Tumor Mutational Burden Scores Research Articles

Therapeutic potential of immune-cold solid tumors through homologous recombination deficiency.

e14585 Background: Genome-wide homologous recombination deficiency (HRD) score is an important parameter to select patients for HRR pathway inhibitors. HRD scores are independent therapeutic predictors unlike tumor mutation burden (TMB), and microsatellite instability (MSI) values to stratify tumors for predicting immunogenicity. Since solid tumors often choose the hallmark of immune evasion to disseminate to distant tissues, their identification and treatment through genomic signatures for immunotherapy is essential. Low TMB and MSI values are often associated with immune evasion and immune cold tumors. For such patients HRD scores can be important determinants to inform on the therapeutic potential of HRR pathway inhibitors and immune checkpoint inhibitors (ICI). In this study, we retrospectively investigated solid tumors with metastatic phenotypes exhibiting microsatellite stable (MSS), MSI-Low and TMB low phenotypes. The presence of HRR pathway deficiency in these patients may lead to chromosomal instabilities and cell surface neo-antigens thereby offering potential therapeutic benefit to PARP inhibitors and ICI. Methods: 53 metastatic cancer patients were retrospectively analysed for genome-wide HRD, TMB and MSI scores based on OncoIndx comprehensive gene panel (CGP). OncoIndx CGP targets 1080 cancer related genes along with 47 HRR genes and 1600 MSI signature sites. HRD, TMB and MSI scores were determined by sequencing the individual sample libraries in pair end mode on Illumina Nextseq platform (depth 5500X). Cutoff scores HRD high (≥50), TMB high (≥10 Mutations/MB), MSI high (≥20). Results: A cohort of 53 solid tumor patients were evaluated retrospectively of which 71.6% (n=38) patients showed metastasis (brain, Popliteal fossa, skeletal, and nodal metastasis). Of these, 9.4% (n=5) patients were detected with MSI-high, 56.6% (n=30) were MSI-Low and 1.8% (n=1) were MSS. 13.2% (n=7) patients were TMB-High, 3.7% (n=2) were TMB intermediate and 41.0% (n=22) were TMB-Low. Most importantly, 41.0% (n=22) patients were both MSI and TMB low thus transforming the tumor suggestively immune-cold. Only 22.7% (n=5) patients showed PD-L1 expression on IHC with scores ranging from TPS: 2% to 20%. In this dominantly immune-cold patient cohort, 40.9% (n=9) patients showed high/intermediate HRD (22.7% high (n=5); 18.18% Intermediate (n=4)). Conclusions: The presence of HRD in 40.9% patients in the dominant immune-cold patients was observed with increased chromosomal instability and cell surface neo-antigens. Thus, HRD could potentially transform tumors to become immune-hot to benefit from PARP inhibitors and ICI.

Comparative genomic profiling of circulating tumor DNA and paired formalin-fixed paraffin-embedded (FFPE) DNA from Indian patients with breast cancer.

e14554 Background: Breast cancer (BC) is the most frequent malignancy and a leading cause of mortality in women worldwide. Although most BCs are treated with curative intent, 30-40 % patients experience disease progression or metastatic relapse. Considering high heterogeneity of BC, mutational profiling of solid biopsy may not be adequate for informed treatment decisions in all cases. Liquid biopsy based on circulating tumor DNA (ctDNA) analysis is emerging as an equivalent and alternative to tissue biopsy in clinical settings. Though extremely critical for management of BC, liquid biopsy is not a standard of care in India. Here we compared comprehensive genomic profiles of ctDNA and paired biopsy samples to determine the efficacy of ctDNA assay in detecting actionable mutational targets. Methods: Retrospectively, genomic DNA and matched ctDNA was isolated from both FFPE and blood samples of14 BC patients. The patients were confirmative with pathological findings, having metastatic infiltrating ductal carcinoma, or triple negative breast cancers. Genome-wide HRD, TMB and MSI scores based on the OncoIndx comprehensive gene panel (CGP) was determined. OncoIndx CGP targets 1080 cancer related genes along with 47 HRR genes and 1600 MSI signature sites. Libraries were prepared using a hybridization-capture method based on custom-designed OncoIndx 1080 CGP and sequenced (depth 5500 X) on Illumina Nextseq 2000 in a pair-end mode (150 x2). Variant calling was performed using a proprietary bioinformatics pipeline iCare. Results: All patients were diagnosed with metastatic infiltrating ductal carcinoma, or triple negative breast cancers. From the patient cohort, microsatellite instability (MSI) from ctDNA showed 100% concordance with FFPE DNA while tumor mutation burden (TMB) and homologous recombination deficiency (HRD) scores showed 71.4 % and 64.2 % concordance with FFPE DNA respectively. At the individual gene mutation level, the concordance TP53, BRCA1/2, PI3K family of genes, ESR1, PTEN, ERBB2, PALB2, and BRAF genes between ctDNA and FFPE DNA was 54.7%, 92.8%, 54.7%, 78.5%, 92.8%, 100%, 100%, and 100% respectively. Many important genomic alterations including PIK3CA:p.L334H, PIK3CA:p.E81K, ESR1:p.Q375L, BRCA2:p.X3040_splice, PTEN:p.D19H were exclusive to ctDNA thereby denoting potential tumor heterogeneities which could be missed from FFPE DNA. Conclusions: Our results suggest a high correlation between ctDNA and FFPE DNA detected by OncoIndx test in metastatic or triple negative breast cancer patients of Indian ethnicity. Although not a part of standard of care, liquid biopsy could be of significant potential for management of BC in the standard clinical settings. However, a thorough investigation of cancer stage, and clinical presentations are necessary to carefully evaluate the selection of ctDNA or FFPE DNA-based genomic profiling.

