Somatic mutations within the exonuclease proofreading domain (EDM) of the DNA polymerase Pol ϵ (POLE) gene are increasingly being discovered in ovarian, colorectal, urological, and, especially, endometrial carcinoma (EC), where these are found in up to 10% of the cases. In EC, there are five confirmed pathogenic somatic POLE-EDM mutations that are located at codons 286, 411, 297, 456, and 459, and these are called \"hotspot\" mutations. POLE mutant tumors are ultramutated entities with a frequency of base substitution mutations that is among the highest in human tumors. Interestingly, these mutations are associated with excellent clinical outcome in EC. An additional six \"non-hotspot\" POLE-EDM EC mutations are also considered pathogenic, and they also confer a favorable prognosis. Currently, de-escalation of adjuvant treatment is recommended for patients with EC with stage I-II tumors involving any of these 11 EDM mutations, even in patients with other clinicopathological risk factors. The high tumor mutational burden and the consequent increased infiltration of immune cells due to the overexpression of different neoantigens are probably responsible for the improved prognosis. Ongoing studies are examining POLE hotspot mutations among many non-gynecologic tumors, although the impact of such mutations on clinical outcomes is still a topic of debate. Therapeutic modalities for these hypermutated tumors are also an important consideration, including the need for or de-escalation of adjuvant treatments and the response to immune therapy. This review addresses the critical role of POLE mutations in gynecologic oncology and oncology in general, focusing on definitions, variants, underlying pathogenic mechanisms, upcoming developments in the field, and the clinic behavior associated with such mutations.

UNASSIGNED: The prognostic implications of tumor mutational burden (TMB) and programmed death ligand 1 (PD-L1) expression are poorly studied in hematologic malignancies.
UNASSIGNED: This study aimed to better understand the characteristics and prognostic value of TMB and PD-1/PD-L1 in hematologic malignancies.
UNASSIGNED: This real-world study was conducted among patients with hematologic malignancies who had next-generation sequencing (NGS) (Foundation Medicine) at the University of California San Diego Moores Cancer Center (2014-2018).
UNASSIGNED: TMB was measured by NGS. PD-L1 expression (tumor proportion score, TPS) was measured by immunohistochemistry (classified as high (⩾50%), low (1-49%), and negative (<1%)). Data was curated from the electronic medical records.
UNASSIGNED: In 388 evaluable patients, the most common diagnoses were B-cell non-Hodgkin lymphoma (NHL) (35%) and Philadelphia chromosome-negative myeloproliferative disorders (16%). Median TMB was 1.6 mutations/Mb (range, 0-46.83). Forty-eight patients (12%) had TMB ⩾10 mutations/Mb, 90% of which were B-cell or T-cell NHL. In 85 samples with available PD-L1 scores, 11 were high; 26, low; and 48, no tumor cell expression. PD-L1 TPS positive (⩾1%) was most common in T-cell NHL (7/9 (77%) cases) followed by B-cell NHL (21/51 (41%) cases). TMB ⩾4 mutations/Mb and PD-L1 score ⩾1% were significantly associated with shorter overall survival (OS) from diagnosis, with hazard ratio (HR) = 1.46 (p = 0.02, 95% confidence interval (CI) 1.05-2.03) and HR = 2.11 (p = 0.04, 95% CI 1.04-4.30), respectively; the relationship was more pronounced when PD-L1 ⩾50% versus <50% was used (HR = 2.80, p = 0.02, 95% CI 1.19-6.59). Higher TMB and higher PD-L1 positivity correlation were significant but weak (Pearson correlation coefficient R 2 = 0.04, p = 0.04).
UNASSIGNED: TMB ⩾4 mutations/Mb and positive PD-L1 TPS are poor prognostic factors, correlating with shorter OS across hematologic malignancies.
UNASSIGNED: ClinicalTrials.gov NCT02478931.

