sensitivity was 79%. Copy number variation profiles were generated for all cases and matched EPIC results in 18/19 (95%) samples, even allowing the identification of diagnostically or therapeutically relevant genomic alterations.ConclusionMethylation-based classification of pediatric CNS tumors based on ultrasonic aspirator-reduced and otherwise discarded tissue is feasible using time- and cost-efficient nanopore sequencing.

Cellular landscape of adrenocortical carcinoma at single-nuclei resolution

Adrenocortical carcinoma (ACC) is a rare yet devastating tumour of the adrenal gland with a molecular pathology that remains incompletely understood. To gain novel insights into the cellular landscape of ACC, we generated single-nuclei RNA sequencing (snRNA-seq) data sets from twelve ACC tumour samples and analysed these alongside snRNA-seq data sets from normal adrenal glands (NAGs). We find the ACC tumour microenvironment to be relatively devoid of immune cells compared to NAG tissues, consistent with known high tumour purity values for ACC as an immunologically “cold” tumour. Our analysis identifies three separate groups of ACC samples that are characterised by different relative compositions of adrenocortical cell types. These include cell populations that are specifically enriched in the most clinically aggressive and hormonally active tumours, displaying hallmarks of reorganised cell mechanobiology and dysregulated steroidogenesis, respectively. We also identified and validated a population of mitotically active adrenocortical cells that strongly overexpress genes POLQ, DIAPH3 and EZH2 to support tumour expansion alongside an LGR4+ progenitor-like or cell-of-origin candidate for adrenocortical carcinogenesis. Trajectory inference suggests the fate adopted by malignant adrenocortical cells upon differentiation is associated with the copy number or allelic balance state of the imprinted DLK1/MEG3 genomic locus, which we verified by assessing bulk tumour DNA methylation status. In conclusion, our results therefore provide new insights into the clinical and cellular heterogeneity of ACC, revealing how genetic perturbations to healthy adrenocortical renewal and zonation provide a molecular basis for disease pathogenesis.

Discovery of PELATON links to the INHBA gene in the TGF-β pathway in colorectal cancer using a combination of bioinformatics and experimental investigations

Colorectal cancer (CRC) is a major worldwide health issue, with high rates of both occurrence and mortality. Dysregulation of the transforming growth factor-beta (TGF-β) signaling pathway is recognized as a pivotal factor in CRC pathogenesis. Notably, the INHBA gene and long non-coding RNAs (lncRNAs) have emerged as key contributors to CRC progression. The aim of this research is to explore the immunological roles of INHBA and PELATON in CRC through a combination of computational predictions and experimental validations, with the goal of enhancing diagnostic and therapeutic strategies. In this study, we utilized bioinformatics analyses, which involved examining differential gene expression (DEG) in the TCGA-COAD dataset and exploring the INHBA gene in relation to the TGF-β pathway. Additionally, we analyzed mutations of INHBA, evaluated the microenvironment and tumor purity, investigated the INHBA's connection to immune checkpoint inhibitors, and measured its potential as an immunotherapy target using the TIDE score. Utilizing bioinformatics analyses of the TCGA-COAD dataset beside experimental methodologies such as RT-qPCR, our investigation revealed significant upregulation of INHBA in CRC. As results, our analysis of the protein-protein interaction network associated with INHBA showed 10 interacting proteins that play a role in CRC-associated processes. We observed a notable prevalence of mutations within INHBA and explored its correlation with the response to immune checkpoint inhibitors. Our study highlights INHBA as a promising target for immunotherapy in CRC. Moreover, our study identified PELATON as a closely correlated lncRNA with INHBA, with experimental validation confirming their concurrent upregulation in CRC tissues. Thus, these findings highlight the importance of INHBA and PELATON in driving CRC progression, suggesting their potential utility as diagnostic and prognostic biomarkers. By integrating computational predictions with experimental validations, this research enhances our understanding of CRC pathogenesis and uncovers prospects for personalized therapeutic interventions.

Pan-cancer analysis of LRRC59 with a focus on prognostic and immunological roles in hepatocellular carcinoma.