Harmonizing tumor mutational burden analysis: Insights from a multicenter study using in silico reference data sets in clinical whole-exome sequencing (WES).

Tumor mutational burden (TMB) is a significant biomarker for predicting immune checkpoint inhibitor response, but the clinical performance of whole-exome sequencing (WES)-based TMB estimation has received less attention compared to panel-based methods. This study aimed to assess the reliability and comparability of WES-based TMB analysis among laboratories under routine testing conditions. A multicenter study was conducted involving 24 laboratories in China using in silico reference data sets. The accuracy and comparability of TMB estimation were evaluated using matched tumor-normal data sets. Factors such as accuracy of variant calls, limit of detection (LOD) of WES test, size of regions of interest (ROIs) used for TMB calculation, and TMB cutoff points were analyzed. The laboratories consistently underestimated the expected TMB scores in matched tumor-normal samples, with only 50% falling within the ±30% TMB interval. Samples with low TMB score (<2.5) received the consensus interpretation. Accuracy of variant calls, LOD of the WES test, ROI, and TMB cutoff points were important factors causing interlaboratory deviations. This study highlights real-world challenges in WES-based TMB analysis that need to be improved and optimized. This research will aid in the selection of more reasonable analytical procedures to minimize potential methodologic biases in estimating TMB in clinical exome sequencing tests. Harmonizing TMB estimation in clinical testing conditions is crucial for accurately evaluating patients' response to immunotherapy.

Molecular and immune characterization of Chinese early-stage non-squamous non-small cell lung cancer: a multi-omics cohort study.

Albeit considered with superior survival, around 30% of the early-stage non-squamous non-small cell lung cancer (Ns-NSCLC) patients relapse within 5 years, suggesting unique biology. However, the biological characteristics of early-stage Ns-NSCLC, especially in the Chinese population, are still unclear. Multi-omics interrogation of early-stage Ns-NSCLC (stage I-III), paired blood samples and normal lung tissues (n=76) by whole-exome sequencing (WES), RNA sequencing, and T-cell receptor (TCR) sequencing were conducted. An average of 128 exonic mutations were identified, and the most frequently mutant gene was EGFR (55%), followed by TP53 (37%) and TTN (26%). Mutations in MUC17, ABCA2, PDE4DIP, and MYO18B predicted significantly unfavorable disease-free survival (DFS). Moreover, cytobands amplifications in 8q24.3, 14q13.1, 14q11.2, and deletion in 3p21.1 were highlighted in recurrent cases. Higher incidence of human leukocyte antigen loss of heterozygosity (HLA-LOH), higher tumor mutational burden (TMB) and tumor neoantigen burden (TNB) were identified in ever-smokers than never-smokers. HLA-LOH also correlated with higher TMB, TNB, intratumoral heterogeneity (ITH), and whole chromosomal instability (wCIN) scores. Interestingly, higher ITH was an independent predictor of better DFS in early-stage Ns-NSCLC. Up-regulation of immune-related genes, including CRABP2, ULBP2, IL31RA, and IL1A, independently portended a dismal prognosis. Enhanced TCR diversity of peripheral blood mononuclear cells (PBMCs) predicted better prognosis, indicative of a noninvasive method for relapse surveillance. Eventually, seven machine-learning (ML) algorithms were employed to evaluate the predictive accuracy of clinical, genomic, transcriptomic, and TCR repertoire data on DFS, showing that clinical and RNA features combination in the random forest (RF) algorithm, with area under the curve (AUC) of 97.5% and 83.3% in the training and testing cohort, respectively, significantly outperformed other methods. This study comprehensively profiled the genomic, transcriptomic, and TCR repertoire spectrums of Chinese early-stage Ns-NSCLC, shedding light on biological underpinnings and candidate biomarkers for prognosis development.