Immune-associated ferroptosis plays an important role in the progression of acute myeloid leukemia (AML); however, the targets that play key roles in this process are currently unknown. This limits the development of mRNA vaccines based on immune-associated ferroptosis for clinical therapeutic applications. In this study, based on the rich data resources of the TCGA-LAML cohort, we analyzed the tumor mutational burden (TMB), gene mutation status, and associations between immune and ferroptosis genes to reveal the disease characteristics of AML patients. To gain a deeper understanding of differentially expressed genes, we applied the Limma package for differential expression analysis and integrated data sources such as ImmPort Shared Data and FerrDb V2. Moreover, we established gene modules related to TMB according to weighted gene coexpression network analysis (WGCNA) and explored the functions of these modules in AML and their relationships with TMB. We focused on the top 30 most frequent genes through a detailed survey of missense mutations and single nucleotide polymorphisms (SNPs) and selected potentially critical gene targets for subsequent analysis. Based on the expression of these genes, we successfully subgrouped AML patients and found that the subgroups associated with TMB (C1 and C2) exhibited significant differences in survival. The differences in the tumor microenvironment and immune cells between C1 and C2 patients were investigated with the ESTIMATE and MCP-counter algorithms. A predictive model of TMB-related genes (TMBRGs) was constructed, and the validity of the model was demonstrated by categorizing patients into high-risk and low-risk groups. The differences in survival between the high-risk patients and high-TMB patients were further investigated, and potential vaccine targets were identified via immune cell-level analysis. The identification of immunity- and ferroptosis-associated signature genes is an independent predictor of survival in AML patients and provides new information on immunotherapy for AML.

The calcium-binding protein S100A9 has emerged as a pivotal biomolecular actor in oncology, implicated in numerous malignancies. This comprehensive bioinformatics study transcends traditional boundaries, investigating the prognostic and therapeutic potential of S100A9 across diverse neoplastic entities. Leveraging a wide array of bioinformatics tools and publicly available cancer genomics databases, such as TCGA, we systematically examined the S100A9 gene. Our approach included differential expression analysis, mutational burden assessment, protein interaction networks, and survival analysis. This robust computational framework provided a high-resolution view of S100A9\'s role in cancer biology. The study meticulously explored S100A9\'s oncogenic facets, incorporating comprehensive analyses of its relationship with prognosis, tumor mutational burden (TMB), microsatellite instability (MSI), DNA methylation, and immune cell infiltration across various tumor types. This study presents a panoramic view of S100A9 expression across a spectrum of human cancers, revealing a heterogeneous expression landscape. Elevated S100A9 expression was detected in malignancies such as BLCA (Bladder Urothelial Carcinoma), CESC (Cervical squamous cell carcinoma and endocervical adenocarcinoma), COAD (Colon adenocarcinoma), ESCA (Esophageal carcinoma), and GBM (Glioblastoma multiforme), while reduced expression was noted in BRCA (Breast invasive carcinoma), HNSC (Head and Neck squamous cell carcinoma), and KICH (Kidney Chromophobe). This disparate expression pattern suggests that S100A9\'s role in cancer biology is multifaceted and context-dependent. Prognostically, S100A9 expression correlates variably with patient outcomes across different cancer types. Furthermore, its expression is intricately associated with TMB and MSI in nine cancer types. Detailed examination of six selected tumors-BRCA, CESC, KIRC (Kidney renal clear cell carcinoma), LUSC (Lung squamous cell carcinoma), SKCM (Skin Cutaneous Melanoma); STAD (Stomach adenocarcinoma)-revealed a negative correlation of S100A9 expression with the infiltration of most immune cells, but a positive correlation with neutrophils, M1 macrophages, and activated NK cells, highlighting the complex interplay between S100A9 and the tumor immune environment. This bioinformatics synthesis posits S100A9 as a significant player in cancer progression, offering valuable prognostic insights. The data underscore the utility of S100A9 as a prognostic biomarker and its potential as a therapeutic target. The therapeutic implications are profound, suggesting that modulation of S100A9 activity could significantly impact cancer management strategies.