LRRC59 is a leucine-rich repeats-containing protein located in the endoplasmic reticulum (ER), it serves as a prognostic marker in several cancers. However, there has been no systematic analysis of its role in the tumor immune microenvironment, nor its predictive value of prognosis and immunotherapy response in different cancers. A comprehensive pan-cancer analysis of LRRC59 was conducted from various databases to elucidate the associations between its expression and the prognosis of cancer, genetic alterations, tumor metabolism, and tumor immunity. Additionally, further functional assays were performed in hepatocellular carcinoma (HCC) to study its biological role in regulating cell proliferation, migration, apoptosis, cell cycle arrest, and sensitivity to immunotherapy. The pan-cancer analysis reveals a significant upregulation of LRRC59 in pan-cancer, and its overexpression is correlated with unfavorable prognosis in cancer patients. LRRC59 is negatively correlated with immune cell infiltration, tumor purity estimation, and immune checkpoint genes. Finally, the validation in HCC demonstrates LRRC59 is significantly overexpressed in cancer tissue and cell lines, and its knockdown inhibits cell proliferation and migration, promotes cell apoptosis, induces cell cycle arrest, and enhances the sensitivity to immunotherapy in HCC cells. LRRC59 emerges as a novel potential prognostic biomarker across malignancies, offering promise for anti-cancer drugs and immunotherapy.

Reactivation of methylation-silenced PAX1 inhibits cervical cancer proliferation and migration via the WNT/TIMELESS pathway.

Although aberrant methylation of PAX1 is closely associated with cervical cancer (CC), PAX1 methylation (PAX1m) and its role in CC remain to be elucidated. Here, we clarified the biological function of PAX1 in CC. First, PAX1m in ThinPrep cytologic test samples was measured via quantitative methylation-specific PCR. The results showed that PAX1 promoter methylation levels were significantly increased in CC patients (p < 0.001). We also found that PAX1 promoter methylation levels were positively correlated with tumor purity but negatively correlated with immune-infiltration via public databases. Then, CRISPR-based methylation perturbation tools (dCas9-Tet1) were constructed to further demonstrate that DNA methylation participates in the regulation of PAX1 expression directly. Gain- and loss-of-function experiments were used to show that PAX1 overexpression restrained proliferation, migration and improved cisplatin sensitivity by interfering with the WNT/TIMELESS axis in CC cells. Additionally, Co-immunoprecipitation assays further confirmed the interaction between PAX1 and TCF7L2. Taken together, our results suggested that a tumor suppressor role of PAX1 in CC and that CRISPR-based PAX1 demethylation editing might be a promising therapeutic strategy for CC.

Transcriptome analysis revealed SMURF2 as a prognostic biomarker for oral cancer.

The activation of TGF-β pathway can facilitate tumorigenesis. Understanding the TGF-related genes (TRGs) in oral cancer and determining their prognostic value is of utmost importance. The TRGs were selected to develop a prognostic model based on lasso regression. Oral cancer patients were classified into high-risk and low-risk groups based on the risk model. Subsequently, multivariate COX regression was employed to identify the prognostic marker. Additionally, the expression of SMURF2 was validated using quantitative real-time polymerase chain reaction (qRT-PCR) and the Human Protein Atlas (HPA) database. To investigate the relationship between SMURF2 expression and immune cell infiltrations, we conducted single-sample Gene Set Enrichment Analysis (ssGSEA) analyses. We identified 16 differentially expressed TRGs in oral cancer, all of which showed upregulation. From these, we selected eight TRGs as prognostic signatures. Furthermore, the high-risk group demonstrated lower infiltration levels of immune cells, immune score, and higher tumor purity. Interestingly, we also found that SMURF2 serves as an independent prognostic biomarker. SMURF2 was upregulated in oral cancer, as confirmed by public databases and qRT-PCR analysis. Importantly, our results indicate a close association between SMURF2 expression and the immune microenvironment. The 8-TRG signature prognosis model that we constructed has the ability to predict the survival rate and immune activity of oral cancer patients. SMURF2 could be effective in recognizing prognosis and evaluating immune efficacy for oral cancer.

Abstract GS03-06: Genomic and transcriptomic profiling of primary tumors from patients with HR+, HER2-, node-positive, high-risk early breast cancer in the monarchE trial