TET1 is a Diagnostic and Prognostic Biomarker Associated with Immune Infiltration in Papillary Thyroid Cancer.

To investigate the function of ten-eleven translocation 1 (TET1) and its underlying mechanism in papillary thyroid cancer (PTC). Using the RNA-Seq data based on GDC TCGA, we analyzed the gene expression pattern of TET1 in PTC. Immunohistochemistry was carried out to assess the TET1 protein level. Then, its diagnostic and prognostic functions were determined by various bioinformatics approaches. Enrichment analysis was performed to explore the potential pathways in which TET1 is mainly involved. Finally, the immune cell infiltration analysis was conducted and the association of TET1 mRNA expression with the expression levels of immune checkpoints, tumor mutation burden (TMB) score, microsatellite instability (MSI) score, and cancer stem cells (CSC) score was examined. TET1 expression was lower in PTC tissues compared with that in normal tissues (P < 0.01). Besides, TET1 had a certain value in diagnosing PTC, and low-TET1 mRNA expression led to favorable disease-specific survival (DSS) (P < 0.01). The enrichment analysis revealed autoimmune thyroid disease and cytokine-cytokine receptor interaction were the consistent pathways in which TET1 participated. TET1 was negatively correlated with the Stromal score and Immune score. The different proportions of immune cell subtypes were observed between high- and low-TET1 expression groups. Interestingly, TET1 mRNA expression was inversely related to the expression levels of immune checkpoints, and TMB, MSI, and CSC scores. TET1 might be a robust diagnostic and prognostic biomarker for PTC. TET1 affected the DSS of PTC patients possibly through the regulation of immune-related pathways and tumor immunity.

Ferroptosis biomarkers predict tumor mutation burden's impact on prognosis in HER2-positive breast cancer.

Ferroptosis has recently been associated with multiple degenerative diseases. Ferroptosis induction in cancer cells is a feasible method for treating neoplastic diseases. However, the association of iron proliferation-related genes with prognosis in HER2+ breast cancer (BC) patients is unclear. To identify and evaluate fresh ferroptosis-related biomarkers for HER2+ BC. First, we obtained the mRNA expression profiles and clinical information of HER2+ BC patients from the TCGA and METABRIC public databases. A four-gene prediction model comprising PROM2, SLC7A11, FANCD2, and FH was subsequently developed in the TCGA cohort and confirmed in the METABRIC cohort. Patients were stratified into high-risk and low-risk groups based on their median risk score, an independent predictor of overall survival (OS). Based on these findings, immune infiltration, mutations, and medication sensitivity were analyzed in various risk groupings. Additionally, we assessed patient prognosis by combining the tumor mutation burden (TMB) with risk score. Finally, we evaluated the expression of critical genes by analyzing single-cell RNA sequencing (scRNA-seq) data from malignant vs normal epithelial cells. We found that the higher the risk score was, the worse the prognosis was (P < 0.05). We also found that the immune cell infiltration, mutation, and drug sensitivity were different between the different risk groups. The high-risk subgroup was associated with lower immune scores and high TMB. Moreover, we found that the combination of the TMB and risk score could stratify patients into three groups with distinct prognoses. HRisk-HTMB patients had the worst prognosis, whereas LRisk-LTMB patients had the best prognosis (P < 0.0001). Analysis of the scRNA-seq data showed that PROM2, SLC7A11, and FANCD2 were significantly differentially expressed, whereas FH was not, suggesting that these genes are expressed mainly in cancer epithelial cells (P < 0.01). Our model helps guide the prognosis of HER2+ breast cancer patients, and its combination with the TMB can aid in more accurate assessment of patient prognosis and provide new ideas for further diagnosis and treatment.

Phase II study of nivolumab in patients with genetic alterations in DNA damage repair and response who progressed after standard treatment for metastatic solid cancers (KM-06)

BackgroundImmune-modulating antibodies targeting programmed cell death protein 1/programmed death-ligand 1 (PD-1/PD-L1) have demonstrated promising antitumor efficacy in various types of cancers, especially highly mutated ones. Genetic alterations in DNA damage...