BACKGROUND: Inflammation plays a critical role in tumor development. Inflammatory cell infiltration and inflammatory mediator synthesis cause changes in the tumor microenvironment (TME) in several cancers, especially in intrahepatic cholangiocellular carcinoma (ICC). However, methods to ascertain the inflammatory state of patients using reliable biomarkers are still being explored.
METHODS: We retrieved the RNA sequencing and somatic mutation analyses results and the clinical characteristics of 244 patients with ICC from published studies. We performed consensus clustering to identify the molecular subtypes associated with inflammation. We compared the prognostic patterns, clinical characteristics, somatic mutation profiles, and immune cell infiltration patterns across inflammatory subtypes. We performed quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC) to confirm gene expression. We performed logistic regression analyses to construct a nomogram predicting the inflammatory status of patients with ICC.
RESULTS: Our results confirmed that ICC can be categorized into an inflammation-high subtype (IHS) and an inflammation-low subtype (ILS). Patients from each group had distinct prognosis, clinical characteristics, and TME composition. Patients with ICC in the IHS group showed poorer prognosis owing to the immunosuppressive microenvironment and high frequency of KRAS and TP53 mutations. Cancer-associated fibroblast (CAF)-derived COLEC11 reduced myeloid inflammatory cell infiltration and attenuated inflammatory responses. The results of qRT-PCR and IHC experiments confirmed that COLEC11 expression levels were significantly reduced in tumor tissues compared to those in paracancerous tissues. Patients with ICC in the IHS group were more likely to respond to treatment with immune checkpoint inhibitors (ICIs) owing to their higher tumor mutational burden (TMB) scores, tumor neoantigen burden (TNB) scores, neoantigen counts, and immune checkpoint expression levels. Finally, we developed a nomogram to effectively predict the inflammatory status of patients with ICC based on their clinical characteristics and inflammatory gene expression levels. We evaluated the calibration, discrimination potential, and clinical utility of the nomogram.
CONCLUSIONS: The inflammatory response in IHS is primarily induced by myeloid cells. COLEC11 can reduce the infiltration level of this group of cells, and myeloid inflammatory cells may be a novel target for ICC treatment. We developed a novel nomogram that could effectively predict the inflammatory state of patients with ICC, which will be useful for guiding individualized treatment plans.

Lymphoepithelioma-like carcinoma of the bladder (LELC-B) is a rare histologic subtype characterized by strong immune cell (IC) infiltrates. A better prognosis and favorable response rates to immune checkpoint inhibitors have been described. We aimed to characterize the molecular profiles and IC infiltration of LELC-B for a better understanding of its therapeutic implications. We identified 11 muscle-invasive bladder cancer cases with pure and mixed LELC-B. Programmed cell death ligand-1 (PD-L1) expression and mismatch repair proteins were evaluated using immunohistochemistry. We calculated the tumor mutational burden and characterized mutational profiles using whole-exome DNA sequencing data. Transcriptomic signatures were detected using the NanoString nCounter PanCancer IO360 Panel. Multiplex immunofluorescence of tumor microenvironment (PD-L1, PanCK, α-SMA, vimentin, CD45, and Ki67) and T cells (CD4, CD3, PD-1, CD163, CD8, and FoxP3) was used to quantify cell populations. All LELC-B cases were highly positive for PD-L1 (median tumor proportion score/tumor cell, 70%; range, 20%-100%; median combined positive score, 100; range, 50-100) and mismatch repair proficient and negative for Epstein-Barr virus infection. IC infiltrates were characterized by a high CD8+ T-cell count and high PD-1/PD-L1 expression on immune and tumor cells. LELC-B showed upregulation of signaling pathways involved in IC response. Most common mutations were found in chromatin remodeling genes causing epigenetic dysregulation. All LELC-B cases showed high tumor mutational burden with a median of 39 mutations/Mb (IQR, 29-66 mutations/Mb). In conclusion, LELC-B is a highly immunogenic tumor, showing strong upregulation of PD-1/PD-L1 and making immune checkpoint inhibitors a promising treatment option.