Abstract Background Two years of adjuvant abemaciclib combined with endocrine therapy (ET) resulted in significant and clinically meaningful improvement in invasive disease-free survival (IDFS) and distant relapse-free survival (DRFS) in patients (pts) with HR+, HER2-, node-positive, high-risk early breast cancer in the monarchE trial (NCT03155997). Abemaciclib benefit was sustained beyond the completion of treatment (tx) with deepening magnitude of absolute benefit in IDFS and DRFS at 5 years. Here, we evaluate comprehensive molecular profiling of archived primary tumor tissue and association with clinical outcomes. Methods For biomarker analysis, a proportionally stratified random sampling case-cohort design was utilized to include all patients who experienced an IDFS event at a pre-specified interim analysis with a median follow up of 54 months. A cohort of 895 pts (189 with IDFS event) in the abemaciclib + ET arm was matched 1:1 with 903 pts (270 with IDFS event) in the ET arm. Baseline primary tumor samples underwent exome-capture RNA sequencing (RNAseq; n=1324, 23% intent-to-treat (ITT) population) and paired tumor-normal (germline blood samples) whole-exome sequencing (WES; n=1234, 22% ITT population). Expression-based intrinsic subtypes (i.e., luminal A (LumA), luminal B (LumB), HER2-enriched (HER2E), basal- and normal-like) were characterized using the Absolute Intrinsic Molecular Subtyping model. The 21-gene expression signature score (Oncotype DX test) was inferred from RNAseq; samples were categorized into lower (0-25) and high (26-100) risk groups. To investigate associations of biomarkers with abemaciclib benefit, WES genomic events including oncogenic and hotspot mutations by OncoKB, and copy number events, of incidence &amp;gt;9% were pre-selected. Results The biomarker subset of monarchE was reflective of the ITT population. A total of 1190 tumors (abemaciclib+ET n= 605; ET alone n=585) yielded adequate RNAseq results. Intrinsic subtype distribution was consistent across tx arms (Table A). Low tumor purity limited assessment of the normal-like subtype. The 4-year IDFS benefit of abemaciclib was consistent across all subtypes. LumA cancers had the lowest risk of recurrence while HER2E and basal-like subtypes had the highest. Inferred 21-gene expression signature score showed similar benefits from abemaciclib in both lower and high-risk groups (Table B). A total of 1173 tumors yielded adequate WES results (abemaciclib+ET n=580; ET alone n=593). Consistent abemaciclib benefit was observed across the most frequently altered genes (Table C). In exploratory analysis, lower benefit from abemaciclib was seen in the subset of focal-high level MYC amplified tumors (n=176, HR 1.30, 95% CI, 0.77, 2.20) compared to MYC non-amplified tumors (n=997, HR 0.62, 95% CI, 0.47, 0.80, nominal interaction p=0.014). The treatment benefit of abemaciclib was observed across all subpopulations of altered genes based on gene expression data. Conclusions Adjuvant abemaciclib+ET maintained IDFS benefit compared to ET alone across all molecular subtypes as measured by RNAseq. Benefit was consistent across most altered genes assessed by WES, except for the subset of tumors with MYC amplification. Additional research is necessary to confirm these findings. Table. Citation Format: Nicholas Turner, Jorge Reis-Filho, Matthew Goetz, Christine Desmedt, Sarat Chandarlapaty, Hironobu Sasano, Carlos Arteaga, Sherene Loi, Stephanie Graff, Deli Liu, Vanessa Rodrik-Outmezguine, Anthony Sireci, Cynthia Sandoval Rubenstein, Helen Won, Lacey M. Litchfield, Maria Munoz, Stephen Johnston. Genomic and transcriptomic profiling of primary tumors from patients with HR+, HER2-, node-positive, high-risk early breast cancer in the monarchE trial [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr GS03-06.

Identification of Hub Genes in Liver Hepatocellular Carcinoma Based on Weighted Gene Co-expression Network Analysis.

Liver hepatocellular carcinoma (LIHC) is a malignant cancer with high incidence and poor prognosis. To investigate the correlation between hub genes and progression of LIHC and to provided potential prognostic markers and therapy targets for LIHC. Our study mainly used The Cancer Genome Atlas (TCGA) LIHC database and the gene expression profiles of GSE54236 from the Gene Expression Omnibus (GEO) to explore the differential co-expression genes between LIHC and normal tissues. The differential co-expression genes were extracted by Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis methods. The Genetic Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were carried out to annotate the function of differential genes. Then the hub genes were validated using protein-protein interaction (PPI) network. And the expression level and prognostic analysis were performed. The probable associations between the expression of hub genes and both tumor purity and infiltration of immune cells were explored by TIMER. A total of 68 differential co-expression genes were extracted. These genes were mainly enriched in complement activation (biological process), collagen trimer (cellular component), carbohydrate binding and receptor ligand activity (molecular function) and cytokine - cytokine receptor interaction. Then we demonstrated that the 10 hub genes (CFP, CLEC1B, CLEC4G, CLEC4M, FCN2, FCN3, PAMR1 and TIMD4) were weakly expressed in LIHC tissues, the qRT-PCR results of clinical samples showed that six genes were significantly downregulated in LIHC patients compared with adjacent tissues. Worse overall survival (OS) and disease-free survival (DFS) in LIHC patients were associated with the lower expression of CFP, CLEC1B, FCN3 and TIMD4. Ten hub genes had positive association with tumor purity. CFP, CLEC1B, FCN3 and TIMD4 could serve as novel potential molecular targets for prognosis prediction in LIHC.