Tumor mutational burden assessment and standardized bioinformatics approach using custom NGS panels in clinical routine

BackgroundHigh tumor mutational burden (TMB) was reported to predict the efficacy of immune checkpoint inhibitors (ICIs). Pembrolizumab, an anti-PD-1, received FDA-approval for the treatment of unresectable/metastatic tumors with high TMB as determined by the FoundationOne®CDx test. It remains to be determined how TMB can also be calculated using other tests.ResultsFFPE/frozen tumor samples from various origins were sequenced in the frame of the Institut Curie (IC) Molecular Tumor Board using an in-house next-generation sequencing (NGS) panel. A TMB calculation method was developed at IC (IC algorithm) and compared to the FoundationOne® (FO) algorithm.Using IC algorithm, an optimal 10% variant allele frequency (VAF) cut-off was established for TMB evaluation on FFPE samples, compared to 5% on frozen samples. The median TMB score for MSS/POLE WT tumors was 8.8 mut/Mb versus 45 mut/Mb for MSI/POLE-mutated tumors. When focusing on MSS/POLE WT tumor samples, the highest median TMB scores were observed in lymphoma, lung, endometrial, and cervical cancers. After biological manual curation of these cases, 21% of them could be reclassified as MSI/POLE tumors and considered as “true TMB high.” Higher TMB values were obtained using FO algorithm on FFPE samples compared to IC algorithm (40 mut/Mb [10–3927] versus 8.2 mut/Mb [2.5–897], p < 0.001).ConclusionsWe herein propose a TMB calculation method and a bioinformatics tool that is customizable to different NGS panels and sample types. We were not able to retrieve TMB values from FO algorithm using our own algorithm and NGS panel.

Machine learning developed an intratumor heterogeneity signature for predicting prognosis and immunotherapy benefits in skin cutaneous melanoma.

Intratumor heterogeneity (ITH) is defined as differences in molecular and phenotypic profiles between different tumor cells and immune cells within a tumor. ITH was involved in the cancer progression, aggressiveness, therapy resistance and cancer recurrence. Integrative machine learning procedure including 10 methods was conducted to develop an ITH-related signature (IRS) in The Cancer Genome Atlas (TCGA), GSE54467, GSE59455 and GSE65904 cohort. Several scores, including tumor immune dysfunction and exclusion (TIDE) score, tumor mutation burden (TMB) score and immunophenoscore (IPS), were used to evaluate the role of IRS in predicting immunotherapy benefits. Two immunotherapy datasets (GSE91061 and GSE78220) were utilized to the role of IRS in predicting immunotherapy benefits of skin cutaneous melanoma (SKCM) patients. The optimal prognostic IRS constructed by Lasso method acted as an independent risk factor and had a stable and powerful performance in predicting the overall survival rate in SKCM, with the area under the curve of 2-, 3- and 4-year receiver operating characteristic curve being 0.722, 0.722 and 0.737 in TCGA cohort. We also constructed a nomogram and the actual 1-, 3- and 5-year survival times were highly consistent with the predicted survival times. SKCM patients with low IRS scores had a lower TIDE score, lower immune escape score and higher TMB score, higher PD1&CTLA4 IPS. Moreover, SKCM patients with low IRS scores had a lower gene sets score involved in DNA repair, angiogenesis, glycolysis, hypoxia, IL2-STAT5 signaling, MTORC1 signaling, NOTCH signaling and P53 pathway. The current study constructed a novel IRS in SKCM using 10 machine learning methods. This IRS acted as an indicator for predicting the prognosis and immunotherapy benefits of SKCM patients.

Molecular map of disulfidptosis-related genes in lung adenocarcinoma: the perspective toward immune microenvironment and prognosis

BackgroundDisulfidptosis is a recently discovered form of programmed cell death that could impact cancer development. Nevertheless, the prognostic significance of disulfidptosis-related genes (DRGs) in lung adenocarcinoma (LUAD) requires further clarification.MethodsThis study systematically explores the genetic and transcriptional variability, prognostic relevance, and expression profiles of DRGs. Clusters related to disulfidptosis were identified through consensus clustering. We used single-sample gene set enrichment analysis and ESTIMATE to assess the tumor microenvironment (TME) in different subgroups. We conducted a functional analysis of differentially expressed genes between subgroups, which involved gene ontology, the Kyoto encyclopedia of genes and genomes, and gene set variation analysis, in order to elucidate their functional status. Prognostic risk models were developed using univariate Cox regression and the least absolute shrinkage and selection operator regression. Additionally, single-cell clustering and cell communication analysis were conducted to enhance the understanding of the importance of signature genes. Lastly, qRT-PCR was employed to validate the prognostic model.ResultsTwo clearly defined DRG clusters were identified through a consensus-based, unsupervised clustering analysis. Observations were made concerning the correlation between changes in multilayer DRG and various clinical characteristics, prognosis, and the infiltration of TME cells. A well-executed risk assessment model, known as the DRG score, was developed to predict the prognosis of LUAD patients. A high DRG score indicates increased TME cell infiltration, a higher mutation burden, elevated TME scores, and a poorer prognosis. Additionally, the DRG score showed a significant correlation with the tumor mutation burden score and the tumor immune dysfunction and exclusion score. Subsequently, a nomogram was established for facilitating the clinical application of the DRG score, showing good predictive ability and calibration. Additionally, crucial DRGs were further validated by single-cell sequencing data. Finally, crucial DRGs were further validated by qRT-PCR and immunohistochemistry.ConclusionOur new DRG signature risk score can predict the immune landscape and prognosis of LUAD. It also serves as a reference for LUAD's immunotherapy and chemotherapy.