暂无摘要。

Lung cancer is one of the most common malignant tumors in the world, of which non-small cell lung cancer (NSCLC) is the majority. The emergence of immune checkpoint inhibitors (ICIs) has greatly changed the treatment strategy of NSCLC and improved the prognosis of patients. However, in reality, only a small number of patients can achieve long-term benefit. Therefore, the identification of reliable predictive biomarkers is essential for the selection of treatment modalities. With the development of molecular biology and genome sequencing technology in recent years, as well as the in-depth understanding of tumor and its host immune microenvironment, research on biomarkers has emerged in an endless stream. This review focuses on the predictive biomarkers of immunotherapy efficacy in NSCLC, in order to provide some guidance for precision immunotherapy.
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【中文题目：非小细胞肺癌免疫治疗疗效的
预测生物标志物研究进展】 【中文摘要：肺癌是世界上最常见的恶性肿瘤之一，其中非小细胞肺癌（non-small cell lung cancer, NSCLC）占大多数。免疫检查点抑制剂（immune checkpoint inhibitors, ICIs）的出现极大地改变了NSCLC的治疗策略，并改善了患者预后，然而现实中只有少部分患者能够获得长期受益。因此，确定可靠的预测生物标志物对选择治疗方式至关重要。随着近年来分子生物学、基因组测序技术的发展以及对肿瘤及其宿主免疫微环境的认识不断深入，生物标志物的研究层出不穷。本文围绕NSCLC免疫治疗疗效的预测生物标志物进行综述，以期为精准免疫治疗提供指导。
】 【中文关键词：肺肿瘤；免疫治疗；肿瘤突变负荷；生物标志物；预测】.

BACKGROUND: High tumor mutational burden (TMB) is one of the widely researched predictive biomarkers of immune checkpoint inhibitors and has been shown to be closely related with response to immunotherapy in multiple cancer types. However, for patients who have failed conventional therapy and are about to undergo immunotherapy, there is no consensus recommendation on the timing of tumor sampling for TMB analysis, and the effects of different therapies on TMB have not been clarified. This retrospective observational study aimed to investigate the heterogeneity of TMB and genomic mutation under the treatment pressure.
METHODS: We retrospectively collected the available genomic and therapeutic information from 8051 samples across 15 tumor types (>50 samples/tumor) found in 30 published studies and investigated the distribution and heterogeneity of TMB under treatment across diverse cohorts.
RESULTS: This integrated analysis has shown anticancer treatments increased TMB. Significant effects of treatment on TMB were more frequently observed in tumor types with lower treatment-naïve TMB, including breast, prostate, and pediatric cancers. For different cancer therapies, chemotherapy was prone to be correlated with an increased TMB in most cancer types. Meanwhile, the fraction of the TMB-high category of breast, prostate, and bladder cancers and glioma increased significantly after chemotherapy. Several actionable genes including ERS1 and NF1 in breast cancer, as well as some prognostic markers including TERT in bladder cancer and IDH1 in glioma, were significantly changed in post-chemotherapy tumors compared to treatment-naïve tumors.
CONCLUSIONS: Our study reveals the heterogeneity of TMB under treatment across diverse cancer types and provides evidences that chemotherapy was associated with increases in TMB as well as the fraction of TMB-high category, suggesting that resampling tumor tissues for calculating post-chemotherapy TMB could be a better option for predicting the response to immunotherapy, especially for tumors with initially low TMB.

Transcriptomic expression profiles of immune checkpoint markers are of interest in order to decipher the mechanisms of immunotherapy response and resistance. Overall, 514 patients with various solid tumors were retrospectively analyzed in this study. The RNA expression levels of tumor checkpoint markers (ADORA2A, BTLA, CD276, CTLA4, IDO1, IDO2, LAG3, NOS2, PD-1, PD-L1, PD-L2, PVR, TIGIT, TIM3, VISTA, and VTCN) were ranked from 0-100 percentile based on a reference population. The expression of each checkpoint was correlated with cancer type, microsatellite instability (MSI), tumor mutational burden (TMB), and programmed death-ligand 1 (PD-L1) by immunohistochemistry (IHC). The cohort included 30 different tumor types, with colorectal cancer being the most common (27%). When RNA percentile rank values were categorized as \"Low\" (0-24), \"Intermediate\" (25-74), and \"High\" (75-100), each patient had a distinctive portfolio of the categorical expression of 16 checkpoint markers. Association between some checkpoint markers and cancer types were observed; NOS2 showed significantly higher expression in colorectal and stomach cancer (P < 0.001). Principal component analysis demonstrated no clear association between combined RNA expression patterns of 16 checkpoint markers and cancer types, TMB, MSI or PD-L1 IHC. Immune checkpoint RNA expression varies from patient to patient, both within and between tumor types, though colorectal and stomach cancer showed the highest levels of NOS2, a mediator of inflammation and immunosuppression. There were no specific combined expression patterns correlated with MSI, TMB or PD-L1 IHC. Next generation immunotherapy trials may benefit from individual analysis of patient tumors as selection criteria for specific immunomodulatory approaches.