A novel sub-regional radiomics model to predict immunotherapy response in non-small cell lung carcinoma.

Identifying precise biomarkers of immunotherapy response for non-small cell lung carcinoma (NSCLC) before treatment is challenging. This study aimed to construct and investigate the potential performance of a sub-regional radiomics model (SRRM) as a novel tumor biomarker in predicting the response of patients with NSCLC treated with immune checkpoint inhibitors, and test whether its predictive performance is superior to that of conventional radiomics, tumor mutational burden (TMB) score and programmed death ligand-1 (PD-L1) expression. We categorized 264 patients from retrospective databases of two centers into training (n = 159) and validation (n = 105) cohorts. Radiomic features were extracted from three sub-regions of the tumor region of interest using the K-means method. We extracted 1,896 features from each sub-region, resulting in 5688 features per sample. The least absolute shrinkage and selection operator regression method was used to select sub-regional radiomic features. The SRRM was constructed and validated using the support vector machine algorithm. We used next-generation sequencing to classify patients from the two cohorts into high TMB (≥ 10 muts/Mb) and low TMB (< 10 muts/Mb) groups; immunohistochemistry was performed to assess PD-L1 expression in formalin-fixed, paraffin-embedded tumor sections, with high expression defined as ≥ 50% of tumor cells being positive. Associations between the SRRM and progression-free survival (PFS) and variant genes were assessed. Eleven sub-regional radiomic features were employed to develop the SRRM. The areas under the receiver operating characteristic curve (AUCs) of the proposed SRRM were 0.90 (95% confidence interval [CI] 0.84-0.96) and 0.86 (95% CI 0.76-0.95) in the training and validation cohorts, respectively. The SRRM (low vs. high; cutoff value = 0.936) was significantly associated with PFS in the training (hazard ratio [HR] = 0.35 [0.24-0.50], P < 0.001) and validation (HR = 0.42 [0.26-0.67], P = 0.001) cohorts. A significant correlation between the SRRM and three variant genes (H3C4, PAX5, and EGFR) was observed. In the validation cohort, the SRRM demonstrated a higher AUC (0.86, P < 0.001) than that for PD-L1 expression (0.66, P = 0.034) and TMB score (0.54, P = 0.552). The SRRM had better predictive performance and was superior to conventional radiomics, PD-L1 expression, and TMB score. The SRRM effectively stratified the progression-free survival (PFS) risk among patients with NSCLC receiving immunotherapy.

Exploration of Key Genes Combining with Immune Infiltration Level and Tumor Mutational Burden in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a lethal malignancy due to its heterogeneity and aggressive behavior. Recently, somatic mutations and tumor cell interactions with the surrounding tumor immune microenvironment (TIME) have been reported to participate in HCC carcinogenesis and predict HCC progression. In this study, we aimed to investigate the association between tumor mutational burden (TMB) and TIME in HCC. Additionally, we sought to identify differentially expressed genes (DEGs) associated with HCC prognosis and progression. The expression, clinical, and mutational data were downloaded from the cancer genome atlas (TCGA) database. The immune infiltration levels and TMB levels of the HCC samples were estimated and the samples were divided into immune cluster (ICR)-1 and 2 based on immune infiltration score and high and low TMB groups based on TMB score. Thereafter, differential gene expression analysis was conducted to identify the DEGs in the ICR1/2 and high/low TMB groups, and the intersecting DEGs were selected. Thereafter, Cox regression analysis was performed on 89 significant DEGs, among which 19 were associated with prognosis. These 19 DEGs were then used to construct a prognostic model based on their expression levels and regression coefficients. Thereafter, we analyzed the DEGs in mutant and wildtype TP53 HCC samples and identified high BCL10 and TRAF3 expression in the mutant TP53 samples. BCL10 and TRAF3 expression was detected by real-time quantitative reverse transcription PCR and immunohistochemistry, and their clinical correlation, biological function, and immune infiltration levels were analyzed by chi-square analyses, Gene Set Enrichment Analysis (GSEA), and “ssGSEA”, respectively. The results of our study revealed that immune infiltration level was correlated with TMB and that they synergistically predicted poor prognosis of HCC patients. DEGs enriched in immune-related pathways could serve as indicators of immunotherapy response in HCC. Among these DEGs, BCL10 and TRAF3 were highly expressed in HCC tissues, especially in the mutant TP53 group, and they co-operatively exhibited immunological function, thereby affecting HCC progression and prognosis. In this study, we identified BCL10 and TRAF3 as potential prognostic indicators in HCC patients. Additionally, we found that BCL10 and TRAF3 influence TMB and TIME in HCC patients and can be used for the development of immune-based therapies for improving the long-term survival of HCC patients.

Clinical significance and immune characteristics analysis of miR-221-3p and its key target genes related to epithelial-mesenchymal transition in breast cancer.

MicroRNA-221-3p (miR-221-3p) facilitates the advancement of breast cancer (BC) through the induction of epithelial-mesenchymal transition (EMT). Our research aimed to utilize bioinformatics to discover possible EMT-related target genes (ETGs) of miR-221-3p and examine their roles in breast cancer. We employed bioinformatics techniques to identify ten key ETGs of miR-221-3p. Subsequently, we conducted an extensive analysis of both miR-221-3p and the ten ETGs, including clinical significance and immune characteristics. The expression of miR-221-3p was notably higher in Basal-like BC compared to other subtypes and adjacent normal tissue. Our pathway analysis suggested that miR-221-3p might regulate EMT through the MAPK signaling pathway by targeting its ETGs. Among the ETGs, seven core genes (EGFR, IGF1, KDR, FGF2, KIT, FGFR1, and FGF1) exhibited downregulation in BC. Conversely, ERBB2, SDC1, and MMP14 showed upregulation in BC and displayed potential diagnostic value. The analysis of prognostication indicated that increased levels of SDC1 and MMP14 were correlated with an unfavorable prognosis, whereas elevated expression of KIT was associated with a more favorable prognosis. The infiltration of various immune cells and the expression of immune checkpoint genes (ICGs) exhibited positive correlations with most ETGs and miR-221-3p. SDC1 exhibited a greater tumor mutational burden (TMB) score, while ERBB2, KDR, FGF2, KIT, FGFR1, and FGF1 showed lower TMB scores. Furthermore, decreased ERBB2 and KDR expression levels were correlated with elevated microsatellite instability (MSI) scores. Elevated expression of ETGs was linked to decreased mRNA stemness indices (mRNAsi), whereas miR-221-3p displayed the opposite pattern. Most ETGs and miR-221-3p expression exhibited a negative correlation with IC50 values for drugs. Among the ETGs, amplification was the most significant genetic alteration, except for IGF1. In conclusion, miR-221-3p acts as a unique indicator for Basal-like BC. The examination revealed ten essential ETGs of miR-221-3p, some of which show potential as diagnostic and prognostic markers. The in-depth examination of these ten ETGs and miR-221-3p indicates their participation in the development of BC, emphasizing their promise as innovative targets for therapy in BC patients.

Comprehensive characterization of PKHD1 mutation in human colon cancer.

The PKHD1 (Polycystic Kidney and Hepatic Disease 1) gene is essential for producing fibrocystin or polyductin, which is crucial in various cellular functions. Mutations in PKHD1 have been found to be involved in the development and progression of colorectal cancer (CRC). Along with APC, TP53, and KRAS, PKHD1 is one of the most frequently mutated genes in CRC. PKHD1 expression is governed by the Wnt/PCP pathway, often dysregulated in CRC. Targeting this pathway, crucial for CRC progression, could unveil potential therapeutic strategies for colon cancer treatment. This study examined an in-house dataset of 3702 colon cancer samples, analyzing mutation landscapes, clinical features, tumor mutational burden (TMB), microsatellite instability (MSI), and chromosomal instability (CIN) score. For the survival analysis of PKHD1 patients, survival data of 436 colon adenocarcinoma samples were obtained from TCGA dataset. Additionally, 433 samples from TCGA with RNA-seq data were used for the assessment of immune cell infiltration and gene set enrichment analysis. Polycystic Kidney and Hepatic Disease 1 mutation was detected in 424 colon cancer patients from our in-house cohort and was associated with increased TMB, higher MSI, and lower CIN score. Importantly, within the TCGA dataset, PKHD1 mutations were identified as an independent prognostic factor, not merely correlated with established prognostic biomarkers, and were associated with poorer overall survival outcomes. In terms of immune response, these mutations correlated with increased enrichment scores for 12 immune cell types, including B cell plasma, macrophages, and naive CD4+ T cells. Additionally, interferon alpha and interferon-gamma gene sets were significantly down-regulated in patients with PKHD1 mutations (FDA q-value < 0.1). Overall, these findings suggest that PKHD1 may be a potential biomarker for the prognosis of colon cancer and provide some insight for personalized immunotherapy.

Identification of the Expression of TIE1 and Its Mediated Immunosuppression in Gastric Cancer.

Background: Recently, various evidence has confirmed that Tyrosine Kinase with Immunoglobulin-like and EGF-like domains 1 (TIE1) promotes tumor growth in many cancers. However, the precise mechanism underlying TIE1's involvement in Gastric Cancer (GC) remains elusive. This research aimed to investigate the biological function of TIE1 in regulating GC progression. Methods: The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), GEPIA2.0, Sangerbox3.0 and TIMER databases were used to analyze the TIE1 expression. Immunohistochemistry (IHC) was used to demonstrate the expression of TIE1. TCGA, GEPIA2.0 and Kaplan-Meier were utilized for survival analysis and to explore the association of TIE1 with clinicopathological features. Protein-Protein Interaction (PPI) networks were constructed using Cytoscape. The potential molecular mechanism of TIE1 was investigated by Gene Ontology (GO), Kyoto Encyclopedia of Gene Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). We studied the relationships between TIE1 and mutations, immune checkpoints (ICs), tumor mutational burden (TMB), as well as microsatellite instability (MSI) to explore the underlying mechanism of immunity in GC. Results: Compared with normal tissue, TIE1 was significantly overexpressed in GC tissues (p = 0.0072) and was associated with poor survival (P < 0.05). According to GO and KEGG enrichment analyses, TIE1 was enriched in signal pathways related to the occurrence, invasion, and migration of malignant tumors (i.e., PI3K-Akt signaling pathway, Calcium signaling pathway, etc.). Immune infiltration analysis suggested that TIE1 is positively correlated with macrophages M2 and negatively correlated with Mast cells, naive B cells and Follicular helper T cells (TFH), which may be a contributing factor to tumor progression. Furthermore, the research on the tumor microenvironment (TME) and tumor purity also proved that TIE1 may be an oncogene. Mutation analysis showed that the high expression group of TIE1 had a higher frequency of mutations in TP53 and ARID1, while the TMB score was lower. Conclusion: TIE1 might be an oncogene via regulating dysregulated immune infiltration to cause immunosuppression in GC and could be identified as a biomarker for prognosis and a therapeutic target for GC.

Combination of oligo-fractionated irradiation with nivolumab can induce immune modulation in gastric cancer

BackgroundTumor-associated antigen (TAA)-specific CD8(+) T cells are essential for nivolumab therapy, and irradiation has been reported to have the potential to generate and activate TAA-specific CD8(+) T cells. However, mechanistic...

TREM1 is involved in the mechanism between asthma and lung cancer by regulating the Toll‑like receptor signaling pathway.

Lung cancer and asthma are both global health problems with significant economic consequences. Recent studies have demonstrated that asthma may be a risk factor for lung cancer. The present study aimed to explore the pathogenesis between these two diseases through a comprehensive analysis. Differentially expressed genes (DEGs) screened in the asthma-related GSE165934 dataset were analyzed to find relevant inflammatory pathways. Overlapping genes regulated by inflammatory pathways and lung cancer-DEGs from The Cancer Genome Atlas (TCGA) were obtained and subjected to survival and gene-wide mutation analyses, and nomogram construction to determine the hub gene. The hub gene was further analyzed through expression validation, immunoassays and functional experiments to investigate its role and mechanism in lung cancer. Functional enrichment analysis showed that 1,275 DEGs from GSE165934 were closely associated with the Toll-like receptor signaling pathway, and 8 overlapping genes were identified from 12 genes regulated by the Toll-like receptor signaling pathway and 3,134 TCGA-DEGs. After a series of bioinformatics analyses, it was found that triggering receptor expressed on myeloid cells 1 (TREM1) was the hub gene involved in the mechanism of asthma and lung cancer. TREM1 was also found to be a suppressor gene in lung cancer correlated with immune cells, immune checkpoint-related genes and tumor mutational burden score. Additionally, the results of Cell Counting Kit-8 and Transwell experiments demonstrated that overexpression of TREM1 could significantly inhibit the invasion, proliferation and migration of lung cancer cells. Reverse transcription-quantitative PCR and western blotting demonstrated that the overexpression of TREM1 could also significantly reduce the level of Toll-like receptor signaling pathway proteins. The present findings suggest that TREM1 is associated with the mechanism of asthma and lung cancer through its regulation of the Toll-like receptor signaling pathway. Furthermore, TREM1 may serve as a potential treatment target and prognostic indicator for patients with lung cancer.

Identification of cancer-associated fibroblasts signature for predicting the prognosis and immunotherapy response in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common malignancies globally with poor prognosis. Cancer-associated fibroblasts (CAFs) play multiple functions in the regulation of tumorigenesis, metastasis and therapeutic resistance of cancer. The current study aimed to explore the role of CAFs-related genes in the prognosis and immunotherapy response in HCC. CAFs-related genes were identified by using single-cell RNA-sequencing analysis. Least absolute shrinkage and selection operator (LASSO) analysis was conducted to develop a CAFs-related prognostic signature (FRPS) in TCGA dataset and verified in ICGC, GSE14520 and GSE76427 cohorts. Several tools, including Tumor Immune Dysfunction and Exclusion (TIDE) score, immunophenoscore, and Tumor Mutation Burden (TMB) score were used to evaluate the value of FRPS in predicting immunotherapy benefits. The FRPS constructed based on 10 genes (RGS5, CNN3, PALLD, FLNA, KLHL23, MYC, NDRG2, SERPINE1, CD151 CALU) served as an independent risk factor and showed stable and powerful performance in predicting the overall survival rate of HCC patients with an AUCs of 0. 734, 0.727, and 0.717 in 2-, 3-, and 4-year ROC curve in TCGA cohort. Low risk score indicated a higher abundance of CD8+ T cells and NK, and lower abundance of Treg. Moreover, HCC patients with low risk score had a higher PD1&CTLA4 immunophenoscore, higher TMB score, and lower TIDE score. Moreover, high risk score indicated a lower IC50 value of 5-fluorouracil, camptothecin, cisplatin, docetaxel, gemcitabine, paclitaxel, afatinib, crizotinib, dasatinib, erlotinib, erlotinib, gefitinib, lapatinib, and osimertinib in HCC. Our study develops a novel FRPS HCC. The FRPS acts as a risk factor for the prognosis of HCC patients and it can predict the immunotherapy benefits of HCC patients.

Development and validation of a novel anoikis-related gene signature in clear cell renal cell carcinoma.

Despite numerous treatments available, clear cell renal cell carcinoma (ccRCC) remains a deadly and invasive cancer. Anoikis-related genes (ARGs) are essential regulators of tumor metastasis and development. However, the potential roles of ARGs in ccRCC remain unclear. Based on the TCGA-KIRC cohort and GeneCards database, we identified differentially expressed ARGs in ccRCC. Then a 4 ARGs risk model was created by Cox regression and LASSO. The Kaplan-Meier and receiver operating characteristic (ROC) curves were utilized to verify the predictive efficacy of the prognostic signature. Subsequently, the possible molecular mechanism of ARGs was investigated by functional enrichment analysis. To assess the immune infiltration, immune checkpoint genes, and immune function in various risk groups, single sample gene set enrichment (ssGSEA) algorithm was employed. Furthermore, the low-risk and high-risk groups were compared in terms of tumor mutation burden (TMB). Ultimately, we analyzed the protein expression of these four ARGs utilizing the western blot test. Four genes were utilized to create a risk signature that may predict prognosis, enabling the classification of KIRC patients into groups with low or high risk. The reliability of the signature was examined utilizing survival analysis and ROC analysis. According to the multivariate Cox regression result, the risk score was a reliable independent prognostic predictor for KIRC patients. The novel risk model could differentiate between KIRC patients with various clinical outcomes and represent KIRC's specific immune status. An analysis of the correlation of TMB and risk score indicated a positive correlation between them, with high TMB being potentially linked to worse outcomes. Based on our findings, the prognostic signature of ARGs may be employed as an independent prognostic factor for ccRCC patients. It may introduce alternative perspectives on prognosis evaluation and serve as a prominent reference for personalized and precise therapy in KIRC.

Circulating Tumor DNA in Colorectal Cancer Liver Metastasis: Analysis of Patients Receiving Liver Resection and Transplant.

Liver metastases occur in about 50% of colorectal cancer cases and drive patient outcomes. Circulating tumor DNA (ctDNA) is emerging as a diagnostic, surveillance, and tumor mutational information tool. Patients with colorectal cancer liver metastasis (CCLM) seen in a multidisciplinary liver tumor clinic from January to August 2022 received ctDNA testing on each visit. ctDNA was obtained using the Guardant360 platform. Tumor mutational burden (TMB) is defined as the number of identified mutations per megabase of genome analyzed. Fifty-two patients had available ctDNA, with 34 (65%) tested preoperatively and 18 (35%) postoperatively; nine patients had sequential pre- and postoperative testing. The median time to test result was 12 days (IQR, 10-13.5). There were a greater number of somatic mutations identified preoperatively (n = 29 v n = 11) and a greater genomic heterogeneity (P = .0069). The mean TMB score was 12.77 in those without pathologic response to cytotoxic therapy and 6.0 in those with pathologic response (P = .10). All nine patients with sequential testing were positive preoperatively, compared with just three (33.3%) postoperatively (P = .0090). Positive postoperative ctDNA was associated with the increased likelihood of disease recurrence after resection (57%) versus negative ctDNA (0%, P = .0419). Routine ctDNA screening in patients with CCLM is logistically feasible. Liver resection and/or transplant may be associated with clearance of detectable ctDNA and a reduction in TMB or genomic heterogeneity. Persistence of ctDNA alterations postresection appears predictive of disease recurrence. Further studies are necessary to confirm these findings, and longitudinal ctDNA testing is needed to monitor changing tumor biology.